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_32500 | 2026-01-01T00:00:00 | SWE-bench style real-repo evaluation | compare | expert | Task: compare
Topic: SWE-bench style real-repo evaluation
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
| [] | {
"target_language": "SQL",
"developer_needs": [
"ci_integration",
"reproducibility",
"governance",
"tests_are_truth"
],
"moe_experts": [
"performance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 4b65097b6beaeca96551ecbd747fc5b8af0a59e2 | |
train_32501 | 2026-01-01T00:00:00 | SWE-bench style real-repo evaluation | compare | expert | Task: compare
Topic: SWE-bench style real-repo evaluation
Difficulty: expert
Target language: TypeScript
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
| [] | {
"target_language": "TypeScript",
"developer_needs": [
"reproducibility",
"documentation",
"tooling",
"cost_latency_tradeoffs"
],
"moe_experts": [
"performance_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 47fdcb15f82b98d7ddb1032e20c82b5e12260fa0 | |
train_32502 | 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: 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.
Loop: Plan → Edit → Test → Reflect → Human gate
| [] | {
"target_language": "Python",
"developer_needs": [
"security_gates",
"tests_are_truth",
"evaluation_metrics",
"ci_integration"
],
"moe_experts": [
"evaluation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 5f9b927e0bcf7a8a815ae327449ae36d2812ef58 | |
train_32503 | 2026-01-01T00:00:00 | Agentic coding systems (plan→edit→test→reflect) | review | advanced | Task: review
Topic: Agentic coding systems (plan→edit→test→reflect)
Difficulty: advanced
Target language: Bash
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
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": [
"security_gates",
"tests_are_truth",
"documentation",
"reproducibility"
],
"moe_experts": [
"security_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 65708bebf748ca275fabb103aa632ca480830b5a | |
train_32504 | 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: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "SQL",
"developer_needs": [
"evaluation_metrics",
"tooling",
"reproducibility",
"cost_latency_tradeoffs"
],
"moe_experts": [
"coding_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 733844c65e13fc7db0231422c0f4bba821fc2f75 | |
train_32505 | 2026-01-01T00:00:00 | Code-specialized model families and sizing tradeoffs | patch_diff | intermediate | Task: patch_diff
Topic: Code-specialized model families and sizing tradeoffs
Difficulty: intermediate
Target language: Python
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
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": "Python",
"developer_needs": [
"cost_latency_tradeoffs",
"reproducibility",
"documentation",
"ci_integration"
],
"moe_experts": [
"security_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 5ba60deba972a2dedf60b2a68190cf41bd4327ad | |
train_32506 | 2026-01-01T00:00:00 | Tool calling, sandboxes, and CI integration | design | expert | Task: design
Topic: Tool calling, sandboxes, and CI integration
Difficulty: expert
Target language: JavaScript
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "JavaScript",
"developer_needs": [
"ci_integration",
"security_gates",
"governance",
"repo_scale_reasoning"
],
"moe_experts": [
"evaluation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 32b903233822e835d7adb3f795ca4efdce8437b0 | |
train_32507 | 2026-01-01T00:00:00 | Governance, provenance, and licensing for code data | code | expert | Task: code
Topic: Governance, provenance, and licensing for code data
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
```
| [
"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",
"tooling",
"governance",
"evaluation_metrics"
],
"moe_experts": [
"performance_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 9bf3097ef769219d511f1b3be31901d69f06b537 | |
train_32508 | 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: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "TypeScript",
"developer_needs": [
"security_gates",
"cost_latency_tradeoffs",
"repo_scale_reasoning",
"documentation"
],
"moe_experts": [
"agentic_systems_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 7a27f7aa335f0c56e6531cb0bd6728f6c1ae33b4 | |
train_32509 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | explain | advanced | Task: explain
Topic: Latency, cost, and reliability optimization
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": [
"ci_integration",
"security_gates",
"auditability",
"reproducibility"
],
"moe_experts": [
"agentic_systems_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 926b754563f02daf27756e13be3e0f8e4440f6d2 | |
train_32510 | 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: JavaScript
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "JavaScript",
"developer_needs": [
"reproducibility",
"auditability",
"cost_latency_tradeoffs",
"ci_integration"
],
"moe_experts": [
"coding_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 2869875a5511c5c9b0e7dea837f6f1c979dc6783 | |
train_32511 | 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: C#
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "C#",
"developer_needs": [
"evaluation_metrics",
"cost_latency_tradeoffs",
"documentation",
"tooling"
],
"moe_experts": [
"security_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | b630594deae0d9e4e500df3ec1d2568a4445cd2e | |
train_32512 | 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: Python
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Python",
"developer_needs": [
"tooling",
"documentation",
"auditability",
"cost_latency_tradeoffs"
],
"moe_experts": [
"coding_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 5bbab08a6958b7b73fe9bc1090f6610b9d6b3b41 | |
train_32513 | 2026-01-01T00:00:00 | Secure code generation and policy gates | code | advanced | Task: code
Topic: Secure code generation and policy gates
Difficulty: advanced
Target language: Go
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Go",
"developer_needs": [
"tooling",
"governance",
"documentation",
"ci_integration"
],
"moe_experts": [
"agentic_systems_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 25d7aa2a90d58f0a7b61ee08b80b98d1fecb01f1 | |
