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train_02800
2026-01-01T00:00:00
Model merging, distillation, and continued pretraining
failure_analysis
expert
Task: failure_analysis Topic: Model merging, distillation, and continued pretraining Difficulty: expert Target language: Java Context: High-traffic service with latency SLOs. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Failure: - Initial patch broke edge case Reflection: - Missing zero-input guard Correction: - Add explicit validation + test
[]
{ "target_language": "Java", "developer_needs": [ "cost_latency_tradeoffs", "tests_are_truth", "ci_integration", "repo_scale_reasoning" ], "moe_experts": [ "data_curation_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
7b6c5b8a8a0c7d92a5b13e7487461cc1393ca48d
train_02801
2026-01-01T00:00:00
Mixture-of-Experts (MoE) for code
eval
advanced
Task: eval Topic: Mixture-of-Experts (MoE) for code Difficulty: advanced Target language: Java Context: High-traffic service with latency SLOs. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Eval: pass@k, time-to-green, regressions, diff size
[]
{ "target_language": "Java", "developer_needs": [ "tooling", "tests_are_truth", "repo_scale_reasoning", "reproducibility" ], "moe_experts": [ "evaluation_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
af29038155a39af50c5978ad5340c1da614a2704
train_02802
2026-01-01T00:00:00
Governance, provenance, and licensing for code data
review
advanced
Task: review Topic: Governance, provenance, and licensing for code data Difficulty: advanced Target language: JavaScript Context: Regulated environment requiring audit trails. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Review: correctness, security, performance, governance
[]
{ "target_language": "JavaScript", "developer_needs": [ "auditability", "tooling", "security_gates", "ci_integration" ], "moe_experts": [ "coding_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
174e31e2f04d1a97debaf773add5d68fc8b4b1d0
train_02803
2026-01-01T00:00:00
Tool calling, sandboxes, and CI integration
patch_diff
expert
Task: patch_diff Topic: Tool calling, sandboxes, and CI integration Difficulty: expert Target language: Rust Context: Offline/local deployment with limited compute. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Patch (diff-style): ```diff - if x == 0: - return 1/x + if x == 0: + raise ValueError('division by zero') ``` Acceptance: - Tests pass - No new regressions
[]
{ "target_language": "Rust", "developer_needs": [ "security_gates", "ci_integration", "auditability", "tooling" ], "moe_experts": [ "data_curation_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
b716db6f9c2c9738504c3f2795d916c963fe6f5e
train_02804
2026-01-01T00:00:00
SWE-bench style real-repo evaluation
design
advanced
Task: design Topic: SWE-bench style real-repo evaluation Difficulty: advanced Target language: Rust Context: Offline/local deployment with limited compute. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "Rust", "developer_needs": [ "auditability", "ci_integration", "cost_latency_tradeoffs", "repo_scale_reasoning" ], "moe_experts": [ "security_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
0ec4fb6ffbd5fc303f8996bff3ec87093ea66a4f
train_02805
2026-01-01T00:00:00
Dataset curation pipelines (filter, dedupe, quality)
review
expert
Task: review Topic: Dataset curation pipelines (filter, dedupe, quality) Difficulty: expert Target language: SQL Context: Regulated environment requiring audit trails. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Review: correctness, security, performance, governance
[]
{ "target_language": "SQL", "developer_needs": [ "security_gates", "documentation", "tooling", "evaluation_metrics" ], "moe_experts": [ "coding_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
d7ebfbbb6cc110f332b1fcc4378bf9e7de0c6201
train_02806
2026-01-01T00:00:00
Code-specialized model families and sizing tradeoffs
explain
advanced
Task: explain Topic: Code-specialized model families and sizing tradeoffs Difficulty: advanced Target language: TypeScript Context: Regulated environment requiring audit trails. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "TypeScript", "developer_needs": [ "auditability", "reproducibility", "tooling", "repo_scale_reasoning" ], "moe_experts": [ "evaluation_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
e519c5f9aa05b5dd8ac993d2505d86473b1624a9
train_02807
2026-01-01T00:00:00
Model merging, distillation, and continued pretraining
review
advanced
Task: review Topic: Model merging, distillation, and continued pretraining Difficulty: advanced Target language: C# Context: Research team validating claims against real repos. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Review: correctness, security, performance, governance
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "C#", "developer_needs": [ "governance", "auditability", "reproducibility", "evaluation_metrics" ], "moe_experts": [ "coding_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
9d5b19930f3c6fd9d6a6b0f283e8e96567d081a9
train_02808
2026-01-01T00:00:00
Governance, provenance, and licensing for code data
eval
advanced
Task: eval Topic: Governance, provenance, and licensing for code data Difficulty: advanced Target language: Go Context: Offline/local deployment with limited compute. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Eval: pass@k, time-to-green, regressions, diff size
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Go", "developer_needs": [ "reproducibility", "tests_are_truth", "auditability", "governance" ], "moe_experts": [ "security_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
63a362527e20190f0f65b2fd92b89091ed5e0f6a
train_02809
2026-01-01T00:00:00
Model merging, distillation, and continued pretraining
failure_analysis
expert
Task: failure_analysis Topic: Model merging, distillation, and continued pretraining Difficulty: expert Target language: Java Context: Research team validating claims against real repos. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Failure: - Initial patch broke edge case Reflection: - Missing zero-input guard Correction: - Add explicit validation + test
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Java", "developer_needs": [ "tooling", "documentation", "ci_integration", "evaluation_metrics" ], "moe_experts": [ "governance_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
b6fe28c6b240180a69666b904d31812548e52a0b
train_02810
2026-01-01T00:00:00
Model merging, distillation, and continued pretraining
agent_loop
intermediate
Task: agent_loop Topic: Model merging, distillation, and continued pretraining Difficulty: intermediate Target language: Rust Context: Large monorepo with flaky tests and strict CI. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Loop: Plan → Edit → Test → Reflect → Human gate
[]
{ "target_language": "Rust", "developer_needs": [ "governance", "auditability", "ci_integration", "documentation" ], "moe_experts": [ "data_curation_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
cf45914d0dc5237b37542f318cc50c0a2cd0a541
train_02811
2026-01-01T00:00:00
Mixture-of-Experts (MoE) for code
code
advanced
Task: code Topic: Mixture-of-Experts (MoE) for code Difficulty: advanced Target language: Rust Context: Regulated environment requiring audit trails. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "Rust", "developer_needs": [ "tests_are_truth", "governance", "auditability", "documentation" ], "moe_experts": [ "evaluation_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
b81b8bc1dc7ad1e3b0685301a08cecaf86de39cb
train_02812
2026-01-01T00:00:00
Governance, provenance, and licensing for code data
explain
expert
