data/validation-00000.jsonl

{"id": "val_00000", "created": "2026-01-01", "topic": "Multimodal dev workflows (docs, diagrams, traces)", "task_type": "design", "difficulty": "intermediate", "instruction": "Task: design\nTopic: Multimodal dev workflows (docs, diagrams, traces)\nDifficulty: intermediate\nTarget language: Bash\nContext: Evaluate two coding models for internal rollout under strict governance.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nDesign guidance with risks, metrics, acceptance criteria\n", "metadata": {"target_language": "Bash", "developer_needs": ["security_gates", "repo_scale_reasoning", "evaluation_metrics"]}}
{"id": "val_00001", "created": "2026-01-01", "topic": "Extended context and repo-scale understanding", "task_type": "review", "difficulty": "foundation", "instruction": "Task: review\nTopic: Extended context and repo-scale understanding\nDifficulty: foundation\nTarget language: Bash\nContext: Evaluate two coding models for internal rollout under strict governance.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nReview: correctness, security, performance, governance\n", "metadata": {"target_language": "Bash", "developer_needs": ["tests_are_truth", "security_gates", "repo_scale_reasoning"]}}
{"id": "val_00002", "created": "2026-01-01", "topic": "Code-specialized model families and sizing tradeoffs", "task_type": "eval", "difficulty": "foundation", "instruction": "Task: eval\nTopic: Code-specialized model families and sizing tradeoffs\nDifficulty: foundation\nTarget language: SQL\nContext: Evaluate two coding models for internal rollout under strict governance.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nEval:\n- Tasks: real issues\n- Metrics: pass@k, time-to-green\n- Gates: lint/security\n", "metadata": {"target_language": "SQL", "developer_needs": ["evaluation_metrics", "reproducibility", "cost_latency_tradeoffs"]}}
{"id": "val_00003", "created": "2026-01-01", "topic": "Code-specialized model families and sizing tradeoffs", "task_type": "data_pipeline", "difficulty": "expert", "instruction": "Task: data_pipeline\nTopic: Code-specialized model families and sizing tradeoffs\nDifficulty: expert\nTarget language: SQL\nContext: Create an eval harness that reflects real developer workflows.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nPipeline:\n1) Ingest\n2) Normalize\n3) Filter\n4) Dedupe\n5) Quality score\n6) Sample\n7) Audit\n", "metadata": {"target_language": "SQL", "developer_needs": ["governance", "tests_are_truth", "security_gates"]}}
{"id": "val_00004", "created": "2026-01-01", "topic": "Multimodal dev workflows (docs, diagrams, traces)", "task_type": "agent_loop", "difficulty": "expert", "instruction": "Task: agent_loop\nTopic: Multimodal dev workflows (docs, diagrams, traces)\nDifficulty: expert\nTarget language: C#\nContext: Fix a failing issue with tests as the oracle and produce a safe patch.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nAgent loop: Plan \u2192 Edit (diff) \u2192 Test \u2192 Reflect \u2192 Human gate\n", "metadata": {"target_language": "C#", "developer_needs": ["reproducibility", "tests_are_truth", "security_gates"]}}
{"id": "val_00005", "created": "2026-01-01", "topic": "Extended context and repo-scale understanding", "task_type": "data_pipeline", "difficulty": "expert", "instruction": "Task: data_pipeline\nTopic: Extended context and repo-scale understanding\nDifficulty: expert\nTarget language: C#\nContext: Evaluate two coding models for internal rollout under strict governance.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nPipeline:\n1) Ingest\n2) Normalize\n3) Filter\n4) Dedupe\n5) Quality score\n6) Sample\n7) Audit\n", "metadata": {"target_language": "C#", "developer_needs": ["documentation", "tests_are_truth", "repo_scale_reasoning"]}}
{"id": "val_00006", "created": "2026-01-01", "topic": "Governance, provenance, and licensing for code data", "task_type": "code", "difficulty": "intermediate", "instruction": "Task: code\nTopic: Governance, provenance, and licensing for code data\nDifficulty: intermediate\nTarget language: Go\nContext: Evaluate two coding models for internal rollout under strict governance.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nDesign guidance with risks, metrics, acceptance criteria\n", "metadata": {"target_language": "Go", "developer_needs": ["tests_are_truth", "evaluation_metrics", "tooling"]}}
{"id": "val_00007", "created": "2026-01-01", "topic": "Secure code generation and policy gates", "task_type": "eval", "difficulty": "advanced", "instruction": "Task: eval\nTopic: Secure code generation and policy gates\nDifficulty: advanced\nTarget language: C#\nContext: Design a data pipeline for continued pretraining with auditability.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nEval:\n- Tasks: real issues\n- Metrics: pass@k, time-to-green\n- Gates: lint/security\n", "metadata": {"target_language": "C#", "developer_needs": ["documentation", "governance", "cost_latency_tradeoffs"]}}
{"id": "val_00008", "created": "2026-01-01", "topic": "Code-specialized model families and sizing tradeoffs", "task_type": "data_pipeline", "difficulty": "expert", "instruction": "Task: data_pipeline\nTopic: Code-specialized model families and sizing tradeoffs\nDifficulty: expert\nTarget language: Python\nContext: Evaluate two coding models for internal rollout under strict governance.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nPipeline:\n1) Ingest\n2) Normalize\n3) Filter\n4) Dedupe\n5) Quality score\n6) Sample\n7) Audit\n", "metadata": {"target_language": "Python", "developer_needs": ["governance", "security_gates", "reproducibility"]}}
{"id": "val_00009", "created": "2026-01-01", "topic": "Dataset curation pipelines (filter, dedupe, quality)", "task_type": "eval", "difficulty": "intermediate", "instruction": "Task: eval\nTopic: Dataset curation pipelines (filter, dedupe, quality)\nDifficulty: intermediate\nTarget language: Rust\nContext: Integrate an LLM agent into CI for a large monorepo.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nEval:\n- Tasks: real issues\n- Metrics: pass@k, time-to-green\n- Gates: lint/security\n", "metadata": {"target_language": "Rust", "developer_needs": ["governance", "security_gates", "cost_latency_tradeoffs"]}}
{"id": "val_00010", "created": "2026-01-01", "topic": "Secure code generation and policy gates", "task_type": "explain", "difficulty": "foundation", "instruction": "Task: explain\nTopic: Secure code generation and policy gates\nDifficulty: foundation\nTarget language: SQL\nContext: Evaluate two coding models for internal rollout under strict governance.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nDesign guidance with risks, metrics, acceptance criteria\n", "metadata": {"target_language": "SQL", "developer_needs": ["evaluation_metrics", "tests_are_truth", "governance"]}}
{"id": "val_00011", "created": "2026-01-01", "topic": "Model merging, distillation, and continued pretraining", "task_type": "eval", "difficulty": "expert", "instruction": "Task: eval\nTopic: Model merging, distillation, and continued pretraining\nDifficulty: expert\nTarget language: Python\nContext: Evaluate two coding models for internal rollout under strict governance.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nEval:\n- Tasks: real issues\n- Metrics: pass@k, time-to-green\n- Gates: lint/security\n", "metadata": {"target_language": "Python", "developer_needs": ["evaluation_metrics", "repo_scale_reasoning", "ci_integration"]}}
{"id": "val_00012", "created": "2026-01-01", "topic": "Dataset curation pipelines (filter, dedupe, quality)", "task_type": "review", "difficulty": "advanced", "instruction": "Task: review\nTopic: Dataset curation pipelines (filter, dedupe, quality)\nDifficulty: advanced\nTarget language: Python\nContext: Evaluate two coding models for internal rollout under strict governance.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nReview: correctness, security, performance, governance\n", "metadata": {"target_language": "Python", "developer_needs": ["reproducibility", "security_gates", "ci_integration"]}}
{"id": "val_00013", "created": "2026-01-01", "topic": "Governance, provenance, and licensing for code data", "task_type": "eval", "difficulty": "foundation", "instruction": "Task: eval\nTopic: Governance, provenance, and licensing for code data\nDifficulty: foundation\nTarget language: Rust\nContext: Design a data pipeline for continued pretraining with auditability.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nEval:\n- Tasks: real issues\n- Metrics: pass@k, time-to-green\n- Gates: lint/security\n", "metadata": {"target_language": "Rust", "developer_needs": ["cost_latency_tradeoffs", "security_gates", "evaluation_metrics"]}}
{"id": "val_00014", "created": "2026-01-01", "topic": "Model merging, distillation, and continued pretraining", "task_type": "agent_loop", "difficulty": "intermediate", "instruction": "Task: agent_loop\nTopic: Model merging, distillation, and continued pretraining\nDifficulty: intermediate\nTarget language: Rust\nContext: Design a data pipeline for continued pretraining with auditability.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nAgent loop: Plan \u2192 Edit (diff) \u2192 Test \u2192 Reflect \u2192 Human gate\n", "metadata": {"target_language": "Rust", "developer_needs": ["reproducibility", "repo_scale_reasoning", "governance"]}}
{"id": "val_00015", "created": "2026-01-01", "topic": "Extended context and repo-scale understanding", "task_type": "compare", "difficulty": "intermediate", "instruction": "Task: compare\nTopic: Extended context and repo-scale understanding\nDifficulty: intermediate\nTarget language: Rust\nContext: Create an eval harness that reflects real developer workflows.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nCompare: capability, cost, latency, reliability, governance\n", "metadata": {"target_language": "Rust", "developer_needs": ["documentation", "tests_are_truth", "governance"]}}
{"id": "val_00016", "created": "2026-01-01", "topic": "Multimodal dev workflows (docs, diagrams, traces)", "task_type": "agent_loop", "difficulty": "foundation", "instruction": "Task: agent_loop\nTopic: Multimodal dev workflows (docs, diagrams, traces)\nDifficulty: foundation\nTarget language: TypeScript\nContext: Fix a failing issue with tests as the oracle and produce a safe patch.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nAgent loop: Plan \u2192 Edit (diff) \u2192 Test \u2192 Reflect \u2192 Human gate\n", "metadata": {"target_language": "TypeScript", "developer_needs": ["documentation", "security_gates", "evaluation_metrics"]}}
{"id": "val_00017", "created": "2026-01-01", "topic": "Dataset curation pipelines (filter, dedupe, quality)", "task_type": "agent_loop", "difficulty": "foundation", "instruction": "Task: agent_loop\nTopic: Dataset curation pipelines (filter, dedupe, quality)\nDifficulty: foundation\nTarget language: TypeScript\nContext: Fix a failing issue with tests as the oracle and produce a safe patch.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nAgent loop: Plan \u2192 Edit (diff) \u2192 Test \u2192 Reflect \u2192 Human gate\n", "metadata": {"target_language": "TypeScript", "developer_needs": ["reproducibility", "governance", "cost_latency_tradeoffs"]}}
{"id": "val_00018", "created": "2026-01-01", "topic": "Multimodal dev workflows (docs, diagrams, traces)", "task_type": "compare", "difficulty": "foundation", "instruction": "Task: compare\nTopic: Multimodal dev workflows (docs, diagrams, traces)\nDifficulty: foundation\nTarget language: Rust\nContext: Create an eval harness that reflects real developer workflows.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nCompare: capability, cost, latency, reliability, governance\n", "metadata": {"target_language": "Rust", "developer_needs": ["tooling", "reproducibility", "repo_scale_reasoning"]}}
{"id": "val_00019", "created": "2026-01-01", "topic": "Extended context and repo-scale understanding", "task_type": "data_pipeline", "difficulty": "expert", "instruction": "Task: data_pipeline\nTopic: Extended context and repo-scale understanding\nDifficulty: expert\nTarget language: Python\nContext: Design a data pipeline for continued pretraining with auditability.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nPipeline:\n1) Ingest\n2) Normalize\n3) Filter\n4) Dedupe\n5) Quality score\n6) Sample\n7) Audit\n", "metadata": {"target_language": "Python", "developer_needs": ["documentation", "tests_are_truth", "evaluation_metrics"]}}
{"id": "val_00020", "created": "2026-01-01", "topic": "Governance, provenance, and licensing for code data", "task_type": "agent_loop", "difficulty": "expert", "instruction": "Task: agent_loop\nTopic: Governance, provenance, and licensing for code data\nDifficulty: expert\nTarget language: SQL\nContext: Design a data pipeline for continued pretraining with auditability.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nAgent loop: Plan \u2192 Edit (diff) \u2192 Test \u2192 Reflect \u2192 Human gate\n", "metadata": {"target_language": "SQL", "developer_needs": ["repo_scale_reasoning", "documentation", "evaluation_metrics"]}}
{"id": "val_00021", "created": "2026-01-01", "topic": "Mixture-of-Experts (MoE) for code", "task_type": "agent_loop", "difficulty": "advanced", "instruction": "Task: agent_loop\nTopic: Mixture-of-Experts (MoE) for code\nDifficulty: advanced\nTarget language: Rust\nContext: Integrate an LLM agent into CI for a large monorepo.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nAgent loop: Plan \u2192 Edit (diff) \u2192 Test \u2192 Reflect \u2192 Human gate\n", "metadata": {"target_language": "Rust", "developer_needs": ["documentation", "governance", "ci_integration"]}}
{"id": "val_00022", "created": "2026-01-01", "topic": "Multimodal dev workflows (docs, diagrams, traces)", "task_type": "explain", "difficulty": "intermediate", "instruction": "Task: explain\nTopic: Multimodal dev workflows (docs, diagrams, traces)\nDifficulty: intermediate\nTarget language: Go\nContext: Evaluate two coding models for internal rollout under strict governance.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nDesign guidance with risks, metrics, acceptance criteria\n", "metadata": {"target_language": "Go", "developer_needs": ["tests_are_truth", "tooling", "evaluation_metrics"]}}
{"id": "val_00023", "created": "2026-01-01", "topic": "Mixture-of-Experts (MoE) for code", "task_type": "agent_loop", "difficulty": "intermediate", "instruction": "Task: agent_loop\nTopic: Mixture-of-Experts (MoE) for code\nDifficulty: intermediate\nTarget language: SQL\nContext: Design a data pipeline for continued pretraining with auditability.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nAgent loop: Plan \u2192 Edit (diff) \u2192 Test \u2192 Reflect \u2192 Human gate\n", "metadata": {"target_language": "SQL", "developer_needs": ["governance", "ci_integration", "documentation"]}}
{"id": "val_00024", "created": "2026-01-01", "topic": "Agentic coding systems (plan\u2192edit\u2192test\u2192reflect)", "task_type": "design", "difficulty": "intermediate", "instruction": "Task: design\nTopic: Agentic coding systems (plan\u2192edit\u2192test\u2192reflect)\nDifficulty: intermediate\nTarget language: Bash\nContext: Integrate an LLM agent into CI for a large monorepo.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nDesign guidance with risks, metrics, acceptance criteria\n", "metadata": {"target_language": "Bash", "developer_needs": ["tests_are_truth", "documentation", "reproducibility"]}}