train_32514 | 2026-01-01T00:00:00 | Code-specialized model families and sizing tradeoffs | data_pipeline | advanced | Task: data_pipeline
Topic: Code-specialized model families and sizing tradeoffs
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": [
"reproducibility",
"security_gates",
"governance",
"tests_are_truth"
],
"moe_experts": [
"evaluation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 021611813b9f098596c76080b2b8ba216173017f | |
train_32515 | 2026-01-01T00:00:00 | Extended context and repo-scale understanding | code | advanced | Task: code
Topic: Extended context and repo-scale understanding
Difficulty: advanced
Target language: C#
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "C#",
"developer_needs": [
"reproducibility",
"security_gates",
"governance",
"auditability"
],
"moe_experts": [
"agentic_systems_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | ae02430a5e802fea1163c1995d3be65b7a28e4b4 | |
train_32516 | 2026-01-01T00:00:00 | Extended context and repo-scale understanding | design | expert | Task: design
Topic: Extended context and repo-scale understanding
Difficulty: expert
Target language: Rust
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "Rust",
"developer_needs": [
"documentation",
"reproducibility",
"repo_scale_reasoning",
"tests_are_truth"
],
"moe_experts": [
"governance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 3734e02c7369e3c3d98567e298d6a0776e4a24c7 | |
train_32517 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | patch_diff | intermediate | Task: patch_diff
Topic: Latency, cost, and reliability optimization
Difficulty: intermediate
Target language: 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
| [] | {
"target_language": "Python",
"developer_needs": [
"repo_scale_reasoning",
"documentation",
"ci_integration",
"auditability"
],
"moe_experts": [
"governance_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 5de64494073615e04760d2e19637814d239fde7e | |
train_32518 | 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: 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": "TypeScript",
"developer_needs": [
"repo_scale_reasoning",
"security_gates",
"reproducibility",
"evaluation_metrics"
],
"moe_experts": [
"performance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | c29788ad2991b97036f02cde2902e86ea17c096a | |
train_32519 | 2026-01-01T00:00:00 | Governance, provenance, and licensing for code data | review | intermediate | Task: review
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.
Review: correctness, security, performance, governance
| [] | {
"target_language": "C#",
"developer_needs": [
"documentation",
"ci_integration",
"security_gates",
"reproducibility"
],
"moe_experts": [
"evaluation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 703729f8222cb1ea6d77722356dddbea76053515 | |
train_32520 | 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: 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": [
"repo_scale_reasoning",
"tooling",
"tests_are_truth",
"documentation"
],
"moe_experts": [
"performance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 8a3f424f324686c210cfacb4e5a9a2e656822de9 | |
train_32521 | 2026-01-01T00:00:00 | Self-improving agents and feedback loops | patch_diff | intermediate | Task: patch_diff
Topic: Self-improving agents and feedback loops
Difficulty: intermediate
Target language: 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": [
"reproducibility",
"tests_are_truth",
"repo_scale_reasoning",
"tooling"
],
"moe_experts": [
"governance_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | a0fe7b5f45bdff38c69e575b9323781cba64ed2e | |
train_32522 | 2026-01-01T00:00:00 | Reasoning-first coding models and tunable deliberation | failure_analysis | expert | Task: failure_analysis
Topic: Reasoning-first coding models and tunable deliberation
Difficulty: expert
Target language: Bash
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
| [] | {
"target_language": "Bash",
"developer_needs": [
"repo_scale_reasoning",
"auditability",
"reproducibility",
"ci_integration"
],
"moe_experts": [
"evaluation_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | d808b42bf72faecf3b2ef58a4cb50b3b9d841515 | |
train_32523 | 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: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Review: correctness, security, performance, governance
| [] | {
"target_language": "Java",
"developer_needs": [
"evaluation_metrics",
"cost_latency_tradeoffs",
"auditability",
"documentation"
],
"moe_experts": [
"security_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | cf20e04a3bc81d228e121d0afb34e503dc1577b2 | |
train_32524 | 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: 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.
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",
"auditability",
"tooling",
"reproducibility"
],
"moe_experts": [
"coding_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 8c0b2bcfc388e21bbe55bc67a4882d96266d1b79 | |
train_32525 | 2026-01-01T00:00:00 | Reasoning-first coding models and tunable deliberation | code | advanced | Task: code
Topic: Reasoning-first coding models and tunable deliberation
Difficulty: advanced
Target language: Go
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Go",
"developer_needs": [
"tests_are_truth",
"reproducibility",
"cost_latency_tradeoffs",
"documentation"
],
"moe_experts": [
"coding_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | f25c699f167be89155a248dff77b0d4e9b89babd | |
train_32526 | 2026-01-01T00:00:00 | Governance, provenance, and licensing for code data | design | advanced | Task: design
Topic: Governance, provenance, and licensing for code data
Difficulty: advanced
Target language: Go
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Go",
"developer_needs": [
"auditability",
"ci_integration",
"repo_scale_reasoning",
"governance"
],
"moe_experts": [
"agentic_systems_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | a32a26cd5d71fa7421068aa662fbfdcb6dd5ef88 | |
train_32527 | 2026-01-01T00:00:00 | Secure code generation and policy gates | agent_loop | expert | Task: agent_loop
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.
