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train_33300
2026-01-01T00:00:00
Self-improving agents and feedback loops
review
expert
Task: review Topic: Self-improving agents and feedback loops Difficulty: expert 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": [ "repo_scale_reasoning", "security_gates", "evaluation_metrics", "tests_are_truth" ], "moe_experts": [ "evaluation_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
293d7f5561e2233201b69a3d347c82cd1102957f
train_33301
2026-01-01T00:00:00
Tool calling, sandboxes, and CI integration
eval
advanced
Task: eval Topic: Tool calling, sandboxes, and CI integration 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": [ "reproducibility", "auditability", "tooling", "tests_are_truth" ], "moe_experts": [ "security_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
f1262acff6228eb28e69ceedd28f5914725dfd32
train_33302
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: 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": "JavaScript", "developer_needs": [ "tooling", "reproducibility", "evaluation_metrics", "cost_latency_tradeoffs" ], "moe_experts": [ "security_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
48d34b9bea2d4916906111d5dfb28ad6806481eb
train_33303
2026-01-01T00:00:00
Reasoning-first coding models and tunable deliberation
explain
intermediate
Task: explain Topic: Reasoning-first coding models and tunable deliberation 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
[]
{ "target_language": "Java", "developer_needs": [ "reproducibility", "governance", "ci_integration", "repo_scale_reasoning" ], "moe_experts": [ "governance_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
8a41cde524e82ec46964b6134592daa045976084
train_33304
2026-01-01T00:00:00
Mixture-of-Experts (MoE) for code
failure_analysis
intermediate
Task: failure_analysis Topic: Mixture-of-Experts (MoE) for code Difficulty: intermediate 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. 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": "JavaScript", "developer_needs": [ "tests_are_truth", "evaluation_metrics", "ci_integration", "tooling" ], "moe_experts": [ "performance_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
e1786aa9b99a8a2e5c65405e47f50da8ec5a4310
train_33305
2026-01-01T00:00:00
Extended context and repo-scale understanding
compare
expert
Task: compare Topic: Extended context and repo-scale understanding Difficulty: expert 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. 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": [ "security_gates", "evaluation_metrics", "cost_latency_tradeoffs", "ci_integration" ], "moe_experts": [ "evaluation_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
47a2bd26b9ebeb45f0fc4e16264eb32c23167d59
train_33306
2026-01-01T00:00:00
Latency, cost, and reliability optimization
compare
expert
Task: compare Topic: Latency, cost, and reliability optimization 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. 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": [ "ci_integration", "tooling", "repo_scale_reasoning", "documentation" ], "moe_experts": [ "performance_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
428cd74cc304c641b68cfc623e232c7992f49bca
train_33307
2026-01-01T00:00:00
Extended context and repo-scale understanding
eval
expert
Task: eval 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. Eval: pass@k, time-to-green, regressions, diff size
[]
{ "target_language": "Bash", "developer_needs": [ "evaluation_metrics", "reproducibility", "security_gates", "auditability" ], "moe_experts": [ "coding_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
c5ecebac2cab0654cf9eb6f492d4949f654ec599
train_33308
2026-01-01T00:00:00
Code-specialized model families and sizing tradeoffs
design
advanced
Task: design Topic: Code-specialized model families and sizing tradeoffs 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. 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", "evaluation_metrics", "security_gates", "repo_scale_reasoning" ], "moe_experts": [ "security_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
1d5942a4b616b0830c20cedc655bd8b5adad8d93
train_33309
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: 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
[]
{ "target_language": "C#", "developer_needs": [ "documentation", "ci_integration", "governance", "evaluation_metrics" ], "moe_experts": [ "evaluation_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
3467ad3ed3bfaedf01e1f07fd00d47a07b73b580
train_33310
2026-01-01T00:00:00
Reasoning-first coding models and tunable deliberation
design
advanced
Task: design Topic: Reasoning-first coding models and tunable deliberation 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": [ "repo_scale_reasoning", "tooling", "cost_latency_tradeoffs", "tests_are_truth" ], "moe_experts": [ "data_curation_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
fbb53c4faa101df3ff5af92df7b5369f1ce3ef34
train_33311
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: 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
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Go", "developer_needs": [ "ci_integration", "tests_are_truth", "reproducibility", "evaluation_metrics" ], "moe_experts": [ "coding_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
b50b84a7e6aaec5dd37b6441151d1fd90734591a
train_33312
2026-01-01T00:00:00
Extended context and repo-scale understanding
explain
intermediate
Task: explain Topic: Extended context and repo-scale understanding 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