Task: explain Topic: Governance, provenance, and licensing for code data Difficulty: expert Target language: C# Context: Regulated environment requiring audit trails. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "C#", "developer_needs": [ "auditability", "ci_integration", "repo_scale_reasoning", "tests_are_truth" ], "moe_experts": [ "evaluation_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
69302c240fd0ccca6d084b4a907877c45c8a4a1d
train_02813
2026-01-01T00:00:00
Reasoning-first coding models and tunable deliberation
agent_loop
intermediate
Task: agent_loop Topic: Reasoning-first coding models and tunable deliberation Difficulty: intermediate Target language: Rust Context: High-traffic service with latency SLOs. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Loop: Plan → Edit → Test → Reflect → Human gate
[]
{ "target_language": "Rust", "developer_needs": [ "tooling", "documentation", "governance", "reproducibility" ], "moe_experts": [ "governance_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
286f2fe3e8b8a37b3ea881d525a2cf279c675a3f
train_02814
2026-01-01T00:00:00
Agentic coding systems (plan→edit→test→reflect)
eval
advanced
Task: eval Topic: Agentic coding systems (plan→edit→test→reflect) Difficulty: advanced Target language: Bash Context: Regulated environment requiring audit trails. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Eval: pass@k, time-to-green, regressions, diff size
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Bash", "developer_needs": [ "tests_are_truth", "security_gates", "documentation", "repo_scale_reasoning" ], "moe_experts": [ "agentic_systems_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
5bf3dd125247e36e7d06813cdd0004153083779e
train_02815
2026-01-01T00:00:00
Multimodal dev workflows (docs, diagrams, traces)
code
expert
Task: code Topic: Multimodal dev workflows (docs, diagrams, traces) Difficulty: expert Target language: JavaScript Context: Offline/local deployment with limited compute. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "JavaScript", "developer_needs": [ "repo_scale_reasoning", "documentation", "ci_integration", "auditability" ], "moe_experts": [ "performance_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
c109c997869b92d9f7ede5ba1d193955b9217eff
train_02816
2026-01-01T00:00:00
Model merging, distillation, and continued pretraining
explain
intermediate
Task: explain Topic: Model merging, distillation, and continued pretraining Difficulty: intermediate Target language: Go Context: Research team validating claims against real repos. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Go", "developer_needs": [ "tests_are_truth", "ci_integration", "governance", "auditability" ], "moe_experts": [ "evaluation_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
81683a2d1b3c6232848524adac68dcd3ebeeced1
train_02817
2026-01-01T00:00:00
Model merging, distillation, and continued pretraining
agent_loop
advanced
Task: agent_loop Topic: Model merging, distillation, and continued pretraining Difficulty: advanced Target language: TypeScript Context: High-traffic service with latency SLOs. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Loop: Plan → Edit → Test → Reflect → Human gate
[]
{ "target_language": "TypeScript", "developer_needs": [ "evaluation_metrics", "documentation", "tests_are_truth", "tooling" ], "moe_experts": [ "security_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
42d7cfb0ba8dc2cef89a023507f85b0ed4510a9b
train_02818
2026-01-01T00:00:00
Code-specialized model families and sizing tradeoffs
explain
intermediate
Task: explain Topic: Code-specialized model families and sizing tradeoffs Difficulty: intermediate Target language: C# Context: High-traffic service with latency SLOs. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "C#", "developer_needs": [ "auditability", "ci_integration", "cost_latency_tradeoffs", "evaluation_metrics" ], "moe_experts": [ "security_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
2ba841c79c50b81843770e86753c54a7bdba18d3
train_02819
2026-01-01T00:00:00
Agentic coding systems (plan→edit→test→reflect)
review
expert
Task: review Topic: Agentic coding systems (plan→edit→test→reflect) Difficulty: expert Target language: C# Context: Research team validating claims against real repos. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Review: correctness, security, performance, governance
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "C#", "developer_needs": [ "security_gates", "evaluation_metrics", "reproducibility", "auditability" ], "moe_experts": [ "governance_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
2ac998c08f734f2d5297aad1a3d9b4487393b7de
train_02820
2026-01-01T00:00:00
Tool calling, sandboxes, and CI integration
failure_analysis
advanced
Task: failure_analysis Topic: Tool calling, sandboxes, and CI integration Difficulty: advanced Target language: Go Context: Regulated environment requiring audit trails. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Failure: - Initial patch broke edge case Reflection: - Missing zero-input guard Correction: - Add explicit validation + test
[]
{ "target_language": "Go", "developer_needs": [ "cost_latency_tradeoffs", "repo_scale_reasoning", "evaluation_metrics", "tooling" ], "moe_experts": [ "governance_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
7688955769d308e5ba87e8281c082b6fd3cdb715
train_02821
2026-01-01T00:00:00
Tool calling, sandboxes, and CI integration
data_pipeline
expert
Task: data_pipeline Topic: Tool calling, sandboxes, and CI integration Difficulty: expert Target language: JavaScript Context: Offline/local deployment with limited compute. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Pipeline: Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
[]
{ "target_language": "JavaScript", "developer_needs": [ "repo_scale_reasoning", "cost_latency_tradeoffs", "reproducibility", "tests_are_truth" ], "moe_experts": [ "data_curation_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
92a3074a9ee4f7feaa6c7fd40a1cef11584bb2fd
train_02822
2026-01-01T00:00:00
Dataset curation pipelines (filter, dedupe, quality)
agent_loop
advanced
Task: agent_loop Topic: Dataset curation pipelines (filter, dedupe, quality) Difficulty: advanced Target language: JavaScript Context: Regulated environment requiring audit trails. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Loop: Plan → Edit → Test → Reflect → Human gate
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "JavaScript", "developer_needs": [ "documentation", "tooling", "repo_scale_reasoning", "cost_latency_tradeoffs" ], "moe_experts": [ "agentic_systems_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
8b299289ecc4cad3a8af417aa7df23e9ee308b8e
train_02823
2026-01-01T00:00:00
Secure code generation and policy gates
design
advanced
Task: design Topic: Secure code generation and policy gates Difficulty: advanced Target language: Java Context: Regulated environment requiring audit trails. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "Java", "developer_needs": [ "repo_scale_reasoning", "cost_latency_tradeoffs", "tooling", "governance" ], "moe_experts": [ "security_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
1c26700d2fb0c4bf4e01fb34e43413efd0c8cd8a
train_02824
2026-01-01T00:00:00
Mixture-of-Experts (MoE) for code
patch_diff
advanced
Task: patch_diff Topic: Mixture-of-Experts (MoE) for code Difficulty: advanced Target language: Bash Context: Regulated environment requiring audit trails. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Patch (diff-style): ```diff - if x == 0: - return 1/x + if x == 0: + raise ValueError('division by zero') ``` Acceptance: - Tests pass - No new regressions
[]
{ "target_language": "Bash", "developer_needs": [ "auditability", "governance", "security_gates", "ci_integration" ], "moe_experts": [ "coding_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
