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train_03500
2026-01-01T00:00:00
Mixture-of-Experts (MoE) for code
compare
advanced
Task: compare Topic: Mixture-of-Experts (MoE) for code 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
[]
{ "target_language": "JavaScript", "developer_needs": [ "governance", "cost_latency_tradeoffs", "ci_integration", "repo_scale_reasoning" ], "moe_experts": [ "security_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
5048f0b37380a119b42fbfc5791e0d3b0dd186da
train_03501
2026-01-01T00:00:00
Agentic coding systems (plan→edit→test→reflect)
failure_analysis
intermediate
Task: failure_analysis Topic: Agentic coding systems (plan→edit→test→reflect) Difficulty: intermediate 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. 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": "Bash", "developer_needs": [ "governance", "auditability", "cost_latency_tradeoffs", "documentation" ], "moe_experts": [ "evaluation_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
605a9d35fd76ce2c9748fd0fecca6fbf59d10e96
train_03502
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: 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. 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": [ "evaluation_metrics", "cost_latency_tradeoffs", "governance", "ci_integration" ], "moe_experts": [ "evaluation_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
31b70315c7753574af5243747a0196d0182d4470
train_03503
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: 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. 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": [ "security_gates", "reproducibility", "evaluation_metrics", "repo_scale_reasoning" ], "moe_experts": [ "agentic_systems_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
b4ec470f6afe3a37c02126303209f19d19f96dff
train_03504
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: 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. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "Go", "developer_needs": [ "security_gates", "auditability", "tests_are_truth", "reproducibility" ], "moe_experts": [ "performance_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
a53d0a39b896b4da3a23ef0260b169ceaab0adaa
train_03505
2026-01-01T00:00:00
Tool calling, sandboxes, and CI integration
agent_loop
intermediate
Task: agent_loop Topic: Tool calling, sandboxes, and CI integration 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. Loop: Plan → Edit → Test → Reflect → Human gate
[]
{ "target_language": "Bash", "developer_needs": [ "governance", "documentation", "reproducibility", "evaluation_metrics" ], "moe_experts": [ "performance_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
d3c55836b5e7d8ad6c524a7350b534d6caf67df4
train_03506
2026-01-01T00:00:00
Tool calling, sandboxes, and CI integration
code
expert
Task: code Topic: Tool calling, sandboxes, and CI integration 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. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "SQL", "developer_needs": [ "evaluation_metrics", "auditability", "reproducibility", "ci_integration" ], "moe_experts": [ "security_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
59765da14ba33bd4d01c7cc09160a6188e303505
train_03507
2026-01-01T00:00:00
Self-improving agents and feedback loops
design
intermediate
Task: design Topic: Self-improving agents and feedback loops Difficulty: intermediate 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
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Java", "developer_needs": [ "tests_are_truth", "security_gates", "ci_integration", "governance" ], "moe_experts": [ "evaluation_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
cb2a9301b8ac14b50ea16fbf2a0837c6f65998b9
train_03508
2026-01-01T00:00:00
Tool calling, sandboxes, and CI integration
explain
expert
Task: explain Topic: Tool calling, sandboxes, and CI integration Difficulty: expert 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
[]
{ "target_language": "Python", "developer_needs": [ "auditability", "ci_integration", "security_gates", "documentation" ], "moe_experts": [ "security_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
7f9c136562ec7e7ca997b143c9e14523a7b02f5b
train_03509
2026-01-01T00:00:00
Model merging, distillation, and continued pretraining
data_pipeline
advanced
Task: data_pipeline Topic: Model merging, distillation, and continued pretraining 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. Pipeline: Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
[]
{ "target_language": "Go", "developer_needs": [ "tooling", "evaluation_metrics", "repo_scale_reasoning", "security_gates" ], "moe_experts": [ "performance_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
679b962e9ae7a60717ca4973932c36fd3034ef01
train_03510
2026-01-01T00:00:00
Mixture-of-Experts (MoE) for code
review
advanced
Task: review Topic: Mixture-of-Experts (MoE) for code Difficulty: advanced 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. Review: correctness, security, performance, governance
[]
{ "target_language": "Bash", "developer_needs": [ "cost_latency_tradeoffs", "tooling", "reproducibility", "repo_scale_reasoning" ], "moe_experts": [ "governance_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
c9abe9b2c9d8536616eca68615c78da1335e08bc
train_03511
2026-01-01T00:00:00
Dataset curation pipelines (filter, dedupe, quality)
failure_analysis
expert
Task: failure_analysis Topic: Dataset curation pipelines (filter, dedupe, quality) 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. 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": "Bash", "developer_needs": [ "tests_are_truth", "documentation", "reproducibility", "auditability" ], "moe_experts": [ "performance_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
f645d189f3267c5595fd3f2562486e91161ac388
train_03512
2026-01-01T00:00:00
Governance, provenance, and licensing for code data
code
intermediate
Task: code Topic: Governance, provenance, and licensing for code data Difficulty: intermediate 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
[]
