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_02400 | 2026-01-01T00:00:00 | SWE-bench style real-repo evaluation | patch_diff | expert | Task: patch_diff
Topic: SWE-bench style real-repo evaluation
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.
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": [
"repo_scale_reasoning",
"reproducibility",
"cost_latency_tradeoffs",
"evaluation_metrics"
],
"moe_experts": [
"coding_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | ae8c3874f1ee653a3d5475933dc1979bef5bd254 | |
train_02401 | 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: C#
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
| [] | {
"target_language": "C#",
"developer_needs": [
"tests_are_truth",
"ci_integration",
"governance",
"documentation"
],
"moe_experts": [
"security_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 62448bb0a73dda026db2da8d1bc83835bf847385 | |
train_02402 | 2026-01-01T00:00:00 | Extended context and repo-scale understanding | code | expert | Task: code
Topic: Extended context and repo-scale understanding
Difficulty: expert
Target language: SQL
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
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",
"auditability",
"tooling"
],
"moe_experts": [
"agentic_systems_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | a274516671dafe2f7f0aceb304fa78c960bd2603 | |
train_02403 | 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: Bash
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "Bash",
"developer_needs": [
"tooling",
"ci_integration",
"repo_scale_reasoning",
"reproducibility"
],
"moe_experts": [
"evaluation_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | f83e466f624fd04ba57f76df2875004ec58c3b54 | |
train_02404 | 2026-01-01T00:00:00 | Agentic coding systems (plan→edit→test→reflect) | explain | advanced | Task: explain
Topic: Agentic coding systems (plan→edit→test→reflect)
Difficulty: advanced
Target language: Python
Context: 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": "Python",
"developer_needs": [
"cost_latency_tradeoffs",
"tests_are_truth",
"auditability",
"evaluation_metrics"
],
"moe_experts": [
"governance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 02295434d1b40aaa5926a714c8b03a9de9f9d275 | |
train_02405 | 2026-01-01T00:00:00 | Self-improving agents and feedback loops | compare | intermediate | Task: compare
Topic: Self-improving agents and feedback loops
Difficulty: intermediate
Target language: 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.
Compare: capability, cost, latency, reliability
| [] | {
"target_language": "Java",
"developer_needs": [
"reproducibility",
"repo_scale_reasoning",
"tooling",
"cost_latency_tradeoffs"
],
"moe_experts": [
"evaluation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | e0ff4795f0223e2da8fc18daf5cf84a9f122e26d | |
train_02406 | 2026-01-01T00:00:00 | Dataset curation pipelines (filter, dedupe, quality) | eval | advanced | Task: eval
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: advanced
Target language: Rust
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
| [] | {
"target_language": "Rust",
"developer_needs": [
"governance",
"evaluation_metrics",
"tooling",
"documentation"
],
"moe_experts": [
"coding_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | c0f91f48a23eab920ab1d3a31b49bf9a2c98ce37 | |
train_02407 | 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: 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.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
| [] | {
"target_language": "Go",
"developer_needs": [
"ci_integration",
"reproducibility",
"repo_scale_reasoning",
"security_gates"
],
"moe_experts": [
"security_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 51349b0691920d7509571fe4c86cba924d8978a2 | |
train_02408 | 2026-01-01T00:00:00 | Agentic coding systems (plan→edit→test→reflect) | review | expert | Task: review
Topic: Agentic coding systems (plan→edit→test→reflect)
Difficulty: expert
Target language: C#
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Review: correctness, security, performance, governance
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "C#",
"developer_needs": [
"cost_latency_tradeoffs",
"tests_are_truth",
"governance",
"documentation"
],
"moe_experts": [
"data_curation_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | ac94f79eb3046e7301e451d0377fddc1ad9d27d0 | |
train_02409 | 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: 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.
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": "Bash",
"developer_needs": [
"cost_latency_tradeoffs",
"tooling",
"ci_integration",
"auditability"
],
"moe_experts": [
"coding_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | b161cf7d9915cb773b5f0e40b5f2e38a0607c12d | |
train_02410 | 2026-01-01T00:00:00 | Code-specialized model families and sizing tradeoffs | eval | expert | Task: eval
Topic: Code-specialized model families and sizing tradeoffs
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.