c3be35998aa1177c74ed0ca3ba3834c2c18a45e4
train_02825
2026-01-01T00:00:00
SWE-bench style real-repo evaluation
code
advanced
Task: code Topic: SWE-bench style real-repo evaluation Difficulty: advanced Target language: C# Context: Large monorepo with flaky tests and strict CI. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "C#", "developer_needs": [ "documentation", "tests_are_truth", "auditability", "repo_scale_reasoning" ], "moe_experts": [ "data_curation_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
9500b834e0c761e2229930b65b46678073dbaeb6
train_02826
2026-01-01T00:00:00
Secure code generation and policy gates
code
advanced
Task: code Topic: Secure code generation and policy gates Difficulty: advanced Target language: Go Context: Large monorepo with flaky tests and strict CI. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Go", "developer_needs": [ "auditability", "repo_scale_reasoning", "tests_are_truth", "cost_latency_tradeoffs" ], "moe_experts": [ "agentic_systems_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
25d7aa2a90d58f0a7b61ee08b80b98d1fecb01f1
train_02827
2026-01-01T00:00:00
SWE-bench style real-repo evaluation
design
expert
Task: design Topic: SWE-bench style real-repo evaluation Difficulty: expert Target language: SQL Context: Regulated environment requiring audit trails. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "SQL", "developer_needs": [ "auditability", "tests_are_truth", "reproducibility", "documentation" ], "moe_experts": [ "agentic_systems_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
09d90524b6f6ce82e48abebe5550f5dbf5ef2123
train_02828
2026-01-01T00:00:00
Tool calling, sandboxes, and CI integration
design
advanced
Task: design Topic: Tool calling, sandboxes, and CI integration Difficulty: advanced Target language: SQL Context: High-traffic service with latency SLOs. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "SQL", "developer_needs": [ "auditability", "repo_scale_reasoning", "documentation", "evaluation_metrics" ], "moe_experts": [ "security_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
56ab1520a9438ef55915e101d608ef410b54672b
train_02829
2026-01-01T00:00:00
Mixture-of-Experts (MoE) for code
design
advanced
Task: design Topic: Mixture-of-Experts (MoE) for code Difficulty: advanced Target language: Python Context: Regulated environment requiring audit trails. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Python", "developer_needs": [ "repo_scale_reasoning", "tests_are_truth", "tooling", "security_gates" ], "moe_experts": [ "coding_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
7ce0c15f3b3fae3139251a3c20e6de4cfb7fdbaf
train_02830
2026-01-01T00:00:00
Code-specialized model families and sizing tradeoffs
explain
advanced
Task: explain Topic: Code-specialized model families and sizing tradeoffs Difficulty: advanced Target language: JavaScript Context: Regulated environment requiring audit trails. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "JavaScript", "developer_needs": [ "reproducibility", "repo_scale_reasoning", "evaluation_metrics", "tooling" ], "moe_experts": [ "evaluation_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
4be949a18feec5d4a0779cb8a3324bec82286445
train_02831
2026-01-01T00:00:00
Code-specialized model families and sizing tradeoffs
failure_analysis
expert
Task: failure_analysis Topic: Code-specialized model families and sizing tradeoffs Difficulty: expert Target language: JavaScript Context: Large monorepo with flaky tests and strict CI. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Failure: - Initial patch broke edge case Reflection: - Missing zero-input guard Correction: - Add explicit validation + test
[]
{ "target_language": "JavaScript", "developer_needs": [ "ci_integration", "evaluation_metrics", "tests_are_truth", "security_gates" ], "moe_experts": [ "evaluation_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
63465dcff70f5b810c491b426563577d3dbe0dd3
train_02832
2026-01-01T00:00:00
Mixture-of-Experts (MoE) for code
code
intermediate
Task: code Topic: Mixture-of-Experts (MoE) for code Difficulty: intermediate Target language: Go Context: Offline/local deployment with limited compute. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Go", "developer_needs": [ "repo_scale_reasoning", "ci_integration", "governance", "auditability" ], "moe_experts": [ "performance_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
3c6e9e29341b971a75839d4c8dffb3ca2f6ae4e3
train_02833
2026-01-01T00:00:00
Model merging, distillation, and continued pretraining
agent_loop
intermediate
Task: agent_loop Topic: Model merging, distillation, and continued pretraining Difficulty: intermediate Target language: Go Context: Offline/local deployment with limited compute. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Loop: Plan → Edit → Test → Reflect → Human gate
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Go", "developer_needs": [ "governance", "security_gates", "auditability", "tooling" ], "moe_experts": [ "agentic_systems_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
e523bd2a9474230c0e30815f4210eb0d9709c656
train_02834
2026-01-01T00:00:00
Secure code generation and policy gates
patch_diff
expert
Task: patch_diff Topic: Secure code generation and policy gates Difficulty: expert Target language: Bash Context: Large monorepo with flaky tests and strict CI. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Patch (diff-style): ```diff - if x == 0: - return 1/x + if x == 0: + raise ValueError('division by zero') ``` Acceptance: - Tests pass - No new regressions
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Bash", "developer_needs": [ "tests_are_truth", "security_gates", "tooling", "auditability" ], "moe_experts": [ "evaluation_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
c2f35b65257e47501dab669d0b2872a0d937d84e
train_02835
2026-01-01T00:00:00
Reasoning-first coding models and tunable deliberation
code
advanced
Task: code Topic: Reasoning-first coding models and tunable deliberation Difficulty: advanced Target language: Bash Context: Offline/local deployment with limited compute. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "Bash", "developer_needs": [ "evaluation_metrics", "governance", "cost_latency_tradeoffs", "tooling" ], "moe_experts": [ "governance_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
b4e98a1555660e03fe2c8aca2dba5809b13e90b4
train_02836
2026-01-01T00:00:00
Model merging, distillation, and continued pretraining
eval
advanced
Task: eval Topic: Model merging, distillation, and continued pretraining Difficulty: advanced Target language: JavaScript Context: Large monorepo with flaky tests and strict CI. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Eval: pass@k, time-to-green, regressions, diff size
[]
{ "target_language": "JavaScript", "developer_needs": [ "tests_are_truth", "cost_latency_tradeoffs", "repo_scale_reasoning", "governance" ], "moe_experts": [ "evaluation_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
5a6288970b4dfe00e2657d8cd67792925a6572b6
train_02837
2026-01-01T00:00:00
Multimodal dev workflows (docs, diagrams, traces)
explain
expert
Task: explain Topic: Multimodal dev workflows (docs, diagrams, traces) Difficulty: expert Target language: TypeScript Context: Regulated environment requiring audit trails. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "TypeScript", "developer_needs": [ "security_gates", "ci_integration", "tests_are_truth", "evaluation_metrics" ], "moe_experts": [ "performance_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
466b6bf3ac072515caea2e87ca30aa6930800222
train_02838
2026-01-01T00:00:00
Tool calling, sandboxes, and CI integration
design
intermediate