[]
{ "target_language": "Go", "developer_needs": [ "repo_scale_reasoning", "security_gates", "evaluation_metrics", "governance" ], "moe_experts": [ "security_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
1dad2a22ed227206c4e432f6e28e820007d3c0df
train_33313
2026-01-01T00:00:00
Self-improving agents and feedback loops
design
advanced
Task: design Topic: Self-improving agents and feedback loops 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
[]
{ "target_language": "C#", "developer_needs": [ "tests_are_truth", "tooling", "repo_scale_reasoning", "security_gates" ], "moe_experts": [ "governance_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
3caffd776e9b834034a7c46bb660fdb2b0fea1c1
train_33314
2026-01-01T00:00:00
Agentic coding systems (plan→edit→test→reflect)
patch_diff
advanced
Task: patch_diff Topic: Agentic coding systems (plan→edit→test→reflect) 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. 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": [ "reproducibility", "governance", "evaluation_metrics", "tooling" ], "moe_experts": [ "evaluation_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
a154f28ada9fac9773c1a5a06a1cbf91032b2fd5
train_33315
2026-01-01T00:00:00
Extended context and repo-scale understanding
review
intermediate
Task: review 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. Review: correctness, security, performance, governance
[]
{ "target_language": "C#", "developer_needs": [ "auditability", "tooling", "cost_latency_tradeoffs", "evaluation_metrics" ], "moe_experts": [ "governance_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
4a389d99b18d941231b683d198dcfce8e9d3274a
train_33316
2026-01-01T00:00:00
Secure code generation and policy gates
explain
advanced
Task: explain Topic: Secure code generation and policy gates 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
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Rust", "developer_needs": [ "documentation", "tooling", "cost_latency_tradeoffs", "ci_integration" ], "moe_experts": [ "agentic_systems_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
eb622528085ff0131c5a9a87d726b98a3c9ae79a
train_33317
2026-01-01T00:00:00
Self-improving agents and feedback loops
review
intermediate
Task: review Topic: Self-improving agents and feedback loops 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. Review: correctness, security, performance, governance
[]
{ "target_language": "Python", "developer_needs": [ "tests_are_truth", "documentation", "ci_integration", "security_gates" ], "moe_experts": [ "security_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
92d925411de9e441c577cdcc729796d9236dbfbf
train_33318
2026-01-01T00:00:00
Mixture-of-Experts (MoE) for code
explain
expert
Task: explain Topic: Mixture-of-Experts (MoE) for code 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. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "Java", "developer_needs": [ "repo_scale_reasoning", "evaluation_metrics", "tooling", "cost_latency_tradeoffs" ], "moe_experts": [ "coding_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
3e44c8cdf9dbf638d9de5131683f9a92d4fa88d7
train_33319
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
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Bash", "developer_needs": [ "security_gates", "repo_scale_reasoning", "tooling", "reproducibility" ], "moe_experts": [ "security_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
14b4f4c24241b3ef6fc32300a717f8e5f1b850d2
train_33320
2026-01-01T00:00:00
Tool calling, sandboxes, and CI integration
code
advanced
Task: code Topic: Tool calling, sandboxes, and CI integration Difficulty: advanced 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. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "Rust", "developer_needs": [ "reproducibility", "governance", "security_gates", "auditability" ], "moe_experts": [ "agentic_systems_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
8911da25296421ea5c0d00c21da3e3ae16e7c914
train_33321
2026-01-01T00:00:00
Dataset curation pipelines (filter, dedupe, quality)
design
expert
Task: design Topic: Dataset curation pipelines (filter, dedupe, quality) 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. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "Bash", "developer_needs": [ "evaluation_metrics", "tooling", "cost_latency_tradeoffs", "reproducibility" ], "moe_experts": [ "coding_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
8d2e203c10288c2992cbc29de070acfaef77e0d1
train_33322
2026-01-01T00:00:00
Multimodal dev workflows (docs, diagrams, traces)
eval
intermediate
Task: eval Topic: Multimodal dev workflows (docs, diagrams, traces) 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. Eval: pass@k, time-to-green, regressions, diff size
[]
{ "target_language": "TypeScript", "developer_needs": [ "auditability", "evaluation_metrics", "documentation", "security_gates" ], "moe_experts": [ "governance_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
11adb04d026384c87c50c7e539213614d22f69c0
train_33323
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: 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. 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": [ "evaluation_metrics", "cost_latency_tradeoffs", "tooling", "ci_integration" ], "moe_experts": [ "security_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
f1ebe99fd9de755ca005142a78d7f3fc6a1c3193
train_33324
2026-01-01T00:00:00
Mixture-of-Experts (MoE) for code
agent_loop