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": "C#",
"developer_needs": [
"cost_latency_tradeoffs",
"security_gates",
"auditability",
"ci_integration"
],
"moe_experts": [
"evaluation_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | a9e1a200750a83f26cb7b6670c52163e0171461c | |
train_32528 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | agent_loop | intermediate | Task: agent_loop
Topic: Latency, cost, and reliability optimization
Difficulty: intermediate
Target language: JavaScript
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
| [] | {
"target_language": "JavaScript",
"developer_needs": [
"security_gates",
"auditability",
"evaluation_metrics",
"tests_are_truth"
],
"moe_experts": [
"governance_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 4b902da29659afd5cceb1f5fb734f7def79a34af | |
train_32529 | 2026-01-01T00:00:00 | Model merging, distillation, and continued pretraining | review | expert | Task: review
Topic: Model merging, distillation, and continued pretraining
Difficulty: expert
Target language: Java
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
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": [
"documentation",
"auditability",
"repo_scale_reasoning",
"reproducibility"
],
"moe_experts": [
"governance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 20e287e837627221347da852c241fec6479d4b7b | |
train_32530 | 2026-01-01T00:00:00 | Model merging, distillation, and continued pretraining | code | advanced | Task: code
Topic: Model merging, distillation, and continued pretraining
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.
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": [
"documentation",
"ci_integration",
"security_gates",
"evaluation_metrics"
],
"moe_experts": [
"coding_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | c0f5db405faf68499995807f783432c2688577ef | |
train_32531 | 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: 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.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "C#",
"developer_needs": [
"documentation",
"ci_integration",
"cost_latency_tradeoffs",
"auditability"
],
"moe_experts": [
"coding_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | d01ce6445fcfaf5e6dbb4a99ac743f6f36621f67 | |
train_32532 | 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: JavaScript
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "JavaScript",
"developer_needs": [
"repo_scale_reasoning",
"security_gates",
"cost_latency_tradeoffs",
"ci_integration"
],
"moe_experts": [
"data_curation_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | b350fb02a991a7afe0eed1544853c82fdb68d49f | |
train_32533 | 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: Rust
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Rust",
"developer_needs": [
"tests_are_truth",
"tooling",
"repo_scale_reasoning",
"evaluation_metrics"
],
"moe_experts": [
"agentic_systems_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 02fd9970f134085c77a90ae8f2cdf1b40efa43be | |
train_32534 | 2026-01-01T00:00:00 | Agentic coding systems (plan→edit→test→reflect) | data_pipeline | advanced | Task: data_pipeline
Topic: Agentic coding systems (plan→edit→test→reflect)
Difficulty: advanced
Target language: JavaScript
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
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": [
"auditability",
"security_gates",
"evaluation_metrics",
"repo_scale_reasoning"
],
"moe_experts": [
"coding_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 4c01b97eda432df2d07db8e0c1201af9ae05f166 | |
train_32535 | 2026-01-01T00:00:00 | Governance, provenance, and licensing for code data | failure_analysis | advanced | Task: failure_analysis
Topic: Governance, provenance, and licensing for code data
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.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
| [] | {
"target_language": "Python",
"developer_needs": [
"evaluation_metrics",
"repo_scale_reasoning",
"documentation",
"tooling"
],
"moe_experts": [
"evaluation_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 79ce9f41414f5287d48a4d84d9bf8dbbf1c51035 | |
train_32536 | 2026-01-01T00:00:00 | SWE-bench style real-repo evaluation | code | advanced | Task: code
Topic: SWE-bench style real-repo evaluation
Difficulty: advanced
Target language: SQL
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "SQL",
"developer_needs": [
"security_gates",
"tests_are_truth",
"repo_scale_reasoning",
"ci_integration"
],
"moe_experts": [
"performance_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 628156ae0be9347d2e8d664e126abd3870767a7f | |
train_32537 | 2026-01-01T00:00:00 | Model merging, distillation, and continued pretraining | eval | expert | Task: eval
Topic: Model merging, distillation, and continued pretraining
Difficulty: expert
Target language: Java
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Java",
"developer_needs": [
"governance",
"security_gates",
"repo_scale_reasoning",
"evaluation_metrics"
],
"moe_experts": [
"governance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 37ac29b012721f565722cd3b520d428b096163b0 | |
train_32538 | 2026-01-01T00:00:00 | Model merging, distillation, and continued pretraining | code | advanced | Task: code
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.
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": [
"evaluation_metrics",
"ci_integration",
"tooling",
"repo_scale_reasoning"
],
"moe_experts": [
"data_curation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 1075e0b4274a44173cfaf446355f66f30ebcc8ca | |
train_32539 | 2026-01-01T00:00:00 | Tool calling, sandboxes, and CI integration | review | intermediate | Task: review
Topic: Tool calling, sandboxes, and CI integration
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.
