id stringlengths 11 11 | created timestamp[s]date 2026-01-01 00:00:00 2026-01-01 00:00:00 | topic stringclasses 14 values | task_type stringclasses 10 values | difficulty stringclasses 3 values | instruction stringlengths 189 248 | input stringclasses 1 value | output stringclasses 9 values | reasoning_steps listlengths 0 5 | metadata dict | hash stringlengths 40 40 |
|---|---|---|---|---|---|---|---|---|---|---|
train_31900 | 2026-01-01T00:00:00 | Code-specialized model families and sizing tradeoffs | agent_loop | advanced | Task: agent_loop
Topic: Code-specialized model families and sizing tradeoffs
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.
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": "Rust",
"developer_needs": [
"tests_are_truth",
"reproducibility",
"security_gates",
"ci_integration"
],
"moe_experts": [
"performance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | ae5126d6b9cc3cef53c2a5a02e64f5605dcd13c1 | |
train_31901 | 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: 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.
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": "Java",
"developer_needs": [
"tests_are_truth",
"security_gates",
"repo_scale_reasoning",
"auditability"
],
"moe_experts": [
"agentic_systems_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 8e4c07a193413a67f97062c85d994e4bf6e7fb76 | |
train_31902 | 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: 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": [
"security_gates",
"cost_latency_tradeoffs",
"tooling",
"evaluation_metrics"
],
"moe_experts": [
"agentic_systems_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | e690abdfb8e8e7506207eb3f6abdbc8018fb00d0 | |
train_31903 | 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: Bash
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
| [] | {
"target_language": "Bash",
"developer_needs": [
"repo_scale_reasoning",
"tooling",
"cost_latency_tradeoffs",
"evaluation_metrics"
],
"moe_experts": [
"security_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 38d20241845ae96d5b33f4e67637915dcaa97079 | |
train_31904 | 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: 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": [
"auditability",
"ci_integration",
"cost_latency_tradeoffs",
"security_gates"
],
"moe_experts": [
"evaluation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 3df1fa9cf9e391f9e855210c66d67066ca60ed95 | |
train_31905 | 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: 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",
"evaluation_metrics",
"ci_integration"
],
"moe_experts": [
"coding_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 7cb318219bdfc9d42699ffa51084b08556f16f55 | |
train_31906 | 2026-01-01T00:00:00 | Secure code generation and policy gates | design | intermediate | Task: design
Topic: Secure code generation and policy gates
Difficulty: intermediate
Target language: 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
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Python",
"developer_needs": [
"tooling",
"security_gates",
"cost_latency_tradeoffs",
"evaluation_metrics"
],
"moe_experts": [
"governance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 72176f7a920dcd7adf0f51229be8d8c3eb0c959a | |
train_31907 | 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: 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": [
"documentation",
"ci_integration",
"repo_scale_reasoning",
"tooling"
],
"moe_experts": [
"evaluation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 9e951ac0833b2df5d32334ecb630b561dc094722 | |
train_31908 | 2026-01-01T00:00:00 | Secure code generation and policy gates | eval | intermediate | Task: eval
Topic: Secure code generation and policy gates
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.
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": [
"evaluation_metrics",
"documentation",
"repo_scale_reasoning",
"governance"
],
"moe_experts": [
"governance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | e5d94c5bd9a8f98f5b7f06698052cad6450ea40a | |
train_31909 | 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: 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.
Eval:
pass@k, time-to-green, regressions, diff size
| [] | {
"target_language": "Java",
"developer_needs": [
"documentation",
"reproducibility",
"tooling",
"governance"
],
"moe_experts": [
"governance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 443f6380179dfd9531445d373e9083c099b2e0fb | |
train_31910 | 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: 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.
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": [
"ci_integration",
"auditability",
"reproducibility",
"governance"
],
"moe_experts": [
"data_curation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | b985dbfe4f3173e14a8bac99cc406b891912fb60 | |
train_31911 | 2026-01-01T00:00:00 | SWE-bench style real-repo evaluation | compare | intermediate | Task: compare
Topic: SWE-bench style real-repo evaluation
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.
Compare: capability, cost, latency, reliability
| [] | {
"target_language": "Go",
"developer_needs": [
"tests_are_truth",
"auditability",
"ci_integration",
"cost_latency_tradeoffs"
],
"moe_experts": [
"security_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | a7188ee3cb0de5721e815a26041eb4992a7e14b4 | |
train_31912 | 2026-01-01T00:00:00 | Tool calling, sandboxes, and CI integration | design | intermediate | Task: design
Topic: Tool calling, sandboxes, and CI integration
Difficulty: intermediate
Target language: 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": [
"auditability",
"cost_latency_tradeoffs",
"ci_integration",
"governance"
],
"moe_experts": [
"coding_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | f5cd521284c498dce77f6b49f132e6489a1b1604 | |
train_31913 | 2026-01-01T00:00:00 | Extended context and repo-scale understanding | compare | intermediate | Task: compare
Topic: Extended context and repo-scale understanding
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.