Task: design Topic: Tool calling, sandboxes, and CI integration Difficulty: intermediate Target language: JavaScript Context: Large monorepo with flaky tests and strict CI. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "JavaScript", "developer_needs": [ "ci_integration", "reproducibility", "tests_are_truth", "auditability" ], "moe_experts": [ "coding_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
10485de161ed7183af99737129cea22e6ac81f79
train_02839
2026-01-01T00:00:00
Multimodal dev workflows (docs, diagrams, traces)
compare
intermediate
Task: compare Topic: Multimodal dev workflows (docs, diagrams, traces) Difficulty: intermediate Target language: Go Context: Regulated environment requiring audit trails. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Compare: capability, cost, latency, reliability
[]
{ "target_language": "Go", "developer_needs": [ "auditability", "tooling", "reproducibility", "governance" ], "moe_experts": [ "data_curation_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
1c3bb85f41bae068b7421f166a6722b9afeb91dc
train_02840
2026-01-01T00:00:00
Agentic coding systems (plan→edit→test→reflect)
code
advanced
Task: code Topic: Agentic coding systems (plan→edit→test→reflect) Difficulty: advanced Target language: TypeScript Context: High-traffic service with latency SLOs. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "TypeScript", "developer_needs": [ "tests_are_truth", "tooling", "governance", "auditability" ], "moe_experts": [ "governance_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
1845afb6a5351ecbec5be6283fa6ef49e09006e1
train_02841
2026-01-01T00:00:00
Latency, cost, and reliability optimization
explain
expert
Task: explain Topic: Latency, cost, and reliability optimization Difficulty: expert Target language: C# Context: Regulated environment requiring audit trails. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "C#", "developer_needs": [ "documentation", "repo_scale_reasoning", "evaluation_metrics", "cost_latency_tradeoffs" ], "moe_experts": [ "governance_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
73794dcdff1eee73547bebac58d6e4720506b4ba
train_02842
2026-01-01T00:00:00
Latency, cost, and reliability optimization
patch_diff
intermediate
Task: patch_diff Topic: Latency, cost, and reliability optimization Difficulty: intermediate Target language: SQL Context: Regulated environment requiring audit trails. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Patch (diff-style): ```diff - if x == 0: - return 1/x + if x == 0: + raise ValueError('division by zero') ``` Acceptance: - Tests pass - No new regressions
[]
{ "target_language": "SQL", "developer_needs": [ "evaluation_metrics", "tests_are_truth", "cost_latency_tradeoffs", "governance" ], "moe_experts": [ "security_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
f095d746bcf6695a1b998c1db9654c74c9ff9139
train_02843
2026-01-01T00:00:00
Code-specialized model families and sizing tradeoffs
review
advanced
Task: review Topic: Code-specialized model families and sizing tradeoffs Difficulty: advanced Target language: C# Context: Research team validating claims against real repos. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Review: correctness, security, performance, governance
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "C#", "developer_needs": [ "governance", "repo_scale_reasoning", "evaluation_metrics", "cost_latency_tradeoffs" ], "moe_experts": [ "security_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
44a160c26691805ede6a34172fd1fad10555368e
train_02844
2026-01-01T00:00:00
Reasoning-first coding models and tunable deliberation
failure_analysis
expert
Task: failure_analysis Topic: Reasoning-first coding models and tunable deliberation Difficulty: expert Target language: SQL Context: Regulated environment requiring audit trails. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Failure: - Initial patch broke edge case Reflection: - Missing zero-input guard Correction: - Add explicit validation + test
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "SQL", "developer_needs": [ "cost_latency_tradeoffs", "documentation", "tests_are_truth", "tooling" ], "moe_experts": [ "evaluation_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
81f5b2fa7c2dae50067b301421ed27e38e6b6fcd
train_02845
2026-01-01T00:00:00
Mixture-of-Experts (MoE) for code
eval
intermediate
Task: eval Topic: Mixture-of-Experts (MoE) for code Difficulty: intermediate Target language: Bash Context: Research team validating claims against real repos. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Eval: pass@k, time-to-green, regressions, diff size
[]
{ "target_language": "Bash", "developer_needs": [ "documentation", "cost_latency_tradeoffs", "evaluation_metrics", "ci_integration" ], "moe_experts": [ "performance_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
faf054b49fdccc3f34ef69efd6822879f8544f77
train_02846
2026-01-01T00:00:00
Secure code generation and policy gates
data_pipeline
intermediate
Task: data_pipeline Topic: Secure code generation and policy gates Difficulty: intermediate Target language: C# Context: Research team validating claims against real repos. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Pipeline: Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "C#", "developer_needs": [ "reproducibility", "documentation", "auditability", "cost_latency_tradeoffs" ], "moe_experts": [ "agentic_systems_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
edb919decda4d5294e68fae9302da61ea57ff360
train_02847
2026-01-01T00:00:00
Self-improving agents and feedback loops
failure_analysis
advanced
Task: failure_analysis Topic: Self-improving agents and feedback loops Difficulty: advanced Target language: Python Context: Research team validating claims against real repos. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Failure: - Initial patch broke edge case Reflection: - Missing zero-input guard Correction: - Add explicit validation + test
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Python", "developer_needs": [ "governance", "ci_integration", "repo_scale_reasoning", "evaluation_metrics" ], "moe_experts": [ "security_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
3556719c9655b93b9cacf04ae19fa82b4ae9cda4
train_02848
2026-01-01T00:00:00
Secure code generation and policy gates
review
expert
Task: review Topic: Secure code generation and policy gates Difficulty: expert Target language: SQL Context: Offline/local deployment with limited compute. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Review: correctness, security, performance, governance
[]
{ "target_language": "SQL", "developer_needs": [ "documentation", "tests_are_truth", "repo_scale_reasoning", "evaluation_metrics" ], "moe_experts": [ "data_curation_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
b98bb0240f54edc63d3345d5e0f5269d90e60422
train_02849
2026-01-01T00:00:00
Model merging, distillation, and continued pretraining
patch_diff
expert
Task: patch_diff Topic: Model merging, distillation, and continued pretraining Difficulty: expert Target language: Java Context: Large monorepo with flaky tests and strict CI. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Patch (diff-style): ```diff - if x == 0: - return 1/x + if x == 0: + raise ValueError('division by zero') ``` Acceptance: - Tests pass - No new regressions
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Java", "developer_needs": [ "auditability", "evaluation_metrics", "cost_latency_tradeoffs", "ci_integration" ], "moe_experts": [ "agentic_systems_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
dc1febbdb502b355e98fffe58917d2135d8dfe34
train_02850
2026-01-01T00:00:00
Dataset curation pipelines (filter, dedupe, quality)
data_pipeline
advanced