intermediate
Task: agent_loop Topic: Mixture-of-Experts (MoE) for code 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. Loop: Plan → Edit → Test → Reflect → Human gate
[]
{ "target_language": "Go", "developer_needs": [ "governance", "evaluation_metrics", "tooling", "security_gates" ], "moe_experts": [ "performance_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
e531473fbb3c86823b6382cf519760019c14735a
train_33325
2026-01-01T00:00:00
Model merging, distillation, and continued pretraining
failure_analysis
advanced
Task: failure_analysis Topic: Model merging, distillation, and continued pretraining 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. 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": [ "security_gates", "tooling", "auditability", "documentation" ], "moe_experts": [ "governance_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
1aa4c98c93cccba255d6e142d5e769c43b23868a
train_33326
2026-01-01T00:00:00
Latency, cost, and reliability optimization
failure_analysis
advanced
Task: failure_analysis Topic: Latency, cost, and reliability optimization 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": [ "auditability", "tooling", "cost_latency_tradeoffs", "evaluation_metrics" ], "moe_experts": [ "performance_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
7703a4b1c92b82ee9a76df754ab18a08266ec365
train_33327
2026-01-01T00:00:00
Latency, cost, and reliability optimization
design
intermediate
Task: design Topic: Latency, cost, and reliability optimization Difficulty: intermediate 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. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "Python", "developer_needs": [ "reproducibility", "repo_scale_reasoning", "security_gates", "tests_are_truth" ], "moe_experts": [ "agentic_systems_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
87e39b05d6506fd6dbb920befe2bb668caeee720
train_33328
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: 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. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "SQL", "developer_needs": [ "repo_scale_reasoning", "ci_integration", "security_gates", "governance" ], "moe_experts": [ "governance_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
b893c3b8da8a81ae23d56b41cff55334bef6e99e
train_33329
2026-01-01T00:00:00
Mixture-of-Experts (MoE) for code
data_pipeline
expert
Task: data_pipeline Topic: Mixture-of-Experts (MoE) for code 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. Pipeline: Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
[]
{ "target_language": "Go", "developer_needs": [ "tests_are_truth", "documentation", "repo_scale_reasoning", "governance" ], "moe_experts": [ "security_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
08ca2b069c7f8fa7883251c3b6fa2aac25a9fa1e
train_33330
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: 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. 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": [ "security_gates", "governance", "documentation", "auditability" ], "moe_experts": [ "security_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
52c48b33267de16d2f2648633d8bc3d5ab9dec35
train_33331
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: 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": [ "security_gates", "repo_scale_reasoning", "tests_are_truth", "tooling" ], "moe_experts": [ "governance_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
49d41657b62777a0b248c4c598ab76d5ac4d83ba
train_33332
2026-01-01T00:00:00
Extended context and repo-scale understanding
compare
expert
Task: compare Topic: Extended context and repo-scale understanding 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. Compare: capability, cost, latency, reliability
[]
{ "target_language": "JavaScript", "developer_needs": [ "tests_are_truth", "tooling", "cost_latency_tradeoffs", "repo_scale_reasoning" ], "moe_experts": [ "security_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
787a4f2e5ef65c6ec6591dd56f9e3eed1288295e
train_33333
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: 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": [ "reproducibility", "tooling", "auditability", "tests_are_truth" ], "moe_experts": [ "performance_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
d60e7b9aedff94b2a7cf5afe3bb58e2f5c6ae9b2
train_33334
2026-01-01T00:00:00
Extended context and repo-scale understanding
failure_analysis
expert
Task: failure_analysis 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. 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": "Rust", "developer_needs": [ "tooling", "security_gates", "documentation", "evaluation_metrics" ], "moe_experts": [ "data_curation_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
72cde4bb62c0ecfe135382a7ebf4486b79174688
train_33335
2026-01-01T00:00:00
Extended context and repo-scale understanding
patch_diff
intermediate
Task: patch_diff Topic: Extended context and repo-scale understanding 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. 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": [ "tooling", "cost_latency_tradeoffs", "repo_scale_reasoning", "security_gates" ], "moe_experts": [ "performance_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
0595739edf2316af653519ca1276c21e6fbe762b
train_33336
2026-01-01T00:00:00
Latency, cost, and reliability optimization
review
intermediate
Task: review Topic: Latency, cost, and reliability optimization 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. Review: correctness, security, performance, governance