Compare: capability, cost, latency, reliability
| [] | {
"target_language": "Go",
"developer_needs": [
"tooling",
"reproducibility",
"evaluation_metrics",
"auditability"
],
"moe_experts": [
"data_curation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 0e1a375e0f8645dfbdb3042176d7b6930eed5df8 | |
train_31914 | 2026-01-01T00:00:00 | Self-improving agents and feedback loops | explain | advanced | Task: explain
Topic: Self-improving agents and feedback loops
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.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "Bash",
"developer_needs": [
"security_gates",
"governance",
"documentation",
"tests_are_truth"
],
"moe_experts": [
"security_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 25171d09929af7ad2b02c16b5d7813eadbabe616 | |
train_31915 | 2026-01-01T00:00:00 | Code-specialized model families and sizing tradeoffs | data_pipeline | expert | Task: data_pipeline
Topic: Code-specialized model families and sizing tradeoffs
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.
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": "Java",
"developer_needs": [
"governance",
"ci_integration",
"security_gates",
"repo_scale_reasoning"
],
"moe_experts": [
"security_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | e6c145cef6418ee8f71c83374951789b20d8f380 | |
train_31916 | 2026-01-01T00:00:00 | Multimodal dev workflows (docs, diagrams, traces) | explain | expert | Task: explain
Topic: Multimodal dev workflows (docs, diagrams, traces)
Difficulty: expert
Target language: 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
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Rust",
"developer_needs": [
"security_gates",
"documentation",
"ci_integration",
"evaluation_metrics"
],
"moe_experts": [
"evaluation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | b919603f2b9831f2df289efcf3b2e76e934630e6 | |
train_31917 | 2026-01-01T00:00:00 | Mixture-of-Experts (MoE) for code | agent_loop | expert | Task: agent_loop
Topic: Mixture-of-Experts (MoE) for code
Difficulty: expert
Target language: SQL
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
| [] | {
"target_language": "SQL",
"developer_needs": [
"security_gates",
"reproducibility",
"ci_integration",
"repo_scale_reasoning"
],
"moe_experts": [
"performance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | bbe2d3c0b4fd59ad0c18190af9e2b81ae74751fe | |
train_31918 | 2026-01-01T00:00:00 | Mixture-of-Experts (MoE) for code | design | intermediate | Task: design
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.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "Java",
"developer_needs": [
"cost_latency_tradeoffs",
"repo_scale_reasoning",
"reproducibility",
"ci_integration"
],
"moe_experts": [
"evaluation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | cbb08e283bdf529dbfab297be21710434737f52f | |
train_31919 | 2026-01-01T00:00:00 | Secure code generation and policy gates | data_pipeline | advanced | Task: data_pipeline
Topic: Secure code generation and policy gates
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.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
| [] | {
"target_language": "Python",
"developer_needs": [
"governance",
"security_gates",
"evaluation_metrics",
"reproducibility"
],
"moe_experts": [
"governance_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | c89fbc512e04133217ae88af3c90883914cba1b3 | |
train_31920 | 2026-01-01T00:00:00 | Mixture-of-Experts (MoE) for code | eval | expert | Task: eval
Topic: Mixture-of-Experts (MoE) for code
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.
Eval:
pass@k, time-to-green, regressions, diff size
| [] | {
"target_language": "SQL",
"developer_needs": [
"reproducibility",
"documentation",
"security_gates",
"evaluation_metrics"
],
"moe_experts": [
"security_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | cafb000d1a43e50ad8194ff0d63931ced50aac36 | |
train_31921 | 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: 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
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "C#",
"developer_needs": [
"auditability",
"documentation",
"cost_latency_tradeoffs",
"security_gates"
],
"moe_experts": [
"coding_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 4d451035841d6421f76fd7bd79d3091f56353b6a | |
train_31922 | 2026-01-01T00:00:00 | Mixture-of-Experts (MoE) for code | patch_diff | expert | Task: patch_diff
Topic: Mixture-of-Experts (MoE) for code
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.
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": "Go",
"developer_needs": [
"reproducibility",
"tooling",
"security_gates",
"cost_latency_tradeoffs"
],
"moe_experts": [
"performance_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 7efb8c4d041bf08e6fe9c17d12d68e67df613ad8 | |
train_31923 | 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: SQL
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
| [] | {
"target_language": "SQL",
"developer_needs": [
"auditability",
"security_gates",
"reproducibility",
"cost_latency_tradeoffs"
],
"moe_experts": [
"coding_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | b2bf9615748ef4a77aa9fc72788da3275cb66423 | |
train_31924 | 2026-01-01T00:00:00 | Tool calling, sandboxes, and CI integration | failure_analysis | expert | Task: failure_analysis
Topic: Tool calling, sandboxes, and CI integration
Difficulty: expert
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.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
| [] | {
"target_language": "Python",
"developer_needs": [
"tooling",
"cost_latency_tradeoffs",
"documentation",
"evaluation_metrics"
],
"moe_experts": [
"evaluation_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 29a841c02be961e67a9f5206ea31a26f20b71000 | |
train_31925 | 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: 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.