Eval:
pass@k, time-to-green, regressions, diff size
| [] | {
"target_language": "Rust",
"developer_needs": [
"repo_scale_reasoning",
"governance",
"evaluation_metrics",
"tooling"
],
"moe_experts": [
"security_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 304db5a7c62fe821b5d309dd872b4247ee70fc25 | |
train_02411 | 2026-01-01T00:00:00 | Reasoning-first coding models and tunable deliberation | agent_loop | advanced | Task: agent_loop
Topic: Reasoning-first coding models and tunable deliberation
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.
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",
"evaluation_metrics",
"reproducibility",
"tooling"
],
"moe_experts": [
"evaluation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | dd1b1c59bfb8e18fc5cb0300fa461d3c936e593f | |
train_02412 | 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: 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.
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": "JavaScript",
"developer_needs": [
"ci_integration",
"security_gates",
"auditability",
"reproducibility"
],
"moe_experts": [
"performance_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 82061c3b512ad5604af7185008ed8b85cfe7e12e | |
train_02413 | 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: TypeScript
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
| [] | {
"target_language": "TypeScript",
"developer_needs": [
"reproducibility",
"security_gates",
"governance",
"ci_integration"
],
"moe_experts": [
"performance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 16d040084b72b37b8ef8346d68f13ab7ba27fffe | |
train_02414 | 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: SQL
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Review: correctness, security, performance, governance
| [] | {
"target_language": "SQL",
"developer_needs": [
"security_gates",
"tests_are_truth",
"tooling",
"repo_scale_reasoning"
],
"moe_experts": [
"agentic_systems_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | d7cd44bc799f19f35b5b64b418fb4b1857c4adbd | |
train_02415 | 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: Python
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Python",
"developer_needs": [
"tests_are_truth",
"auditability",
"repo_scale_reasoning",
"cost_latency_tradeoffs"
],
"moe_experts": [
"evaluation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 8d33947143dfd6263b379d7c2a41f89ffdd89fd0 | |
train_02416 | 2026-01-01T00:00:00 | Model merging, distillation, and continued pretraining | design | advanced | Task: design
Topic: Model merging, distillation, and continued pretraining
Difficulty: advanced
Target language: Go
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "Go",
"developer_needs": [
"auditability",
"reproducibility",
"security_gates",
"tests_are_truth"
],
"moe_experts": [
"performance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 0a81e247249f0ee46319f36b4b4d6d8b153c0e0a | |
train_02417 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | compare | expert | Task: compare
Topic: Latency, cost, and reliability optimization
Difficulty: expert
Target language: Rust
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
| [] | {
"target_language": "Rust",
"developer_needs": [
"documentation",
"auditability",
"tests_are_truth",
"evaluation_metrics"
],
"moe_experts": [
"evaluation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 6a9a21e3c98faa030eacbf1104e13cad187b2e26 | |
train_02418 | 2026-01-01T00:00:00 | Mixture-of-Experts (MoE) for code | agent_loop | expert | Task: agent_loop
Topic: Mixture-of-Experts (MoE) for code
Difficulty: expert
Target language: Go
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Go",
"developer_needs": [
"governance",
"auditability",
"ci_integration",
"documentation"
],
"moe_experts": [
"governance_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | e04c4e3042c851f1f11eb4f2aa1b1c974799982a | |
train_02419 | 2026-01-01T00:00:00 | Mixture-of-Experts (MoE) for code | design | expert | Task: design
Topic: Mixture-of-Experts (MoE) for code
Difficulty: expert
Target language: Python
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "Python",
"developer_needs": [
"governance",
"cost_latency_tradeoffs",
"documentation",
"auditability"
],
"moe_experts": [
"governance_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 580a39b7191b2df3db058658581bf7336bc18ef4 | |
train_02420 | 2026-01-01T00:00:00 | Governance, provenance, and licensing for code data | code | advanced | Task: code
Topic: Governance, provenance, and licensing for code data
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": [
"reproducibility",
"security_gates",
"evaluation_metrics",
"governance"
],
"moe_experts": [
"performance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 070d2bfd797815af888d4c0f835bb62bafb4434c | |
train_02421 | 2026-01-01T00:00:00 | Mixture-of-Experts (MoE) for code | design | expert | Task: design
Topic: Mixture-of-Experts (MoE) for code
Difficulty: expert
Target language: Rust
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "Rust",
"developer_needs": [
"cost_latency_tradeoffs",
"documentation",
"tooling",
"evaluation_metrics"
],
"moe_experts": [
"coding_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 7393d04495d22eaf9e4359066035d3c5a2ca6763 | |
train_02422 | 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: 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.