{ "target_language": "TypeScript", "developer_needs": [ "auditability", "reproducibility", "evaluation_metrics", "cost_latency_tradeoffs" ], "moe_experts": [ "coding_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
f8bb7de103f35b9690a6e29a9a1560d177105bdd
train_03513
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: 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
[]
{ "target_language": "Bash", "developer_needs": [ "repo_scale_reasoning", "tests_are_truth", "governance", "auditability" ], "moe_experts": [ "agentic_systems_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
d01a3b8200df41c4c6b7d1cc0fbb0ad39a11019c
train_03514
2026-01-01T00:00:00
Agentic coding systems (plan→edit→test→reflect)
compare
expert
Task: compare Topic: Agentic coding systems (plan→edit→test→reflect) Difficulty: expert 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. Compare: capability, cost, latency, reliability
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Go", "developer_needs": [ "governance", "repo_scale_reasoning", "tooling", "security_gates" ], "moe_experts": [ "agentic_systems_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
3c4022c4b3fa89de13da049d7983757c7e8c30d4
train_03515
2026-01-01T00:00:00
Latency, cost, and reliability optimization
code
intermediate
Task: code Topic: Latency, cost, and reliability optimization 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. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "TypeScript", "developer_needs": [ "repo_scale_reasoning", "reproducibility", "governance", "cost_latency_tradeoffs" ], "moe_experts": [ "agentic_systems_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
77252909ca10958847406ba2787946635974695c
train_03516
2026-01-01T00:00:00
SWE-bench style real-repo evaluation
patch_diff
advanced
Task: patch_diff Topic: SWE-bench style real-repo evaluation Difficulty: advanced 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. 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": "TypeScript", "developer_needs": [ "tooling", "tests_are_truth", "auditability", "governance" ], "moe_experts": [ "evaluation_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
9459dc9d18d6b5ffc973ec6b453c7f6de16b62e7
train_03517
2026-01-01T00:00:00
Dataset curation pipelines (filter, dedupe, quality)
compare
intermediate
Task: compare Topic: Dataset curation pipelines (filter, dedupe, quality) Difficulty: intermediate 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. Compare: capability, cost, latency, reliability
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "SQL", "developer_needs": [ "reproducibility", "tests_are_truth", "ci_integration", "tooling" ], "moe_experts": [ "data_curation_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
633b6525ae89589c8fa3a3ab61a9bf6ea3dd7cd2
train_03518
2026-01-01T00:00:00
Model merging, distillation, and continued pretraining
design
expert
Task: design Topic: Model merging, distillation, and continued pretraining Difficulty: expert 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
[]
{ "target_language": "JavaScript", "developer_needs": [ "cost_latency_tradeoffs", "tooling", "auditability", "governance" ], "moe_experts": [ "security_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
9e849179b75021ed34cb0e8d765264e1f173f0ca
train_03519
2026-01-01T00:00:00
Latency, cost, and reliability optimization
failure_analysis
intermediate
Task: failure_analysis Topic: Latency, cost, and reliability optimization 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. Failure: - Initial patch broke edge case Reflection: - Missing zero-input guard Correction: - Add explicit validation + test
[]
{ "target_language": "JavaScript", "developer_needs": [ "ci_integration", "documentation", "evaluation_metrics", "reproducibility" ], "moe_experts": [ "performance_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
9c3770e7a94151089c6377d1dd1956a798f6b87f
train_03520
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: 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
[]
{ "target_language": "JavaScript", "developer_needs": [ "security_gates", "repo_scale_reasoning", "ci_integration", "governance" ], "moe_experts": [ "security_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
fa0ca77cad6aa070c1d1fba3632e413886ec3c61
train_03521
2026-01-01T00:00:00
Model merging, distillation, and continued pretraining
compare
intermediate
Task: compare Topic: Model merging, distillation, and continued pretraining 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": [ "security_gates", "tooling", "cost_latency_tradeoffs", "reproducibility" ], "moe_experts": [ "agentic_systems_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
1a63cdd152c163f5905a8258f3889e176889332a
train_03522
2026-01-01T00:00:00
Dataset curation pipelines (filter, dedupe, quality)
design
advanced
Task: design Topic: Dataset curation pipelines (filter, dedupe, quality) Difficulty: advanced 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. 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": "Java", "developer_needs": [ "governance", "cost_latency_tradeoffs", "ci_integration", "evaluation_metrics" ], "moe_experts": [ "evaluation_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
7cb47f40e814d024258c1b01cd7c7b194360875e
train_03523
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: 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. Compare: capability, cost, latency, reliability
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Go", "developer_needs": [ "security_gates", "auditability", "evaluation_metrics", "tests_are_truth" ], "moe_experts": [ "governance_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
2c96a5b682e237e36eae507d04ecc855468cc63e
train_03524
2026-01-01T00:00:00
SWE-bench style real-repo evaluation
patch_diff
advanced
Task: patch_diff Topic: SWE-bench style real-repo evaluation 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. 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": [ "evaluation_metrics", "governance", "tests_are_truth", "repo_scale_reasoning" ], "moe_experts": [ "governance_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