Review: correctness, security, performance, governance
| [] | {
"target_language": "Java",
"developer_needs": [
"tests_are_truth",
"ci_integration",
"cost_latency_tradeoffs",
"documentation"
],
"moe_experts": [
"security_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 947e71047ca350e691d2f88d0ac3305def9916bc | |
train_32540 | 2026-01-01T00:00:00 | Model merging, distillation, and continued pretraining | explain | expert | Task: explain
Topic: Model merging, distillation, and continued pretraining
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.
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": [
"reproducibility",
"documentation",
"cost_latency_tradeoffs",
"evaluation_metrics"
],
"moe_experts": [
"performance_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | a7f37bca45abb139e8daf3e674fdaf7bd8747abc | |
train_32541 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | compare | intermediate | Task: compare
Topic: Latency, cost, and reliability optimization
Difficulty: intermediate
Target language: TypeScript
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
| [] | {
"target_language": "TypeScript",
"developer_needs": [
"repo_scale_reasoning",
"ci_integration",
"reproducibility",
"security_gates"
],
"moe_experts": [
"performance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | c57564d49c95dcf5dd8de5aa462eb7e3b0330c45 | |
train_32542 | 2026-01-01T00:00:00 | Multimodal dev workflows (docs, diagrams, traces) | patch_diff | expert | Task: patch_diff
Topic: Multimodal dev workflows (docs, diagrams, traces)
Difficulty: expert
Target language: 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": [
"reproducibility",
"documentation",
"cost_latency_tradeoffs",
"repo_scale_reasoning"
],
"moe_experts": [
"performance_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | c9309dfafd33ae702239cf56164e79e7270863aa | |
train_32543 | 2026-01-01T00:00:00 | Governance, provenance, and licensing for code data | code | expert | Task: code
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
| [] | {
"target_language": "TypeScript",
"developer_needs": [
"repo_scale_reasoning",
"reproducibility",
"cost_latency_tradeoffs",
"ci_integration"
],
"moe_experts": [
"governance_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | b80bf8c1f19e711f875bec8f7b379fd1e72fe5b1 | |
train_32544 | 2026-01-01T00:00:00 | Dataset curation pipelines (filter, dedupe, quality) | failure_analysis | advanced | Task: failure_analysis
Topic: Dataset curation pipelines (filter, dedupe, quality)
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.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
| [] | {
"target_language": "C#",
"developer_needs": [
"evaluation_metrics",
"ci_integration",
"documentation",
"auditability"
],
"moe_experts": [
"coding_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | df0646b3eee38852a887bcf11dabbde677e5b5a1 | |
train_32545 | 2026-01-01T00:00:00 | Tool calling, sandboxes, and CI integration | design | advanced | Task: design
Topic: Tool calling, sandboxes, and CI integration
Difficulty: advanced
Target language: Go
Context: 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": [
"tests_are_truth",
"tooling",
"cost_latency_tradeoffs",
"governance"
],
"moe_experts": [
"agentic_systems_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 9be090042940d511db98c8f55ca6a14b038929b0 | |
train_32546 | 2026-01-01T00:00:00 | SWE-bench style real-repo evaluation | explain | intermediate | Task: explain
Topic: SWE-bench style real-repo evaluation
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.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "Java",
"developer_needs": [
"auditability",
"tests_are_truth",
"governance",
"ci_integration"
],
"moe_experts": [
"governance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 4ad8499d8a36d08b32bde056c894f38b6851e8a8 | |
train_32547 | 2026-01-01T00:00:00 | Extended context and repo-scale understanding | data_pipeline | intermediate | Task: data_pipeline
Topic: Extended context and repo-scale understanding
Difficulty: intermediate
Target language: Rust
Context: 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": "Rust",
"developer_needs": [
"auditability",
"governance",
"reproducibility",
"evaluation_metrics"
],
"moe_experts": [
"governance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | f57d4a3c37c622f45436d50c36ffc317a70ee8e1 | |
train_32548 | 2026-01-01T00:00:00 | Governance, provenance, and licensing for code data | eval | advanced | Task: eval
Topic: Governance, provenance, and licensing for code data
Difficulty: advanced
Target language: 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.