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": [
"auditability",
"reproducibility",
"repo_scale_reasoning",
"security_gates"
],
"moe_experts": [
"agentic_systems_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | ac1f9abdf028f35042561f4c553d8c657d480bd3 | |
train_02423 | 2026-01-01T00:00:00 | SWE-bench style real-repo evaluation | explain | expert | Task: explain
Topic: SWE-bench style real-repo evaluation
Difficulty: expert
Target language: Bash
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "Bash",
"developer_needs": [
"cost_latency_tradeoffs",
"repo_scale_reasoning",
"governance",
"evaluation_metrics"
],
"moe_experts": [
"data_curation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 21df9a7600330da9ef888552dbc0e59e0d38acca | |
train_02424 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | eval | intermediate | Task: eval
Topic: Latency, cost, and reliability optimization
Difficulty: intermediate
Target language: Go
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
| [] | {
"target_language": "Go",
"developer_needs": [
"tests_are_truth",
"ci_integration",
"evaluation_metrics",
"reproducibility"
],
"moe_experts": [
"data_curation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 07a69f61710db9e665370538306ea6ae62220b31 | |
train_02425 | 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: 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": [
"documentation",
"repo_scale_reasoning",
"tooling",
"evaluation_metrics"
],
"moe_experts": [
"security_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 80585e1fae64fbd10d5a35186163d8ebe9af4018 | |
train_02426 | 2026-01-01T00:00:00 | Agentic coding systems (plan→edit→test→reflect) | data_pipeline | expert | Task: data_pipeline
Topic: Agentic coding systems (plan→edit→test→reflect)
Difficulty: expert
Target language: Rust
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Rust",
"developer_needs": [
"security_gates",
"cost_latency_tradeoffs",
"governance",
"tooling"
],
"moe_experts": [
"security_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | f28437e797ddebe867b3d920a94dea8829b1fac0 | |
train_02427 | 2026-01-01T00:00:00 | Model merging, distillation, and continued pretraining | explain | intermediate | Task: explain
Topic: Model merging, distillation, and continued pretraining
Difficulty: intermediate
Target language: Rust
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "Rust",
"developer_needs": [
"auditability",
"cost_latency_tradeoffs",
"reproducibility",
"security_gates"
],
"moe_experts": [
"security_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | ce69a1bb940fe885194ab96fd71dbd4135030ea3 | |
train_02428 | 2026-01-01T00:00:00 | Model merging, distillation, and continued pretraining | compare | expert | Task: compare
Topic: Model merging, distillation, and continued pretraining
Difficulty: expert
Target language: SQL
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "SQL",
"developer_needs": [
"cost_latency_tradeoffs",
"auditability",
"governance",
"tooling"
],
"moe_experts": [
"evaluation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | f7d056e11c1c09ce2e6c2e445aca2fe6705484ed | |
train_02429 | 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: Bash
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "Bash",
"developer_needs": [
"auditability",
"documentation",
"tests_are_truth",
"repo_scale_reasoning"
],
"moe_experts": [
"data_curation_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | cb1cf62ce85b77364d632fcef9fe9a3712c674a5 | |
train_02430 | 2026-01-01T00:00:00 | Dataset curation pipelines (filter, dedupe, quality) | data_pipeline | intermediate | Task: data_pipeline
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: intermediate
Target language: SQL
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "SQL",
"developer_needs": [
"repo_scale_reasoning",
"documentation",
"security_gates",
"auditability"
],
"moe_experts": [
"security_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 6635da64d705e88321c1feb952cc5a8c24151dc8 | |
train_02431 | 2026-01-01T00:00:00 | Multimodal dev workflows (docs, diagrams, traces) | patch_diff | advanced | Task: patch_diff
Topic: Multimodal dev workflows (docs, diagrams, traces)
Difficulty: advanced
Target language: TypeScript
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Patch (diff-style):
```diff
- if x == 0:
- return 1/x
+ if x == 0:
+ raise ValueError('division by zero')
```
Acceptance:
- Tests pass
- No new regressions
| [] | {
"target_language": "TypeScript",
"developer_needs": [
"documentation",
"tests_are_truth",
"auditability",
"ci_integration"
],
"moe_experts": [
"evaluation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | bca70ad3e009fad7bac664144322f060d5561bd7 | |
train_02432 | 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: 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.