Task: data_pipeline Topic: Dataset curation pipelines (filter, dedupe, quality) Difficulty: advanced Target language: Rust Context: High-traffic service with latency SLOs. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Pipeline: Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
[]
{ "target_language": "Rust", "developer_needs": [ "reproducibility", "documentation", "tooling", "governance" ], "moe_experts": [ "performance_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
ad49338b7f8ef8f42b778c64f44f3cf9ae62296d
train_02851
2026-01-01T00:00:00
Latency, cost, and reliability optimization
agent_loop
advanced
Task: agent_loop Topic: Latency, cost, and reliability optimization Difficulty: advanced Target language: C# Context: Regulated environment requiring audit trails. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Loop: Plan → Edit → Test → Reflect → Human gate
[]
{ "target_language": "C#", "developer_needs": [ "tests_are_truth", "tooling", "ci_integration", "security_gates" ], "moe_experts": [ "data_curation_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
f66268f32345c71b216b447ebd03e73851908776
train_02852
2026-01-01T00:00:00
Latency, cost, and reliability optimization
explain
expert
Task: explain Topic: Latency, cost, and reliability optimization Difficulty: expert Target language: Rust Context: Research team validating claims against real repos. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "Rust", "developer_needs": [ "reproducibility", "tooling", "security_gates", "auditability" ], "moe_experts": [ "governance_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
2985006bf6b2dd4fabf0a79b744e3014ab2de5bd
train_02853
2026-01-01T00:00:00
Latency, cost, and reliability optimization
eval
intermediate
Task: eval Topic: Latency, cost, and reliability optimization Difficulty: intermediate Target language: SQL Context: Regulated environment requiring audit trails. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Eval: pass@k, time-to-green, regressions, diff size
[]
{ "target_language": "SQL", "developer_needs": [ "repo_scale_reasoning", "tooling", "tests_are_truth", "governance" ], "moe_experts": [ "data_curation_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
25c6da5fbd251fbb2b51cc069dc7db58f4bac432
train_02854
2026-01-01T00:00:00
Tool calling, sandboxes, and CI integration
review
advanced
Task: review Topic: Tool calling, sandboxes, and CI integration Difficulty: advanced Target language: TypeScript Context: High-traffic service with latency SLOs. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Review: correctness, security, performance, governance
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "TypeScript", "developer_needs": [ "auditability", "tooling", "tests_are_truth", "reproducibility" ], "moe_experts": [ "agentic_systems_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
770446aef23deef5f4733ae323c7bcf48adacb42
train_02855
2026-01-01T00:00:00
Dataset curation pipelines (filter, dedupe, quality)
failure_analysis
intermediate
Task: failure_analysis Topic: Dataset curation pipelines (filter, dedupe, quality) Difficulty: intermediate Target language: TypeScript Context: Regulated environment requiring audit trails. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Failure: - Initial patch broke edge case Reflection: - Missing zero-input guard Correction: - Add explicit validation + test
[]
{ "target_language": "TypeScript", "developer_needs": [ "repo_scale_reasoning", "governance", "cost_latency_tradeoffs", "security_gates" ], "moe_experts": [ "governance_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
df84a920525517e34858a39906ee28f8004216b5
train_02856
2026-01-01T00:00:00
Mixture-of-Experts (MoE) for code
failure_analysis
expert
Task: failure_analysis Topic: Mixture-of-Experts (MoE) for code Difficulty: expert Target language: C# Context: Regulated environment requiring audit trails. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Failure: - Initial patch broke edge case Reflection: - Missing zero-input guard Correction: - Add explicit validation + test
[]
{ "target_language": "C#", "developer_needs": [ "evaluation_metrics", "reproducibility", "cost_latency_tradeoffs", "documentation" ], "moe_experts": [ "security_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
d359f449eb60183ba2b943a12a0d4c49e68e3d67
train_02857
2026-01-01T00:00:00
Tool calling, sandboxes, and CI integration
failure_analysis
intermediate
Task: failure_analysis Topic: Tool calling, sandboxes, and CI integration Difficulty: intermediate Target language: Python Context: Offline/local deployment with limited compute. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Failure: - Initial patch broke edge case Reflection: - Missing zero-input guard Correction: - Add explicit validation + test
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Python", "developer_needs": [ "repo_scale_reasoning", "cost_latency_tradeoffs", "tests_are_truth", "auditability" ], "moe_experts": [ "performance_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
c42634743ae6d00af3620679c766356e6f203e57
train_02858
2026-01-01T00:00:00
Dataset curation pipelines (filter, dedupe, quality)
eval
expert
Task: eval Topic: Dataset curation pipelines (filter, dedupe, quality) Difficulty: expert Target language: SQL Context: Large monorepo with flaky tests and strict CI. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Eval: pass@k, time-to-green, regressions, diff size
[]
{ "target_language": "SQL", "developer_needs": [ "repo_scale_reasoning", "tests_are_truth", "cost_latency_tradeoffs", "tooling" ], "moe_experts": [ "evaluation_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
898fcea0ffc73526515df5abdfee84bc7777ac8c
train_02859
2026-01-01T00:00:00
Multimodal dev workflows (docs, diagrams, traces)
data_pipeline
expert
Task: data_pipeline Topic: Multimodal dev workflows (docs, diagrams, traces) Difficulty: expert Target language: SQL Context: High-traffic service with latency SLOs. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Pipeline: Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
[]
{ "target_language": "SQL", "developer_needs": [ "cost_latency_tradeoffs", "documentation", "repo_scale_reasoning", "evaluation_metrics" ], "moe_experts": [ "governance_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
b3708d9ea50ddc19ac9889af380b53ca52e07d7d
train_02860
2026-01-01T00:00:00
Secure code generation and policy gates
patch_diff
intermediate
Task: patch_diff Topic: Secure code generation and policy gates Difficulty: intermediate Target language: Go Context: Large monorepo with flaky tests and strict CI. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Patch (diff-style): ```diff - if x == 0: - return 1/x + if x == 0: + raise ValueError('division by zero') ``` Acceptance: - Tests pass - No new regressions
[]
{ "target_language": "Go", "developer_needs": [ "evaluation_metrics", "cost_latency_tradeoffs", "reproducibility", "repo_scale_reasoning" ], "moe_experts": [ "evaluation_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
8205b568b3b3f62b7980bc242c6f513fefdf6e5e
train_02861
2026-01-01T00:00:00
Governance, provenance, and licensing for code data
explain
advanced
Task: explain Topic: Governance, provenance, and licensing for code data Difficulty: advanced Target language: Bash Context: Large monorepo with flaky tests and strict CI. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Bash", "developer_needs": [ "tests_are_truth", "tooling", "repo_scale_reasoning", "security_gates" ], "moe_experts": [ "data_curation_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
041d9f4ec29572e4e26c59ee12cc35d3cd022afd
train_02862
2026-01-01T00:00:00
Agentic coding systems (plan→edit→test→reflect)
agent_loop
expert