Eval:
pass@k, time-to-green, regressions, diff size
| [] | {
"target_language": "Rust",
"developer_needs": [
"governance",
"documentation",
"reproducibility",
"ci_integration"
],
"moe_experts": [
"agentic_systems_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 600b6ab32794b15b593506f50d5dada52e1dc47a | |
train_32549 | 2026-01-01T00:00:00 | Self-improving agents and feedback loops | data_pipeline | advanced | Task: data_pipeline
Topic: Self-improving agents and feedback loops
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.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
| [] | {
"target_language": "TypeScript",
"developer_needs": [
"ci_integration",
"governance",
"tooling",
"auditability"
],
"moe_experts": [
"security_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 92e50bb026ee197b27411aaeff76bad55a18651b | |
train_32550 | 2026-01-01T00:00:00 | Tool calling, sandboxes, and CI integration | patch_diff | intermediate | Task: patch_diff
Topic: Tool calling, sandboxes, and CI integration
Difficulty: intermediate
Target language: Bash
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Patch (diff-style):
```diff
- if x == 0:
- return 1/x
+ if x == 0:
+ raise ValueError('division by zero')
```
Acceptance:
- Tests pass
- No new regressions
| [] | {
"target_language": "Bash",
"developer_needs": [
"evaluation_metrics",
"reproducibility",
"cost_latency_tradeoffs",
"tests_are_truth"
],
"moe_experts": [
"performance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | e562123d3a95c1e1b937f776fda023a6a2821a87 | |
train_32551 | 2026-01-01T00:00:00 | Multimodal dev workflows (docs, diagrams, traces) | patch_diff | expert | Task: patch_diff
Topic: Multimodal dev workflows (docs, diagrams, traces)
Difficulty: expert
Target language: 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.
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": [
"cost_latency_tradeoffs",
"repo_scale_reasoning",
"evaluation_metrics",
"tooling"
],
"moe_experts": [
"data_curation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | dc606dd2000e2f526be2869a6db88bb29ae1a9a9 | |
train_32552 | 2026-01-01T00:00:00 | Self-improving agents and feedback loops | compare | advanced | Task: compare
Topic: Self-improving agents and feedback loops
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.
Compare: capability, cost, latency, reliability
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Python",
"developer_needs": [
"documentation",
"security_gates",
"auditability",
"repo_scale_reasoning"
],
"moe_experts": [
"coding_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | afda002eb12abb36cf6ed25c332f88d6252463af | |
train_32553 | 2026-01-01T00:00:00 | Governance, provenance, and licensing for code data | compare | expert | Task: compare
Topic: Governance, provenance, and licensing for code data
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.
Compare: capability, cost, latency, reliability
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Bash",
"developer_needs": [
"evaluation_metrics",
"tooling",
"tests_are_truth",
"ci_integration"
],
"moe_experts": [
"coding_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 00e540845e92b4a1cd15a61bbf20cbc2ae9e7930 | |
train_32554 | 2026-01-01T00:00:00 | Governance, provenance, and licensing for code data | agent_loop | expert | Task: agent_loop
Topic: Governance, provenance, and licensing for code data
Difficulty: expert
Target language: 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.
Loop: Plan → Edit → Test → Reflect → Human gate
| [] | {
"target_language": "JavaScript",
"developer_needs": [
"reproducibility",
"governance",
"security_gates",
"evaluation_metrics"
],
"moe_experts": [
"evaluation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 5fa965e763290722a84996a5f42422a35c08c3ae | |
train_32555 | 2026-01-01T00:00:00 | Tool calling, sandboxes, and CI integration | design | advanced | Task: design
Topic: Tool calling, sandboxes, and CI integration
Difficulty: advanced
Target language: SQL
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "SQL",
"developer_needs": [
"reproducibility",
"security_gates",
"documentation",
"evaluation_metrics"
],
"moe_experts": [
"data_curation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 56ab1520a9438ef55915e101d608ef410b54672b | |
train_32556 | 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: 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.
Eval:
pass@k, time-to-green, regressions, diff size
| [] | {
"target_language": "SQL",
"developer_needs": [
"security_gates",
"cost_latency_tradeoffs",
"auditability",
"repo_scale_reasoning"
],
"moe_experts": [
"agentic_systems_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 1533cee1db8a38c6d5e3aadd2ed4d6f346a6dfba | |
train_32557 | 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: 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.
Patch (diff-style):
```diff
- if x == 0:
- return 1/x
+ if x == 0:
+ raise ValueError('division by zero')
```
Acceptance:
- Tests pass
- No new regressions
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Rust",
"developer_needs": [
"governance",
"cost_latency_tradeoffs",
"evaluation_metrics",
"tooling"
],
"moe_experts": [
"governance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 0463b0c866e29afe58388863659675ff8a3af261 | |
train_32558 | 2026-01-01T00:00:00 | Tool calling, sandboxes, and CI integration | explain | intermediate | Task: explain
Topic: Tool calling, sandboxes, and CI integration
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.
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": [
"governance",
"cost_latency_tradeoffs",
"auditability",
"ci_integration"
],
"moe_experts": [
"governance_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 168557b7a25794c4fdfb8b0ef2455230c365f389 | |
train_32559 | 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: 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": [
"auditability",
"governance",
"cost_latency_tradeoffs",
"repo_scale_reasoning"
],
"moe_experts": [
"security_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | a19095ce24a4610417aba3096103c4416fb0dfa3 | |
train_32560 | 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: 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.
Eval:
pass@k, time-to-green, regressions, diff size
| [] | {
"target_language": "SQL",
"developer_needs": [
"tests_are_truth",
"security_gates",
"documentation",
"cost_latency_tradeoffs"
],
"moe_experts": [
"evaluation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 97a9d00133ebe0dd803f0a66e8f61b724abac2b8 | |
train_32561 | 2026-01-01T00:00:00 | Extended context and repo-scale understanding | review | advanced | Task: review
Topic: Extended context and repo-scale understanding
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.