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": [
"cost_latency_tradeoffs",
"tests_are_truth",
"ci_integration",
"documentation"
],
"moe_experts": [
"security_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 4cefdcdb4419b5762bb410dbf4893f24ba6301ff | |
train_02433 | 2026-01-01T00:00:00 | Secure code generation and policy gates | data_pipeline | intermediate | Task: data_pipeline
Topic: Secure code generation and policy gates
Difficulty: intermediate
Target language: 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.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
| [] | {
"target_language": "Java",
"developer_needs": [
"tests_are_truth",
"governance",
"tooling",
"documentation"
],
"moe_experts": [
"performance_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | e6544cad276c07e214ed4d1eceda9b4597e294b8 | |
train_02434 | 2026-01-01T00:00:00 | Code-specialized model families and sizing tradeoffs | design | advanced | Task: design
Topic: Code-specialized model families and sizing tradeoffs
Difficulty: advanced
Target language: Python
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Python",
"developer_needs": [
"tests_are_truth",
"documentation",
"ci_integration",
"tooling"
],
"moe_experts": [
"security_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | fd06a59dc9445b512857c9e9922c05f57f984205 | |
train_02435 | 2026-01-01T00:00:00 | Code-specialized model families and sizing tradeoffs | review | advanced | Task: review
Topic: Code-specialized model families and sizing tradeoffs
Difficulty: advanced
Target language: Bash
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Review: correctness, security, performance, governance
| [] | {
"target_language": "Bash",
"developer_needs": [
"evaluation_metrics",
"tests_are_truth",
"governance",
"reproducibility"
],
"moe_experts": [
"performance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | c0cee180d601c2951f056633f30a4f527efb9f84 | |
train_02436 | 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: Bash
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "Bash",
"developer_needs": [
"ci_integration",
"evaluation_metrics",
"security_gates",
"tooling"
],
"moe_experts": [
"data_curation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 15c8edc47de1af67786ebc80e5896d3bfa833d6b | |
train_02437 | 2026-01-01T00:00:00 | Code-specialized model families and sizing tradeoffs | eval | expert | Task: eval
Topic: Code-specialized model families and sizing tradeoffs
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.
Eval:
pass@k, time-to-green, regressions, diff size
| [] | {
"target_language": "TypeScript",
"developer_needs": [
"ci_integration",
"reproducibility",
"documentation",
"tooling"
],
"moe_experts": [
"agentic_systems_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | e84100486f020f94ac48f7de64e4933af1a8d498 | |
train_02438 | 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: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "SQL",
"developer_needs": [
"auditability",
"tooling",
"evaluation_metrics",
"cost_latency_tradeoffs"
],
"moe_experts": [
"governance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 0544610cc00d2c14fee43b7935985133ec9d95e1 | |
train_02439 | 2026-01-01T00:00:00 | Self-improving agents and feedback loops | eval | intermediate | Task: eval
Topic: Self-improving agents and feedback loops
Difficulty: intermediate
Target language: Java
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Java",
"developer_needs": [
"tooling",
"governance",
"reproducibility",
"documentation"
],
"moe_experts": [
"evaluation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 443f6380179dfd9531445d373e9083c099b2e0fb | |
train_02440 | 2026-01-01T00:00:00 | Tool calling, sandboxes, and CI integration | compare | expert | Task: compare
Topic: Tool calling, sandboxes, and CI integration
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
| [] | {
"target_language": "Bash",
"developer_needs": [
"auditability",
"evaluation_metrics",
"governance",
"security_gates"
],
"moe_experts": [
"agentic_systems_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | f4e3429065e2e69c9941698710fd0b3ec62f16a9 | |
train_02441 | 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: 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
| [] | {
"target_language": "SQL",
"developer_needs": [
"reproducibility",
"security_gates",
"evaluation_metrics",
"ci_integration"
],
"moe_experts": [
"security_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 79ede69ca9491332e393f7596172cce91984d246 | |
train_02442 | 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: Bash
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Bash",
"developer_needs": [
"ci_integration",
"tests_are_truth",
"documentation",
"repo_scale_reasoning"
],
"moe_experts": [
"evaluation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | acd7b86a52636c005097a4701bddb86785577779 | |
train_02443 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | patch_diff | advanced | Task: patch_diff
Topic: Latency, cost, and reliability optimization
Difficulty: advanced
Target language: 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.