{"id": "val_00025", "created": "2026-01-01", "topic": "Model merging, distillation, and continued pretraining", "task_type": "review", "difficulty": "expert", "instruction": "Task: review\nTopic: Model merging, distillation, and continued pretraining\nDifficulty: expert\nTarget language: Java\nContext: Create an eval harness that reflects real developer workflows.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nReview: correctness, security, performance, governance\n", "metadata": {"target_language": "Java", "developer_needs": ["governance", "security_gates", "tooling"]}}
{"id": "val_00026", "created": "2026-01-01", "topic": "Code-specialized model families and sizing tradeoffs", "task_type": "agent_loop", "difficulty": "intermediate", "instruction": "Task: agent_loop\nTopic: Code-specialized model families and sizing tradeoffs\nDifficulty: intermediate\nTarget language: Rust\nContext: Integrate an LLM agent into CI for a large monorepo.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nAgent loop: Plan \u2192 Edit (diff) \u2192 Test \u2192 Reflect \u2192 Human gate\n", "metadata": {"target_language": "Rust", "developer_needs": ["reproducibility", "governance", "tests_are_truth"]}}
{"id": "val_00027", "created": "2026-01-01", "topic": "Agentic coding systems (plan\u2192edit\u2192test\u2192reflect)", "task_type": "review", "difficulty": "expert", "instruction": "Task: review\nTopic: Agentic coding systems (plan\u2192edit\u2192test\u2192reflect)\nDifficulty: expert\nTarget language: Java\nContext: Evaluate two coding models for internal rollout under strict governance.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nReview: correctness, security, performance, governance\n", "metadata": {"target_language": "Java", "developer_needs": ["tooling", "cost_latency_tradeoffs", "reproducibility"]}}
{"id": "val_00028", "created": "2026-01-01", "topic": "SWE-bench style real-repo evaluation", "task_type": "data_pipeline", "difficulty": "advanced", "instruction": "Task: data_pipeline\nTopic: SWE-bench style real-repo evaluation\nDifficulty: advanced\nTarget language: C#\nContext: Integrate an LLM agent into CI for a large monorepo.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nPipeline:\n1) Ingest\n2) Normalize\n3) Filter\n4) Dedupe\n5) Quality score\n6) Sample\n7) Audit\n", "metadata": {"target_language": "C#", "developer_needs": ["cost_latency_tradeoffs", "evaluation_metrics", "reproducibility"]}}
{"id": "val_00029", "created": "2026-01-01", "topic": "Governance, provenance, and licensing for code data", "task_type": "code", "difficulty": "expert", "instruction": "Task: code\nTopic: Governance, provenance, and licensing for code data\nDifficulty: expert\nTarget language: Java\nContext: Integrate an LLM agent into CI for a large monorepo.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nDesign guidance with risks, metrics, acceptance criteria\n", "metadata": {"target_language": "Java", "developer_needs": ["ci_integration", "cost_latency_tradeoffs", "tooling"]}}
{"id": "val_00030", "created": "2026-01-01", "topic": "Reasoning-first coding models and tunable deliberation", "task_type": "review", "difficulty": "intermediate", "instruction": "Task: review\nTopic: Reasoning-first coding models and tunable deliberation\nDifficulty: intermediate\nTarget language: JavaScript\nContext: Create an eval harness that reflects real developer workflows.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nReview: correctness, security, performance, governance\n", "metadata": {"target_language": "JavaScript", "developer_needs": ["ci_integration", "reproducibility", "tooling"]}}
{"id": "val_00031", "created": "2026-01-01", "topic": "Agentic coding systems (plan\u2192edit\u2192test\u2192reflect)", "task_type": "code", "difficulty": "intermediate", "instruction": "Task: code\nTopic: Agentic coding systems (plan\u2192edit\u2192test\u2192reflect)\nDifficulty: intermediate\nTarget language: C#\nContext: Create an eval harness that reflects real developer workflows.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nDesign guidance with risks, metrics, acceptance criteria\n", "metadata": {"target_language": "C#", "developer_needs": ["repo_scale_reasoning", "security_gates", "reproducibility"]}}
{"id": "val_00032", "created": "2026-01-01", "topic": "Mixture-of-Experts (MoE) for code", "task_type": "data_pipeline", "difficulty": "advanced", "instruction": "Task: data_pipeline\nTopic: Mixture-of-Experts (MoE) for code\nDifficulty: advanced\nTarget language: TypeScript\nContext: Create an eval harness that reflects real developer workflows.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nPipeline:\n1) Ingest\n2) Normalize\n3) Filter\n4) Dedupe\n5) Quality score\n6) Sample\n7) Audit\n", "metadata": {"target_language": "TypeScript", "developer_needs": ["tooling", "cost_latency_tradeoffs", "reproducibility"]}}
{"id": "val_00033", "created": "2026-01-01", "topic": "Mixture-of-Experts (MoE) for code", "task_type": "code", "difficulty": "foundation", "instruction": "Task: code\nTopic: Mixture-of-Experts (MoE) for code\nDifficulty: foundation\nTarget language: Go\nContext: Design a data pipeline for continued pretraining with auditability.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nDesign guidance with risks, metrics, acceptance criteria\n", "metadata": {"target_language": "Go", "developer_needs": ["reproducibility", "evaluation_metrics", "repo_scale_reasoning"]}}
{"id": "val_00034", "created": "2026-01-01", "topic": "SWE-bench style real-repo evaluation", "task_type": "explain", "difficulty": "expert", "instruction": "Task: explain\nTopic: SWE-bench style real-repo evaluation\nDifficulty: expert\nTarget language: JavaScript\nContext: Integrate an LLM agent into CI for a large monorepo.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nDesign guidance with risks, metrics, acceptance criteria\n", "metadata": {"target_language": "JavaScript", "developer_needs": ["evaluation_metrics", "security_gates", "tooling"]}}
{"id": "val_00035", "created": "2026-01-01", "topic": "Agentic coding systems (plan\u2192edit\u2192test\u2192reflect)", "task_type": "eval", "difficulty": "foundation", "instruction": "Task: eval\nTopic: Agentic coding systems (plan\u2192edit\u2192test\u2192reflect)\nDifficulty: foundation\nTarget language: Rust\nContext: Evaluate two coding models for internal rollout under strict governance.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nEval:\n- Tasks: real issues\n- Metrics: pass@k, time-to-green\n- Gates: lint/security\n", "metadata": {"target_language": "Rust", "developer_needs": ["cost_latency_tradeoffs", "evaluation_metrics", "tooling"]}}
{"id": "val_00036", "created": "2026-01-01", "topic": "Secure code generation and policy gates", "task_type": "compare", "difficulty": "intermediate", "instruction": "Task: compare\nTopic: Secure code generation and policy gates\nDifficulty: intermediate\nTarget language: Python\nContext: Integrate an LLM agent into CI for a large monorepo.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nCompare: capability, cost, latency, reliability, governance\n", "metadata": {"target_language": "Python", "developer_needs": ["tooling", "tests_are_truth", "governance"]}}
{"id": "val_00037", "created": "2026-01-01", "topic": "Mixture-of-Experts (MoE) for code", "task_type": "agent_loop", "difficulty": "advanced", "instruction": "Task: agent_loop\nTopic: Mixture-of-Experts (MoE) for code\nDifficulty: advanced\nTarget language: Rust\nContext: Create an eval harness that reflects real developer workflows.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nAgent loop: Plan \u2192 Edit (diff) \u2192 Test \u2192 Reflect \u2192 Human gate\n", "metadata": {"target_language": "Rust", "developer_needs": ["security_gates", "governance", "repo_scale_reasoning"]}}
{"id": "val_00038", "created": "2026-01-01", "topic": "Secure code generation and policy gates", "task_type": "agent_loop", "difficulty": "foundation", "instruction": "Task: agent_loop\nTopic: Secure code generation and policy gates\nDifficulty: foundation\nTarget language: Python\nContext: Fix a failing issue with tests as the oracle and produce a safe patch.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nAgent loop: Plan \u2192 Edit (diff) \u2192 Test \u2192 Reflect \u2192 Human gate\n", "metadata": {"target_language": "Python", "developer_needs": ["tests_are_truth", "cost_latency_tradeoffs", "ci_integration"]}}
{"id": "val_00039", "created": "2026-01-01", "topic": "Reasoning-first coding models and tunable deliberation", "task_type": "data_pipeline", "difficulty": "expert", "instruction": "Task: data_pipeline\nTopic: Reasoning-first coding models and tunable deliberation\nDifficulty: expert\nTarget language: C#\nContext: Create an eval harness that reflects real developer workflows.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nPipeline:\n1) Ingest\n2) Normalize\n3) Filter\n4) Dedupe\n5) Quality score\n6) Sample\n7) Audit\n", "metadata": {"target_language": "C#", "developer_needs": ["reproducibility", "ci_integration", "security_gates"]}}
{"id": "val_00040", "created": "2026-01-01", "topic": "Governance, provenance, and licensing for code data", "task_type": "review", "difficulty": "intermediate", "instruction": "Task: review\nTopic: Governance, provenance, and licensing for code data\nDifficulty: intermediate\nTarget language: Rust\nContext: Evaluate two coding models for internal rollout under strict governance.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nReview: correctness, security, performance, governance\n", "metadata": {"target_language": "Rust", "developer_needs": ["ci_integration", "security_gates", "repo_scale_reasoning"]}}
{"id": "val_00041", "created": "2026-01-01", "topic": "Tool calling, sandboxes, and CI integration", "task_type": "agent_loop", "difficulty": "advanced", "instruction": "Task: agent_loop\nTopic: Tool calling, sandboxes, and CI integration\nDifficulty: advanced\nTarget language: JavaScript\nContext: Fix a failing issue with tests as the oracle and produce a safe patch.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nAgent loop: Plan \u2192 Edit (diff) \u2192 Test \u2192 Reflect \u2192 Human gate\n", "metadata": {"target_language": "JavaScript", "developer_needs": ["governance", "reproducibility", "documentation"]}}
{"id": "val_00042", "created": "2026-01-01", "topic": "Code-specialized model families and sizing tradeoffs", "task_type": "data_pipeline", "difficulty": "advanced", "instruction": "Task: data_pipeline\nTopic: Code-specialized model families and sizing tradeoffs\nDifficulty: advanced\nTarget language: JavaScript\nContext: Integrate an LLM agent into CI for a large monorepo.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nPipeline:\n1) Ingest\n2) Normalize\n3) Filter\n4) Dedupe\n5) Quality score\n6) Sample\n7) Audit\n", "metadata": {"target_language": "JavaScript", "developer_needs": ["cost_latency_tradeoffs", "ci_integration", "tests_are_truth"]}}
{"id": "val_00043", "created": "2026-01-01", "topic": "Governance, provenance, and licensing for code data", "task_type": "review", "difficulty": "advanced", "instruction": "Task: review\nTopic: Governance, provenance, and licensing for code data\nDifficulty: advanced\nTarget language: JavaScript\nContext: Create an eval harness that reflects real developer workflows.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nReview: correctness, security, performance, governance\n", "metadata": {"target_language": "JavaScript", "developer_needs": ["documentation", "tooling", "governance"]}}
{"id": "val_00044", "created": "2026-01-01", "topic": "Extended context and repo-scale understanding", "task_type": "code", "difficulty": "advanced", "instruction": "Task: code\nTopic: Extended context and repo-scale understanding\nDifficulty: advanced\nTarget language: Rust\nContext: Integrate an LLM agent into CI for a large monorepo.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nDesign guidance with risks, metrics, acceptance criteria\n", "metadata": {"target_language": "Rust", "developer_needs": ["tooling", "ci_integration", "repo_scale_reasoning"]}}
{"id": "val_00045", "created": "2026-01-01", "topic": "Tool calling, sandboxes, and CI integration", "task_type": "design", "difficulty": "advanced", "instruction": "Task: design\nTopic: Tool calling, sandboxes, and CI integration\nDifficulty: advanced\nTarget language: Go\nContext: Create an eval harness that reflects real developer workflows.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nDesign guidance with risks, metrics, acceptance criteria\n", "metadata": {"target_language": "Go", "developer_needs": ["reproducibility", "governance", "cost_latency_tradeoffs"]}}
{"id": "val_00046", "created": "2026-01-01", "topic": "SWE-bench style real-repo evaluation", "task_type": "code", "difficulty": "advanced", "instruction": "Task: code\nTopic: SWE-bench style real-repo evaluation\nDifficulty: advanced\nTarget language: TypeScript\nContext: Create an eval harness that reflects real developer workflows.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nDesign guidance with risks, metrics, acceptance criteria\n", "metadata": {"target_language": "TypeScript", "developer_needs": ["cost_latency_tradeoffs", "reproducibility", "ci_integration"]}}
{"id": "val_00047", "created": "2026-01-01", "topic": "Tool calling, sandboxes, and CI integration", "task_type": "design", "difficulty": "intermediate", "instruction": "Task: design\nTopic: Tool calling, sandboxes, and CI integration\nDifficulty: intermediate\nTarget language: TypeScript\nContext: Evaluate two coding models for internal rollout under strict governance.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nDesign guidance with risks, metrics, acceptance criteria\n", "metadata": {"target_language": "TypeScript", "developer_needs": ["ci_integration", "security_gates", "tooling"]}}
{"id": "val_00048", "created": "2026-01-01", "topic": "Model merging, distillation, and continued pretraining", "task_type": "compare", "difficulty": "intermediate", "instruction": "Task: compare\nTopic: Model merging, distillation, and continued pretraining\nDifficulty: intermediate\nTarget language: Rust\nContext: Fix a failing issue with tests as the oracle and produce a safe patch.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nCompare: capability, cost, latency, reliability, governance\n", "metadata": {"target_language": "Rust", "developer_needs": ["security_gates", "tooling", "documentation"]}}
{"id": "val_00049", "created": "2026-01-01", "topic": "SWE-bench style real-repo evaluation", "task_type": "design", "difficulty": "intermediate", "instruction": "Task: design\nTopic: SWE-bench style real-repo evaluation\nDifficulty: intermediate\nTarget language: Bash\nContext: Fix a failing issue with tests as the oracle and produce a safe patch.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nDesign guidance with risks, metrics, acceptance criteria\n", "metadata": {"target_language": "Bash", "developer_needs": ["repo_scale_reasoning", "governance", "evaluation_metrics"]}}
{"id": "val_00050", "created": "2026-01-01", "topic": "Reasoning-first coding models and tunable deliberation", "task_type": "code", "difficulty": "foundation", "instruction": "Task: code\nTopic: Reasoning-first coding models and tunable deliberation\nDifficulty: foundation\nTarget language: Java\nContext: Integrate an LLM agent into CI for a large monorepo.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nDesign guidance with risks, metrics, acceptance criteria\n", "metadata": {"target_language": "Java", "developer_needs": ["cost_latency_tradeoffs", "ci_integration", "documentation"]}}