Task: agent_loop Topic: Agentic coding systems (plan→edit→test→reflect) Difficulty: expert Target language: Bash Context: Research team validating claims against real repos. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Loop: Plan → Edit → Test → Reflect → Human gate
[]
{ "target_language": "Bash", "developer_needs": [ "auditability", "evaluation_metrics", "tests_are_truth", "tooling" ], "moe_experts": [ "security_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
486a402923c39128fb10b0a97ee4877722b5372d
train_02863
2026-01-01T00:00:00
Reasoning-first coding models and tunable deliberation
compare
advanced
Task: compare Topic: Reasoning-first coding models and tunable deliberation Difficulty: advanced Target language: Python Context: Research team validating claims against real repos. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Compare: capability, cost, latency, reliability
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Python", "developer_needs": [ "auditability", "governance", "cost_latency_tradeoffs", "ci_integration" ], "moe_experts": [ "coding_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
f05fed70d41c575b9ea166b634b01b8028f56d75
train_02864
2026-01-01T00:00:00
Dataset curation pipelines (filter, dedupe, quality)
compare
advanced
Task: compare Topic: Dataset curation pipelines (filter, dedupe, quality) Difficulty: advanced Target language: JavaScript Context: Research team validating claims against real repos. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Compare: capability, cost, latency, reliability
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "JavaScript", "developer_needs": [ "tests_are_truth", "tooling", "security_gates", "governance" ], "moe_experts": [ "evaluation_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
6df90cb7cd7f1fbb39f563ea78414e16c836f3fb
train_02865
2026-01-01T00:00:00
Agentic coding systems (plan→edit→test→reflect)
failure_analysis
expert
Task: failure_analysis Topic: Agentic coding systems (plan→edit→test→reflect) Difficulty: expert Target language: Bash Context: Research team validating claims against real repos. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Failure: - Initial patch broke edge case Reflection: - Missing zero-input guard Correction: - Add explicit validation + test
[]
{ "target_language": "Bash", "developer_needs": [ "security_gates", "governance", "evaluation_metrics", "repo_scale_reasoning" ], "moe_experts": [ "governance_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
14b4f4c24241b3ef6fc32300a717f8e5f1b850d2
train_02866
2026-01-01T00:00:00
Extended context and repo-scale understanding
failure_analysis
intermediate
Task: failure_analysis Topic: Extended context and repo-scale understanding Difficulty: intermediate Target language: Java Context: Research team validating claims against real repos. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Failure: - Initial patch broke edge case Reflection: - Missing zero-input guard Correction: - Add explicit validation + test
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Java", "developer_needs": [ "repo_scale_reasoning", "reproducibility", "tests_are_truth", "documentation" ], "moe_experts": [ "governance_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
8277ad08cc8b51c787ece9d5b8cd375c1d953a1a
train_02867
2026-01-01T00:00:00
Mixture-of-Experts (MoE) for code
explain
intermediate
Task: explain Topic: Mixture-of-Experts (MoE) for code Difficulty: intermediate Target language: C# Context: High-traffic service with latency SLOs. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "C#", "developer_needs": [ "tests_are_truth", "ci_integration", "governance", "evaluation_metrics" ], "moe_experts": [ "security_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
735e5b25be1b4953c525779778bb9314664a5bb1
train_02868
2026-01-01T00:00:00
Latency, cost, and reliability optimization
eval
expert
Task: eval Topic: Latency, cost, and reliability optimization Difficulty: expert Target language: Rust Context: Large monorepo with flaky tests and strict CI. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Eval: pass@k, time-to-green, regressions, diff size
[]
{ "target_language": "Rust", "developer_needs": [ "security_gates", "ci_integration", "auditability", "tests_are_truth" ], "moe_experts": [ "data_curation_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
f94e1052ff4fe16ce22fd275309a35f19c9736d4
train_02869
2026-01-01T00:00:00
Agentic coding systems (plan→edit→test→reflect)
review
intermediate
Task: review Topic: Agentic coding systems (plan→edit→test→reflect) Difficulty: intermediate Target language: SQL Context: Research team validating claims against real repos. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Review: correctness, security, performance, governance
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "SQL", "developer_needs": [ "reproducibility", "repo_scale_reasoning", "governance", "security_gates" ], "moe_experts": [ "coding_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
ab7ffacff5e2f307fa820066718a7a364f606d3c
train_02870
2026-01-01T00:00:00
Self-improving agents and feedback loops
eval
intermediate
Task: eval Topic: Self-improving agents and feedback loops Difficulty: intermediate Target language: C# Context: Research team validating claims against real repos. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Eval: pass@k, time-to-green, regressions, diff size
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "C#", "developer_needs": [ "evaluation_metrics", "documentation", "governance", "ci_integration" ], "moe_experts": [ "coding_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
288f29b1bd60e76339565134f7bd1c98f03ed2b2
train_02871
2026-01-01T00:00:00
Mixture-of-Experts (MoE) for code
data_pipeline
intermediate
Task: data_pipeline Topic: Mixture-of-Experts (MoE) for code Difficulty: intermediate Target language: TypeScript Context: Offline/local deployment with limited compute. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Pipeline: Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "TypeScript", "developer_needs": [ "governance", "auditability", "cost_latency_tradeoffs", "evaluation_metrics" ], "moe_experts": [ "evaluation_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
af53434fb3cb3949f5cea09593c18971f48b051a
train_02872
2026-01-01T00:00:00
Secure code generation and policy gates
eval
expert
Task: eval Topic: Secure code generation and policy gates Difficulty: expert Target language: Java Context: Regulated environment requiring audit trails. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Eval: pass@k, time-to-green, regressions, diff size
[]
{ "target_language": "Java", "developer_needs": [ "security_gates", "repo_scale_reasoning", "governance", "tests_are_truth" ], "moe_experts": [ "agentic_systems_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
b75788aba9ea859cf9df25bca91594fa8bcb21e7
train_02873
2026-01-01T00:00:00
SWE-bench style real-repo evaluation
code
intermediate
Task: code Topic: SWE-bench style real-repo evaluation Difficulty: intermediate Target language: C# Context: Offline/local deployment with limited compute. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "C#", "developer_needs": [ "auditability", "documentation", "ci_integration", "reproducibility" ], "moe_experts": [ "governance_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
56a4625d5ce33da2b43abf776e77c604d735d2ad
train_02874
2026-01-01T00:00:00
SWE-bench style real-repo evaluation
review
intermediate
Task: review Topic: SWE-bench style real-repo evaluation Difficulty: intermediate Target language: SQL Context: High-traffic service with latency SLOs. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Review: correctness, security, performance, governance
[]