Patch (diff-style):
```diff
- if x == 0:
- return 1/x
+ if x == 0:
+ raise ValueError('division by zero')
```
Acceptance:
- Tests pass
- No new regressions
| [] | {
"target_language": "Java",
"developer_needs": [
"documentation",
"cost_latency_tradeoffs",
"tests_are_truth",
"ci_integration"
],
"moe_experts": [
"governance_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 7aef68c7955ba40edc5ebe963460f3da50e2164b | |
train_02444 | 2026-01-01T00:00:00 | Reasoning-first coding models and tunable deliberation | design | intermediate | Task: design
Topic: Reasoning-first coding models and tunable deliberation
Difficulty: intermediate
Target language: 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": [
"cost_latency_tradeoffs",
"reproducibility",
"auditability",
"security_gates"
],
"moe_experts": [
"governance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 86af4a5a31302810dabbf1502551bc18391c7b9e | |
train_02445 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | design | expert | Task: design
Topic: Latency, cost, and reliability optimization
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.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "SQL",
"developer_needs": [
"reproducibility",
"ci_integration",
"security_gates",
"tooling"
],
"moe_experts": [
"agentic_systems_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | bf8e3d344cca7cdbebdb35ccc218f5a068de4e32 | |
train_02446 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | failure_analysis | advanced | Task: failure_analysis
Topic: Latency, cost, and reliability optimization
Difficulty: advanced
Target language: 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
| [] | {
"target_language": "Rust",
"developer_needs": [
"tests_are_truth",
"governance",
"tooling",
"auditability"
],
"moe_experts": [
"security_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | aeac8e982f9737db89781ef1fe36cdc0afacc692 | |
train_02447 | 2026-01-01T00:00:00 | Governance, provenance, and licensing for code data | review | advanced | Task: review
Topic: Governance, provenance, and licensing for code data
Difficulty: advanced
Target language: JavaScript
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Review: correctness, security, performance, governance
| [] | {
"target_language": "JavaScript",
"developer_needs": [
"documentation",
"tooling",
"security_gates",
"ci_integration"
],
"moe_experts": [
"governance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 85380657f7568c1a33d2778b05ebc0fe3f0b4efd | |
train_02448 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | code | intermediate | Task: code
Topic: Latency, cost, and reliability optimization
Difficulty: intermediate
Target language: Bash
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "Bash",
"developer_needs": [
"auditability",
"security_gates",
"repo_scale_reasoning",
"tests_are_truth"
],
"moe_experts": [
"data_curation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 1356476f063ba9efb9971401c566e348b2a7ccd7 | |
train_02449 | 2026-01-01T00:00:00 | Agentic coding systems (plan→edit→test→reflect) | design | expert | Task: design
Topic: Agentic coding systems (plan→edit→test→reflect)
Difficulty: expert
Target language: Python
Context: 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": "Python",
"developer_needs": [
"documentation",
"ci_integration",
"reproducibility",
"evaluation_metrics"
],
"moe_experts": [
"data_curation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | fb0accc78c6ff598d18f8ac0fad84e2b336753d2 | |
train_02450 | 2026-01-01T00:00:00 | Self-improving agents and feedback loops | code | expert | Task: code
Topic: Self-improving agents and feedback loops
Difficulty: expert
Target language: JavaScript
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "JavaScript",
"developer_needs": [
"evaluation_metrics",
"documentation",
"security_gates",
"tests_are_truth"
],
"moe_experts": [
"coding_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 9c64c29f0fa38ad291684e0fbb4f6e4dcea6a134 | |
train_02451 | 2026-01-01T00:00:00 | Secure code generation and policy gates | review | intermediate | Task: review
Topic: Secure code generation and policy gates
Difficulty: intermediate
Target language: 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": [
"cost_latency_tradeoffs",
"tooling",
"security_gates",
"documentation"
],
"moe_experts": [
"coding_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | c60a044fa4bbd720e897a0644dee29baf1e9b6c9 | |
train_02452 | 2026-01-01T00:00:00 | Secure code generation and policy gates | data_pipeline | intermediate | Task: data_pipeline
Topic: Secure code generation and policy gates
Difficulty: intermediate
Target language: Python
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Python",
"developer_needs": [
"auditability",
"reproducibility",
"evaluation_metrics",
"governance"
],
"moe_experts": [
"security_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | c66a291fa24bb3cd0239ccfd321f38cbe3b7cd0d | |
train_02453 | 2026-01-01T00:00:00 | Self-improving agents and feedback loops | agent_loop | intermediate | Task: agent_loop
Topic: Self-improving agents and feedback loops
Difficulty: intermediate
Target language: Java
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
| [] | {
"target_language": "Java",
"developer_needs": [
"tests_are_truth",
"documentation",
"cost_latency_tradeoffs",
"evaluation_metrics"
],
"moe_experts": [
"performance_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 03a7d73d54f482814c12d7f363e46c22801fe4d9 | |
train_02454 | 2026-01-01T00:00:00 | SWE-bench style real-repo evaluation | patch_diff | intermediate | Task: patch_diff
Topic: SWE-bench style real-repo evaluation
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.