{"id": "val_00051", "created": "2026-01-01", "topic": "Dataset curation pipelines (filter, dedupe, quality)", "task_type": "design", "difficulty": "foundation", "instruction": "Task: design\nTopic: Dataset curation pipelines (filter, dedupe, quality)\nDifficulty: foundation\nTarget language: TypeScript\nContext: Evaluate two coding models for internal rollout under strict governance.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nDesign guidance with risks, metrics, acceptance criteria\n", "metadata": {"target_language": "TypeScript", "developer_needs": ["repo_scale_reasoning", "tests_are_truth", "reproducibility"]}}
{"id": "val_00052", "created": "2026-01-01", "topic": "Agentic coding systems (plan\u2192edit\u2192test\u2192reflect)", "task_type": "agent_loop", "difficulty": "expert", "instruction": "Task: agent_loop\nTopic: Agentic coding systems (plan\u2192edit\u2192test\u2192reflect)\nDifficulty: expert\nTarget language: Rust\nContext: Integrate an LLM agent into CI for a large monorepo.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nAgent loop: Plan \u2192 Edit (diff) \u2192 Test \u2192 Reflect \u2192 Human gate\n", "metadata": {"target_language": "Rust", "developer_needs": ["documentation", "cost_latency_tradeoffs", "security_gates"]}}
{"id": "val_00053", "created": "2026-01-01", "topic": "Tool calling, sandboxes, and CI integration", "task_type": "data_pipeline", "difficulty": "foundation", "instruction": "Task: data_pipeline\nTopic: Tool calling, sandboxes, and CI integration\nDifficulty: foundation\nTarget language: JavaScript\nContext: Evaluate two coding models for internal rollout under strict governance.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nPipeline:\n1) Ingest\n2) Normalize\n3) Filter\n4) Dedupe\n5) Quality score\n6) Sample\n7) Audit\n", "metadata": {"target_language": "JavaScript", "developer_needs": ["repo_scale_reasoning", "tests_are_truth", "evaluation_metrics"]}}
{"id": "val_00054", "created": "2026-01-01", "topic": "Code-specialized model families and sizing tradeoffs", "task_type": "review", "difficulty": "advanced", "instruction": "Task: review\nTopic: Code-specialized model families and sizing tradeoffs\nDifficulty: advanced\nTarget language: Python\nContext: Evaluate two coding models for internal rollout under strict governance.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nReview: correctness, security, performance, governance\n", "metadata": {"target_language": "Python", "developer_needs": ["governance", "documentation", "reproducibility"]}}
{"id": "val_00055", "created": "2026-01-01", "topic": "Model merging, distillation, and continued pretraining", "task_type": "eval", "difficulty": "foundation", "instruction": "Task: eval\nTopic: Model merging, distillation, and continued pretraining\nDifficulty: foundation\nTarget language: Java\nContext: Integrate an LLM agent into CI for a large monorepo.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nEval:\n- Tasks: real issues\n- Metrics: pass@k, time-to-green\n- Gates: lint/security\n", "metadata": {"target_language": "Java", "developer_needs": ["documentation", "tests_are_truth", "evaluation_metrics"]}}
{"id": "val_00056", "created": "2026-01-01", "topic": "Code-specialized model families and sizing tradeoffs", "task_type": "compare", "difficulty": "advanced", "instruction": "Task: compare\nTopic: Code-specialized model families and sizing tradeoffs\nDifficulty: advanced\nTarget language: Go\nContext: Create an eval harness that reflects real developer workflows.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nCompare: capability, cost, latency, reliability, governance\n", "metadata": {"target_language": "Go", "developer_needs": ["reproducibility", "governance", "repo_scale_reasoning"]}}
{"id": "val_00057", "created": "2026-01-01", "topic": "Code-specialized model families and sizing tradeoffs", "task_type": "agent_loop", "difficulty": "foundation", "instruction": "Task: agent_loop\nTopic: Code-specialized model families and sizing tradeoffs\nDifficulty: foundation\nTarget language: JavaScript\nContext: Fix a failing issue with tests as the oracle and produce a safe patch.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nAgent loop: Plan \u2192 Edit (diff) \u2192 Test \u2192 Reflect \u2192 Human gate\n", "metadata": {"target_language": "JavaScript", "developer_needs": ["documentation", "security_gates", "evaluation_metrics"]}}
{"id": "val_00058", "created": "2026-01-01", "topic": "Dataset curation pipelines (filter, dedupe, quality)", "task_type": "data_pipeline", "difficulty": "intermediate", "instruction": "Task: data_pipeline\nTopic: Dataset curation pipelines (filter, dedupe, quality)\nDifficulty: intermediate\nTarget language: Python\nContext: Design a data pipeline for continued pretraining with auditability.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nPipeline:\n1) Ingest\n2) Normalize\n3) Filter\n4) Dedupe\n5) Quality score\n6) Sample\n7) Audit\n", "metadata": {"target_language": "Python", "developer_needs": ["repo_scale_reasoning", "security_gates", "tests_are_truth"]}}
{"id": "val_00059", "created": "2026-01-01", "topic": "Governance, provenance, and licensing for code data", "task_type": "code", "difficulty": "advanced", "instruction": "Task: code\nTopic: Governance, provenance, and licensing for code data\nDifficulty: advanced\nTarget language: C#\nContext: Create an eval harness that reflects real developer workflows.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nDesign guidance with risks, metrics, acceptance criteria\n", "metadata": {"target_language": "C#", "developer_needs": ["tests_are_truth", "repo_scale_reasoning", "tooling"]}}
{"id": "val_00060", "created": "2026-01-01", "topic": "Model merging, distillation, and continued pretraining", "task_type": "agent_loop", "difficulty": "intermediate", "instruction": "Task: agent_loop\nTopic: Model merging, distillation, and continued pretraining\nDifficulty: intermediate\nTarget language: Go\nContext: Fix a failing issue with tests as the oracle and produce a safe patch.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nAgent loop: Plan \u2192 Edit (diff) \u2192 Test \u2192 Reflect \u2192 Human gate\n", "metadata": {"target_language": "Go", "developer_needs": ["evaluation_metrics", "ci_integration", "documentation"]}}
{"id": "val_00061", "created": "2026-01-01", "topic": "Extended context and repo-scale understanding", "task_type": "review", "difficulty": "intermediate", "instruction": "Task: review\nTopic: Extended context and repo-scale understanding\nDifficulty: intermediate\nTarget language: Bash\nContext: Fix a failing issue with tests as the oracle and produce a safe patch.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nReview: correctness, security, performance, governance\n", "metadata": {"target_language": "Bash", "developer_needs": ["repo_scale_reasoning", "ci_integration", "tooling"]}}
{"id": "val_00062", "created": "2026-01-01", "topic": "Tool calling, sandboxes, and CI integration", "task_type": "code", "difficulty": "expert", "instruction": "Task: code\nTopic: Tool calling, sandboxes, and CI integration\nDifficulty: expert\nTarget language: Bash\nContext: Create an eval harness that reflects real developer workflows.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nDesign guidance with risks, metrics, acceptance criteria\n", "metadata": {"target_language": "Bash", "developer_needs": ["documentation", "security_gates", "evaluation_metrics"]}}
{"id": "val_00063", "created": "2026-01-01", "topic": "Dataset curation pipelines (filter, dedupe, quality)", "task_type": "design", "difficulty": "intermediate", "instruction": "Task: design\nTopic: Dataset curation pipelines (filter, dedupe, quality)\nDifficulty: intermediate\nTarget language: JavaScript\nContext: Integrate an LLM agent into CI for a large monorepo.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nDesign guidance with risks, metrics, acceptance criteria\n", "metadata": {"target_language": "JavaScript", "developer_needs": ["ci_integration", "tooling", "repo_scale_reasoning"]}}
{"id": "val_00064", "created": "2026-01-01", "topic": "Secure code generation and policy gates", "task_type": "review", "difficulty": "intermediate", "instruction": "Task: review\nTopic: Secure code generation and policy gates\nDifficulty: intermediate\nTarget language: Java\nContext: Evaluate two coding models for internal rollout under strict governance.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nReview: correctness, security, performance, governance\n", "metadata": {"target_language": "Java", "developer_needs": ["cost_latency_tradeoffs", "repo_scale_reasoning", "tooling"]}}
{"id": "val_00065", "created": "2026-01-01", "topic": "Secure code generation and policy gates", "task_type": "review", "difficulty": "intermediate", "instruction": "Task: review\nTopic: Secure code generation and policy gates\nDifficulty: intermediate\nTarget language: Rust\nContext: Design a data pipeline for continued pretraining with auditability.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nReview: correctness, security, performance, governance\n", "metadata": {"target_language": "Rust", "developer_needs": ["tooling", "governance", "security_gates"]}}
{"id": "val_00066", "created": "2026-01-01", "topic": "Code-specialized model families and sizing tradeoffs", "task_type": "design", "difficulty": "foundation", "instruction": "Task: design\nTopic: Code-specialized model families and sizing tradeoffs\nDifficulty: foundation\nTarget language: Java\nContext: Integrate an LLM agent into CI for a large monorepo.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nDesign guidance with risks, metrics, acceptance criteria\n", "metadata": {"target_language": "Java", "developer_needs": ["reproducibility", "documentation", "ci_integration"]}}
{"id": "val_00067", "created": "2026-01-01", "topic": "SWE-bench style real-repo evaluation", "task_type": "eval", "difficulty": "foundation", "instruction": "Task: eval\nTopic: SWE-bench style real-repo evaluation\nDifficulty: foundation\nTarget language: Rust\nContext: Integrate an LLM agent into CI for a large monorepo.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nEval:\n- Tasks: real issues\n- Metrics: pass@k, time-to-green\n- Gates: lint/security\n", "metadata": {"target_language": "Rust", "developer_needs": ["evaluation_metrics", "cost_latency_tradeoffs", "tooling"]}}
{"id": "val_00068", "created": "2026-01-01", "topic": "Tool calling, sandboxes, and CI integration", "task_type": "eval", "difficulty": "advanced", "instruction": "Task: eval\nTopic: Tool calling, sandboxes, and CI integration\nDifficulty: advanced\nTarget language: Go\nContext: Design a data pipeline for continued pretraining with auditability.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nEval:\n- Tasks: real issues\n- Metrics: pass@k, time-to-green\n- Gates: lint/security\n", "metadata": {"target_language": "Go", "developer_needs": ["cost_latency_tradeoffs", "documentation", "ci_integration"]}}
{"id": "val_00069", "created": "2026-01-01", "topic": "Mixture-of-Experts (MoE) for code", "task_type": "code", "difficulty": "intermediate", "instruction": "Task: code\nTopic: Mixture-of-Experts (MoE) for code\nDifficulty: intermediate\nTarget language: C#\nContext: Design a data pipeline for continued pretraining with auditability.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nDesign guidance with risks, metrics, acceptance criteria\n", "metadata": {"target_language": "C#", "developer_needs": ["cost_latency_tradeoffs", "documentation", "tests_are_truth"]}}
{"id": "val_00070", "created": "2026-01-01", "topic": "Dataset curation pipelines (filter, dedupe, quality)", "task_type": "eval", "difficulty": "foundation", "instruction": "Task: eval\nTopic: Dataset curation pipelines (filter, dedupe, quality)\nDifficulty: foundation\nTarget language: JavaScript\nContext: Fix a failing issue with tests as the oracle and produce a safe patch.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nEval:\n- Tasks: real issues\n- Metrics: pass@k, time-to-green\n- Gates: lint/security\n", "metadata": {"target_language": "JavaScript", "developer_needs": ["ci_integration", "repo_scale_reasoning", "tests_are_truth"]}}
{"id": "val_00071", "created": "2026-01-01", "topic": "Model merging, distillation, and continued pretraining", "task_type": "explain", "difficulty": "intermediate", "instruction": "Task: explain\nTopic: Model merging, distillation, and continued pretraining\nDifficulty: intermediate\nTarget language: Rust\nContext: Create an eval harness that reflects real developer workflows.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nDesign guidance with risks, metrics, acceptance criteria\n", "metadata": {"target_language": "Rust", "developer_needs": ["tooling", "cost_latency_tradeoffs", "repo_scale_reasoning"]}}
{"id": "val_00072", "created": "2026-01-01", "topic": "Code-specialized model families and sizing tradeoffs", "task_type": "review", "difficulty": "advanced", "instruction": "Task: review\nTopic: Code-specialized model families and sizing tradeoffs\nDifficulty: advanced\nTarget language: Java\nContext: Fix a failing issue with tests as the oracle and produce a safe patch.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nReview: correctness, security, performance, governance\n", "metadata": {"target_language": "Java", "developer_needs": ["tests_are_truth", "tooling", "evaluation_metrics"]}}
{"id": "val_00073", "created": "2026-01-01", "topic": "Code-specialized model families and sizing tradeoffs", "task_type": "agent_loop", "difficulty": "foundation", "instruction": "Task: agent_loop\nTopic: Code-specialized model families and sizing tradeoffs\nDifficulty: foundation\nTarget language: C#\nContext: Integrate an LLM agent into CI for a large monorepo.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nAgent loop: Plan \u2192 Edit (diff) \u2192 Test \u2192 Reflect \u2192 Human gate\n", "metadata": {"target_language": "C#", "developer_needs": ["ci_integration", "evaluation_metrics", "repo_scale_reasoning"]}}
{"id": "val_00074", "created": "2026-01-01", "topic": "Secure code generation and policy gates", "task_type": "compare", "difficulty": "advanced", "instruction": "Task: compare\nTopic: Secure code generation and policy gates\nDifficulty: advanced\nTarget language: TypeScript\nContext: Design a data pipeline for continued pretraining with auditability.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nCompare: capability, cost, latency, reliability, governance\n", "metadata": {"target_language": "TypeScript", "developer_needs": ["repo_scale_reasoning", "ci_integration", "reproducibility"]}}
{"id": "val_00075", "created": "2026-01-01", "topic": "Dataset curation pipelines (filter, dedupe, quality)", "task_type": "compare", "difficulty": "intermediate", "instruction": "Task: compare\nTopic: Dataset curation pipelines (filter, dedupe, quality)\nDifficulty: intermediate\nTarget language: Go\nContext: Evaluate two coding models for internal rollout under strict governance.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nCompare: capability, cost, latency, reliability, governance\n", "metadata": {"target_language": "Go", "developer_needs": ["security_gates", "documentation", "cost_latency_tradeoffs"]}}