08a69669d36a212bd92bea9efafad033d301da79
train_03525
2026-01-01T00:00:00
Multimodal dev workflows (docs, diagrams, traces)
eval
advanced
Task: eval Topic: Multimodal dev workflows (docs, diagrams, traces) 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. Eval: pass@k, time-to-green, regressions, diff size
[]
{ "target_language": "Go", "developer_needs": [ "cost_latency_tradeoffs", "documentation", "security_gates", "repo_scale_reasoning" ], "moe_experts": [ "evaluation_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
73fce57081cdf2ffdc0ea156ab5756fa608b133f
train_03526
2026-01-01T00:00:00
Model merging, distillation, and continued pretraining
review
intermediate
Task: review Topic: Model merging, distillation, and continued pretraining Difficulty: intermediate 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. Review: correctness, security, performance, governance
[]
{ "target_language": "Java", "developer_needs": [ "documentation", "cost_latency_tradeoffs", "governance", "evaluation_metrics" ], "moe_experts": [ "agentic_systems_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
828c20ce5b6619eb48714b1917c4382492c8f3d2
train_03527
2026-01-01T00:00:00
Dataset curation pipelines (filter, dedupe, quality)
compare
expert
Task: compare Topic: Dataset curation pipelines (filter, dedupe, quality) Difficulty: expert 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. Compare: capability, cost, latency, reliability
[]
{ "target_language": "Go", "developer_needs": [ "reproducibility", "cost_latency_tradeoffs", "tests_are_truth", "repo_scale_reasoning" ], "moe_experts": [ "data_curation_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
54a6821e1bdbe9d866396da7328ade128f62318b
train_03528
2026-01-01T00:00:00
Code-specialized model families and sizing tradeoffs
code
advanced
Task: code Topic: Code-specialized model families and sizing tradeoffs 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
[]
{ "target_language": "TypeScript", "developer_needs": [ "tests_are_truth", "governance", "documentation", "evaluation_metrics" ], "moe_experts": [ "security_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
73cf9767179918833811b6390e15a92ac85fcd26
train_03529
2026-01-01T00:00:00
Reasoning-first coding models and tunable deliberation
data_pipeline
expert
Task: data_pipeline Topic: Reasoning-first coding models and tunable deliberation Difficulty: expert Target language: TypeScript 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
[]
{ "target_language": "TypeScript", "developer_needs": [ "repo_scale_reasoning", "tooling", "evaluation_metrics", "tests_are_truth" ], "moe_experts": [ "security_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
72cc124fda3220813498c23131c37ce7107effb7
train_03530
2026-01-01T00:00:00
Self-improving agents and feedback loops
patch_diff
intermediate
Task: patch_diff Topic: Self-improving agents and feedback loops 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. 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": "TypeScript", "developer_needs": [ "evaluation_metrics", "security_gates", "documentation", "tooling" ], "moe_experts": [ "governance_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
89949ad9187b7b0b63d898af5d26c404adce0f22
train_03531
2026-01-01T00:00:00
Self-improving agents and feedback loops
data_pipeline
intermediate
Task: data_pipeline Topic: Self-improving agents and feedback loops 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. Pipeline: Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
[]
{ "target_language": "Java", "developer_needs": [ "reproducibility", "cost_latency_tradeoffs", "ci_integration", "security_gates" ], "moe_experts": [ "agentic_systems_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
96b2bc0d12a5288865547552e4f1bbd6f1528b00
train_03532
2026-01-01T00:00:00
Tool calling, sandboxes, and CI integration
agent_loop
expert
Task: agent_loop Topic: Tool calling, sandboxes, and CI integration Difficulty: expert 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. Loop: Plan → Edit → Test → Reflect → Human gate
[]
{ "target_language": "C#", "developer_needs": [ "repo_scale_reasoning", "reproducibility", "tooling", "security_gates" ], "moe_experts": [ "data_curation_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
110172fc3f44931c6fa802dfa00b69849ef359fd
train_03533
2026-01-01T00:00:00
Reasoning-first coding models and tunable deliberation
patch_diff
advanced
Task: patch_diff Topic: Reasoning-first coding models and tunable deliberation 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. 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": "JavaScript", "developer_needs": [ "cost_latency_tradeoffs", "documentation", "security_gates", "reproducibility" ], "moe_experts": [ "performance_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
f70b54edd263b60147625bf51957deb6183a724a
train_03534
2026-01-01T00:00:00
Governance, provenance, and licensing for code data
design
intermediate
Task: design Topic: Governance, provenance, and licensing for code data 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. 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", "reproducibility", "documentation", "repo_scale_reasoning" ], "moe_experts": [ "governance_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
615a83e8bee4e5aefbe9d7779e2889db2eb52c94
train_03535
2026-01-01T00:00:00
Extended context and repo-scale understanding
design
intermediate
Task: design Topic: Extended context and repo-scale understanding Difficulty: intermediate 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
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Rust", "developer_needs": [ "tests_are_truth", "reproducibility", "security_gates", "ci_integration" ], "moe_experts": [ "data_curation_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
eff2337e41c2c2255cbcf300afa97d3b9d397f05
train_03536
2026-01-01T00:00:00
Mixture-of-Experts (MoE) for code
compare
intermediate
Task: compare Topic: Mixture-of-Experts (MoE) for code Difficulty: intermediate 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. Compare: capability, cost, latency, reliability