{ "target_language": "SQL", "developer_needs": [ "auditability", "ci_integration", "evaluation_metrics", "reproducibility" ], "moe_experts": [ "data_curation_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
cbba8fff8f166317721cf895f39d2d33c25b98e2
train_02875
2026-01-01T00:00:00
Tool calling, sandboxes, and CI integration
failure_analysis
advanced
Task: failure_analysis Topic: Tool calling, sandboxes, and CI integration Difficulty: advanced Target language: SQL Context: Regulated environment requiring audit trails. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Failure: - Initial patch broke edge case Reflection: - Missing zero-input guard Correction: - Add explicit validation + test
[]
{ "target_language": "SQL", "developer_needs": [ "governance", "tooling", "auditability", "tests_are_truth" ], "moe_experts": [ "coding_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
e910d2c94f57dd63d51d92f7dd486c19a2e50f54
train_02876
2026-01-01T00:00:00
Agentic coding systems (plan→edit→test→reflect)
explain
advanced
Task: explain Topic: Agentic coding systems (plan→edit→test→reflect) Difficulty: advanced Target language: Python Context: Offline/local deployment with limited compute. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Python", "developer_needs": [ "cost_latency_tradeoffs", "evaluation_metrics", "repo_scale_reasoning", "tests_are_truth" ], "moe_experts": [ "data_curation_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
9a4caea74258787176aa9f6373d993e94b5fc329
train_02877
2026-01-01T00:00:00
Latency, cost, and reliability optimization
data_pipeline
expert
Task: data_pipeline Topic: Latency, cost, and reliability optimization Difficulty: expert Target language: Python Context: Offline/local deployment with limited compute. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Pipeline: Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
[]
{ "target_language": "Python", "developer_needs": [ "tooling", "ci_integration", "documentation", "reproducibility" ], "moe_experts": [ "evaluation_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
b98bab65dfec8814fe25dce736b760c463c2dd8f
train_02878
2026-01-01T00:00:00
Dataset curation pipelines (filter, dedupe, quality)
eval
intermediate
Task: eval Topic: Dataset curation pipelines (filter, dedupe, quality) Difficulty: intermediate Target language: Bash Context: Large monorepo with flaky tests and strict CI. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Eval: pass@k, time-to-green, regressions, diff size
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Bash", "developer_needs": [ "documentation", "tooling", "security_gates", "ci_integration" ], "moe_experts": [ "governance_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
26ef1b976690417c5409fbd5cece2527b282ae75
train_02879
2026-01-01T00:00:00
Multimodal dev workflows (docs, diagrams, traces)
design
expert
Task: design Topic: Multimodal dev workflows (docs, diagrams, traces) Difficulty: expert Target language: Go Context: Large monorepo with flaky tests and strict CI. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "Go", "developer_needs": [ "tests_are_truth", "evaluation_metrics", "ci_integration", "cost_latency_tradeoffs" ], "moe_experts": [ "agentic_systems_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
740610224de50d51e86589690140bcc4ec7f1758
train_02880
2026-01-01T00:00:00
Agentic coding systems (plan→edit→test→reflect)
review
intermediate
Task: review Topic: Agentic coding systems (plan→edit→test→reflect) Difficulty: intermediate Target language: SQL Context: High-traffic service with latency SLOs. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Review: correctness, security, performance, governance
[]
{ "target_language": "SQL", "developer_needs": [ "security_gates", "tooling", "tests_are_truth", "documentation" ], "moe_experts": [ "data_curation_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
702dbf27f2f2325b62e727804893f526222944ee
train_02881
2026-01-01T00:00:00
Mixture-of-Experts (MoE) for code
design
advanced
Task: design Topic: Mixture-of-Experts (MoE) for code Difficulty: advanced Target language: Bash Context: High-traffic service with latency SLOs. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "Bash", "developer_needs": [ "tooling", "repo_scale_reasoning", "tests_are_truth", "evaluation_metrics" ], "moe_experts": [ "security_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
6ab5f74f7bc4d955678c20f7da27373ed8c0da15
train_02882
2026-01-01T00:00:00
Reasoning-first coding models and tunable deliberation
agent_loop
intermediate
Task: agent_loop Topic: Reasoning-first coding models and tunable deliberation Difficulty: intermediate Target language: JavaScript Context: Research team validating claims against real repos. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Loop: Plan → Edit → Test → Reflect → Human gate
[]
{ "target_language": "JavaScript", "developer_needs": [ "cost_latency_tradeoffs", "ci_integration", "tests_are_truth", "auditability" ], "moe_experts": [ "security_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
3cdc46bc3cbdad20901ea8cd0d9f11a0cc8f8489
train_02883
2026-01-01T00:00:00
Secure code generation and policy gates
design
intermediate
Task: design Topic: Secure code generation and policy gates Difficulty: intermediate Target language: C# Context: Regulated environment requiring audit trails. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "C#", "developer_needs": [ "evaluation_metrics", "repo_scale_reasoning", "cost_latency_tradeoffs", "documentation" ], "moe_experts": [ "agentic_systems_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
ef98dec268911f9fa20867bc6031a319cf972fed
train_02884
2026-01-01T00:00:00
Self-improving agents and feedback loops
compare
intermediate
Task: compare Topic: Self-improving agents and feedback loops Difficulty: intermediate Target language: Rust Context: Research team validating claims against real repos. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Compare: capability, cost, latency, reliability
[]
{ "target_language": "Rust", "developer_needs": [ "repo_scale_reasoning", "reproducibility", "tests_are_truth", "auditability" ], "moe_experts": [ "performance_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
9b1c1c98e4f60772f7a89538a6e473eef6463d44
train_02885
2026-01-01T00:00:00
Dataset curation pipelines (filter, dedupe, quality)
code
expert
Task: code Topic: Dataset curation pipelines (filter, dedupe, quality) Difficulty: expert Target language: TypeScript Context: Offline/local deployment with limited compute. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "TypeScript", "developer_needs": [ "documentation", "tooling", "security_gates", "governance" ], "moe_experts": [ "performance_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
39cfea606c2efabffe6df9971e6f15ef7cb1ce7b
train_02886
2026-01-01T00:00:00
Agentic coding systems (plan→edit→test→reflect)
agent_loop
expert
Task: agent_loop Topic: Agentic coding systems (plan→edit→test→reflect) Difficulty: expert Target language: Bash Context: Research team validating claims against real repos. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Loop: Plan → Edit → Test → Reflect → Human gate
[]
{ "target_language": "Bash", "developer_needs": [ "governance", "cost_latency_tradeoffs", "reproducibility", "auditability" ], "moe_experts": [ "coding_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
486a402923c39128fb10b0a97ee4877722b5372d
train_02887
2026-01-01T00:00:00
Tool calling, sandboxes, and CI integration
data_pipeline
advanced
Task: data_pipeline Topic: Tool calling, sandboxes, and CI integration Difficulty: advanced Target language: Python Context: Regulated environment requiring audit trails. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Pipeline: Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Python", "developer_needs": [ "tooling", "security_gates", "repo_scale_reasoning", "documentation" ], "moe_experts": [ "evaluation_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