[]
{ "target_language": "Go", "developer_needs": [ "tests_are_truth", "reproducibility", "auditability", "documentation" ], "moe_experts": [ "data_curation_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
71aa36d01fd476d061e65a302346673a07f3495a
train_33337
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: 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
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Go", "developer_needs": [ "tooling", "security_gates", "tests_are_truth", "reproducibility" ], "moe_experts": [ "coding_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
4477c0814345bda870da30eec1d33ad60d4af2ae
train_33338
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: 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. Eval: pass@k, time-to-green, regressions, diff size
[]
{ "target_language": "JavaScript", "developer_needs": [ "tests_are_truth", "evaluation_metrics", "security_gates", "governance" ], "moe_experts": [ "agentic_systems_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
b639ec601af1d4b3310e0a0171ee0f5d6c451b2e
train_33339
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: 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
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Java", "developer_needs": [ "security_gates", "auditability", "ci_integration", "documentation" ], "moe_experts": [ "security_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
d0ea7cc9b972fede0e368386eb07c9207522c242
train_33340
2026-01-01T00:00:00
Dataset curation pipelines (filter, dedupe, quality)
patch_diff
intermediate
Task: patch_diff Topic: Dataset curation pipelines (filter, dedupe, quality) Difficulty: intermediate Target language: Python 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": "Python", "developer_needs": [ "tests_are_truth", "documentation", "reproducibility", "evaluation_metrics" ], "moe_experts": [ "evaluation_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
0ec1edb8df0cff038ddb705b89f507ebb76e03a6
train_33341
2026-01-01T00:00:00
Model merging, distillation, and continued pretraining
design
intermediate
Task: design Topic: Model merging, distillation, and continued pretraining Difficulty: intermediate 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
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Rust", "developer_needs": [ "documentation", "reproducibility", "security_gates", "governance" ], "moe_experts": [ "security_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
e308f53d9e0cd9a774b4051536a7887d8afb7675
train_33342
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: 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
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "C#", "developer_needs": [ "tooling", "evaluation_metrics", "ci_integration", "tests_are_truth" ], "moe_experts": [ "agentic_systems_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
11bba03d8882611bbd35a30c88e66cbcbbe3f46b
train_33343
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: 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", "reproducibility", "tests_are_truth", "governance" ], "moe_experts": [ "security_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
85e1c393e4c6a23397d06bf5d4f30bd3e8fa09a3
train_33344
2026-01-01T00:00:00
Dataset curation pipelines (filter, dedupe, quality)
patch_diff
advanced
Task: patch_diff Topic: Dataset curation pipelines (filter, dedupe, quality) 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. 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": "C#", "developer_needs": [ "ci_integration", "security_gates", "tooling", "tests_are_truth" ], "moe_experts": [ "performance_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
1fbec6149d0cf93fccd4d8af6bab4bb7115f8974
train_33345
2026-01-01T00:00:00
Secure code generation and policy gates
failure_analysis
advanced
Task: failure_analysis Topic: Secure code generation and policy gates 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. Failure: - Initial patch broke edge case Reflection: - Missing zero-input guard Correction: - Add explicit validation + test
[]
{ "target_language": "Bash", "developer_needs": [ "ci_integration", "cost_latency_tradeoffs", "security_gates", "reproducibility" ], "moe_experts": [ "security_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
4185f3cd1ccc688bb4ced14134fac66ad038eb33
train_33346
2026-01-01T00:00:00
Self-improving agents and feedback loops
design
advanced
Task: design 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. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "TypeScript", "developer_needs": [ "auditability", "ci_integration", "evaluation_metrics", "documentation" ], "moe_experts": [ "governance_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
dc36d4c851d969df742a045603317bb16611be72
train_33347
2026-01-01T00:00:00
Secure code generation and policy gates
code
intermediate
Task: code Topic: Secure code generation and policy gates 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. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "Bash", "developer_needs": [ "tooling", "auditability", "governance", "security_gates" ], "moe_experts": [ "security_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
0ae7350ec9773fd5575e5eb4d7d13c9618431eba
train_33348
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: 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": [ "tooling", "reproducibility", "auditability", "cost_latency_tradeoffs" ], "moe_experts": [ "data_curation_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