Review: correctness, security, performance, governance
| [] | {
"target_language": "C#",
"developer_needs": [
"documentation",
"ci_integration",
"reproducibility",
"cost_latency_tradeoffs"
],
"moe_experts": [
"security_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | c0dfc7525da3d12fbefa36df45338e1c56105539 | |
train_32562 | 2026-01-01T00:00:00 | Code-specialized model families and sizing tradeoffs | review | expert | Task: review
Topic: Code-specialized model families and sizing tradeoffs
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": [
"cost_latency_tradeoffs",
"repo_scale_reasoning",
"security_gates",
"tooling"
],
"moe_experts": [
"agentic_systems_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | c21ac80968d04d45684403df130cb160b32d2179 | |
train_32563 | 2026-01-01T00:00:00 | Code-specialized model families and sizing tradeoffs | review | expert | Task: review
Topic: Code-specialized model families and sizing tradeoffs
Difficulty: expert
Target language: Go
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Review: correctness, security, performance, governance
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Go",
"developer_needs": [
"reproducibility",
"tooling",
"tests_are_truth",
"cost_latency_tradeoffs"
],
"moe_experts": [
"evaluation_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | f3875f0f0aa729e265dbe052eaf28a236fa938ed | |
train_32564 | 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: 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": [
"security_gates",
"evaluation_metrics",
"cost_latency_tradeoffs",
"governance"
],
"moe_experts": [
"agentic_systems_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | d76e7da16e97b55f1fd589fc89459fe39bfa5dc8 | |
train_32565 | 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: 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": [
"repo_scale_reasoning",
"reproducibility",
"security_gates",
"cost_latency_tradeoffs"
],
"moe_experts": [
"evaluation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 9e3f8403554c3facd6bb536fbb4b9e210a200963 | |
train_32566 | 2026-01-01T00:00:00 | Dataset curation pipelines (filter, dedupe, quality) | failure_analysis | intermediate | Task: failure_analysis
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: intermediate
Target language: 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.
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": [
"tests_are_truth",
"repo_scale_reasoning",
"reproducibility",
"cost_latency_tradeoffs"
],
"moe_experts": [
"evaluation_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 02e58272c04d7c53a062e4f73867dd96881ab4c6 | |
train_32567 | 2026-01-01T00:00:00 | SWE-bench style real-repo evaluation | review | intermediate | Task: review
Topic: SWE-bench style real-repo evaluation
Difficulty: intermediate
Target language: 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": [
"auditability",
"cost_latency_tradeoffs",
"repo_scale_reasoning",
"ci_integration"
],
"moe_experts": [
"agentic_systems_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | a38d3d78f873e656b6c5992b014b1f8394eb74db | |
train_32568 | 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
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Python",
"developer_needs": [
"ci_integration",
"evaluation_metrics",
"reproducibility",
"tooling"
],
"moe_experts": [
"security_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | d32174f8157aabdbbe515c9f387a31960a156516 | |
train_32569 | 2026-01-01T00:00:00 | Code-specialized model families and sizing tradeoffs | review | expert | Task: review
Topic: Code-specialized model families and sizing tradeoffs
Difficulty: expert
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
| [] | {
"target_language": "Python",
"developer_needs": [
"security_gates",
"cost_latency_tradeoffs",
"tests_are_truth",
"reproducibility"
],
"moe_experts": [
"governance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | d70b7e4a1eec8ff8a7a1522c7ab0b66f7325c9ec | |
train_32570 | 2026-01-01T00:00:00 | Mixture-of-Experts (MoE) for code | compare | expert | Task: compare
Topic: Mixture-of-Experts (MoE) for code
Difficulty: expert
Target language: C#
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
| [] | {
"target_language": "C#",
"developer_needs": [
"tests_are_truth",
"reproducibility",
"auditability",
"evaluation_metrics"
],
"moe_experts": [
"security_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 07aa946516de48383f3146c1d8125abfab1d6a76 | |
train_32571 | 2026-01-01T00:00:00 | Extended context and repo-scale understanding | code | intermediate | Task: code
Topic: Extended context and repo-scale understanding
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": [
"documentation",
"tooling",
"governance",
"security_gates"
],
"moe_experts": [
"performance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 17f213ce8be682f5985c358bcb2dc64788066dfd | |
train_32572 | 2026-01-01T00:00:00 | Extended context and repo-scale understanding | compare | advanced | Task: compare
Topic: Extended context and repo-scale understanding
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.
Compare: capability, cost, latency, reliability
| [] | {
"target_language": "Bash",
"developer_needs": [
"documentation",
"reproducibility",
"tooling",
"ci_integration"
],
"moe_experts": [
"agentic_systems_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 0988ed8c7cdb098ea22dbeced4156e8ce016875c | |
train_32573 | 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: 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": [
"repo_scale_reasoning",
"reproducibility",
"documentation",
"tests_are_truth"
],
"moe_experts": [
"data_curation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 877517f9d1ca474f0e26258ce45c107989e202d3 | |
train_32574 | 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: 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
| [
"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",
"documentation"
],
"moe_experts": [
"performance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | cec4d00eeb0dde799495cde24e6f711adbd9b2f9 | |
train_32575 | 2026-01-01T00:00:00 | Code-specialized model families and sizing tradeoffs | agent_loop | intermediate | Task: agent_loop
Topic: Code-specialized model families and sizing tradeoffs
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.