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",
"auditability",
"governance",
"cost_latency_tradeoffs"
],
"moe_experts": [
"coding_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | ee824c30a5dff7cfde7644ad3235d94df18d4449 | |
train_31926 | 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: 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.
Patch (diff-style):
```diff
- if x == 0:
- return 1/x
+ if x == 0:
+ raise ValueError('division by zero')
```
Acceptance:
- Tests pass
- No new regressions
| [] | {
"target_language": "SQL",
"developer_needs": [
"reproducibility",
"security_gates",
"cost_latency_tradeoffs",
"ci_integration"
],
"moe_experts": [
"data_curation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | bdf83212b2ada54c7d73fbffdd81f6ca6df95d40 | |
train_31927 | 2026-01-01T00:00:00 | SWE-bench style real-repo evaluation | code | expert | Task: code
Topic: SWE-bench style real-repo evaluation
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
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "JavaScript",
"developer_needs": [
"security_gates",
"cost_latency_tradeoffs",
"tests_are_truth",
"documentation"
],
"moe_experts": [
"agentic_systems_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 6937b78c23dfc6d52c3550e37c6cd59200224028 | |
train_31928 | 2026-01-01T00:00:00 | Tool calling, sandboxes, and CI integration | design | advanced | Task: design
Topic: Tool calling, sandboxes, and CI integration
Difficulty: advanced
Target language: SQL
Context: 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": "SQL",
"developer_needs": [
"security_gates",
"reproducibility",
"auditability",
"governance"
],
"moe_experts": [
"evaluation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 4bc35357431479b0b35f9d120afd25950bf258d7 | |
train_31929 | 2026-01-01T00:00:00 | Reasoning-first coding models and tunable deliberation | compare | advanced | Task: compare
Topic: Reasoning-first coding models and tunable deliberation
Difficulty: advanced
Target language: 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.
Compare: capability, cost, latency, reliability
| [] | {
"target_language": "JavaScript",
"developer_needs": [
"repo_scale_reasoning",
"security_gates",
"ci_integration",
"tests_are_truth"
],
"moe_experts": [
"performance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 35bd1d79b2b8e198e28abb7e2163b290d8021b44 | |
train_31930 | 2026-01-01T00:00:00 | Governance, provenance, and licensing for code data | agent_loop | intermediate | Task: agent_loop
Topic: Governance, provenance, and licensing for code data
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",
"cost_latency_tradeoffs",
"auditability",
"evaluation_metrics"
],
"moe_experts": [
"data_curation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 0845d7f12152810a0096d7b025299e30ebf388e3 | |
train_31931 | 2026-01-01T00:00:00 | Code-specialized model families and sizing tradeoffs | design | expert | Task: design
Topic: Code-specialized model families and sizing tradeoffs
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.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "SQL",
"developer_needs": [
"governance",
"repo_scale_reasoning",
"reproducibility",
"security_gates"
],
"moe_experts": [
"governance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 05bd7681089f817e7de4a3379b5e0323b2d60110 | |
train_31932 | 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: C#
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
| [] | {
"target_language": "C#",
"developer_needs": [
"repo_scale_reasoning",
"governance",
"security_gates",
"auditability"
],
"moe_experts": [
"performance_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 24fda8d5098ff394d02401a444c94ddc35f67661 | |
train_31933 | 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: 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": [
"cost_latency_tradeoffs",
"ci_integration",
"reproducibility",
"documentation"
],
"moe_experts": [
"data_curation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 6c9b66da4403a2bfc33d62454df7ad3ccf721f34 | |
train_31934 | 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: 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
| [] | {
"target_language": "Rust",
"developer_needs": [
"tooling",
"documentation",
"security_gates",
"evaluation_metrics"
],
"moe_experts": [
"data_curation_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 01cb51f3c50fe6822c591ba7b7c26a5e21d50ce0 | |
train_31935 | 2026-01-01T00:00:00 | Code-specialized model families and sizing tradeoffs | code | expert | Task: code
Topic: Code-specialized model families and sizing tradeoffs
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": [
"tooling",
"governance",
"security_gates",
"repo_scale_reasoning"
],
"moe_experts": [
"security_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 42057a934e945af10faf0d22d83376241455e967 | |
train_31936 | 2026-01-01T00:00:00 | Mixture-of-Experts (MoE) for code | failure_analysis | advanced | Task: failure_analysis
Topic: Mixture-of-Experts (MoE) for code
Difficulty: advanced
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.