c14e01c1033f52ef67d1f9bb3ad2b84a6c471616
train_33349
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: 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
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "JavaScript", "developer_needs": [ "repo_scale_reasoning", "auditability", "evaluation_metrics", "reproducibility" ], "moe_experts": [ "agentic_systems_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
d90845ef073529a9ea24da0328ecc8de051ea498
train_33350
2026-01-01T00:00:00
Self-improving agents and feedback loops
eval
expert
Task: eval Topic: Self-improving agents and feedback loops 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", "tooling", "reproducibility", "repo_scale_reasoning" ], "moe_experts": [ "security_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
6b22725a92aa036ed829cd7e10ff84ae09d7dd8a
train_33351
2026-01-01T00:00:00
Dataset curation pipelines (filter, dedupe, quality)
agent_loop
intermediate
Task: agent_loop Topic: Dataset curation pipelines (filter, dedupe, quality) 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. Loop: Plan → Edit → Test → Reflect → Human gate
[]
{ "target_language": "Python", "developer_needs": [ "governance", "cost_latency_tradeoffs", "auditability", "ci_integration" ], "moe_experts": [ "evaluation_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
3d14d5b86e126931c7b1a64bf4ea5ecaaf384c0e
train_33352
2026-01-01T00:00:00
Dataset curation pipelines (filter, dedupe, quality)
explain
intermediate
Task: explain Topic: Dataset curation pipelines (filter, dedupe, quality) 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. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "Rust", "developer_needs": [ "cost_latency_tradeoffs", "security_gates", "repo_scale_reasoning", "ci_integration" ], "moe_experts": [ "security_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
718caadc4b772839ad5d0ff1a888c9c8bd655054
train_33353
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: 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": [ "cost_latency_tradeoffs", "repo_scale_reasoning", "reproducibility", "ci_integration" ], "moe_experts": [ "governance_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
ebe5b3fe380edbf2eda526c55e0dcf0f83161817
train_33354
2026-01-01T00:00:00
Reasoning-first coding models and tunable deliberation
code
expert
Task: code Topic: Reasoning-first coding models and tunable deliberation 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. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "Go", "developer_needs": [ "documentation", "reproducibility", "tooling", "cost_latency_tradeoffs" ], "moe_experts": [ "security_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
3ed4549d29521c9ca861d2e0e77ca871ecc44eff
train_33355
2026-01-01T00:00:00
Governance, provenance, and licensing for code data
patch_diff
advanced
Task: patch_diff Topic: Governance, provenance, and licensing for code data 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. 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": "C#", "developer_needs": [ "cost_latency_tradeoffs", "repo_scale_reasoning", "evaluation_metrics", "security_gates" ], "moe_experts": [ "coding_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
66b1ecb6492c7da4cc1d7362ebcdf8f69b0c1062
train_33356
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: 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. 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 ```
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Python", "developer_needs": [ "tooling", "reproducibility", "auditability", "cost_latency_tradeoffs" ], "moe_experts": [ "coding_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
aabc477eb2ca5c772d75b6593ac7b2b74f260b44
train_33357
2026-01-01T00:00:00
Latency, cost, and reliability optimization
explain
intermediate
Task: explain Topic: Latency, cost, and reliability optimization 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", "reproducibility", "tests_are_truth", "evaluation_metrics" ], "moe_experts": [ "coding_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
53668dc6d6545164b0f3626bb1d453a003c135f4
train_33358
2026-01-01T00:00:00
Agentic coding systems (plan→edit→test→reflect)
design
advanced
Task: design Topic: Agentic coding systems (plan→edit→test→reflect) Difficulty: advanced Target language: Java 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": "Java", "developer_needs": [ "documentation", "auditability", "tooling", "cost_latency_tradeoffs" ], "moe_experts": [ "agentic_systems_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
82a76af5afc4b041a30f6677a22a609b7622ac9a
train_33359
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: 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. Failure: - Initial patch broke edge case Reflection: - Missing zero-input guard Correction: - Add explicit validation + test
[]
{ "target_language": "Rust", "developer_needs": [ "documentation", "evaluation_metrics", "tests_are_truth", "cost_latency_tradeoffs" ], "moe_experts": [ "coding_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
699663e1359c37be749705cbe447c9d45809f05d
train_33360
2026-01-01T00:00:00
Agentic coding systems (plan→edit→test→reflect)
explain
expert
Task: explain 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": [ "governance", "reproducibility", "evaluation_metrics", "tests_are_truth" ], "moe_experts": [ "data_curation_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
d32174f8157aabdbbe515c9f387a31960a156516
train_33361