{"id": "val_00076", "created": "2026-01-01", "topic": "Code-specialized model families and sizing tradeoffs", "task_type": "eval", "difficulty": "advanced", "instruction": "Task: eval\nTopic: Code-specialized model families and sizing tradeoffs\nDifficulty: advanced\nTarget language: Rust\nContext: Fix a failing issue with tests as the oracle and produce a safe patch.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nEval:\n- Tasks: real issues\n- Metrics: pass@k, time-to-green\n- Gates: lint/security\n", "metadata": {"target_language": "Rust", "developer_needs": ["documentation", "security_gates", "reproducibility"]}}
{"id": "val_00077", "created": "2026-01-01", "topic": "SWE-bench style real-repo evaluation", "task_type": "design", "difficulty": "intermediate", "instruction": "Task: design\nTopic: SWE-bench style real-repo evaluation\nDifficulty: intermediate\nTarget language: JavaScript\nContext: Create an eval harness that reflects real developer workflows.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nDesign guidance with risks, metrics, acceptance criteria\n", "metadata": {"target_language": "JavaScript", "developer_needs": ["reproducibility", "documentation", "evaluation_metrics"]}}
{"id": "val_00078", "created": "2026-01-01", "topic": "Multimodal dev workflows (docs, diagrams, traces)", "task_type": "code", "difficulty": "expert", "instruction": "Task: code\nTopic: Multimodal dev workflows (docs, diagrams, traces)\nDifficulty: expert\nTarget language: Java\nContext: Create an eval harness that reflects real developer workflows.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nDesign guidance with risks, metrics, acceptance criteria\n", "metadata": {"target_language": "Java", "developer_needs": ["reproducibility", "tests_are_truth", "cost_latency_tradeoffs"]}}
{"id": "val_00079", "created": "2026-01-01", "topic": "Governance, provenance, and licensing for code data", "task_type": "design", "difficulty": "expert", "instruction": "Task: design\nTopic: Governance, provenance, and licensing for code data\nDifficulty: expert\nTarget language: TypeScript\nContext: Create an eval harness that reflects real developer workflows.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nDesign guidance with risks, metrics, acceptance criteria\n", "metadata": {"target_language": "TypeScript", "developer_needs": ["reproducibility", "repo_scale_reasoning", "governance"]}}
{"id": "val_00080", "created": "2026-01-01", "topic": "Dataset curation pipelines (filter, dedupe, quality)", "task_type": "review", "difficulty": "advanced", "instruction": "Task: review\nTopic: Dataset curation pipelines (filter, dedupe, quality)\nDifficulty: advanced\nTarget language: Go\nContext: Design a data pipeline for continued pretraining with auditability.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nReview: correctness, security, performance, governance\n", "metadata": {"target_language": "Go", "developer_needs": ["ci_integration", "documentation", "governance"]}}
{"id": "val_00081", "created": "2026-01-01", "topic": "Secure code generation and policy gates", "task_type": "review", "difficulty": "foundation", "instruction": "Task: review\nTopic: Secure code generation and policy gates\nDifficulty: foundation\nTarget language: C#\nContext: Fix a failing issue with tests as the oracle and produce a safe patch.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nReview: correctness, security, performance, governance\n", "metadata": {"target_language": "C#", "developer_needs": ["cost_latency_tradeoffs", "security_gates", "tests_are_truth"]}}
{"id": "val_00082", "created": "2026-01-01", "topic": "Mixture-of-Experts (MoE) for code", "task_type": "compare", "difficulty": "intermediate", "instruction": "Task: compare\nTopic: Mixture-of-Experts (MoE) for code\nDifficulty: intermediate\nTarget language: Java\nContext: Fix a failing issue with tests as the oracle and produce a safe patch.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nCompare: capability, cost, latency, reliability, governance\n", "metadata": {"target_language": "Java", "developer_needs": ["security_gates", "evaluation_metrics", "ci_integration"]}}
{"id": "val_00083", "created": "2026-01-01", "topic": "Mixture-of-Experts (MoE) for code", "task_type": "eval", "difficulty": "advanced", "instruction": "Task: eval\nTopic: Mixture-of-Experts (MoE) for code\nDifficulty: advanced\nTarget language: Python\nContext: Integrate an LLM agent into CI for a large monorepo.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nEval:\n- Tasks: real issues\n- Metrics: pass@k, time-to-green\n- Gates: lint/security\n", "metadata": {"target_language": "Python", "developer_needs": ["tooling", "cost_latency_tradeoffs", "ci_integration"]}}
{"id": "val_00084", "created": "2026-01-01", "topic": "SWE-bench style real-repo evaluation", "task_type": "eval", "difficulty": "expert", "instruction": "Task: eval\nTopic: SWE-bench style real-repo evaluation\nDifficulty: expert\nTarget language: C#\nContext: Create an eval harness that reflects real developer workflows.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nEval:\n- Tasks: real issues\n- Metrics: pass@k, time-to-green\n- Gates: lint/security\n", "metadata": {"target_language": "C#", "developer_needs": ["ci_integration", "governance", "tooling"]}}
{"id": "val_00085", "created": "2026-01-01", "topic": "Agentic coding systems (plan\u2192edit\u2192test\u2192reflect)", "task_type": "explain", "difficulty": "expert", "instruction": "Task: explain\nTopic: Agentic coding systems (plan\u2192edit\u2192test\u2192reflect)\nDifficulty: expert\nTarget language: Bash\nContext: Integrate an LLM agent into CI for a large monorepo.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nDesign guidance with risks, metrics, acceptance criteria\n", "metadata": {"target_language": "Bash", "developer_needs": ["ci_integration", "tooling", "governance"]}}
{"id": "val_00086", "created": "2026-01-01", "topic": "Reasoning-first coding models and tunable deliberation", "task_type": "compare", "difficulty": "foundation", "instruction": "Task: compare\nTopic: Reasoning-first coding models and tunable deliberation\nDifficulty: foundation\nTarget language: Go\nContext: Evaluate two coding models for internal rollout under strict governance.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nCompare: capability, cost, latency, reliability, governance\n", "metadata": {"target_language": "Go", "developer_needs": ["tests_are_truth", "cost_latency_tradeoffs", "tooling"]}}
{"id": "val_00087", "created": "2026-01-01", "topic": "Reasoning-first coding models and tunable deliberation", "task_type": "review", "difficulty": "foundation", "instruction": "Task: review\nTopic: Reasoning-first coding models and tunable deliberation\nDifficulty: foundation\nTarget language: Python\nContext: Design a data pipeline for continued pretraining with auditability.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nReview: correctness, security, performance, governance\n", "metadata": {"target_language": "Python", "developer_needs": ["repo_scale_reasoning", "ci_integration", "cost_latency_tradeoffs"]}}
{"id": "val_00088", "created": "2026-01-01", "topic": "Agentic coding systems (plan\u2192edit\u2192test\u2192reflect)", "task_type": "data_pipeline", "difficulty": "expert", "instruction": "Task: data_pipeline\nTopic: Agentic coding systems (plan\u2192edit\u2192test\u2192reflect)\nDifficulty: expert\nTarget language: Python\nContext: Evaluate two coding models for internal rollout under strict governance.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nPipeline:\n1) Ingest\n2) Normalize\n3) Filter\n4) Dedupe\n5) Quality score\n6) Sample\n7) Audit\n", "metadata": {"target_language": "Python", "developer_needs": ["ci_integration", "evaluation_metrics", "governance"]}}
{"id": "val_00089", "created": "2026-01-01", "topic": "Governance, provenance, and licensing for code data", "task_type": "eval", "difficulty": "intermediate", "instruction": "Task: eval\nTopic: Governance, provenance, and licensing for code data\nDifficulty: intermediate\nTarget language: JavaScript\nContext: Create an eval harness that reflects real developer workflows.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nEval:\n- Tasks: real issues\n- Metrics: pass@k, time-to-green\n- Gates: lint/security\n", "metadata": {"target_language": "JavaScript", "developer_needs": ["cost_latency_tradeoffs", "reproducibility", "ci_integration"]}}
{"id": "val_00090", "created": "2026-01-01", "topic": "Tool calling, sandboxes, and CI integration", "task_type": "data_pipeline", "difficulty": "intermediate", "instruction": "Task: data_pipeline\nTopic: Tool calling, sandboxes, and CI integration\nDifficulty: intermediate\nTarget language: JavaScript\nContext: Create an eval harness that reflects real developer workflows.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nPipeline:\n1) Ingest\n2) Normalize\n3) Filter\n4) Dedupe\n5) Quality score\n6) Sample\n7) Audit\n", "metadata": {"target_language": "JavaScript", "developer_needs": ["documentation", "ci_integration", "reproducibility"]}}
{"id": "val_00091", "created": "2026-01-01", "topic": "Multimodal dev workflows (docs, diagrams, traces)", "task_type": "compare", "difficulty": "advanced", "instruction": "Task: compare\nTopic: Multimodal dev workflows (docs, diagrams, traces)\nDifficulty: advanced\nTarget language: Bash\nContext: Create an eval harness that reflects real developer workflows.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nCompare: capability, cost, latency, reliability, governance\n", "metadata": {"target_language": "Bash", "developer_needs": ["documentation", "reproducibility", "tests_are_truth"]}}
{"id": "val_00092", "created": "2026-01-01", "topic": "Multimodal dev workflows (docs, diagrams, traces)", "task_type": "code", "difficulty": "intermediate", "instruction": "Task: code\nTopic: Multimodal dev workflows (docs, diagrams, traces)\nDifficulty: intermediate\nTarget language: Java\nContext: Fix a failing issue with tests as the oracle and produce a safe patch.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nDesign guidance with risks, metrics, acceptance criteria\n", "metadata": {"target_language": "Java", "developer_needs": ["reproducibility", "security_gates", "cost_latency_tradeoffs"]}}
{"id": "val_00093", "created": "2026-01-01", "topic": "Dataset curation pipelines (filter, dedupe, quality)", "task_type": "data_pipeline", "difficulty": "intermediate", "instruction": "Task: data_pipeline\nTopic: Dataset curation pipelines (filter, dedupe, quality)\nDifficulty: intermediate\nTarget language: Go\nContext: Design a data pipeline for continued pretraining with auditability.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nPipeline:\n1) Ingest\n2) Normalize\n3) Filter\n4) Dedupe\n5) Quality score\n6) Sample\n7) Audit\n", "metadata": {"target_language": "Go", "developer_needs": ["ci_integration", "cost_latency_tradeoffs", "evaluation_metrics"]}}
{"id": "val_00094", "created": "2026-01-01", "topic": "Code-specialized model families and sizing tradeoffs", "task_type": "compare", "difficulty": "foundation", "instruction": "Task: compare\nTopic: Code-specialized model families and sizing tradeoffs\nDifficulty: foundation\nTarget language: Rust\nContext: Create an eval harness that reflects real developer workflows.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nCompare: capability, cost, latency, reliability, governance\n", "metadata": {"target_language": "Rust", "developer_needs": ["repo_scale_reasoning", "governance", "ci_integration"]}}
{"id": "val_00095", "created": "2026-01-01", "topic": "Multimodal dev workflows (docs, diagrams, traces)", "task_type": "agent_loop", "difficulty": "advanced", "instruction": "Task: agent_loop\nTopic: Multimodal dev workflows (docs, diagrams, traces)\nDifficulty: advanced\nTarget language: TypeScript\nContext: Evaluate two coding models for internal rollout under strict governance.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nAgent loop: Plan \u2192 Edit (diff) \u2192 Test \u2192 Reflect \u2192 Human gate\n", "metadata": {"target_language": "TypeScript", "developer_needs": ["documentation", "security_gates", "tests_are_truth"]}}
{"id": "val_00096", "created": "2026-01-01", "topic": "Tool calling, sandboxes, and CI integration", "task_type": "design", "difficulty": "expert", "instruction": "Task: design\nTopic: Tool calling, sandboxes, and CI integration\nDifficulty: expert\nTarget language: Go\nContext: Evaluate two coding models for internal rollout under strict governance.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nDesign guidance with risks, metrics, acceptance criteria\n", "metadata": {"target_language": "Go", "developer_needs": ["tooling", "evaluation_metrics", "repo_scale_reasoning"]}}
{"id": "val_00097", "created": "2026-01-01", "topic": "Governance, provenance, and licensing for code data", "task_type": "review", "difficulty": "expert", "instruction": "Task: review\nTopic: Governance, provenance, and licensing for code data\nDifficulty: expert\nTarget language: C#\nContext: Fix a failing issue with tests as the oracle and produce a safe patch.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nReview: correctness, security, performance, governance\n", "metadata": {"target_language": "C#", "developer_needs": ["cost_latency_tradeoffs", "tests_are_truth", "governance"]}}
{"id": "val_00098", "created": "2026-01-01", "topic": "Extended context and repo-scale understanding", "task_type": "explain", "difficulty": "intermediate", "instruction": "Task: explain\nTopic: Extended context and repo-scale understanding\nDifficulty: intermediate\nTarget language: Python\nContext: Fix a failing issue with tests as the oracle and produce a safe patch.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nDesign guidance with risks, metrics, acceptance criteria\n", "metadata": {"target_language": "Python", "developer_needs": ["reproducibility", "tests_are_truth", "repo_scale_reasoning"]}}
{"id": "val_00099", "created": "2026-01-01", "topic": "Secure code generation and policy gates", "task_type": "code", "difficulty": "intermediate", "instruction": "Task: code\nTopic: Secure code generation and policy gates\nDifficulty: intermediate\nTarget language: C#\nContext: Create an eval harness that reflects real developer workflows.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nDesign guidance with risks, metrics, acceptance criteria\n", "metadata": {"target_language": "C#", "developer_needs": ["governance", "security_gates", "reproducibility"]}}
{"id": "val_00100", "created": "2026-01-01", "topic": "Governance, provenance, and licensing for code data", "task_type": "design", "difficulty": "expert", "instruction": "Task: design\nTopic: Governance, provenance, and licensing for code data\nDifficulty: expert\nTarget language: SQL\nContext: Design a data pipeline for continued pretraining with auditability.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nDesign guidance with risks, metrics, acceptance criteria\n", "metadata": {"target_language": "SQL", "developer_needs": ["tooling", "documentation", "tests_are_truth"]}}
{"id": "val_00101", "created": "2026-01-01", "topic": "Governance, provenance, and licensing for code data", "task_type": "code", "difficulty": "foundation", "instruction": "Task: code\nTopic: Governance, provenance, and licensing for code data\nDifficulty: foundation\nTarget language: Go\nContext: Fix a failing issue with tests as the oracle and produce a safe patch.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nDesign guidance with risks, metrics, acceptance criteria\n", "metadata": {"target_language": "Go", "developer_needs": ["ci_integration", "repo_scale_reasoning", "tooling"]}}