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",
"evaluation_metrics",
"reproducibility",
"documentation"
],
"moe_experts": [
"security_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | a06244f23fc693d1f724f1aecb8136f2e29b7f33 | |
train_31937 | 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: C#
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
| [] | {
"target_language": "C#",
"developer_needs": [
"evaluation_metrics",
"reproducibility",
"tooling",
"cost_latency_tradeoffs"
],
"moe_experts": [
"governance_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 6cf2f3cc7e1d7521b5dd1e473fc260aa8ab8e48d | |
train_31938 | 2026-01-01T00:00:00 | Agentic coding systems (plan→edit→test→reflect) | failure_analysis | advanced | Task: failure_analysis
Topic: Agentic coding systems (plan→edit→test→reflect)
Difficulty: advanced
Target language: JavaScript
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
| [] | {
"target_language": "JavaScript",
"developer_needs": [
"ci_integration",
"repo_scale_reasoning",
"tooling",
"security_gates"
],
"moe_experts": [
"security_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 2f595102971c1722de7c703d1eb167802f212299 | |
train_31939 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | design | advanced | Task: design
Topic: Latency, cost, and reliability optimization
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": [
"governance",
"evaluation_metrics",
"auditability",
"cost_latency_tradeoffs"
],
"moe_experts": [
"evaluation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | bfc6f4aa4ba246a63b5206e06a1465f51744a6af | |
train_31940 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | eval | advanced | Task: eval
Topic: Latency, cost, and reliability optimization
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.
Eval:
pass@k, time-to-green, regressions, diff size
| [] | {
"target_language": "JavaScript",
"developer_needs": [
"documentation",
"security_gates",
"repo_scale_reasoning",
"governance"
],
"moe_experts": [
"coding_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 1d8def0861a9907f767265c1076085995b79aeeb | |
train_31941 | 2026-01-01T00:00:00 | Dataset curation pipelines (filter, dedupe, quality) | code | intermediate | Task: code
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: intermediate
Target language: JavaScript
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "JavaScript",
"developer_needs": [
"tooling",
"reproducibility",
"documentation",
"evaluation_metrics"
],
"moe_experts": [
"agentic_systems_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 4856d236b6d7e059bcb005acd5d4279e63d1d1cb | |
train_31942 | 2026-01-01T00:00:00 | Model merging, distillation, and continued pretraining | data_pipeline | intermediate | Task: data_pipeline
Topic: Model merging, distillation, and continued pretraining
Difficulty: intermediate
Target language: C#
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
| [] | {
"target_language": "C#",
"developer_needs": [
"documentation",
"governance",
"security_gates",
"repo_scale_reasoning"
],
"moe_experts": [
"data_curation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | a8cc6efb179dc3013bcff1be76a74921543ef5f5 | |
train_31943 | 2026-01-01T00:00:00 | Reasoning-first coding models and tunable deliberation | code | intermediate | Task: code
Topic: Reasoning-first coding models and tunable deliberation
Difficulty: intermediate
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": [
"tooling",
"tests_are_truth",
"reproducibility",
"ci_integration"
],
"moe_experts": [
"evaluation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 97cd3224985c5c2ff2746f0e9c19ffa17b634536 | |
train_31944 | 2026-01-01T00:00:00 | Code-specialized model families and sizing tradeoffs | compare | expert | Task: compare
Topic: Code-specialized model families and sizing tradeoffs
Difficulty: expert
Target language: SQL
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
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": [
"governance",
"ci_integration",
"reproducibility",
"repo_scale_reasoning"
],
"moe_experts": [
"security_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | d1da88f61f6ada844bf45332f0e8a31e3560d8b1 | |
train_31945 | 2026-01-01T00:00:00 | SWE-bench style real-repo evaluation | design | intermediate | Task: design
Topic: SWE-bench style real-repo evaluation
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.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "Go",
"developer_needs": [
"tooling",
"auditability",
"evaluation_metrics",
"cost_latency_tradeoffs"
],
"moe_experts": [
"performance_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 3e05aab42546efde141269e154397ebe7f90ab9e | |
train_31946 | 2026-01-01T00:00:00 | Model merging, distillation, and continued pretraining | failure_analysis | intermediate | Task: failure_analysis
Topic: Model merging, distillation, and continued pretraining
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.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Python",
"developer_needs": [
"evaluation_metrics",
"tooling",
"auditability",
"repo_scale_reasoning"
],
"moe_experts": [
"governance_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 595f941516057c0ccaba1feaae84cdc6f3f65819 | |
train_31947 | 2026-01-01T00:00:00 | Governance, provenance, and licensing for code data | design | expert | Task: design
Topic: Governance, provenance, and licensing for code data
Difficulty: expert
Target language: SQL
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "SQL",
"developer_needs": [
"tooling",
"repo_scale_reasoning",
"tests_are_truth",
"cost_latency_tradeoffs"
],
"moe_experts": [
"governance_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | c11444599bb8a86cc409a791fe8aba950a94adf8 | |
train_31948 | 2026-01-01T00:00:00 | Self-improving agents and feedback loops | eval | advanced | Task: eval
Topic: Self-improving agents and feedback loops
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.