[]
{ "target_language": "Java", "developer_needs": [ "repo_scale_reasoning", "auditability", "cost_latency_tradeoffs", "tooling" ], "moe_experts": [ "performance_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
e032b2d3de634e79492d713cfb0f11c840b64984
train_03537
2026-01-01T00:00:00
Mixture-of-Experts (MoE) for code
code
expert
Task: code Topic: Mixture-of-Experts (MoE) for code Difficulty: expert 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", "auditability", "tooling", "reproducibility" ], "moe_experts": [ "data_curation_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
a9567731fbe9c6ba02d8ee3ae091b08fcb8220cb
train_03538
2026-01-01T00:00:00
Tool calling, sandboxes, and CI integration
agent_loop
expert
Task: agent_loop Topic: Tool calling, sandboxes, and CI integration 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. 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", "evaluation_metrics", "auditability", "reproducibility" ], "moe_experts": [ "performance_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
9921047d2d4694eabc94bc3f07966ab20a7ef4ea
train_03539
2026-01-01T00:00:00
Self-improving agents and feedback loops
agent_loop
expert
Task: agent_loop Topic: Self-improving agents and feedback loops 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. 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": [ "governance", "tests_are_truth", "cost_latency_tradeoffs", "documentation" ], "moe_experts": [ "agentic_systems_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
cf9c6b4cf431b7e69f4031fe1def6d5306819807
train_03540
2026-01-01T00:00:00
Mixture-of-Experts (MoE) for code
patch_diff
intermediate
Task: patch_diff Topic: Mixture-of-Experts (MoE) for code Difficulty: intermediate 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. 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": [ "evaluation_metrics", "security_gates", "repo_scale_reasoning", "documentation" ], "moe_experts": [ "security_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
b3a7be1615f13557524072c9df6ac0eac07b9b12
train_03541
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: 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
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Go", "developer_needs": [ "governance", "reproducibility", "tooling", "documentation" ], "moe_experts": [ "security_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
a3a1b3dae635a45ea975f870d871f5eeb0407fed
train_03542
2026-01-01T00:00:00
Dataset curation pipelines (filter, dedupe, quality)
data_pipeline
intermediate
Task: data_pipeline Topic: Dataset curation pipelines (filter, dedupe, quality) Difficulty: intermediate 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. Pipeline: Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
[]
{ "target_language": "SQL", "developer_needs": [ "security_gates", "evaluation_metrics", "governance", "repo_scale_reasoning" ], "moe_experts": [ "coding_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
6635da64d705e88321c1feb952cc5a8c24151dc8
train_03543
2026-01-01T00:00:00
Multimodal dev workflows (docs, diagrams, traces)
patch_diff
expert
Task: patch_diff Topic: Multimodal dev workflows (docs, diagrams, traces) Difficulty: expert Target language: TypeScript 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. 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": "TypeScript", "developer_needs": [ "tooling", "security_gates", "tests_are_truth", "ci_integration" ], "moe_experts": [ "data_curation_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
a163d7556d6475c45e5ebcb5eca72df834c0238e
train_03544
2026-01-01T00:00:00
Model merging, distillation, and continued pretraining
design
expert
Task: design Topic: Model merging, distillation, and continued pretraining Difficulty: expert 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": [ "cost_latency_tradeoffs", "tests_are_truth", "evaluation_metrics", "ci_integration" ], "moe_experts": [ "agentic_systems_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
6b877419056b01ced904c8749934d65be9432696
train_03545
2026-01-01T00:00:00
Model merging, distillation, and continued pretraining
design
advanced
Task: design 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. 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": [ "cost_latency_tradeoffs", "tooling", "tests_are_truth", "evaluation_metrics" ], "moe_experts": [ "security_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
f133fb7f0b48b8e6873e2aa1b34573f9fe3da4d2
train_03546
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: 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. Eval: pass@k, time-to-green, regressions, diff size
[]
{ "target_language": "Python", "developer_needs": [ "governance", "ci_integration", "tests_are_truth", "cost_latency_tradeoffs" ], "moe_experts": [ "data_curation_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
c875d8c8844cc43831bd2f3304443fb3cfd4b681
train_03547
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: 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": "Go", "developer_needs": [ "auditability", "repo_scale_reasoning", "tests_are_truth", "reproducibility" ], "moe_experts": [ "governance_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
32a779c5c08edb61893cc6133238958ea21055bb
train_03548
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: 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. Review: correctness, security, performance, governance
[]
{ "target_language": "Bash", "developer_needs": [ "tests_are_truth", "reproducibility", "repo_scale_reasoning", "tooling" ], "moe_experts": [ "governance_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
af6fac4b9e7274cb6b65913a741a7c029af49403
train_03549
2026-01-01T00:00:00
Mixture-of-Experts (MoE) for code
review
expert
Task: review Topic: Mixture-of-Experts (MoE) for code Difficulty: expert Target language: JavaScript 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": "JavaScript", "developer_needs": [ "tests_are_truth", "governance", "documentation", "repo_scale_reasoning" ], "moe_experts": [ "data_curation_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