f42d9f9702aad676c4878230909df787ad1570cb
train_02888
2026-01-01T00:00:00
SWE-bench style real-repo evaluation
data_pipeline
intermediate
Task: data_pipeline Topic: SWE-bench style real-repo evaluation Difficulty: intermediate Target language: Go Context: Regulated environment requiring audit trails. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Pipeline: Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
[]
{ "target_language": "Go", "developer_needs": [ "governance", "security_gates", "reproducibility", "auditability" ], "moe_experts": [ "coding_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
8113bb751621a96cac4d4ec2c5f8e7936093d029
train_02889
2026-01-01T00:00:00
Agentic coding systems (plan→edit→test→reflect)
failure_analysis
advanced
Task: failure_analysis Topic: Agentic coding systems (plan→edit→test→reflect) Difficulty: advanced Target language: SQL Context: Research team validating claims against real repos. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Failure: - Initial patch broke edge case Reflection: - Missing zero-input guard Correction: - Add explicit validation + test
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "SQL", "developer_needs": [ "auditability", "evaluation_metrics", "tooling", "documentation" ], "moe_experts": [ "security_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
b5c04876c3a0da32658605e0f0244a311d736d06
train_02890
2026-01-01T00:00:00
SWE-bench style real-repo evaluation
failure_analysis
intermediate
Task: failure_analysis Topic: SWE-bench style real-repo evaluation Difficulty: intermediate Target language: Python Context: Offline/local deployment with limited compute. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Failure: - Initial patch broke edge case Reflection: - Missing zero-input guard Correction: - Add explicit validation + test
[]
{ "target_language": "Python", "developer_needs": [ "security_gates", "reproducibility", "cost_latency_tradeoffs", "tests_are_truth" ], "moe_experts": [ "performance_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
95c7ed704c16951b82bcc0b1f58e43ee0455e065
train_02891
2026-01-01T00:00:00
Extended context and repo-scale understanding
data_pipeline
expert
Task: data_pipeline Topic: Extended context and repo-scale understanding Difficulty: expert Target language: Bash Context: High-traffic service with latency SLOs. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Pipeline: Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Bash", "developer_needs": [ "evaluation_metrics", "security_gates", "governance", "reproducibility" ], "moe_experts": [ "performance_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
2d203de9227da61dc39fbba059c42b77cbebfecf
train_02892
2026-01-01T00:00:00
Model merging, distillation, and continued pretraining
agent_loop
expert
Task: agent_loop Topic: Model merging, distillation, and continued pretraining Difficulty: expert Target language: TypeScript Context: Large monorepo with flaky tests and strict CI. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Loop: Plan → Edit → Test → Reflect → Human gate
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "TypeScript", "developer_needs": [ "repo_scale_reasoning", "tooling", "ci_integration", "security_gates" ], "moe_experts": [ "security_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
87a69130c04dd73f000176eb9ac38d5a2f400aee
train_02893
2026-01-01T00:00:00
Extended context and repo-scale understanding
data_pipeline
intermediate
Task: data_pipeline Topic: Extended context and repo-scale understanding Difficulty: intermediate Target language: C# Context: Regulated environment requiring audit trails. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Pipeline: Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "C#", "developer_needs": [ "documentation", "auditability", "ci_integration", "security_gates" ], "moe_experts": [ "governance_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
ffed4af49f0f3d6c21e6ae4ac0e3109853f578c6
train_02894
2026-01-01T00:00:00
Self-improving agents and feedback loops
patch_diff
expert
Task: patch_diff Topic: Self-improving agents and feedback loops Difficulty: expert Target language: Java Context: Large monorepo with flaky tests and strict CI. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Patch (diff-style): ```diff - if x == 0: - return 1/x + if x == 0: + raise ValueError('division by zero') ``` Acceptance: - Tests pass - No new regressions
[]
{ "target_language": "Java", "developer_needs": [ "governance", "security_gates", "ci_integration", "repo_scale_reasoning" ], "moe_experts": [ "agentic_systems_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
227675d01f91459382ad62d84f0c74cb020212af
train_02895
2026-01-01T00:00:00
SWE-bench style real-repo evaluation
design
advanced
Task: design Topic: SWE-bench style real-repo evaluation Difficulty: advanced Target language: Go Context: High-traffic service with latency SLOs. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "Go", "developer_needs": [ "cost_latency_tradeoffs", "security_gates", "governance", "repo_scale_reasoning" ], "moe_experts": [ "evaluation_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
c48f8250326cb8ddf4af95491be28a0bbcad33a8
train_02896
2026-01-01T00:00:00
Code-specialized model families and sizing tradeoffs
compare
advanced
Task: compare Topic: Code-specialized model families and sizing tradeoffs Difficulty: advanced Target language: Go Context: High-traffic service with latency SLOs. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Compare: capability, cost, latency, reliability
[]
{ "target_language": "Go", "developer_needs": [ "governance", "security_gates", "evaluation_metrics", "tooling" ], "moe_experts": [ "governance_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
4c8b83a0095fb77aee8b423ec204faa8194d807b
train_02897
2026-01-01T00:00:00
SWE-bench style real-repo evaluation
data_pipeline
intermediate
Task: data_pipeline Topic: SWE-bench style real-repo evaluation Difficulty: intermediate Target language: Go Context: Regulated environment requiring audit trails. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Pipeline: Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
[]
{ "target_language": "Go", "developer_needs": [ "governance", "documentation", "cost_latency_tradeoffs", "evaluation_metrics" ], "moe_experts": [ "security_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
8113bb751621a96cac4d4ec2c5f8e7936093d029
train_02898
2026-01-01T00:00:00
Dataset curation pipelines (filter, dedupe, quality)
code
expert
Task: code Topic: Dataset curation pipelines (filter, dedupe, quality) Difficulty: expert Target language: TypeScript Context: Regulated environment requiring audit trails. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "TypeScript", "developer_needs": [ "security_gates", "governance", "tooling", "auditability" ], "moe_experts": [ "security_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
1583e48fcf3a0c237c27cef020b4f06fca63bc18
train_02899
2026-01-01T00:00:00
Governance, provenance, and licensing for code data
explain
intermediate
Task: explain Topic: Governance, provenance, and licensing for code data Difficulty: intermediate Target language: Go Context: High-traffic service with latency SLOs. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Go", "developer_needs": [ "cost_latency_tradeoffs", "auditability", "tooling", "evaluation_metrics" ], "moe_experts": [ "performance_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
9782f6762a029f25b3e8f6166d328efd2697443f