Eval:
pass@k, time-to-green, regressions, diff size
| [] | {
"target_language": "C#",
"developer_needs": [
"tests_are_truth",
"ci_integration",
"auditability",
"governance"
],
"moe_experts": [
"security_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 91f709fbdff60230ad5274bb144c0ec59b937613 | |
train_31949 | 2026-01-01T00:00:00 | Self-improving agents and feedback loops | design | expert | Task: design
Topic: Self-improving agents and feedback loops
Difficulty: expert
Target language: Rust
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "Rust",
"developer_needs": [
"cost_latency_tradeoffs",
"tooling",
"reproducibility",
"ci_integration"
],
"moe_experts": [
"security_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 0eb8a06942b0211868595ddc62fff87bc210d941 | |
train_31950 | 2026-01-01T00:00:00 | Secure code generation and policy gates | data_pipeline | intermediate | Task: data_pipeline
Topic: Secure code generation and policy gates
Difficulty: intermediate
Target language: C#
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
| [] | {
"target_language": "C#",
"developer_needs": [
"ci_integration",
"repo_scale_reasoning",
"documentation",
"auditability"
],
"moe_experts": [
"governance_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | edb919decda4d5294e68fae9302da61ea57ff360 | |
train_31951 | 2026-01-01T00:00:00 | Secure code generation and policy gates | agent_loop | intermediate | Task: agent_loop
Topic: Secure code generation and policy gates
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.
Loop: Plan → Edit → Test → Reflect → Human gate
| [] | {
"target_language": "Go",
"developer_needs": [
"evaluation_metrics",
"governance",
"repo_scale_reasoning",
"auditability"
],
"moe_experts": [
"agentic_systems_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 60069090cb0d4ad3f4368bed9929e4eaa7a1cba6 | |
train_31952 | 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: 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": [
"governance",
"documentation",
"ci_integration",
"security_gates"
],
"moe_experts": [
"coding_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 64f3019544736c5dbafa95c4510102e00fd87732 | |
train_31953 | 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
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Java",
"developer_needs": [
"security_gates",
"reproducibility",
"ci_integration",
"auditability"
],
"moe_experts": [
"coding_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 96b2bc0d12a5288865547552e4f1bbd6f1528b00 | |
train_31954 | 2026-01-01T00:00:00 | Reasoning-first coding models and tunable deliberation | patch_diff | expert | Task: patch_diff
Topic: Reasoning-first coding models and tunable deliberation
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.
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": "Go",
"developer_needs": [
"security_gates",
"tooling",
"evaluation_metrics",
"auditability"
],
"moe_experts": [
"governance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 55e9f48673bd9d9015cff77c0ce7a77ac0eee71e | |
train_31955 | 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: 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.
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": [
"documentation",
"reproducibility",
"tests_are_truth",
"auditability"
],
"moe_experts": [
"evaluation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 5c4690dadb6d8dc79094afda89b90afc9232b215 | |
train_31956 | 2026-01-01T00:00:00 | Agentic coding systems (plan→edit→test→reflect) | eval | expert | Task: eval
Topic: Agentic coding systems (plan→edit→test→reflect)
Difficulty: expert
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": [
"governance",
"documentation",
"evaluation_metrics",
"security_gates"
],
"moe_experts": [
"governance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | f20546f6fdbdfba1e24087ac64ac31ee6832d3cf | |
train_31957 | 2026-01-01T00:00:00 | Agentic coding systems (plan→edit→test→reflect) | agent_loop | intermediate | Task: agent_loop
Topic: Agentic coding systems (plan→edit→test→reflect)
Difficulty: intermediate
Target language: Rust
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
| [] | {
"target_language": "Rust",
"developer_needs": [
"documentation",
"ci_integration",
"governance",
"security_gates"
],
"moe_experts": [
"data_curation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 787129152f7be2c0beb93db10e5b30a32295163c | |
train_31958 | 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: 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": [
"repo_scale_reasoning",
"evaluation_metrics",
"cost_latency_tradeoffs",
"governance"
],
"moe_experts": [
"performance_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 3d958ef4665f45beea5c9c308050d087c890e822 | |
train_31959 | 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: 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": [
"security_gates",
"ci_integration",
"tooling",
"repo_scale_reasoning"
],
"moe_experts": [
"coding_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 440aa4a0639c7c385f9387bfefe0133f3e68bff6 | |
train_31960 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | data_pipeline | intermediate | Task: data_pipeline
Topic: Latency, cost, and reliability optimization
Difficulty: intermediate
Target language: SQL
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
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": "SQL",
"developer_needs": [
"governance",
"evaluation_metrics",
"repo_scale_reasoning",
"reproducibility"
],
"moe_experts": [
"agentic_systems_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 0d57225d3f9fed2a586aace31f39872aa6a04ab0 | |
train_31961 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | compare | advanced | Task: compare
Topic: Latency, cost, and reliability optimization
Difficulty: advanced
Target language: JavaScript
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
| [] | {
"target_language": "JavaScript",
"developer_needs": [
"reproducibility",
"evaluation_metrics",
"auditability",
"governance"
],
"moe_experts": [
"security_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 7829c14d22f97cbe4d26abe85e58e6c1955d0a4d | |
train_31962 | 2026-01-01T00:00:00 | SWE-bench style real-repo evaluation | agent_loop | expert | Task: agent_loop
Topic: SWE-bench style real-repo evaluation
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.