214c29199f262534dab640cdaf4ad2ec41752826
train_03550
2026-01-01T00:00:00
Tool calling, sandboxes, and CI integration
compare
advanced
Task: compare 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. Compare: capability, cost, latency, reliability
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "TypeScript", "developer_needs": [ "security_gates", "cost_latency_tradeoffs", "tests_are_truth", "auditability" ], "moe_experts": [ "coding_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
704dbfd79d4d3a7c04c97906159cbc2c97ae705a
train_03551
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: 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. 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": [ "governance", "reproducibility", "evaluation_metrics", "repo_scale_reasoning" ], "moe_experts": [ "coding_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
873f8469b20596af12a8289e2c231bf9c3ea5a5d
train_03552
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: TypeScript 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": "TypeScript", "developer_needs": [ "governance", "documentation", "auditability", "evaluation_metrics" ], "moe_experts": [ "coding_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
d39782139042eab69609be5158aa007297725857
train_03553
2026-01-01T00:00:00
Agentic coding systems (plan→edit→test→reflect)
compare
intermediate
Task: compare Topic: Agentic coding systems (plan→edit→test→reflect) 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. Compare: capability, cost, latency, reliability
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "TypeScript", "developer_needs": [ "governance", "reproducibility", "security_gates", "tests_are_truth" ], "moe_experts": [ "agentic_systems_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
10db25b1e23163c93816e33359449476e7a728c7
train_03554
2026-01-01T00:00:00
Secure code generation and policy gates
data_pipeline
expert
Task: data_pipeline Topic: Secure code generation and policy gates 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
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "JavaScript", "developer_needs": [ "governance", "evaluation_metrics", "security_gates", "ci_integration" ], "moe_experts": [ "evaluation_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
8982f5c1093ead68741db1c1b01c22c8d1c22d42
train_03555
2026-01-01T00:00:00
Secure code generation and policy gates
explain
expert
Task: explain Topic: Secure code generation and policy gates Difficulty: expert 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. 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": [ "documentation", "tests_are_truth", "evaluation_metrics", "tooling" ], "moe_experts": [ "coding_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
4b38bf21315dc5aaf15da3705f5d919c48e29603
train_03556
2026-01-01T00:00:00
Reasoning-first coding models and tunable deliberation
data_pipeline
advanced
Task: data_pipeline Topic: Reasoning-first coding models and tunable deliberation Difficulty: advanced 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. Pipeline: Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
[]
{ "target_language": "C#", "developer_needs": [ "repo_scale_reasoning", "evaluation_metrics", "governance", "reproducibility" ], "moe_experts": [ "governance_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
dd65112b4cd35001ab66dd80c200d019fb9a7fb1
train_03557
2026-01-01T00:00:00
Latency, cost, and reliability optimization
code
advanced
Task: code Topic: Latency, cost, and reliability optimization Difficulty: advanced 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": [ "ci_integration", "tooling", "tests_are_truth", "repo_scale_reasoning" ], "moe_experts": [ "data_curation_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
57cfeb3f8e1c37e6af897d62a954b1c711c5041b
train_03558
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: 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. Review: correctness, security, performance, governance
[]
{ "target_language": "Go", "developer_needs": [ "evaluation_metrics", "governance", "security_gates", "reproducibility" ], "moe_experts": [ "data_curation_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
234bd9a182e487cfc1e25b4e75abb8763cecfc33
train_03559
2026-01-01T00:00:00
Multimodal dev workflows (docs, diagrams, traces)
patch_diff
advanced
Task: patch_diff Topic: Multimodal dev workflows (docs, diagrams, traces) 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. 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": "Rust", "developer_needs": [ "auditability", "reproducibility", "cost_latency_tradeoffs", "tests_are_truth" ], "moe_experts": [ "performance_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
64cad735fbe618bf73e9290f6a77e521b004e0bb
train_03560
2026-01-01T00:00:00
Latency, cost, and reliability optimization
code
intermediate
Task: code Topic: Latency, cost, and reliability optimization Difficulty: intermediate 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
[]
{ "target_language": "TypeScript", "developer_needs": [ "ci_integration", "auditability", "evaluation_metrics", "repo_scale_reasoning" ], "moe_experts": [ "data_curation_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
93ce79aa2e12257f4f442a7338cae3d50644e309
train_03561
2026-01-01T00:00:00
Model merging, distillation, and continued pretraining
eval
intermediate
Task: eval Topic: Model merging, distillation, and continued pretraining 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. 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": [ "tests_are_truth", "evaluation_metrics", "ci_integration", "auditability" ], "moe_experts": [ "coding_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
2cf779481ea613fa8415d01ad9c4e2f156c0a232
train_03562
2026-01-01T00:00:00
Code-specialized model families and sizing tradeoffs
failure_analysis
intermediate
Task: failure_analysis Topic: Code-specialized model families and sizing tradeoffs Difficulty: intermediate 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. Failure: - Initial patch broke edge case Reflection: - Missing zero-input guard Correction: - Add explicit validation + test