2026-01-01T00:00:00
Mixture-of-Experts (MoE) for code
explain
advanced
Task: explain Topic: Mixture-of-Experts (MoE) for code 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": [ "documentation", "tests_are_truth", "security_gates", "tooling" ], "moe_experts": [ "security_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
ee158e9bb24006bc9464ebd6d7357c71612aa63c
train_33362
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: 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. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "Python", "developer_needs": [ "documentation", "tooling", "tests_are_truth", "governance" ], "moe_experts": [ "data_curation_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
8a3f8d0fcc3b8e015f0cb595cc781b08e6e92b14
train_33363
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: 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": "C#", "developer_needs": [ "documentation", "cost_latency_tradeoffs", "tests_are_truth", "tooling" ], "moe_experts": [ "security_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
d0454e5c1baca1fecfe1a37db70ab18348ed749c
train_33364
2026-01-01T00:00:00
Extended context and repo-scale understanding
eval
advanced
Task: eval Topic: Extended context and repo-scale understanding 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. 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": "Python", "developer_needs": [ "reproducibility", "security_gates", "governance", "tests_are_truth" ], "moe_experts": [ "governance_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
7381b00502c7d4e519a5cafef2ac1ca70fa9e41e
train_33365
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: 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": [ "tooling", "cost_latency_tradeoffs", "auditability", "tests_are_truth" ], "moe_experts": [ "security_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
58808287ddd2e84d1b83c1ae64e995f0b85b814f
train_33366
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: 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": [ "cost_latency_tradeoffs", "reproducibility", "documentation", "tooling" ], "moe_experts": [ "data_curation_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
959e9e8ae2d2e11f16add861c2e3b6df65b1bb7b
train_33367
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: 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. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "JavaScript", "developer_needs": [ "evaluation_metrics", "documentation", "reproducibility", "security_gates" ], "moe_experts": [ "agentic_systems_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
672123e76babb36ef5e34d7d7684c300291f34bb
train_33368
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: 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. Review: correctness, security, performance, governance
[]
{ "target_language": "Go", "developer_needs": [ "cost_latency_tradeoffs", "reproducibility", "documentation", "auditability" ], "moe_experts": [ "performance_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
259b1ace6f8b9f32c7f6474872e464bc4138d2f8
train_33369
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: 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": "JavaScript", "developer_needs": [ "security_gates", "governance", "evaluation_metrics", "documentation" ], "moe_experts": [ "coding_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
977225192a4094feced41f9cfc22d056516675f3
train_33370
2026-01-01T00:00:00
Reasoning-first coding models and tunable deliberation
review
intermediate
Task: review Topic: Reasoning-first coding models and tunable deliberation 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. Review: correctness, security, performance, governance
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Python", "developer_needs": [ "tests_are_truth", "cost_latency_tradeoffs", "evaluation_metrics", "repo_scale_reasoning" ], "moe_experts": [ "security_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
472fe1f79c19e2695c0741619313d59f5ddc013e
train_33371
2026-01-01T00:00:00
Self-improving agents and feedback loops
data_pipeline
expert
Task: data_pipeline Topic: Self-improving agents and feedback loops 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. 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": [ "evaluation_metrics", "tooling", "cost_latency_tradeoffs", "auditability" ], "moe_experts": [ "evaluation_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
db6f4f2ba2d551b6746ddc7742416dd248602410
train_33372
2026-01-01T00:00:00
Multimodal dev workflows (docs, diagrams, traces)
data_pipeline
advanced
Task: data_pipeline Topic: Multimodal dev workflows (docs, diagrams, traces) 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": [ "documentation", "repo_scale_reasoning", "tooling", "evaluation_metrics" ], "moe_experts": [ "agentic_systems_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
bad4aac8e328ef35b756680fadd16858311e9e4e
train_33373
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: 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. Failure: - Initial patch broke edge case Reflection: - Missing zero-input guard Correction: - Add explicit validation + test
[]
{ "target_language": "Go", "developer_needs": [ "governance", "tests_are_truth", "repo_scale_reasoning", "reproducibility" ], "moe_experts": [ "agentic_systems_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
617d5e9644b5d5f58e9bd88655b253f0148fe3f3
train_33374