Loop: Plan → Edit → Test → Reflect → Human gate
| [] | {
"target_language": "Bash",
"developer_needs": [
"documentation",
"auditability",
"tests_are_truth",
"cost_latency_tradeoffs"
],
"moe_experts": [
"governance_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | bdb92ed0543a9abeff5940ae0c18500cf7986781 | |
train_31963 | 2026-01-01T00:00:00 | Multimodal dev workflows (docs, diagrams, traces) | patch_diff | intermediate | Task: patch_diff
Topic: Multimodal dev workflows (docs, diagrams, traces)
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.
Patch (diff-style):
```diff
- if x == 0:
- return 1/x
+ if x == 0:
+ raise ValueError('division by zero')
```
Acceptance:
- Tests pass
- No new regressions
| [] | {
"target_language": "SQL",
"developer_needs": [
"tests_are_truth",
"reproducibility",
"auditability",
"repo_scale_reasoning"
],
"moe_experts": [
"data_curation_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 04bbaae5822744ee7dfa0372900683bc2b62c077 | |
train_31964 | 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: 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": [
"governance",
"security_gates",
"repo_scale_reasoning",
"reproducibility"
],
"moe_experts": [
"security_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 8dd88837163aec56f9695a16ced6a531581b3a4d | |
train_31965 | 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: 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
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Rust",
"developer_needs": [
"evaluation_metrics",
"reproducibility",
"governance",
"repo_scale_reasoning"
],
"moe_experts": [
"data_curation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 7f2bd183c4ca8925bd4315f05d72d87f9ca9cd1c | |
train_31966 | 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: 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
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Rust",
"developer_needs": [
"security_gates",
"auditability",
"evaluation_metrics",
"reproducibility"
],
"moe_experts": [
"security_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | e14af08fc4ddf48398753d9ad17c34007f720d8b | |
train_31967 | 2026-01-01T00:00:00 | Code-specialized model families and sizing tradeoffs | explain | intermediate | Task: explain
Topic: Code-specialized model families and sizing tradeoffs
Difficulty: intermediate
Target language: SQL
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "SQL",
"developer_needs": [
"tests_are_truth",
"security_gates",
"repo_scale_reasoning",
"ci_integration"
],
"moe_experts": [
"agentic_systems_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 7b52bdbc6d423f93294a73e4a26d72ebdbc69a12 | |
train_31968 | 2026-01-01T00:00:00 | Governance, provenance, and licensing for code data | agent_loop | advanced | Task: agent_loop
Topic: Governance, provenance, and licensing for code data
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.
Loop: Plan → Edit → Test → Reflect → Human gate
| [] | {
"target_language": "Go",
"developer_needs": [
"evaluation_metrics",
"documentation",
"ci_integration",
"cost_latency_tradeoffs"
],
"moe_experts": [
"performance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | ab0ea050403be478d5d2119bc0e53a735c8b8c34 | |
train_31969 | 2026-01-01T00:00:00 | Mixture-of-Experts (MoE) for code | design | advanced | Task: design
Topic: Mixture-of-Experts (MoE) for code
Difficulty: advanced
Target language: 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",
"reproducibility",
"documentation"
],
"moe_experts": [
"data_curation_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 0d26c4399a52eb6878cfd2ee399d9695365c7535 | |
train_31970 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | patch_diff | advanced | Task: patch_diff
Topic: Latency, cost, and reliability optimization
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.
Patch (diff-style):
```diff
- if x == 0:
- return 1/x
+ if x == 0:
+ raise ValueError('division by zero')
```
Acceptance:
- Tests pass
- No new regressions
| [] | {
"target_language": "Bash",
"developer_needs": [
"auditability",
"repo_scale_reasoning",
"security_gates",
"governance"
],
"moe_experts": [
"coding_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | a75e610ddb2ccc87b67c4bd8199e34db752def81 | |
train_31971 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | design | expert | Task: design
Topic: Latency, cost, and reliability optimization
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": [
"reproducibility",
"auditability",
"ci_integration",
"repo_scale_reasoning"
],
"moe_experts": [
"agentic_systems_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 5ec3709e67816cc979eb6f5e5e56e07068a32b84 | |
train_31972 | 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: 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",
"ci_integration",
"tests_are_truth",
"governance"
],
"moe_experts": [
"agentic_systems_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 8d740f511fbad84dadf48b485c5b441bab5cc456 | |
train_31973 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | data_pipeline | expert | Task: data_pipeline
Topic: Latency, cost, and reliability optimization
Difficulty: expert
Target language: 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
| [
"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",
"tooling",
"auditability"
],
"moe_experts": [
"coding_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 60a580e05487b5048eb20072dd209692d7054528 | |
train_31974 | 2026-01-01T00:00:00 | Multimodal dev workflows (docs, diagrams, traces) | explain | advanced | Task: explain
Topic: Multimodal dev workflows (docs, diagrams, traces)
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
| [] | {
"target_language": "JavaScript",
"developer_needs": [
"security_gates",
"tests_are_truth",
"reproducibility",
"cost_latency_tradeoffs"
],
"moe_experts": [
"performance_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 556c5fd1d5b47920d3ff5d2c8a6aa353c589f28a | |