[]
{ "target_language": "Bash", "developer_needs": [ "governance", "cost_latency_tradeoffs", "tests_are_truth", "documentation" ], "moe_experts": [ "security_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
37cdeab78224b7c9054c7dbcd742d2dd06a3090e
train_03563
2026-01-01T00:00:00
Reasoning-first coding models and tunable deliberation
explain
expert
Task: explain Topic: Reasoning-first coding models and tunable deliberation 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. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "C#", "developer_needs": [ "reproducibility", "evaluation_metrics", "tooling", "cost_latency_tradeoffs" ], "moe_experts": [ "governance_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
6fca1b025f0db1c6789b7972dd3d0d8816b06019
train_03564
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: 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. Failure: - Initial patch broke edge case Reflection: - Missing zero-input guard Correction: - Add explicit validation + test
[]
{ "target_language": "C#", "developer_needs": [ "cost_latency_tradeoffs", "tests_are_truth", "ci_integration", "security_gates" ], "moe_experts": [ "data_curation_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
73f60dcf6ea236f13915295e4e0f4cd73759ba66
train_03565
2026-01-01T00:00:00
Governance, provenance, and licensing for code data
failure_analysis
intermediate
Task: failure_analysis Topic: Governance, provenance, and licensing for code data 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. 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": "Bash", "developer_needs": [ "repo_scale_reasoning", "security_gates", "cost_latency_tradeoffs", "reproducibility" ], "moe_experts": [ "agentic_systems_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
79fd8daab2dd4d02dc682cedad5e6e1e68a389ad
train_03566
2026-01-01T00:00:00
Code-specialized model families and sizing tradeoffs
eval
intermediate
Task: eval Topic: Code-specialized model families and sizing tradeoffs 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. 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": [ "cost_latency_tradeoffs", "auditability", "ci_integration", "tests_are_truth" ], "moe_experts": [ "governance_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
b2abb516b785d0a08d483043a9606fe7983362a4
train_03567
2026-01-01T00:00:00
Self-improving agents and feedback loops
explain
intermediate
Task: explain Topic: Self-improving agents and feedback loops Difficulty: intermediate 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": [ "tooling", "auditability", "reproducibility", "governance" ], "moe_experts": [ "data_curation_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
a95b967bd2368d72f2ed2480d55afc2bc2b27a30
train_03568
2026-01-01T00:00:00
Self-improving agents and feedback loops
patch_diff
advanced
Task: patch_diff Topic: Self-improving agents and feedback loops 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. 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": "TypeScript", "developer_needs": [ "security_gates", "documentation", "tooling", "auditability" ], "moe_experts": [ "evaluation_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
4a85eec1f7d0a639ae836acd3742c8172a961719
train_03569
2026-01-01T00:00:00
Governance, provenance, and licensing for code data
agent_loop
expert
Task: agent_loop Topic: Governance, provenance, and licensing for code data 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. Loop: Plan → Edit → Test → Reflect → Human gate
[]
{ "target_language": "Java", "developer_needs": [ "repo_scale_reasoning", "auditability", "cost_latency_tradeoffs", "reproducibility" ], "moe_experts": [ "security_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
b68dd0f37c27fcc29356f00ab9206b84ebce4e28
train_03570
2026-01-01T00:00:00
Agentic coding systems (plan→edit→test→reflect)
design
expert
Task: design Topic: Agentic coding systems (plan→edit→test→reflect) Difficulty: expert 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
[]
{ "target_language": "Python", "developer_needs": [ "reproducibility", "evaluation_metrics", "ci_integration", "security_gates" ], "moe_experts": [ "agentic_systems_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
5032ef50ba56b1f10458f3cfad34f49964ce708d
train_03571
2026-01-01T00:00:00
Reasoning-first coding models and tunable deliberation
eval
advanced
Task: eval Topic: Reasoning-first coding models and tunable deliberation Difficulty: advanced 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. Eval: pass@k, time-to-green, regressions, diff size
[]
{ "target_language": "Java", "developer_needs": [ "tests_are_truth", "auditability", "governance", "cost_latency_tradeoffs" ], "moe_experts": [ "security_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
0e8338a247da74c90fb31648746a2f551bccbf25
train_03572
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: 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": [ "auditability", "governance", "evaluation_metrics", "tooling" ], "moe_experts": [ "performance_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
1debcc43cc5c4df1836cea94b31582c03183683d
train_03573
2026-01-01T00:00:00
Agentic coding systems (plan→edit→test→reflect)
design
expert
Task: design Topic: Agentic coding systems (plan→edit→test→reflect) 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
[ "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", "reproducibility", "cost_latency_tradeoffs", "auditability" ], "moe_experts": [ "coding_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
24983bfc251a6ec44496cf06055852819998e4e2
train_03574
2026-01-01T00:00:00
Latency, cost, and reliability optimization
code
intermediate
Task: code Topic: Latency, cost, and reliability optimization 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. Scaffold: ```python def agent_loop(plan, edit, test, issue, max_iters=4): history = [] p = plan(issue) for _ in range(max_iters): patch = edit(issue, p) ok, report = test(patch) history.append({"plan": p, "ok": ok}) if ok: return patch, history p = p + " | refine" return patch, history ```