{"id": "val_00102", "created": "2026-01-01", "topic": "Model merging, distillation, and continued pretraining", "task_type": "review", "difficulty": "expert", "instruction": "Task: review\nTopic: Model merging, distillation, and continued pretraining\nDifficulty: expert\nTarget language: SQL\nContext: Fix a failing issue with tests as the oracle and produce a safe patch.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nReview: correctness, security, performance, governance\n", "metadata": {"target_language": "SQL", "developer_needs": ["reproducibility", "cost_latency_tradeoffs", "repo_scale_reasoning"]}}
{"id": "val_00103", "created": "2026-01-01", "topic": "SWE-bench style real-repo evaluation", "task_type": "explain", "difficulty": "expert", "instruction": "Task: explain\nTopic: SWE-bench style real-repo evaluation\nDifficulty: expert\nTarget language: TypeScript\nContext: Evaluate two coding models for internal rollout under strict governance.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nDesign guidance with risks, metrics, acceptance criteria\n", "metadata": {"target_language": "TypeScript", "developer_needs": ["evaluation_metrics", "ci_integration", "cost_latency_tradeoffs"]}}
{"id": "val_00104", "created": "2026-01-01", "topic": "Model merging, distillation, and continued pretraining", "task_type": "data_pipeline", "difficulty": "advanced", "instruction": "Task: data_pipeline\nTopic: Model merging, distillation, and continued pretraining\nDifficulty: advanced\nTarget language: Python\nContext: Design a data pipeline for continued pretraining with auditability.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nPipeline:\n1) Ingest\n2) Normalize\n3) Filter\n4) Dedupe\n5) Quality score\n6) Sample\n7) Audit\n", "metadata": {"target_language": "Python", "developer_needs": ["governance", "repo_scale_reasoning", "evaluation_metrics"]}}
{"id": "val_00105", "created": "2026-01-01", "topic": "Tool calling, sandboxes, and CI integration", "task_type": "design", "difficulty": "advanced", "instruction": "Task: design\nTopic: Tool calling, sandboxes, and CI integration\nDifficulty: advanced\nTarget language: C#\nContext: Evaluate two coding models for internal rollout under strict governance.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nDesign guidance with risks, metrics, acceptance criteria\n", "metadata": {"target_language": "C#", "developer_needs": ["governance", "documentation", "tests_are_truth"]}}
{"id": "val_00106", "created": "2026-01-01", "topic": "Dataset curation pipelines (filter, dedupe, quality)", "task_type": "data_pipeline", "difficulty": "advanced", "instruction": "Task: data_pipeline\nTopic: Dataset curation pipelines (filter, dedupe, quality)\nDifficulty: advanced\nTarget language: Java\nContext: Create an eval harness that reflects real developer workflows.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nPipeline:\n1) Ingest\n2) Normalize\n3) Filter\n4) Dedupe\n5) Quality score\n6) Sample\n7) Audit\n", "metadata": {"target_language": "Java", "developer_needs": ["governance", "reproducibility", "security_gates"]}}
{"id": "val_00107", "created": "2026-01-01", "topic": "Model merging, distillation, and continued pretraining", "task_type": "code", "difficulty": "expert", "instruction": "Task: code\nTopic: Model merging, distillation, and continued pretraining\nDifficulty: expert\nTarget language: Bash\nContext: Design a data pipeline for continued pretraining with auditability.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nDesign guidance with risks, metrics, acceptance criteria\n", "metadata": {"target_language": "Bash", "developer_needs": ["evaluation_metrics", "reproducibility", "security_gates"]}}
{"id": "val_00108", "created": "2026-01-01", "topic": "Multimodal dev workflows (docs, diagrams, traces)", "task_type": "review", "difficulty": "expert", "instruction": "Task: review\nTopic: Multimodal dev workflows (docs, diagrams, traces)\nDifficulty: expert\nTarget language: Rust\nContext: Evaluate two coding models for internal rollout under strict governance.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nReview: correctness, security, performance, governance\n", "metadata": {"target_language": "Rust", "developer_needs": ["documentation", "governance", "security_gates"]}}
{"id": "val_00109", "created": "2026-01-01", "topic": "SWE-bench style real-repo evaluation", "task_type": "agent_loop", "difficulty": "intermediate", "instruction": "Task: agent_loop\nTopic: SWE-bench style real-repo evaluation\nDifficulty: intermediate\nTarget language: C#\nContext: Design a data pipeline for continued pretraining with auditability.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nAgent loop: Plan \u2192 Edit (diff) \u2192 Test \u2192 Reflect \u2192 Human gate\n", "metadata": {"target_language": "C#", "developer_needs": ["ci_integration", "repo_scale_reasoning", "tests_are_truth"]}}
{"id": "val_00110", "created": "2026-01-01", "topic": "Extended context and repo-scale understanding", "task_type": "code", "difficulty": "expert", "instruction": "Task: code\nTopic: Extended context and repo-scale understanding\nDifficulty: expert\nTarget language: Bash\nContext: Create an eval harness that reflects real developer workflows.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nDesign guidance with risks, metrics, acceptance criteria\n", "metadata": {"target_language": "Bash", "developer_needs": ["cost_latency_tradeoffs", "governance", "repo_scale_reasoning"]}}
{"id": "val_00111", "created": "2026-01-01", "topic": "Governance, provenance, and licensing for code data", "task_type": "data_pipeline", "difficulty": "expert", "instruction": "Task: data_pipeline\nTopic: Governance, provenance, and licensing for code data\nDifficulty: expert\nTarget language: Go\nContext: Evaluate two coding models for internal rollout under strict governance.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nPipeline:\n1) Ingest\n2) Normalize\n3) Filter\n4) Dedupe\n5) Quality score\n6) Sample\n7) Audit\n", "metadata": {"target_language": "Go", "developer_needs": ["reproducibility", "cost_latency_tradeoffs", "evaluation_metrics"]}}
{"id": "val_00112", "created": "2026-01-01", "topic": "SWE-bench style real-repo evaluation", "task_type": "explain", "difficulty": "expert", "instruction": "Task: explain\nTopic: SWE-bench style real-repo evaluation\nDifficulty: expert\nTarget language: Go\nContext: Integrate an LLM agent into CI for a large monorepo.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nDesign guidance with risks, metrics, acceptance criteria\n", "metadata": {"target_language": "Go", "developer_needs": ["ci_integration", "tests_are_truth", "repo_scale_reasoning"]}}
{"id": "val_00113", "created": "2026-01-01", "topic": "Governance, provenance, and licensing for code data", "task_type": "design", "difficulty": "foundation", "instruction": "Task: design\nTopic: Governance, provenance, and licensing for code data\nDifficulty: foundation\nTarget language: Rust\nContext: Design a data pipeline for continued pretraining with auditability.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nDesign guidance with risks, metrics, acceptance criteria\n", "metadata": {"target_language": "Rust", "developer_needs": ["tooling", "ci_integration", "governance"]}}
{"id": "val_00114", "created": "2026-01-01", "topic": "Code-specialized model families and sizing tradeoffs", "task_type": "data_pipeline", "difficulty": "advanced", "instruction": "Task: data_pipeline\nTopic: Code-specialized model families and sizing tradeoffs\nDifficulty: advanced\nTarget language: Python\nContext: Evaluate two coding models for internal rollout under strict governance.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nPipeline:\n1) Ingest\n2) Normalize\n3) Filter\n4) Dedupe\n5) Quality score\n6) Sample\n7) Audit\n", "metadata": {"target_language": "Python", "developer_needs": ["reproducibility", "security_gates", "governance"]}}
{"id": "val_00115", "created": "2026-01-01", "topic": "Tool calling, sandboxes, and CI integration", "task_type": "code", "difficulty": "expert", "instruction": "Task: code\nTopic: Tool calling, sandboxes, and CI integration\nDifficulty: expert\nTarget language: Rust\nContext: Fix a failing issue with tests as the oracle and produce a safe patch.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nDesign guidance with risks, metrics, acceptance criteria\n", "metadata": {"target_language": "Rust", "developer_needs": ["tests_are_truth", "security_gates", "documentation"]}}
{"id": "val_00116", "created": "2026-01-01", "topic": "Reasoning-first coding models and tunable deliberation", "task_type": "review", "difficulty": "expert", "instruction": "Task: review\nTopic: Reasoning-first coding models and tunable deliberation\nDifficulty: expert\nTarget language: Go\nContext: Fix a failing issue with tests as the oracle and produce a safe patch.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nReview: correctness, security, performance, governance\n", "metadata": {"target_language": "Go", "developer_needs": ["cost_latency_tradeoffs", "reproducibility", "repo_scale_reasoning"]}}
{"id": "val_00117", "created": "2026-01-01", "topic": "Multimodal dev workflows (docs, diagrams, traces)", "task_type": "code", "difficulty": "intermediate", "instruction": "Task: code\nTopic: Multimodal dev workflows (docs, diagrams, traces)\nDifficulty: intermediate\nTarget language: C#\nContext: Evaluate two coding models for internal rollout under strict governance.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nDesign guidance with risks, metrics, acceptance criteria\n", "metadata": {"target_language": "C#", "developer_needs": ["repo_scale_reasoning", "security_gates", "tooling"]}}
{"id": "val_00118", "created": "2026-01-01", "topic": "Tool calling, sandboxes, and CI integration", "task_type": "code", "difficulty": "expert", "instruction": "Task: code\nTopic: Tool calling, sandboxes, and CI integration\nDifficulty: expert\nTarget language: JavaScript\nContext: Design a data pipeline for continued pretraining with auditability.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nDesign guidance with risks, metrics, acceptance criteria\n", "metadata": {"target_language": "JavaScript", "developer_needs": ["governance", "reproducibility", "cost_latency_tradeoffs"]}}
{"id": "val_00119", "created": "2026-01-01", "topic": "Mixture-of-Experts (MoE) for code", "task_type": "compare", "difficulty": "expert", "instruction": "Task: compare\nTopic: Mixture-of-Experts (MoE) for code\nDifficulty: expert\nTarget language: Java\nContext: Integrate an LLM agent into CI for a large monorepo.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nCompare: capability, cost, latency, reliability, governance\n", "metadata": {"target_language": "Java", "developer_needs": ["evaluation_metrics", "repo_scale_reasoning", "documentation"]}}
{"id": "val_00120", "created": "2026-01-01", "topic": "Model merging, distillation, and continued pretraining", "task_type": "compare", "difficulty": "intermediate", "instruction": "Task: compare\nTopic: Model merging, distillation, and continued pretraining\nDifficulty: intermediate\nTarget language: TypeScript\nContext: Design a data pipeline for continued pretraining with auditability.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nCompare: capability, cost, latency, reliability, governance\n", "metadata": {"target_language": "TypeScript", "developer_needs": ["documentation", "tooling", "cost_latency_tradeoffs"]}}
{"id": "val_00121", "created": "2026-01-01", "topic": "Code-specialized model families and sizing tradeoffs", "task_type": "code", "difficulty": "intermediate", "instruction": "Task: code\nTopic: Code-specialized model families and sizing tradeoffs\nDifficulty: intermediate\nTarget language: Python\nContext: Design a data pipeline for continued pretraining with auditability.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nReference scaffold:\n```python\ndef agent_loop(plan, edit, test, issue, max_iters=3):\n    history = []\n    p = plan(issue)\n    for _ in range(max_iters):\n        patch = edit(issue, p)\n        ok, report = test(patch)\n        history.append({\"plan\": p, \"passed\": ok, \"report\": report[:200]})\n        if ok:\n            return patch, history\n        p = p + \" | refine from failures\"\n    return patch, history\n\n```\nOperational notes: sandbox, pinned deps, human gate.", "metadata": {"target_language": "Python", "developer_needs": ["tooling", "repo_scale_reasoning", "reproducibility"]}}
{"id": "val_00122", "created": "2026-01-01", "topic": "Reasoning-first coding models and tunable deliberation", "task_type": "data_pipeline", "difficulty": "foundation", "instruction": "Task: data_pipeline\nTopic: Reasoning-first coding models and tunable deliberation\nDifficulty: foundation\nTarget language: JavaScript\nContext: Design a data pipeline for continued pretraining with auditability.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nPipeline:\n1) Ingest\n2) Normalize\n3) Filter\n4) Dedupe\n5) Quality score\n6) Sample\n7) Audit\n", "metadata": {"target_language": "JavaScript", "developer_needs": ["evaluation_metrics", "cost_latency_tradeoffs", "security_gates"]}}
{"id": "val_00123", "created": "2026-01-01", "topic": "Extended context and repo-scale understanding", "task_type": "agent_loop", "difficulty": "foundation", "instruction": "Task: agent_loop\nTopic: Extended context and repo-scale understanding\nDifficulty: foundation\nTarget language: Go\nContext: Integrate an LLM agent into CI for a large monorepo.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nAgent loop: Plan \u2192 Edit (diff) \u2192 Test \u2192 Reflect \u2192 Human gate\n", "metadata": {"target_language": "Go", "developer_needs": ["security_gates", "governance", "repo_scale_reasoning"]}}
{"id": "val_00124", "created": "2026-01-01", "topic": "Mixture-of-Experts (MoE) for code", "task_type": "eval", "difficulty": "intermediate", "instruction": "Task: eval\nTopic: Mixture-of-Experts (MoE) for code\nDifficulty: intermediate\nTarget language: TypeScript\nContext: Fix a failing issue with tests as the oracle and produce a safe patch.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nEval:\n- Tasks: real issues\n- Metrics: pass@k, time-to-green\n- Gates: lint/security\n", "metadata": {"target_language": "TypeScript", "developer_needs": ["reproducibility", "repo_scale_reasoning", "security_gates"]}}
{"id": "val_00125", "created": "2026-01-01", "topic": "Code-specialized model families and sizing tradeoffs", "task_type": "explain", "difficulty": "expert", "instruction": "Task: explain\nTopic: Code-specialized model families and sizing tradeoffs\nDifficulty: expert\nTarget language: Rust\nContext: Integrate an LLM agent into CI for a large monorepo.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nDesign guidance with risks, metrics, acceptance criteria\n", "metadata": {"target_language": "Rust", "developer_needs": ["evaluation_metrics", "ci_integration", "security_gates"]}}