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: Java 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": "Java", "developer_needs": [ "reproducibility", "repo_scale_reasoning", "cost_latency_tradeoffs", "tooling" ], "moe_experts": [ "coding_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
888f7c1cbc2a27a53a4aa9d09e43edd992b3a4fa
train_33375
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: 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. Loop: Plan → Edit → Test → Reflect → Human gate
[]
{ "target_language": "TypeScript", "developer_needs": [ "reproducibility", "cost_latency_tradeoffs", "repo_scale_reasoning", "tooling" ], "moe_experts": [ "data_curation_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
b1e27cfdef1ff0822658835911d98e4d36d88acb
train_33376
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: 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": [ "repo_scale_reasoning", "auditability", "cost_latency_tradeoffs", "reproducibility" ], "moe_experts": [ "data_curation_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
9b0bcf06825c4ebee4d342389322a9e5ea756803
train_33377
2026-01-01T00:00:00
Code-specialized model families and sizing tradeoffs
data_pipeline
intermediate
Task: data_pipeline Topic: Code-specialized model families and sizing tradeoffs 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": [ "cost_latency_tradeoffs", "repo_scale_reasoning", "evaluation_metrics", "tooling" ], "moe_experts": [ "performance_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
ea32362cbb0969ae00084011f1c3552c08e1d2f5
train_33378
2026-01-01T00:00:00
Secure code generation and policy gates
patch_diff
advanced
Task: patch_diff Topic: Secure code generation and policy gates 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. 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": [ "documentation", "cost_latency_tradeoffs", "evaluation_metrics", "auditability" ], "moe_experts": [ "coding_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
7b185884742440f41f0017609fef9962bfe8d62e
train_33379
2026-01-01T00:00:00
Multimodal dev workflows (docs, diagrams, traces)
review
advanced
Task: review Topic: Multimodal dev workflows (docs, diagrams, traces) Difficulty: advanced Target language: Java 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": "Java", "developer_needs": [ "cost_latency_tradeoffs", "governance", "tooling", "reproducibility" ], "moe_experts": [ "security_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
a5bb88c403efbcf4b537a1f1d41dd0404c06e044
train_33380
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
[]
{ "target_language": "Go", "developer_needs": [ "documentation", "auditability", "security_gates", "governance" ], "moe_experts": [ "governance_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
9782f6762a029f25b3e8f6166d328efd2697443f
train_33381
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: 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. Review: correctness, security, performance, governance
[]
{ "target_language": "Python", "developer_needs": [ "security_gates", "governance", "evaluation_metrics", "auditability" ], "moe_experts": [ "security_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
09fc79d3df3eeff15eee7e27c5ed47ce150c7dd4
train_33382
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: 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. 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", "ci_integration", "cost_latency_tradeoffs", "repo_scale_reasoning" ], "moe_experts": [ "data_curation_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
d53cd677de34b26041d1e4c253aaaafa5fdd5e23
train_33383
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: 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
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Bash", "developer_needs": [ "auditability", "evaluation_metrics", "tooling", "security_gates" ], "moe_experts": [ "data_curation_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
2316773b59921a6b4f068bcafea4895e2b49b59b
train_33384
2026-01-01T00:00:00
SWE-bench style real-repo evaluation
data_pipeline
expert
Task: data_pipeline Topic: SWE-bench style real-repo evaluation 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. Pipeline: Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
[]
{ "target_language": "JavaScript", "developer_needs": [ "auditability", "tests_are_truth", "cost_latency_tradeoffs", "evaluation_metrics" ], "moe_experts": [ "security_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
c5a96afbfcc89105d26381720143ff922609b2dd
train_33385
2026-01-01T00:00:00
Model merging, distillation, and continued pretraining
compare
advanced
Task: compare Topic: Model merging, distillation, and continued pretraining 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. Compare: capability, cost, latency, reliability
[]
{ "target_language": "Java", "developer_needs": [ "governance", "security_gates", "evaluation_metrics", "documentation" ], "moe_experts": [ "governance_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
a845acecc75678ab4870ac9467b4fc304bbac0f9
train_33386
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
[]
{ "target_language": "Python", "developer_needs": [ "reproducibility", "tooling", "security_gates", "repo_scale_reasoning" ], "moe_experts": [ "data_curation_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
3556719c9655b93b9cacf04ae19fa82b4ae9cda4
train_33387
2026-01-01T00:00:00
Dataset curation pipelines (filter, dedupe, quality)
explain
intermediate