train_31975 | 2026-01-01T00:00:00 | Agentic coding systems (plan→edit→test→reflect) | data_pipeline | intermediate | Task: data_pipeline
Topic: Agentic coding systems (plan→edit→test→reflect)
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.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
| [] | {
"target_language": "C#",
"developer_needs": [
"ci_integration",
"tests_are_truth",
"governance",
"reproducibility"
],
"moe_experts": [
"data_curation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 861e6e716c0ba30d78d5072de22a554f994ac765 | |
train_31976 | 2026-01-01T00:00:00 | SWE-bench style real-repo evaluation | code | intermediate | Task: code
Topic: SWE-bench style real-repo evaluation
Difficulty: intermediate
Target language: 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
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Java",
"developer_needs": [
"reproducibility",
"tests_are_truth",
"cost_latency_tradeoffs",
"tooling"
],
"moe_experts": [
"agentic_systems_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 76bf4e87480e2c81d14c2c85b31ac4d74d2e1620 | |
train_31977 | 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: 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": [
"auditability",
"ci_integration",
"security_gates",
"governance"
],
"moe_experts": [
"agentic_systems_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | ac29755b8471a09c12f017e6e6c3299eb05e1fe1 | |
train_31978 | 2026-01-01T00:00:00 | Mixture-of-Experts (MoE) for code | data_pipeline | intermediate | Task: data_pipeline
Topic: Mixture-of-Experts (MoE) for code
Difficulty: intermediate
Target language: 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": [
"ci_integration",
"governance",
"auditability",
"repo_scale_reasoning"
],
"moe_experts": [
"coding_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 69d5d1e52735d748343b83705291fafa767d26c5 | |
train_31979 | 2026-01-01T00:00:00 | Multimodal dev workflows (docs, diagrams, traces) | code | intermediate | Task: code
Topic: Multimodal dev workflows (docs, diagrams, traces)
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.
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": [
"governance",
"evaluation_metrics",
"tooling",
"cost_latency_tradeoffs"
],
"moe_experts": [
"data_curation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 3213f3797854cd617db4ea8ce0c697e56e23f800 | |
train_31980 | 2026-01-01T00:00:00 | Self-improving agents and feedback loops | explain | expert | Task: explain
Topic: Self-improving agents and feedback loops
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": [
"reproducibility",
"security_gates",
"evaluation_metrics",
"tooling"
],
"moe_experts": [
"coding_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | fc6cd40dc5c7a00c26141b05c405952b6242e534 | |
train_31981 | 2026-01-01T00:00:00 | Governance, provenance, and licensing for code data | explain | expert | Task: explain
Topic: Governance, provenance, and licensing for code data
Difficulty: expert
Target language: TypeScript
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "TypeScript",
"developer_needs": [
"governance",
"reproducibility",
"auditability",
"tooling"
],
"moe_experts": [
"agentic_systems_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 6f8dae52150dcfd0b9bf2aad7c8e4ca671b35cc6 | |
train_31982 | 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: 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.
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": [
"ci_integration",
"evaluation_metrics",
"cost_latency_tradeoffs",
"security_gates"
],
"moe_experts": [
"coding_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | ca5ac0582c1aa918dad80fcbda56bbbf850069a9 | |
train_31983 | 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": [
"documentation",
"cost_latency_tradeoffs",
"evaluation_metrics",
"tooling"
],
"moe_experts": [
"security_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 617d5e9644b5d5f58e9bd88655b253f0148fe3f3 | |
train_31984 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | code | advanced | Task: code
Topic: Latency, cost, and reliability optimization
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
| [] | {
"target_language": "Bash",
"developer_needs": [
"auditability",
"evaluation_metrics",
"repo_scale_reasoning",
"tests_are_truth"
],
"moe_experts": [
"evaluation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | df497903e01912f4a53a5675b49eb956e757f4c8 | |
train_31985 | 2026-01-01T00:00:00 | Extended context and repo-scale understanding | agent_loop | expert | Task: agent_loop
Topic: Extended context and repo-scale understanding
Difficulty: expert
Target language: SQL
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
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": "SQL",
"developer_needs": [
"governance",
"documentation",
"ci_integration",
"security_gates"
],
"moe_experts": [
"performance_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 4e5f0dd2d556b6f6eed0b06d5ef577e48a30d306 | |
train_31986 | 2026-01-01T00:00:00 | Self-improving agents and feedback loops | agent_loop | advanced | Task: agent_loop
Topic: Self-improving agents and feedback loops
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.
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": "Java",
"developer_needs": [
"tests_are_truth",
"security_gates",
"documentation",
"auditability"
],
"moe_experts": [
"performance_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | dbbd1683c2155f573c2dd731218589e1160c76d9 | |
train_31987 | 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: 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": [
"reproducibility",
"documentation",
"tooling",
"repo_scale_reasoning"
],
"moe_experts": [
"evaluation_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 7825a59d0f0b677c380f8327a1f8cc27ff6f260f | |
train_31988 | 2026-01-01T00:00:00 | SWE-bench style real-repo evaluation | review | advanced | Task: review
Topic: SWE-bench style real-repo evaluation
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.