{"id": "val_00126", "created": "2026-01-01", "topic": "Tool calling, sandboxes, and CI integration", "task_type": "explain", "difficulty": "expert", "instruction": "Task: explain\nTopic: Tool calling, sandboxes, and CI integration\nDifficulty: expert\nTarget language: C#\nContext: Fix a failing issue with tests as the oracle and produce a safe patch.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nDesign guidance with risks, metrics, acceptance criteria\n", "metadata": {"target_language": "C#", "developer_needs": ["reproducibility", "security_gates", "evaluation_metrics"]}}
{"id": "val_00127", "created": "2026-01-01", "topic": "Multimodal dev workflows (docs, diagrams, traces)", "task_type": "compare", "difficulty": "expert", "instruction": "Task: compare\nTopic: Multimodal dev workflows (docs, diagrams, traces)\nDifficulty: expert\nTarget language: TypeScript\nContext: Evaluate two coding models for internal rollout under strict governance.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nCompare: capability, cost, latency, reliability, governance\n", "metadata": {"target_language": "TypeScript", "developer_needs": ["governance", "documentation", "ci_integration"]}}
{"id": "val_00128", "created": "2026-01-01", "topic": "SWE-bench style real-repo evaluation", "task_type": "data_pipeline", "difficulty": "advanced", "instruction": "Task: data_pipeline\nTopic: SWE-bench style real-repo evaluation\nDifficulty: advanced\nTarget language: Go\nContext: Evaluate two coding models for internal rollout under strict governance.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nPipeline:\n1) Ingest\n2) Normalize\n3) Filter\n4) Dedupe\n5) Quality score\n6) Sample\n7) Audit\n", "metadata": {"target_language": "Go", "developer_needs": ["security_gates", "cost_latency_tradeoffs", "ci_integration"]}}
{"id": "val_00129", "created": "2026-01-01", "topic": "Reasoning-first coding models and tunable deliberation", "task_type": "eval", "difficulty": "intermediate", "instruction": "Task: eval\nTopic: Reasoning-first coding models and tunable deliberation\nDifficulty: intermediate\nTarget language: Python\nContext: Create an eval harness that reflects real developer workflows.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nEval:\n- Tasks: real issues\n- Metrics: pass@k, time-to-green\n- Gates: lint/security\n", "metadata": {"target_language": "Python", "developer_needs": ["governance", "reproducibility", "evaluation_metrics"]}}
{"id": "val_00130", "created": "2026-01-01", "topic": "Agentic coding systems (plan\u2192edit\u2192test\u2192reflect)", "task_type": "code", "difficulty": "advanced", "instruction": "Task: code\nTopic: Agentic coding systems (plan\u2192edit\u2192test\u2192reflect)\nDifficulty: advanced\nTarget language: Rust\nContext: Create an eval harness that reflects real developer workflows.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nDesign guidance with risks, metrics, acceptance criteria\n", "metadata": {"target_language": "Rust", "developer_needs": ["tests_are_truth", "documentation", "reproducibility"]}}
{"id": "val_00131", "created": "2026-01-01", "topic": "Agentic coding systems (plan\u2192edit\u2192test\u2192reflect)", "task_type": "agent_loop", "difficulty": "advanced", "instruction": "Task: agent_loop\nTopic: Agentic coding systems (plan\u2192edit\u2192test\u2192reflect)\nDifficulty: advanced\nTarget language: Java\nContext: Fix a failing issue with tests as the oracle and produce a safe patch.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nAgent loop: Plan \u2192 Edit (diff) \u2192 Test \u2192 Reflect \u2192 Human gate\n", "metadata": {"target_language": "Java", "developer_needs": ["security_gates", "cost_latency_tradeoffs", "tests_are_truth"]}}
{"id": "val_00132", "created": "2026-01-01", "topic": "Reasoning-first coding models and tunable deliberation", "task_type": "design", "difficulty": "intermediate", "instruction": "Task: design\nTopic: Reasoning-first coding models and tunable deliberation\nDifficulty: intermediate\nTarget language: TypeScript\nContext: Evaluate two coding models for internal rollout under strict governance.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nDesign guidance with risks, metrics, acceptance criteria\n", "metadata": {"target_language": "TypeScript", "developer_needs": ["documentation", "cost_latency_tradeoffs", "tooling"]}}
{"id": "val_00133", "created": "2026-01-01", "topic": "Code-specialized model families and sizing tradeoffs", "task_type": "explain", "difficulty": "foundation", "instruction": "Task: explain\nTopic: Code-specialized model families and sizing tradeoffs\nDifficulty: foundation\nTarget language: SQL\nContext: Create an eval harness that reflects real developer workflows.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nDesign guidance with risks, metrics, acceptance criteria\n", "metadata": {"target_language": "SQL", "developer_needs": ["cost_latency_tradeoffs", "ci_integration", "tests_are_truth"]}}
{"id": "val_00134", "created": "2026-01-01", "topic": "Extended context and repo-scale understanding", "task_type": "review", "difficulty": "expert", "instruction": "Task: review\nTopic: Extended context and repo-scale understanding\nDifficulty: expert\nTarget language: JavaScript\nContext: Evaluate two coding models for internal rollout under strict governance.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nReview: correctness, security, performance, governance\n", "metadata": {"target_language": "JavaScript", "developer_needs": ["repo_scale_reasoning", "reproducibility", "ci_integration"]}}
{"id": "val_00135", "created": "2026-01-01", "topic": "Code-specialized model families and sizing tradeoffs", "task_type": "eval", "difficulty": "expert", "instruction": "Task: eval\nTopic: Code-specialized model families and sizing tradeoffs\nDifficulty: expert\nTarget language: TypeScript\nContext: Integrate an LLM agent into CI for a large monorepo.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nEval:\n- Tasks: real issues\n- Metrics: pass@k, time-to-green\n- Gates: lint/security\n", "metadata": {"target_language": "TypeScript", "developer_needs": ["security_gates", "repo_scale_reasoning", "tests_are_truth"]}}
{"id": "val_00136", "created": "2026-01-01", "topic": "Secure code generation and policy gates", "task_type": "compare", "difficulty": "foundation", "instruction": "Task: compare\nTopic: Secure code generation and policy gates\nDifficulty: foundation\nTarget language: JavaScript\nContext: Fix a failing issue with tests as the oracle and produce a safe patch.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nCompare: capability, cost, latency, reliability, governance\n", "metadata": {"target_language": "JavaScript", "developer_needs": ["evaluation_metrics", "documentation", "ci_integration"]}}
{"id": "val_00137", "created": "2026-01-01", "topic": "Mixture-of-Experts (MoE) for code", "task_type": "data_pipeline", "difficulty": "advanced", "instruction": "Task: data_pipeline\nTopic: Mixture-of-Experts (MoE) for code\nDifficulty: advanced\nTarget language: JavaScript\nContext: Design a data pipeline for continued pretraining with auditability.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nPipeline:\n1) Ingest\n2) Normalize\n3) Filter\n4) Dedupe\n5) Quality score\n6) Sample\n7) Audit\n", "metadata": {"target_language": "JavaScript", "developer_needs": ["documentation", "cost_latency_tradeoffs", "reproducibility"]}}
{"id": "val_00138", "created": "2026-01-01", "topic": "Agentic coding systems (plan\u2192edit\u2192test\u2192reflect)", "task_type": "eval", "difficulty": "advanced", "instruction": "Task: eval\nTopic: Agentic coding systems (plan\u2192edit\u2192test\u2192reflect)\nDifficulty: advanced\nTarget language: Go\nContext: Integrate an LLM agent into CI for a large monorepo.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nEval:\n- Tasks: real issues\n- Metrics: pass@k, time-to-green\n- Gates: lint/security\n", "metadata": {"target_language": "Go", "developer_needs": ["governance", "ci_integration", "cost_latency_tradeoffs"]}}
{"id": "val_00139", "created": "2026-01-01", "topic": "Governance, provenance, and licensing for code data", "task_type": "review", "difficulty": "intermediate", "instruction": "Task: review\nTopic: Governance, provenance, and licensing for code data\nDifficulty: intermediate\nTarget language: JavaScript\nContext: Evaluate two coding models for internal rollout under strict governance.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nReview: correctness, security, performance, governance\n", "metadata": {"target_language": "JavaScript", "developer_needs": ["tooling", "tests_are_truth", "governance"]}}
{"id": "val_00140", "created": "2026-01-01", "topic": "Multimodal dev workflows (docs, diagrams, traces)", "task_type": "code", "difficulty": "intermediate", "instruction": "Task: code\nTopic: Multimodal dev workflows (docs, diagrams, traces)\nDifficulty: intermediate\nTarget language: JavaScript\nContext: Create an eval harness that reflects real developer workflows.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nDesign guidance with risks, metrics, acceptance criteria\n", "metadata": {"target_language": "JavaScript", "developer_needs": ["evaluation_metrics", "tooling", "tests_are_truth"]}}
{"id": "val_00141", "created": "2026-01-01", "topic": "Reasoning-first coding models and tunable deliberation", "task_type": "agent_loop", "difficulty": "advanced", "instruction": "Task: agent_loop\nTopic: Reasoning-first coding models and tunable deliberation\nDifficulty: advanced\nTarget language: JavaScript\nContext: Create an eval harness that reflects real developer workflows.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nAgent loop: Plan \u2192 Edit (diff) \u2192 Test \u2192 Reflect \u2192 Human gate\n", "metadata": {"target_language": "JavaScript", "developer_needs": ["security_gates", "ci_integration", "documentation"]}}
{"id": "val_00142", "created": "2026-01-01", "topic": "Dataset curation pipelines (filter, dedupe, quality)", "task_type": "data_pipeline", "difficulty": "advanced", "instruction": "Task: data_pipeline\nTopic: Dataset curation pipelines (filter, dedupe, quality)\nDifficulty: advanced\nTarget language: C#\nContext: Fix a failing issue with tests as the oracle and produce a safe patch.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nPipeline:\n1) Ingest\n2) Normalize\n3) Filter\n4) Dedupe\n5) Quality score\n6) Sample\n7) Audit\n", "metadata": {"target_language": "C#", "developer_needs": ["documentation", "evaluation_metrics", "reproducibility"]}}
{"id": "val_00143", "created": "2026-01-01", "topic": "Code-specialized model families and sizing tradeoffs", "task_type": "design", "difficulty": "foundation", "instruction": "Task: design\nTopic: Code-specialized model families and sizing tradeoffs\nDifficulty: foundation\nTarget language: C#\nContext: Fix a failing issue with tests as the oracle and produce a safe patch.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nDesign guidance with risks, metrics, acceptance criteria\n", "metadata": {"target_language": "C#", "developer_needs": ["cost_latency_tradeoffs", "documentation", "tests_are_truth"]}}
{"id": "val_00144", "created": "2026-01-01", "topic": "Secure code generation and policy gates", "task_type": "data_pipeline", "difficulty": "advanced", "instruction": "Task: data_pipeline\nTopic: Secure code generation and policy gates\nDifficulty: advanced\nTarget language: TypeScript\nContext: Fix a failing issue with tests as the oracle and produce a safe patch.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nPipeline:\n1) Ingest\n2) Normalize\n3) Filter\n4) Dedupe\n5) Quality score\n6) Sample\n7) Audit\n", "metadata": {"target_language": "TypeScript", "developer_needs": ["cost_latency_tradeoffs", "repo_scale_reasoning", "evaluation_metrics"]}}
{"id": "val_00145", "created": "2026-01-01", "topic": "Agentic coding systems (plan\u2192edit\u2192test\u2192reflect)", "task_type": "agent_loop", "difficulty": "advanced", "instruction": "Task: agent_loop\nTopic: Agentic coding systems (plan\u2192edit\u2192test\u2192reflect)\nDifficulty: advanced\nTarget language: C#\nContext: Create an eval harness that reflects real developer workflows.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nAgent loop: Plan \u2192 Edit (diff) \u2192 Test \u2192 Reflect \u2192 Human gate\n", "metadata": {"target_language": "C#", "developer_needs": ["repo_scale_reasoning", "documentation", "evaluation_metrics"]}}
{"id": "val_00146", "created": "2026-01-01", "topic": "Code-specialized model families and sizing tradeoffs", "task_type": "explain", "difficulty": "advanced", "instruction": "Task: explain\nTopic: Code-specialized model families and sizing tradeoffs\nDifficulty: advanced\nTarget language: Python\nContext: Create an eval harness that reflects real developer workflows.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nDesign guidance with risks, metrics, acceptance criteria\n", "metadata": {"target_language": "Python", "developer_needs": ["tooling", "repo_scale_reasoning", "security_gates"]}}
{"id": "val_00147", "created": "2026-01-01", "topic": "Reasoning-first coding models and tunable deliberation", "task_type": "agent_loop", "difficulty": "intermediate", "instruction": "Task: agent_loop\nTopic: Reasoning-first coding models and tunable deliberation\nDifficulty: intermediate\nTarget language: JavaScript\nContext: Design a data pipeline for continued pretraining with auditability.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nAgent loop: Plan \u2192 Edit (diff) \u2192 Test \u2192 Reflect \u2192 Human gate\n", "metadata": {"target_language": "JavaScript", "developer_needs": ["evaluation_metrics", "security_gates", "repo_scale_reasoning"]}}
{"id": "val_00148", "created": "2026-01-01", "topic": "Reasoning-first coding models and tunable deliberation", "task_type": "review", "difficulty": "foundation", "instruction": "Task: review\nTopic: Reasoning-first coding models and tunable deliberation\nDifficulty: foundation\nTarget language: Go\nContext: Design a data pipeline for continued pretraining with auditability.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nReview: correctness, security, performance, governance\n", "metadata": {"target_language": "Go", "developer_needs": ["governance", "cost_latency_tradeoffs", "security_gates"]}}
{"id": "val_00149", "created": "2026-01-01", "topic": "Mixture-of-Experts (MoE) for code", "task_type": "compare", "difficulty": "expert", "instruction": "Task: compare\nTopic: Mixture-of-Experts (MoE) for code\nDifficulty: expert\nTarget language: TypeScript\nContext: Create an eval harness that reflects real developer workflows.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nCompare: capability, cost, latency, reliability, governance\n", "metadata": {"target_language": "TypeScript", "developer_needs": ["governance", "cost_latency_tradeoffs", "reproducibility"]}}
{"id": "val_00150", "created": "2026-01-01", "topic": "Model merging, distillation, and continued pretraining", "task_type": "design", "difficulty": "advanced", "instruction": "Task: design\nTopic: Model merging, distillation, and continued pretraining\nDifficulty: advanced\nTarget language: Bash\nContext: Create an eval harness that reflects real developer workflows.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nDesign guidance with risks, metrics, acceptance criteria\n", "metadata": {"target_language": "Bash", "developer_needs": ["ci_integration", "documentation", "reproducibility"]}}