Patch (diff-style):
```diff
- if x == 0:
- return 1/x
+ if x == 0:
+ raise ValueError('division by zero')
```
Acceptance:
- Tests pass
- No new regressions
| [] | {
"target_language": "TypeScript",
"developer_needs": [
"governance",
"reproducibility",
"ci_integration",
"security_gates"
],
"moe_experts": [
"security_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 3125d830fc2079ea4a3ca2e565e863bfbd2d14f9 | |
train_02455 | 2026-01-01T00:00:00 | Dataset curation pipelines (filter, dedupe, quality) | explain | expert | Task: explain
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: expert
Target language: Rust
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Rust",
"developer_needs": [
"documentation",
"evaluation_metrics",
"cost_latency_tradeoffs",
"repo_scale_reasoning"
],
"moe_experts": [
"performance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | d4ee6163e373b8c9d857c0eba9eb49912bd83f6c | |
train_02456 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | explain | intermediate | Task: explain
Topic: Latency, cost, and reliability optimization
Difficulty: intermediate
Target language: Bash
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "Bash",
"developer_needs": [
"reproducibility",
"documentation",
"ci_integration",
"cost_latency_tradeoffs"
],
"moe_experts": [
"agentic_systems_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 3d8816e55b59eea212fc76b148a63e11d73795b0 | |
train_02457 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | failure_analysis | expert | Task: failure_analysis
Topic: Latency, cost, and reliability optimization
Difficulty: expert
Target language: Bash
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
| [] | {
"target_language": "Bash",
"developer_needs": [
"cost_latency_tradeoffs",
"governance",
"evaluation_metrics",
"security_gates"
],
"moe_experts": [
"evaluation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 323e1a854fb79d0baa0aefdff67bcf80fb93a954 | |
train_02458 | 2026-01-01T00:00:00 | Multimodal dev workflows (docs, diagrams, traces) | review | advanced | Task: review
Topic: Multimodal dev workflows (docs, diagrams, traces)
Difficulty: advanced
Target language: SQL
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Review: correctness, security, performance, governance
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "SQL",
"developer_needs": [
"ci_integration",
"cost_latency_tradeoffs",
"repo_scale_reasoning",
"evaluation_metrics"
],
"moe_experts": [
"evaluation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 25c044c4b7412ae57af73a9bd74653ba918ef589 | |
train_02459 | 2026-01-01T00:00:00 | Agentic coding systems (plan→edit→test→reflect) | code | intermediate | Task: code
Topic: Agentic coding systems (plan→edit→test→reflect)
Difficulty: intermediate
Target language: 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.
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": [
"repo_scale_reasoning",
"documentation",
"ci_integration",
"evaluation_metrics"
],
"moe_experts": [
"performance_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 672e9f4a5f927846dc1669585d9676175bc8aebf | |
train_02460 | 2026-01-01T00:00:00 | Tool calling, sandboxes, and CI integration | explain | expert | Task: explain
Topic: Tool calling, sandboxes, and CI integration
Difficulty: expert
Target language: 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": [
"evaluation_metrics",
"reproducibility",
"auditability",
"security_gates"
],
"moe_experts": [
"governance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | d57c209086fe0555d3042dc1f26a58a4ad91ee49 | |
train_02461 | 2026-01-01T00:00:00 | Tool calling, sandboxes, and CI integration | compare | intermediate | Task: compare
Topic: Tool calling, sandboxes, and CI integration
Difficulty: intermediate
Target language: 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.