[]
{ "target_language": "Python", "developer_needs": [ "repo_scale_reasoning", "tooling", "ci_integration", "tests_are_truth" ], "moe_experts": [ "governance_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
effe54370f24e8a826d6834ecae516ff9488ca80
train_03575
2026-01-01T00:00:00
Agentic coding systems (plan→edit→test→reflect)
patch_diff
intermediate
Task: patch_diff Topic: Agentic coding systems (plan→edit→test→reflect) 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. 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": [ "documentation", "cost_latency_tradeoffs", "tooling", "ci_integration" ], "moe_experts": [ "performance_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
1979ff7244e1a4553418793392f21788322f93a7
train_03576
2026-01-01T00:00:00
Tool calling, sandboxes, and CI integration
review
expert
Task: review Topic: Tool calling, sandboxes, and CI integration Difficulty: expert 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. Review: correctness, security, performance, governance
[]
{ "target_language": "Go", "developer_needs": [ "tooling", "repo_scale_reasoning", "reproducibility", "security_gates" ], "moe_experts": [ "agentic_systems_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
0c4157e4682befd30cc65dc1931b7d56eb8dd3bd
train_03577
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: 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
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Rust", "developer_needs": [ "documentation", "repo_scale_reasoning", "tooling", "tests_are_truth" ], "moe_experts": [ "performance_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
737d1d360e2b3419c9de6cf1cda6974b57a1e799
train_03578
2026-01-01T00:00:00
SWE-bench style real-repo evaluation
data_pipeline
advanced
Task: data_pipeline Topic: SWE-bench style real-repo evaluation 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. 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", "documentation", "repo_scale_reasoning" ], "moe_experts": [ "coding_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
b5a5492b31db2b43cababd37fdb4bd2a0c0e1ac9
train_03579
2026-01-01T00:00:00
SWE-bench style real-repo evaluation
explain
advanced
Task: explain Topic: SWE-bench style real-repo evaluation Difficulty: advanced Target language: Python 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": "Python", "developer_needs": [ "tooling", "auditability", "documentation", "evaluation_metrics" ], "moe_experts": [ "governance_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
cbce10eaf65628d0a0a6c6c9317611a80f3b5e45
train_03580
2026-01-01T00:00:00
Code-specialized model families and sizing tradeoffs
eval
intermediate
Task: eval Topic: Code-specialized model families and sizing tradeoffs Difficulty: intermediate 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. Eval: pass@k, time-to-green, regressions, diff size
[]
{ "target_language": "Python", "developer_needs": [ "evaluation_metrics", "cost_latency_tradeoffs", "repo_scale_reasoning", "reproducibility" ], "moe_experts": [ "data_curation_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
c844924d8587ce8872f82acc169b876241c921f5
train_03581
2026-01-01T00:00:00
Self-improving agents and feedback loops
failure_analysis
intermediate
Task: failure_analysis Topic: Self-improving agents and feedback loops Difficulty: intermediate Target language: Python 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": "Python", "developer_needs": [ "tests_are_truth", "reproducibility", "governance", "tooling" ], "moe_experts": [ "evaluation_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
018bc656c902284b180eaf0ba2a1f8cf0d1218fc
train_03582
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: 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": [ "ci_integration", "tooling", "tests_are_truth", "governance" ], "moe_experts": [ "coding_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
4dc2ff91481d76d165df2956108f88bf3bbad8f7
train_03583
2026-01-01T00:00:00
SWE-bench style real-repo evaluation
eval
intermediate
Task: eval Topic: SWE-bench style real-repo evaluation 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
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "SQL", "developer_needs": [ "reproducibility", "evaluation_metrics", "documentation", "security_gates" ], "moe_experts": [ "agentic_systems_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
e9a0596065b50c8527bc95ef552b9335683485e4
train_03584
2026-01-01T00:00:00
Agentic coding systems (plan→edit→test→reflect)
code
intermediate
Task: code Topic: Agentic coding systems (plan→edit→test→reflect) Difficulty: intermediate 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. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "SQL", "developer_needs": [ "tooling", "governance", "auditability", "tests_are_truth" ], "moe_experts": [ "coding_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
bc52b2d717d670f552605b1a72dfd1469751a825
train_03585
2026-01-01T00:00:00
Self-improving agents and feedback loops
patch_diff
intermediate
Task: patch_diff Topic: Self-improving agents and feedback loops Difficulty: intermediate 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. 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": [ "ci_integration", "security_gates", "tests_are_truth", "cost_latency_tradeoffs" ], "moe_experts": [ "data_curation_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
cd7a9bffa10ae435b59b12895282dc9dc511bb18
train_03586
2026-01-01T00:00:00
Multimodal dev workflows (docs, diagrams, traces)
review
intermediate
Task: review Topic: Multimodal dev workflows (docs, diagrams, traces) 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. Review: correctness, security, performance, governance
[]
{ "target_language": "Go", "developer_needs": [ "security_gates", "evaluation_metrics", "tooling", "ci_integration" ], "moe_experts": [ "governance_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
659c3b0513902b3d5f6e12f221a2972d0456ada4
train_03587