Task: explain Topic: Dataset curation pipelines (filter, dedupe, quality) 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", "tooling", "documentation", "ci_integration" ], "moe_experts": [ "performance_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
328c4eb47787808e6e2b23c696da93c1a767779b
train_33388
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: 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": [ "evaluation_metrics", "cost_latency_tradeoffs", "tooling", "governance" ], "moe_experts": [ "evaluation_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
5ebfffceb75d2ecfbb77ed4c2ab530845f6fa452
train_33389
2026-01-01T00:00:00
Tool calling, sandboxes, and CI integration
eval
expert
Task: eval Topic: Tool calling, sandboxes, and CI integration 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. 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": "TypeScript", "developer_needs": [ "governance", "tooling", "tests_are_truth", "documentation" ], "moe_experts": [ "governance_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
ac09899250bde01c7fb4236f186c314529822c7a
train_33390
2026-01-01T00:00:00
Model merging, distillation, and continued pretraining
code
intermediate
Task: code Topic: Model merging, distillation, and continued pretraining 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": [ "security_gates", "documentation", "repo_scale_reasoning", "tests_are_truth" ], "moe_experts": [ "evaluation_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
9dfecbbb89f0ff5bc6a212a996e9525fd9b5beca
train_33391
2026-01-01T00:00:00
Latency, cost, and reliability optimization
eval
advanced
Task: eval Topic: Latency, cost, and reliability optimization 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. Eval: pass@k, time-to-green, regressions, diff size
[]
{ "target_language": "Python", "developer_needs": [ "security_gates", "tooling", "repo_scale_reasoning", "documentation" ], "moe_experts": [ "security_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
f44d5576a95591216ec0d22f0b45a359154344aa
train_33392
2026-01-01T00:00:00
Multimodal dev workflows (docs, diagrams, traces)
review
expert
Task: review Topic: Multimodal dev workflows (docs, diagrams, traces) 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. Review: correctness, security, performance, governance
[]
{ "target_language": "Java", "developer_needs": [ "cost_latency_tradeoffs", "repo_scale_reasoning", "documentation", "tests_are_truth" ], "moe_experts": [ "security_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
d4ffd1faee426cff582e01e7b1141aad59d67f3d
train_33393
2026-01-01T00:00:00
Reasoning-first coding models and tunable deliberation
review
expert
Task: review Topic: Reasoning-first coding models and tunable deliberation 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. Review: correctness, security, performance, governance
[]
{ "target_language": "SQL", "developer_needs": [ "security_gates", "cost_latency_tradeoffs", "evaluation_metrics", "tooling" ], "moe_experts": [ "coding_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
18f562ed9b7c88fde4d64c9efe1ed5c42decfd8b
train_33394
2026-01-01T00:00:00
Reasoning-first coding models and tunable deliberation
design
intermediate
Task: design 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. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "Bash", "developer_needs": [ "reproducibility", "tooling", "repo_scale_reasoning", "documentation" ], "moe_experts": [ "evaluation_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
9dd226efe21c54f54000cb7a4bd3f37d13c540c1
train_33395
2026-01-01T00:00:00
Reasoning-first coding models and tunable deliberation
design
expert
Task: design Topic: Reasoning-first coding models and tunable deliberation 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
[]
{ "target_language": "JavaScript", "developer_needs": [ "tests_are_truth", "ci_integration", "cost_latency_tradeoffs", "auditability" ], "moe_experts": [ "evaluation_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
630bbcf205efc6c2d03defe8f8552c4445a973d0
train_33396
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: 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": [ "ci_integration", "cost_latency_tradeoffs", "reproducibility", "evaluation_metrics" ], "moe_experts": [ "agentic_systems_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
9a33d2554accaa5b604a66fef12a03d346a41dd6
train_33397
2026-01-01T00:00:00
Governance, provenance, and licensing for code data
review
expert
Task: review Topic: Governance, provenance, and licensing for code data Difficulty: expert Target language: Java 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": "Java", "developer_needs": [ "tests_are_truth", "ci_integration", "reproducibility", "cost_latency_tradeoffs" ], "moe_experts": [ "performance_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
a37899ddb5cf4ab6753e3f3a825bac14ba385c16
train_33398
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": [ "evaluation_metrics", "cost_latency_tradeoffs", "governance", "documentation" ], "moe_experts": [ "data_curation_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
e519c5f9aa05b5dd8ac993d2505d86473b1624a9
train_33399
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: 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. 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": [ "governance", "tests_are_truth", "evaluation_metrics", "security_gates" ], "moe_experts": [ "security_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
a1e54fe372bb6ab5a265e8253f32ed3ad0294251