Compare: capability, cost, latency, reliability
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Java",
"developer_needs": [
"tooling",
"repo_scale_reasoning",
"reproducibility",
"cost_latency_tradeoffs"
],
"moe_experts": [
"security_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 4a483e6afdecdb4de5934f43ceb68749eeec3350 | |
train_02462 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | review | intermediate | Task: review
Topic: Latency, cost, and reliability optimization
Difficulty: intermediate
Target language: TypeScript
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Review: correctness, security, performance, governance
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "TypeScript",
"developer_needs": [
"governance",
"documentation",
"security_gates",
"repo_scale_reasoning"
],
"moe_experts": [
"coding_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 17d2e9262759c5ccb65082fca2317f221296dadc | |
train_02463 | 2026-01-01T00:00:00 | Multimodal dev workflows (docs, diagrams, traces) | review | expert | Task: review
Topic: Multimodal dev workflows (docs, diagrams, traces)
Difficulty: expert
Target language: Go
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Review: correctness, security, performance, governance
| [] | {
"target_language": "Go",
"developer_needs": [
"reproducibility",
"tests_are_truth",
"cost_latency_tradeoffs",
"repo_scale_reasoning"
],
"moe_experts": [
"coding_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 2851264525351f589538d1ab6ad1d843f12b06b4 | |
train_02464 | 2026-01-01T00:00:00 | Model merging, distillation, and continued pretraining | data_pipeline | expert | Task: data_pipeline
Topic: Model merging, distillation, and continued pretraining
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.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
| [] | {
"target_language": "C#",
"developer_needs": [
"documentation",
"ci_integration",
"reproducibility",
"tooling"
],
"moe_experts": [
"performance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 5536d4d4942da67d7157304409c447ed682fac72 | |
train_02465 | 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: 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
| [] | {
"target_language": "Go",
"developer_needs": [
"tooling",
"governance",
"tests_are_truth",
"auditability"
],
"moe_experts": [
"evaluation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 494a02624d179f9c3da3852a5817131860892f44 | |
train_02466 | 2026-01-01T00:00:00 | Agentic coding systems (plan→edit→test→reflect) | compare | advanced | Task: compare
Topic: Agentic coding systems (plan→edit→test→reflect)
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.
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": [
"tooling",
"auditability",
"repo_scale_reasoning",
"reproducibility"
],
"moe_experts": [
"data_curation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 6219950162418951b7aa8033705cbf8855baf72e | |
train_02467 | 2026-01-01T00:00:00 | Agentic coding systems (plan→edit→test→reflect) | failure_analysis | expert | Task: failure_analysis
Topic: Agentic coding systems (plan→edit→test→reflect)
Difficulty: expert
Target language: 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": [
"ci_integration",
"reproducibility",
"tooling",
"evaluation_metrics"
],
"moe_experts": [
"security_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 5ac3aedc2d2c5f9b2bd9286e7f8fb7e0792c1182 | |
train_02468 | 2026-01-01T00:00:00 | Multimodal dev workflows (docs, diagrams, traces) | eval | advanced | Task: eval
Topic: Multimodal dev workflows (docs, diagrams, traces)
Difficulty: advanced
Target language: Java
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
| [] | {
"target_language": "Java",
"developer_needs": [
"cost_latency_tradeoffs",
"auditability",
"ci_integration",
"tooling"
],
"moe_experts": [
"security_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 4fb8495eda994adfc6ad25ec603bb29b2d5cc551 | |
train_02469 | 2026-01-01T00:00:00 | Reasoning-first coding models and tunable deliberation | eval | intermediate | Task: eval
Topic: Reasoning-first coding models and tunable deliberation
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.