{"id": "val_00151", "created": "2026-01-01", "topic": "Tool calling, sandboxes, and CI integration", "task_type": "eval", "difficulty": "expert", "instruction": "Task: eval\nTopic: Tool calling, sandboxes, and CI integration\nDifficulty: expert\nTarget language: Java\nContext: Fix a failing issue with tests as the oracle and produce a safe patch.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nEval:\n- Tasks: real issues\n- Metrics: pass@k, time-to-green\n- Gates: lint/security\n", "metadata": {"target_language": "Java", "developer_needs": ["cost_latency_tradeoffs", "ci_integration", "security_gates"]}}
{"id": "val_00152", "created": "2026-01-01", "topic": "Code-specialized model families and sizing tradeoffs", "task_type": "compare", "difficulty": "foundation", "instruction": "Task: compare\nTopic: Code-specialized model families and sizing tradeoffs\nDifficulty: foundation\nTarget language: Java\nContext: Evaluate two coding models for internal rollout under strict governance.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nCompare: capability, cost, latency, reliability, governance\n", "metadata": {"target_language": "Java", "developer_needs": ["tests_are_truth", "governance", "repo_scale_reasoning"]}}
{"id": "val_00153", "created": "2026-01-01", "topic": "Model merging, distillation, and continued pretraining", "task_type": "design", "difficulty": "advanced", "instruction": "Task: design\nTopic: Model merging, distillation, and continued pretraining\nDifficulty: advanced\nTarget language: Python\nContext: Create an eval harness that reflects real developer workflows.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nDesign guidance with risks, metrics, acceptance criteria\n", "metadata": {"target_language": "Python", "developer_needs": ["tests_are_truth", "security_gates", "governance"]}}
{"id": "val_00154", "created": "2026-01-01", "topic": "Governance, provenance, and licensing for code data", "task_type": "review", "difficulty": "expert", "instruction": "Task: review\nTopic: Governance, provenance, and licensing for code data\nDifficulty: expert\nTarget language: Python\nContext: Fix a failing issue with tests as the oracle and produce a safe patch.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nReview: correctness, security, performance, governance\n", "metadata": {"target_language": "Python", "developer_needs": ["cost_latency_tradeoffs", "documentation", "tests_are_truth"]}}
{"id": "val_00155", "created": "2026-01-01", "topic": "Secure code generation and policy gates", "task_type": "agent_loop", "difficulty": "advanced", "instruction": "Task: agent_loop\nTopic: Secure code generation and policy gates\nDifficulty: advanced\nTarget language: Bash\nContext: Integrate an LLM agent into CI for a large monorepo.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nAgent loop: Plan \u2192 Edit (diff) \u2192 Test \u2192 Reflect \u2192 Human gate\n", "metadata": {"target_language": "Bash", "developer_needs": ["repo_scale_reasoning", "ci_integration", "documentation"]}}
{"id": "val_00156", "created": "2026-01-01", "topic": "Agentic coding systems (plan\u2192edit\u2192test\u2192reflect)", "task_type": "explain", "difficulty": "foundation", "instruction": "Task: explain\nTopic: Agentic coding systems (plan\u2192edit\u2192test\u2192reflect)\nDifficulty: foundation\nTarget language: C#\nContext: Create an eval harness that reflects real developer workflows.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nDesign guidance with risks, metrics, acceptance criteria\n", "metadata": {"target_language": "C#", "developer_needs": ["ci_integration", "security_gates", "governance"]}}
{"id": "val_00157", "created": "2026-01-01", "topic": "Governance, provenance, and licensing for code data", "task_type": "explain", "difficulty": "advanced", "instruction": "Task: explain\nTopic: Governance, provenance, and licensing for code data\nDifficulty: advanced\nTarget language: Go\nContext: Design a data pipeline for continued pretraining with auditability.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nDesign guidance with risks, metrics, acceptance criteria\n", "metadata": {"target_language": "Go", "developer_needs": ["tooling", "evaluation_metrics", "cost_latency_tradeoffs"]}}
{"id": "val_00158", "created": "2026-01-01", "topic": "SWE-bench style real-repo evaluation", "task_type": "code", "difficulty": "expert", "instruction": "Task: code\nTopic: SWE-bench style real-repo evaluation\nDifficulty: expert\nTarget language: C#\nContext: Evaluate two coding models for internal rollout under strict governance.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nDesign guidance with risks, metrics, acceptance criteria\n", "metadata": {"target_language": "C#", "developer_needs": ["reproducibility", "evaluation_metrics", "tooling"]}}
{"id": "val_00159", "created": "2026-01-01", "topic": "Multimodal dev workflows (docs, diagrams, traces)", "task_type": "design", "difficulty": "foundation", "instruction": "Task: design\nTopic: Multimodal dev workflows (docs, diagrams, traces)\nDifficulty: foundation\nTarget language: Rust\nContext: Design a data pipeline for continued pretraining with auditability.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nDesign guidance with risks, metrics, acceptance criteria\n", "metadata": {"target_language": "Rust", "developer_needs": ["ci_integration", "documentation", "tooling"]}}
{"id": "val_00160", "created": "2026-01-01", "topic": "Model merging, distillation, and continued pretraining", "task_type": "agent_loop", "difficulty": "foundation", "instruction": "Task: agent_loop\nTopic: Model merging, distillation, and continued pretraining\nDifficulty: foundation\nTarget language: Java\nContext: Create an eval harness that reflects real developer workflows.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nAgent loop: Plan \u2192 Edit (diff) \u2192 Test \u2192 Reflect \u2192 Human gate\n", "metadata": {"target_language": "Java", "developer_needs": ["evaluation_metrics", "cost_latency_tradeoffs", "documentation"]}}
{"id": "val_00161", "created": "2026-01-01", "topic": "Secure code generation and policy gates", "task_type": "code", "difficulty": "foundation", "instruction": "Task: code\nTopic: Secure code generation and policy gates\nDifficulty: foundation\nTarget language: Java\nContext: Create an eval harness that reflects real developer workflows.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nDesign guidance with risks, metrics, acceptance criteria\n", "metadata": {"target_language": "Java", "developer_needs": ["documentation", "cost_latency_tradeoffs", "reproducibility"]}}
{"id": "val_00162", "created": "2026-01-01", "topic": "Tool calling, sandboxes, and CI integration", "task_type": "code", "difficulty": "expert", "instruction": "Task: code\nTopic: Tool calling, sandboxes, and CI integration\nDifficulty: expert\nTarget language: JavaScript\nContext: Create an eval harness that reflects real developer workflows.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nDesign guidance with risks, metrics, acceptance criteria\n", "metadata": {"target_language": "JavaScript", "developer_needs": ["cost_latency_tradeoffs", "security_gates", "evaluation_metrics"]}}
{"id": "val_00163", "created": "2026-01-01", "topic": "Dataset curation pipelines (filter, dedupe, quality)", "task_type": "agent_loop", "difficulty": "intermediate", "instruction": "Task: agent_loop\nTopic: Dataset curation pipelines (filter, dedupe, quality)\nDifficulty: intermediate\nTarget language: JavaScript\nContext: Evaluate two coding models for internal rollout under strict governance.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nAgent loop: Plan \u2192 Edit (diff) \u2192 Test \u2192 Reflect \u2192 Human gate\n", "metadata": {"target_language": "JavaScript", "developer_needs": ["governance", "reproducibility", "tests_are_truth"]}}
{"id": "val_00164", "created": "2026-01-01", "topic": "Governance, provenance, and licensing for code data", "task_type": "data_pipeline", "difficulty": "foundation", "instruction": "Task: data_pipeline\nTopic: Governance, provenance, and licensing for code data\nDifficulty: foundation\nTarget language: Java\nContext: Evaluate two coding models for internal rollout under strict governance.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nPipeline:\n1) Ingest\n2) Normalize\n3) Filter\n4) Dedupe\n5) Quality score\n6) Sample\n7) Audit\n", "metadata": {"target_language": "Java", "developer_needs": ["cost_latency_tradeoffs", "governance", "tooling"]}}
{"id": "val_00165", "created": "2026-01-01", "topic": "Secure code generation and policy gates", "task_type": "data_pipeline", "difficulty": "advanced", "instruction": "Task: data_pipeline\nTopic: Secure code generation and policy gates\nDifficulty: advanced\nTarget language: Go\nContext: Design a data pipeline for continued pretraining with auditability.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nPipeline:\n1) Ingest\n2) Normalize\n3) Filter\n4) Dedupe\n5) Quality score\n6) Sample\n7) Audit\n", "metadata": {"target_language": "Go", "developer_needs": ["security_gates", "governance", "ci_integration"]}}
{"id": "val_00166", "created": "2026-01-01", "topic": "Extended context and repo-scale understanding", "task_type": "compare", "difficulty": "advanced", "instruction": "Task: compare\nTopic: Extended context and repo-scale understanding\nDifficulty: advanced\nTarget language: Bash\nContext: Evaluate two coding models for internal rollout under strict governance.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nCompare: capability, cost, latency, reliability, governance\n", "metadata": {"target_language": "Bash", "developer_needs": ["cost_latency_tradeoffs", "evaluation_metrics", "reproducibility"]}}
{"id": "val_00167", "created": "2026-01-01", "topic": "Tool calling, sandboxes, and CI integration", "task_type": "code", "difficulty": "foundation", "instruction": "Task: code\nTopic: Tool calling, sandboxes, and CI integration\nDifficulty: foundation\nTarget language: Python\nContext: Evaluate two coding models for internal rollout under strict governance.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nReference scaffold:\n```python\ndef agent_loop(plan, edit, test, issue, max_iters=3):\n    history = []\n    p = plan(issue)\n    for _ in range(max_iters):\n        patch = edit(issue, p)\n        ok, report = test(patch)\n        history.append({\"plan\": p, \"passed\": ok, \"report\": report[:200]})\n        if ok:\n            return patch, history\n        p = p + \" | refine from failures\"\n    return patch, history\n\n```\nOperational notes: sandbox, pinned deps, human gate.", "metadata": {"target_language": "Python", "developer_needs": ["cost_latency_tradeoffs", "documentation", "ci_integration"]}}
{"id": "val_00168", "created": "2026-01-01", "topic": "Agentic coding systems (plan\u2192edit\u2192test\u2192reflect)", "task_type": "explain", "difficulty": "intermediate", "instruction": "Task: explain\nTopic: Agentic coding systems (plan\u2192edit\u2192test\u2192reflect)\nDifficulty: intermediate\nTarget language: Bash\nContext: Integrate an LLM agent into CI for a large monorepo.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nDesign guidance with risks, metrics, acceptance criteria\n", "metadata": {"target_language": "Bash", "developer_needs": ["repo_scale_reasoning", "reproducibility", "tooling"]}}
{"id": "val_00169", "created": "2026-01-01", "topic": "Code-specialized model families and sizing tradeoffs", "task_type": "review", "difficulty": "intermediate", "instruction": "Task: review\nTopic: Code-specialized model families and sizing tradeoffs\nDifficulty: intermediate\nTarget language: JavaScript\nContext: Design a data pipeline for continued pretraining with auditability.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nReview: correctness, security, performance, governance\n", "metadata": {"target_language": "JavaScript", "developer_needs": ["tests_are_truth", "reproducibility", "repo_scale_reasoning"]}}
{"id": "val_00170", "created": "2026-01-01", "topic": "Code-specialized model families and sizing tradeoffs", "task_type": "design", "difficulty": "advanced", "instruction": "Task: design\nTopic: Code-specialized model families and sizing tradeoffs\nDifficulty: advanced\nTarget language: Rust\nContext: Integrate an LLM agent into CI for a large monorepo.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nDesign guidance with risks, metrics, acceptance criteria\n", "metadata": {"target_language": "Rust", "developer_needs": ["repo_scale_reasoning", "governance", "evaluation_metrics"]}}
{"id": "val_00171", "created": "2026-01-01", "topic": "Extended context and repo-scale understanding", "task_type": "code", "difficulty": "foundation", "instruction": "Task: code\nTopic: Extended context and repo-scale understanding\nDifficulty: foundation\nTarget language: Bash\nContext: Design a data pipeline for continued pretraining with auditability.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nDesign guidance with risks, metrics, acceptance criteria\n", "metadata": {"target_language": "Bash", "developer_needs": ["tooling", "reproducibility", "ci_integration"]}}
{"id": "val_00172", "created": "2026-01-01", "topic": "Code-specialized model families and sizing tradeoffs", "task_type": "agent_loop", "difficulty": "intermediate", "instruction": "Task: agent_loop\nTopic: Code-specialized model families and sizing tradeoffs\nDifficulty: intermediate\nTarget language: Go\nContext: Fix a failing issue with tests as the oracle and produce a safe patch.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nAgent loop: Plan \u2192 Edit (diff) \u2192 Test \u2192 Reflect \u2192 Human gate\n", "metadata": {"target_language": "Go", "developer_needs": ["documentation", "tooling", "repo_scale_reasoning"]}}
{"id": "val_00173", "created": "2026-01-01", "topic": "Extended context and repo-scale understanding", "task_type": "explain", "difficulty": "foundation", "instruction": "Task: explain\nTopic: Extended context and repo-scale understanding\nDifficulty: foundation\nTarget language: SQL\nContext: Create an eval harness that reflects real developer workflows.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nDesign guidance with risks, metrics, acceptance criteria\n", "metadata": {"target_language": "SQL", "developer_needs": ["security_gates", "cost_latency_tradeoffs", "evaluation_metrics"]}}
{"id": "val_00174", "created": "2026-01-01", "topic": "Agentic coding systems (plan\u2192edit\u2192test\u2192reflect)", "task_type": "agent_loop", "difficulty": "advanced", "instruction": "Task: agent_loop\nTopic: Agentic coding systems (plan\u2192edit\u2192test\u2192reflect)\nDifficulty: advanced\nTarget language: TypeScript\nContext: Design a data pipeline for continued pretraining with auditability.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nAgent loop: Plan \u2192 Edit (diff) \u2192 Test \u2192 Reflect \u2192 Human gate\n", "metadata": {"target_language": "TypeScript", "developer_needs": ["reproducibility", "governance", "documentation"]}}
{"id": "val_00175", "created": "2026-01-01", "topic": "SWE-bench style real-repo evaluation", "task_type": "data_pipeline", "difficulty": "expert", "instruction": "Task: data_pipeline\nTopic: SWE-bench style real-repo evaluation\nDifficulty: expert\nTarget language: Rust\nContext: Evaluate two coding models for internal rollout under strict governance.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nPipeline:\n1) Ingest\n2) Normalize\n3) Filter\n4) Dedupe\n5) Quality score\n6) Sample\n7) Audit\n", "metadata": {"target_language": "Rust", "developer_needs": ["ci_integration", "documentation", "tests_are_truth"]}}