Loop: Plan → Edit → Test → Reflect → Human gate
| [] | {
"target_language": "JavaScript",
"developer_needs": [
"governance",
"evaluation_metrics",
"repo_scale_reasoning",
"tests_are_truth"
],
"moe_experts": [
"coding_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | c69aa89445bb579e874faf3878d428aa1dee9e88 | |
train_32576 | 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: 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.
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",
"evaluation_metrics",
"governance",
"auditability"
],
"moe_experts": [
"evaluation_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 250fb929724e7b0fdc6659b65b4b3c314fbbf164 | |
train_32577 | 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: 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": [
"auditability",
"reproducibility",
"evaluation_metrics",
"cost_latency_tradeoffs"
],
"moe_experts": [
"agentic_systems_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | a40cb459224ae5640510babf1701ab8fda9c7841 | |
train_32578 | 2026-01-01T00:00:00 | Governance, provenance, and licensing for code data | data_pipeline | intermediate | Task: data_pipeline
Topic: Governance, provenance, and licensing for code data
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": [
"tests_are_truth",
"documentation",
"repo_scale_reasoning",
"security_gates"
],
"moe_experts": [
"governance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 43604c89a72bf09fd3e6e4a345cb09fd90bf97c3 | |
train_32579 | 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: 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
| [] | {
"target_language": "TypeScript",
"developer_needs": [
"security_gates",
"reproducibility",
"cost_latency_tradeoffs",
"governance"
],
"moe_experts": [
"governance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 2a7c698a5b477ece7c52f5841ea4ae40effa60a9 | |
train_32580 | 2026-01-01T00:00:00 | Secure code generation and policy gates | failure_analysis | expert | Task: failure_analysis
Topic: Secure code generation and policy gates
Difficulty: expert
Target language: JavaScript
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
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",
"tooling",
"cost_latency_tradeoffs",
"ci_integration"
],
"moe_experts": [
"coding_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 80a131a253d4164ba12ebe4da03284a300026617 | |
train_32581 | 2026-01-01T00:00:00 | Tool calling, sandboxes, and CI integration | agent_loop | expert | Task: agent_loop
Topic: Tool calling, sandboxes, and CI integration
Difficulty: expert
Target language: 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
| [] | {
"target_language": "SQL",
"developer_needs": [
"reproducibility",
"evaluation_metrics",
"cost_latency_tradeoffs",
"security_gates"
],
"moe_experts": [
"agentic_systems_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | bf67944532c01d1d15b161a7e4c82ba310bf309c | |
train_32582 | 2026-01-01T00:00:00 | Self-improving agents and feedback loops | design | intermediate | Task: design
Topic: Self-improving agents and feedback loops
Difficulty: intermediate
Target language: Java
Context: 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": "Java",
"developer_needs": [
"tooling",
"evaluation_metrics",
"tests_are_truth",
"documentation"
],
"moe_experts": [
"coding_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | c7a1287ba1165f848578642e1ecb7264b54e8874 | |
train_32583 | 2026-01-01T00:00:00 | Mixture-of-Experts (MoE) for code | data_pipeline | advanced | Task: data_pipeline
Topic: Mixture-of-Experts (MoE) for code
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.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
| [] | {
"target_language": "TypeScript",
"developer_needs": [
"ci_integration",
"evaluation_metrics",
"security_gates",
"auditability"
],
"moe_experts": [
"security_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 0962e4cd11a2af01aa14162ce958bf3a779ae81f | |
train_32584 | 2026-01-01T00:00:00 | Model merging, distillation, and continued pretraining | agent_loop | expert | Task: agent_loop
Topic: Model merging, distillation, and continued pretraining
Difficulty: expert
Target language: JavaScript
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
| [] | {
"target_language": "JavaScript",
"developer_needs": [
"governance",
"reproducibility",
"repo_scale_reasoning",
"documentation"
],
"moe_experts": [
"performance_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | db9bf85c3182bf2e31c13c62def526feea5517a5 | |
train_32585 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | code | advanced | Task: code
Topic: Latency, cost, and reliability optimization
Difficulty: advanced
Target language: C#
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "C#",
"developer_needs": [
"governance",
"tests_are_truth",
"documentation",
"repo_scale_reasoning"
],
"moe_experts": [
"evaluation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | c740d5d37df90310bd881cf67a330bf3691d9bcd | |
train_32586 | 2026-01-01T00:00:00 | Governance, provenance, and licensing for code data | failure_analysis | intermediate | Task: failure_analysis
Topic: Governance, provenance, and licensing for code data
Difficulty: intermediate
Target language: Bash
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Bash",
"developer_needs": [
"documentation",
"tooling",
"ci_integration",
"cost_latency_tradeoffs"
],
"moe_experts": [
"coding_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 6570985bbe06473e89ae3323f3dc3503f6415607 | |
train_32587 | 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: 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": [
"documentation",
"tests_are_truth",
"tooling",
"cost_latency_tradeoffs"
],
"moe_experts": [
"agentic_systems_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 4a738be0b34d1bcfb8102888bf942ed480e8439a | |
train_32588 | 2026-01-01T00:00:00 | Model merging, distillation, and continued pretraining | patch_diff | intermediate | Task: patch_diff
Topic: Model merging, distillation, and continued pretraining
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.