Review: correctness, security, performance, governance
| [] | {
"target_language": "SQL",
"developer_needs": [
"tests_are_truth",
"ci_integration",
"governance",
"cost_latency_tradeoffs"
],
"moe_experts": [
"evaluation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 408052fb7e92ea3842ee4e75e6ee9d4f784e9d69 | |
train_31989 | 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: 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
| [] | {
"target_language": "Java",
"developer_needs": [
"reproducibility",
"documentation",
"security_gates",
"repo_scale_reasoning"
],
"moe_experts": [
"coding_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 90b12c967788efce0835ef7acafe077564c1811e | |
train_31990 | 2026-01-01T00:00:00 | Code-specialized model families and sizing tradeoffs | agent_loop | expert | Task: agent_loop
Topic: Code-specialized model families and sizing tradeoffs
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.
Loop: Plan → Edit → Test → Reflect → Human gate
| [] | {
"target_language": "Bash",
"developer_needs": [
"reproducibility",
"evaluation_metrics",
"auditability",
"security_gates"
],
"moe_experts": [
"security_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 9eb4fd6514873538b5f1ca8ea4005096a20c1018 | |
train_31991 | 2026-01-01T00:00:00 | Dataset curation pipelines (filter, dedupe, quality) | review | advanced | Task: review
Topic: Dataset curation pipelines (filter, dedupe, quality)
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.
Review: correctness, security, performance, governance
| [] | {
"target_language": "Bash",
"developer_needs": [
"tooling",
"auditability",
"cost_latency_tradeoffs",
"security_gates"
],
"moe_experts": [
"evaluation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | b720c012383d00a7d0fa37176a85144d2c441f6a | |
train_31992 | 2026-01-01T00:00:00 | Code-specialized model families and sizing tradeoffs | explain | expert | Task: explain
Topic: Code-specialized model families and sizing tradeoffs
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": [
"auditability",
"repo_scale_reasoning",
"reproducibility",
"security_gates"
],
"moe_experts": [
"performance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 26d89b049c843d1cd0504067a60c2345706ee631 | |
train_31993 | 2026-01-01T00:00:00 | Mixture-of-Experts (MoE) for code | agent_loop | expert | Task: agent_loop
Topic: Mixture-of-Experts (MoE) for code
Difficulty: expert
Target language: Rust
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
| [] | {
"target_language": "Rust",
"developer_needs": [
"tests_are_truth",
"evaluation_metrics",
"auditability",
"documentation"
],
"moe_experts": [
"security_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | b1038682139592149f733ba82af7a5ac566f224c | |
train_31994 | 2026-01-01T00:00:00 | Tool calling, sandboxes, and CI integration | failure_analysis | intermediate | Task: failure_analysis
Topic: Tool calling, sandboxes, and CI integration
Difficulty: intermediate
Target language: Python
Context: 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": "Python",
"developer_needs": [
"cost_latency_tradeoffs",
"auditability",
"tooling",
"tests_are_truth"
],
"moe_experts": [
"performance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 20ea7fff40772c6a92415b4f9d1adb8b11afac27 | |
train_31995 | 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: 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.
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": [
"governance",
"reproducibility",
"evaluation_metrics",
"auditability"
],
"moe_experts": [
"agentic_systems_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 96382c080afe788551762a89980442540a15f1a6 | |
train_31996 | 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: 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": [
"tests_are_truth",
"governance",
"cost_latency_tradeoffs",
"tooling"
],
"moe_experts": [
"security_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 6d9bd54e775dde0812f6720662b6a1e655c5d35d | |
train_31997 | 2026-01-01T00:00:00 | Mixture-of-Experts (MoE) for code | patch_diff | expert | Task: patch_diff
Topic: Mixture-of-Experts (MoE) for code
Difficulty: expert
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
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "TypeScript",
"developer_needs": [
"governance",
"repo_scale_reasoning",
"cost_latency_tradeoffs",
"tooling"
],
"moe_experts": [
"evaluation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | bb6b7ea46cd50c94c463f9a7cedc8d3fe7d38df4 | |
train_31998 | 2026-01-01T00:00:00 | Mixture-of-Experts (MoE) for code | eval | intermediate | Task: eval
Topic: Mixture-of-Experts (MoE) for code
Difficulty: intermediate
Target language: 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.
Eval:
pass@k, time-to-green, regressions, diff size
| [] | {
"target_language": "Python",
"developer_needs": [
"repo_scale_reasoning",
"security_gates",
"auditability",
"governance"
],
"moe_experts": [
"evaluation_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | a50b4d8d1dcf4e3cfc90b0663ae665ebbc6823fa | |
train_31999 | 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: Java
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Patch (diff-style):
```diff
- if x == 0:
- return 1/x
+ if x == 0:
+ raise ValueError('division by zero')
```
Acceptance:
- Tests pass
- No new regressions
| [] | {
"target_language": "Java",
"developer_needs": [
"repo_scale_reasoning",
"cost_latency_tradeoffs",
"documentation",
"security_gates"
],
"moe_experts": [
"data_curation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | b07eaad9f39e5e8436734ab35c86cd0ea1faaa8d |
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