{"id": "val_00176", "created": "2026-01-01", "topic": "Code-specialized model families and sizing tradeoffs", "task_type": "agent_loop", "difficulty": "advanced", "instruction": "Task: agent_loop\nTopic: Code-specialized model families and sizing tradeoffs\nDifficulty: advanced\nTarget language: TypeScript\nContext: Design a data pipeline for continued pretraining with auditability.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nAgent loop: Plan \u2192 Edit (diff) \u2192 Test \u2192 Reflect \u2192 Human gate\n", "metadata": {"target_language": "TypeScript", "developer_needs": ["security_gates", "governance", "tests_are_truth"]}}
{"id": "val_00177", "created": "2026-01-01", "topic": "Dataset curation pipelines (filter, dedupe, quality)", "task_type": "data_pipeline", "difficulty": "intermediate", "instruction": "Task: data_pipeline\nTopic: Dataset curation pipelines (filter, dedupe, quality)\nDifficulty: intermediate\nTarget language: Rust\nContext: Fix a failing issue with tests as the oracle and produce a safe patch.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nPipeline:\n1) Ingest\n2) Normalize\n3) Filter\n4) Dedupe\n5) Quality score\n6) Sample\n7) Audit\n", "metadata": {"target_language": "Rust", "developer_needs": ["cost_latency_tradeoffs", "ci_integration", "evaluation_metrics"]}}
{"id": "val_00178", "created": "2026-01-01", "topic": "Model merging, distillation, and continued pretraining", "task_type": "data_pipeline", "difficulty": "expert", "instruction": "Task: data_pipeline\nTopic: Model merging, distillation, and continued pretraining\nDifficulty: expert\nTarget language: Bash\nContext: Design a data pipeline for continued pretraining with auditability.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nPipeline:\n1) Ingest\n2) Normalize\n3) Filter\n4) Dedupe\n5) Quality score\n6) Sample\n7) Audit\n", "metadata": {"target_language": "Bash", "developer_needs": ["reproducibility", "evaluation_metrics", "ci_integration"]}}
{"id": "val_00179", "created": "2026-01-01", "topic": "Code-specialized model families and sizing tradeoffs", "task_type": "compare", "difficulty": "foundation", "instruction": "Task: compare\nTopic: Code-specialized model families and sizing tradeoffs\nDifficulty: foundation\nTarget language: Go\nContext: Evaluate two coding models for internal rollout under strict governance.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nCompare: capability, cost, latency, reliability, governance\n", "metadata": {"target_language": "Go", "developer_needs": ["tooling", "documentation", "evaluation_metrics"]}}
{"id": "val_00180", "created": "2026-01-01", "topic": "Extended context and repo-scale understanding", "task_type": "explain", "difficulty": "foundation", "instruction": "Task: explain\nTopic: Extended context and repo-scale understanding\nDifficulty: foundation\nTarget language: C#\nContext: Evaluate two coding models for internal rollout under strict governance.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nDesign guidance with risks, metrics, acceptance criteria\n", "metadata": {"target_language": "C#", "developer_needs": ["governance", "tooling", "tests_are_truth"]}}
{"id": "val_00181", "created": "2026-01-01", "topic": "SWE-bench style real-repo evaluation", "task_type": "code", "difficulty": "foundation", "instruction": "Task: code\nTopic: SWE-bench style real-repo evaluation\nDifficulty: foundation\nTarget language: SQL\nContext: Integrate an LLM agent into CI for a large monorepo.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nDesign guidance with risks, metrics, acceptance criteria\n", "metadata": {"target_language": "SQL", "developer_needs": ["tooling", "evaluation_metrics", "repo_scale_reasoning"]}}
{"id": "val_00182", "created": "2026-01-01", "topic": "Dataset curation pipelines (filter, dedupe, quality)", "task_type": "explain", "difficulty": "expert", "instruction": "Task: explain\nTopic: Dataset curation pipelines (filter, dedupe, quality)\nDifficulty: expert\nTarget language: TypeScript\nContext: Fix a failing issue with tests as the oracle and produce a safe patch.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nDesign guidance with risks, metrics, acceptance criteria\n", "metadata": {"target_language": "TypeScript", "developer_needs": ["governance", "documentation", "reproducibility"]}}
{"id": "val_00183", "created": "2026-01-01", "topic": "Agentic coding systems (plan\u2192edit\u2192test\u2192reflect)", "task_type": "data_pipeline", "difficulty": "foundation", "instruction": "Task: data_pipeline\nTopic: Agentic coding systems (plan\u2192edit\u2192test\u2192reflect)\nDifficulty: foundation\nTarget language: Java\nContext: Design a data pipeline for continued pretraining with auditability.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nPipeline:\n1) Ingest\n2) Normalize\n3) Filter\n4) Dedupe\n5) Quality score\n6) Sample\n7) Audit\n", "metadata": {"target_language": "Java", "developer_needs": ["reproducibility", "evaluation_metrics", "documentation"]}}
{"id": "val_00184", "created": "2026-01-01", "topic": "Reasoning-first coding models and tunable deliberation", "task_type": "agent_loop", "difficulty": "intermediate", "instruction": "Task: agent_loop\nTopic: Reasoning-first coding models and tunable deliberation\nDifficulty: intermediate\nTarget language: Go\nContext: Evaluate two coding models for internal rollout under strict governance.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nAgent loop: Plan \u2192 Edit (diff) \u2192 Test \u2192 Reflect \u2192 Human gate\n", "metadata": {"target_language": "Go", "developer_needs": ["reproducibility", "tests_are_truth", "security_gates"]}}
{"id": "val_00185", "created": "2026-01-01", "topic": "Reasoning-first coding models and tunable deliberation", "task_type": "code", "difficulty": "expert", "instruction": "Task: code\nTopic: Reasoning-first coding models and tunable deliberation\nDifficulty: expert\nTarget language: Go\nContext: Evaluate two coding models for internal rollout under strict governance.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nDesign guidance with risks, metrics, acceptance criteria\n", "metadata": {"target_language": "Go", "developer_needs": ["evaluation_metrics", "reproducibility", "ci_integration"]}}
{"id": "val_00186", "created": "2026-01-01", "topic": "Agentic coding systems (plan\u2192edit\u2192test\u2192reflect)", "task_type": "eval", "difficulty": "advanced", "instruction": "Task: eval\nTopic: Agentic coding systems (plan\u2192edit\u2192test\u2192reflect)\nDifficulty: advanced\nTarget language: Rust\nContext: Design a data pipeline for continued pretraining with auditability.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nEval:\n- Tasks: real issues\n- Metrics: pass@k, time-to-green\n- Gates: lint/security\n", "metadata": {"target_language": "Rust", "developer_needs": ["security_gates", "repo_scale_reasoning", "tests_are_truth"]}}
{"id": "val_00187", "created": "2026-01-01", "topic": "Extended context and repo-scale understanding", "task_type": "data_pipeline", "difficulty": "intermediate", "instruction": "Task: data_pipeline\nTopic: Extended context and repo-scale understanding\nDifficulty: intermediate\nTarget language: C#\nContext: Design a data pipeline for continued pretraining with auditability.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nPipeline:\n1) Ingest\n2) Normalize\n3) Filter\n4) Dedupe\n5) Quality score\n6) Sample\n7) Audit\n", "metadata": {"target_language": "C#", "developer_needs": ["reproducibility", "tests_are_truth", "security_gates"]}}
{"id": "val_00188", "created": "2026-01-01", "topic": "Dataset curation pipelines (filter, dedupe, quality)", "task_type": "agent_loop", "difficulty": "intermediate", "instruction": "Task: agent_loop\nTopic: Dataset curation pipelines (filter, dedupe, quality)\nDifficulty: intermediate\nTarget language: JavaScript\nContext: Integrate an LLM agent into CI for a large monorepo.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nAgent loop: Plan \u2192 Edit (diff) \u2192 Test \u2192 Reflect \u2192 Human gate\n", "metadata": {"target_language": "JavaScript", "developer_needs": ["evaluation_metrics", "ci_integration", "cost_latency_tradeoffs"]}}
{"id": "val_00189", "created": "2026-01-01", "topic": "Agentic coding systems (plan\u2192edit\u2192test\u2192reflect)", "task_type": "review", "difficulty": "intermediate", "instruction": "Task: review\nTopic: Agentic coding systems (plan\u2192edit\u2192test\u2192reflect)\nDifficulty: intermediate\nTarget language: Python\nContext: Integrate an LLM agent into CI for a large monorepo.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nReview: correctness, security, performance, governance\n", "metadata": {"target_language": "Python", "developer_needs": ["reproducibility", "repo_scale_reasoning", "tests_are_truth"]}}
{"id": "val_00190", "created": "2026-01-01", "topic": "Extended context and repo-scale understanding", "task_type": "agent_loop", "difficulty": "advanced", "instruction": "Task: agent_loop\nTopic: Extended context and repo-scale understanding\nDifficulty: advanced\nTarget language: JavaScript\nContext: Design a data pipeline for continued pretraining with auditability.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nAgent loop: Plan \u2192 Edit (diff) \u2192 Test \u2192 Reflect \u2192 Human gate\n", "metadata": {"target_language": "JavaScript", "developer_needs": ["security_gates", "ci_integration", "cost_latency_tradeoffs"]}}
{"id": "val_00191", "created": "2026-01-01", "topic": "Model merging, distillation, and continued pretraining", "task_type": "explain", "difficulty": "foundation", "instruction": "Task: explain\nTopic: Model merging, distillation, and continued pretraining\nDifficulty: foundation\nTarget language: C#\nContext: Create an eval harness that reflects real developer workflows.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nDesign guidance with risks, metrics, acceptance criteria\n", "metadata": {"target_language": "C#", "developer_needs": ["security_gates", "documentation", "repo_scale_reasoning"]}}
{"id": "val_00192", "created": "2026-01-01", "topic": "Tool calling, sandboxes, and CI integration", "task_type": "agent_loop", "difficulty": "foundation", "instruction": "Task: agent_loop\nTopic: Tool calling, sandboxes, and CI integration\nDifficulty: foundation\nTarget language: Go\nContext: Fix a failing issue with tests as the oracle and produce a safe patch.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nAgent loop: Plan \u2192 Edit (diff) \u2192 Test \u2192 Reflect \u2192 Human gate\n", "metadata": {"target_language": "Go", "developer_needs": ["tests_are_truth", "governance", "repo_scale_reasoning"]}}
{"id": "val_00193", "created": "2026-01-01", "topic": "Secure code generation and policy gates", "task_type": "code", "difficulty": "foundation", "instruction": "Task: code\nTopic: Secure code generation and policy gates\nDifficulty: foundation\nTarget language: SQL\nContext: Fix a failing issue with tests as the oracle and produce a safe patch.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nDesign guidance with risks, metrics, acceptance criteria\n", "metadata": {"target_language": "SQL", "developer_needs": ["governance", "ci_integration", "documentation"]}}
{"id": "val_00194", "created": "2026-01-01", "topic": "Multimodal dev workflows (docs, diagrams, traces)", "task_type": "design", "difficulty": "intermediate", "instruction": "Task: design\nTopic: Multimodal dev workflows (docs, diagrams, traces)\nDifficulty: intermediate\nTarget language: Bash\nContext: Design a data pipeline for continued pretraining with auditability.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nDesign guidance with risks, metrics, acceptance criteria\n", "metadata": {"target_language": "Bash", "developer_needs": ["tooling", "repo_scale_reasoning", "tests_are_truth"]}}
{"id": "val_00195", "created": "2026-01-01", "topic": "Extended context and repo-scale understanding", "task_type": "code", "difficulty": "foundation", "instruction": "Task: code\nTopic: Extended context and repo-scale understanding\nDifficulty: foundation\nTarget language: TypeScript\nContext: Evaluate two coding models for internal rollout under strict governance.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nDesign guidance with risks, metrics, acceptance criteria\n", "metadata": {"target_language": "TypeScript", "developer_needs": ["security_gates", "tests_are_truth", "reproducibility"]}}
{"id": "val_00196", "created": "2026-01-01", "topic": "Mixture-of-Experts (MoE) for code", "task_type": "review", "difficulty": "intermediate", "instruction": "Task: review\nTopic: Mixture-of-Experts (MoE) for code\nDifficulty: intermediate\nTarget language: SQL\nContext: Create an eval harness that reflects real developer workflows.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nReview: correctness, security, performance, governance\n", "metadata": {"target_language": "SQL", "developer_needs": ["cost_latency_tradeoffs", "tooling", "ci_integration"]}}
{"id": "val_00197", "created": "2026-01-01", "topic": "Governance, provenance, and licensing for code data", "task_type": "explain", "difficulty": "intermediate", "instruction": "Task: explain\nTopic: Governance, provenance, and licensing for code data\nDifficulty: intermediate\nTarget language: C#\nContext: Fix a failing issue with tests as the oracle and produce a safe patch.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nDesign guidance with risks, metrics, acceptance criteria\n", "metadata": {"target_language": "C#", "developer_needs": ["cost_latency_tradeoffs", "tests_are_truth", "reproducibility"]}}
{"id": "val_00198", "created": "2026-01-01", "topic": "Governance, provenance, and licensing for code data", "task_type": "code", "difficulty": "expert", "instruction": "Task: code\nTopic: Governance, provenance, and licensing for code data\nDifficulty: expert\nTarget language: Python\nContext: Integrate an LLM agent into CI for a large monorepo.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nReference scaffold:\n```python\ndef agent_loop(plan, edit, test, issue, max_iters=3):\n    history = []\n    p = plan(issue)\n    for _ in range(max_iters):\n        patch = edit(issue, p)\n        ok, report = test(patch)\n        history.append({\"plan\": p, \"passed\": ok, \"report\": report[:200]})\n        if ok:\n            return patch, history\n        p = p + \" | refine from failures\"\n    return patch, history\n\n```\nOperational notes: sandbox, pinned deps, human gate.", "metadata": {"target_language": "Python", "developer_needs": ["security_gates", "governance", "tests_are_truth"]}}
{"id": "val_00199", "created": "2026-01-01", "topic": "SWE-bench style real-repo evaluation", "task_type": "eval", "difficulty": "expert", "instruction": "Task: eval\nTopic: SWE-bench style real-repo evaluation\nDifficulty: expert\nTarget language: Python\nContext: Fix a failing issue with tests as the oracle and produce a safe patch.\nDeliver production-grade guidance or artifacts.", "input": "", "output": "Key facts:\n- Modern AI coding emphasizes correctness via tests, agentic loops, and real-repo evaluation.\n- Reasoning-first and MoE approaches improve capability-per-compute when paired with tools.\n\nEval:\n- Tasks: real issues\n- Metrics: pass@k, time-to-green\n- Gates: lint/security\n", "metadata": {"target_language": "Python", "developer_needs": ["security_gates", "tooling", "ci_integration"]}}