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",
"documentation",
"security_gates",
"governance"
],
"moe_experts": [
"security_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | d84fbf494bab2bc739553328da3b22698ad13448 | |
train_32589 | 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: 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": [
"ci_integration",
"tooling",
"tests_are_truth",
"evaluation_metrics"
],
"moe_experts": [
"security_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | a9e555e656c6d90ebce5e5c782101c9b6f691947 | |
train_32590 | 2026-01-01T00:00:00 | Model merging, distillation, and continued pretraining | eval | intermediate | Task: eval
Topic: Model merging, distillation, and continued pretraining
Difficulty: intermediate
Target language: Go
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
| [] | {
"target_language": "Go",
"developer_needs": [
"reproducibility",
"cost_latency_tradeoffs",
"documentation",
"tooling"
],
"moe_experts": [
"coding_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 2cf779481ea613fa8415d01ad9c4e2f156c0a232 | |
train_32591 | 2026-01-01T00:00:00 | Code-specialized model families and sizing tradeoffs | data_pipeline | advanced | Task: data_pipeline
Topic: Code-specialized model families and sizing tradeoffs
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.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
| [] | {
"target_language": "Python",
"developer_needs": [
"cost_latency_tradeoffs",
"repo_scale_reasoning",
"evaluation_metrics",
"tests_are_truth"
],
"moe_experts": [
"performance_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 5f30b6ba9ce9f8f200fc1db340395d69a5234fd6 | |
train_32592 | 2026-01-01T00:00:00 | Self-improving agents and feedback loops | failure_analysis | expert | Task: failure_analysis
Topic: Self-improving agents and feedback loops
Difficulty: expert
Target language: Rust
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
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": [
"security_gates",
"auditability",
"evaluation_metrics",
"governance"
],
"moe_experts": [
"governance_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 54b47341dcd47626ee9e3dea2d5907eac13d8f02 | |
train_32593 | 2026-01-01T00:00:00 | Governance, provenance, and licensing for code data | failure_analysis | expert | Task: failure_analysis
Topic: Governance, provenance, and licensing for code data
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.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
| [] | {
"target_language": "Go",
"developer_needs": [
"governance",
"documentation",
"cost_latency_tradeoffs",
"reproducibility"
],
"moe_experts": [
"security_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | a470137fc5fae2c1625f1161060c4c35acbada8c | |
train_32594 | 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: 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": [
"security_gates",
"tests_are_truth",
"cost_latency_tradeoffs",
"reproducibility"
],
"moe_experts": [
"evaluation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | de7a53c28a059fbb6214e3722d748002d4606d81 | |
train_32595 | 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: TypeScript
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
| [] | {
"target_language": "TypeScript",
"developer_needs": [
"documentation",
"tooling",
"governance",
"cost_latency_tradeoffs"
],
"moe_experts": [
"coding_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | d7abc592e759cdbabe7849351af296020556de1c | |
train_32596 | 2026-01-01T00:00:00 | Agentic coding systems (plan→edit→test→reflect) | agent_loop | advanced | Task: agent_loop
Topic: Agentic coding systems (plan→edit→test→reflect)
Difficulty: advanced
Target language: TypeScript
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "TypeScript",
"developer_needs": [
"evaluation_metrics",
"tooling",
"cost_latency_tradeoffs",
"documentation"
],
"moe_experts": [
"governance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 6dd0fb14faf7cb13eef1f64be75d65ea68e7db2a | |
train_32597 | 2026-01-01T00:00:00 | Governance, provenance, and licensing for code data | eval | intermediate | Task: eval
Topic: Governance, provenance, and licensing for code data
Difficulty: intermediate
Target language: C#
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "C#",
"developer_needs": [
"evaluation_metrics",
"repo_scale_reasoning",
"reproducibility",
"documentation"
],
"moe_experts": [
"governance_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 8f85ab7e42b34059b912dc73abf93ee798022090 | |
train_32598 | 2026-01-01T00:00:00 | Multimodal dev workflows (docs, diagrams, traces) | failure_analysis | intermediate | Task: failure_analysis
Topic: Multimodal dev workflows (docs, diagrams, traces)
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.
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",
"documentation",
"security_gates",
"ci_integration"
],
"moe_experts": [
"performance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 3b3d396a1f79e41bf3620bf515f19db51dcb7d9f | |
train_32599 | 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: 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": [
"tooling",
"tests_are_truth",
"security_gates",
"documentation"
],
"moe_experts": [
"evaluation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 7761a4d129a2b1fb9c6c82b149c34c764f24b0de |
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