2026-01-01T00:00:00
Latency, cost, and reliability optimization
eval
intermediate
Task: eval Topic: Latency, cost, and reliability optimization 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. 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": "Rust", "developer_needs": [ "cost_latency_tradeoffs", "repo_scale_reasoning", "evaluation_metrics", "governance" ], "moe_experts": [ "evaluation_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
84111df6673efa837be24e2b4060bf0ace3aa540
train_03588
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: 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. 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": "Python", "developer_needs": [ "documentation", "ci_integration", "evaluation_metrics", "cost_latency_tradeoffs" ], "moe_experts": [ "data_curation_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
849852e9627652d7365bd90ce4ac1d8cd17c485b
train_03589
2026-01-01T00:00:00
Secure code generation and policy gates
explain
intermediate
Task: explain Topic: Secure code generation and policy gates 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. 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", "security_gates", "auditability", "cost_latency_tradeoffs" ], "moe_experts": [ "security_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
a8e163ca90ba24e95afd2ef83d0221fcbdca1f51
train_03590
2026-01-01T00:00:00
SWE-bench style real-repo evaluation
agent_loop
advanced
Task: agent_loop Topic: SWE-bench style real-repo evaluation 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. 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": "Python", "developer_needs": [ "governance", "cost_latency_tradeoffs", "tests_are_truth", "evaluation_metrics" ], "moe_experts": [ "coding_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
e4da684296a85562912b6dd5f291eac39234d20e
train_03591
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: JavaScript 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": "JavaScript", "developer_needs": [ "governance", "cost_latency_tradeoffs", "documentation", "tooling" ], "moe_experts": [ "coding_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
32de5cf761649c52829fb70be6023c343b1ad722
train_03592
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: 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": [ "cost_latency_tradeoffs", "security_gates", "tests_are_truth", "ci_integration" ], "moe_experts": [ "performance_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
110892f60e28624c5cfd40a7832be3b585662a58
train_03593
2026-01-01T00:00:00
Multimodal dev workflows (docs, diagrams, traces)
eval
expert
Task: eval Topic: Multimodal dev workflows (docs, diagrams, traces) Difficulty: expert 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. Eval: pass@k, time-to-green, regressions, diff size
[]
{ "target_language": "Go", "developer_needs": [ "repo_scale_reasoning", "tests_are_truth", "documentation", "auditability" ], "moe_experts": [ "performance_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
7bd91a3f24f2412708171ddcff51940fe39c40a1
train_03594
2026-01-01T00:00:00
Secure code generation and policy gates
review
intermediate
Task: review Topic: Secure code generation and policy gates 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. 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": [ "reproducibility", "ci_integration", "evaluation_metrics", "security_gates" ], "moe_experts": [ "security_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
54d8326ca3623b8ccc792394e69fdc77058a582b
train_03595
2026-01-01T00:00:00
Tool calling, sandboxes, and CI integration
compare
intermediate
Task: compare Topic: Tool calling, sandboxes, and CI integration Difficulty: intermediate 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. Compare: capability, cost, latency, reliability
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "SQL", "developer_needs": [ "reproducibility", "tooling", "repo_scale_reasoning", "security_gates" ], "moe_experts": [ "coding_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
6e69769463eee34d279dec1d703647d456b0c37f
train_03596
2026-01-01T00:00:00
Reasoning-first coding models and tunable deliberation
patch_diff
intermediate
Task: patch_diff Topic: Reasoning-first coding models and tunable deliberation Difficulty: intermediate 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. 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": [ "ci_integration", "evaluation_metrics", "repo_scale_reasoning", "security_gates" ], "moe_experts": [ "performance_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
2287d8e88e7686d072a35564e87979150d36c406
train_03597
2026-01-01T00:00:00
Latency, cost, and reliability optimization
explain
advanced
Task: explain Topic: Latency, cost, and reliability optimization 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
[]
{ "target_language": "SQL", "developer_needs": [ "repo_scale_reasoning", "ci_integration", "reproducibility", "security_gates" ], "moe_experts": [ "coding_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
fee0b61306f43cb95b0b1eef7124f16de74a8191
train_03598
2026-01-01T00:00:00
Extended context and repo-scale understanding
design
advanced
Task: design Topic: Extended context and repo-scale understanding 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. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "Go", "developer_needs": [ "auditability", "repo_scale_reasoning", "documentation", "reproducibility" ], "moe_experts": [ "data_curation_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
b0e4054eb016d294c90b9a5ee2a24332db80fdcc
train_03599
2026-01-01T00:00:00
Dataset curation pipelines (filter, dedupe, quality)
explain
expert
Task: explain Topic: Dataset curation pipelines (filter, dedupe, quality) 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. 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": [ "repo_scale_reasoning", "tests_are_truth", "reproducibility", "governance" ], "moe_experts": [ "agentic_systems_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
541a4826cc90079099a7006091c69cca757dc675