Eval:
pass@k, time-to-green, regressions, diff size
| [] | {
"target_language": "Rust",
"developer_needs": [
"tests_are_truth",
"repo_scale_reasoning",
"cost_latency_tradeoffs",
"tooling"
],
"moe_experts": [
"data_curation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | da672554539ba693659911120c9f2accd6abb711 | |
train_02470 | 2026-01-01T00:00:00 | Dataset curation pipelines (filter, dedupe, quality) | eval | intermediate | Task: eval
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: intermediate
Target language: Go
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Go",
"developer_needs": [
"cost_latency_tradeoffs",
"documentation",
"tests_are_truth",
"security_gates"
],
"moe_experts": [
"data_curation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | bb81b9103dda8bf6c1fe0eec4ed5bbd297e070ac | |
train_02471 | 2026-01-01T00:00:00 | Mixture-of-Experts (MoE) for code | failure_analysis | intermediate | Task: failure_analysis
Topic: Mixture-of-Experts (MoE) for code
Difficulty: intermediate
Target language: JavaScript
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
| [] | {
"target_language": "JavaScript",
"developer_needs": [
"governance",
"documentation",
"cost_latency_tradeoffs",
"tests_are_truth"
],
"moe_experts": [
"data_curation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | e1786aa9b99a8a2e5c65405e47f50da8ec5a4310 | |
train_02472 | 2026-01-01T00:00:00 | Code-specialized model families and sizing tradeoffs | review | advanced | Task: review
Topic: Code-specialized model families and sizing tradeoffs
Difficulty: advanced
Target language: C#
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Review: correctness, security, performance, governance
| [] | {
"target_language": "C#",
"developer_needs": [
"evaluation_metrics",
"governance",
"security_gates",
"documentation"
],
"moe_experts": [
"governance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | dcf7c65073ef3773f0942de01ff4d9080987c9e6 | |
train_02473 | 2026-01-01T00:00:00 | Code-specialized model families and sizing tradeoffs | design | expert | Task: design
Topic: Code-specialized model families and sizing tradeoffs
Difficulty: expert
Target language: Python
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "Python",
"developer_needs": [
"tests_are_truth",
"evaluation_metrics",
"auditability",
"tooling"
],
"moe_experts": [
"agentic_systems_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 9ed3ea60f58c07f6f70f7589b444c74225fb5eef | |
train_02474 | 2026-01-01T00:00:00 | Reasoning-first coding models and tunable deliberation | design | intermediate | Task: design
Topic: Reasoning-first coding models and tunable deliberation
Difficulty: intermediate
Target language: JavaScript
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "JavaScript",
"developer_needs": [
"governance",
"auditability",
"ci_integration",
"evaluation_metrics"
],
"moe_experts": [
"governance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 8e527d000a086397788c091682f1618527c8bfbc | |
train_02475 | 2026-01-01T00:00:00 | SWE-bench style real-repo evaluation | patch_diff | advanced | Task: patch_diff
Topic: SWE-bench style real-repo evaluation
Difficulty: advanced
Target language: 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": [
"evaluation_metrics",
"tooling",
"security_gates",
"auditability"
],
"moe_experts": [
"security_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | f1055eba9ad97437efd936a4212791b98883d0a4 | |
train_02476 | 2026-01-01T00:00:00 | Multimodal dev workflows (docs, diagrams, traces) | compare | expert | Task: compare
Topic: Multimodal dev workflows (docs, diagrams, traces)
Difficulty: expert
Target language: TypeScript
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "TypeScript",
"developer_needs": [
"evaluation_metrics",
"tooling",
"security_gates",
"documentation"
],
"moe_experts": [
"performance_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | c522f5a77cc750786632dcfd3f6699df2f48fc31 | |
train_02477 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | review | intermediate | Task: review
Topic: Latency, cost, and reliability optimization
Difficulty: intermediate
Target language: JavaScript
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Review: correctness, security, performance, governance
| [] | {
"target_language": "JavaScript",
"developer_needs": [
"governance",
"repo_scale_reasoning",
"documentation",
"auditability"
],
"moe_experts": [
"data_curation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | cf47df14523fc4fc0c8ee625898d0f15274fb1e6 | |
train_02478 | 2026-01-01T00:00:00 | Dataset curation pipelines (filter, dedupe, quality) | design | advanced | Task: design
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: advanced
Target language: Bash
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "Bash",
"developer_needs": [
"security_gates",
"reproducibility",
"documentation",
"tooling"
],
"moe_experts": [
"coding_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 65bfe6efd5103dcddecc918bd7763b9b86c4c3fc | |
train_02479 | 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: 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
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "TypeScript",
"developer_needs": [
"auditability",
"ci_integration",
"tests_are_truth",
"repo_scale_reasoning"
],
"moe_experts": [
"evaluation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | e741f1662246ce3e762af07dc2fafce91ac8e2b4 | |
train_02480 | 2026-01-01T00:00:00 | Governance, provenance, and licensing for code data | eval | expert | Task: eval
Topic: Governance, provenance, and licensing for code data
Difficulty: expert
Target language: TypeScript
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
| [] | {
"target_language": "TypeScript",
"developer_needs": [
"repo_scale_reasoning",
"cost_latency_tradeoffs",
"documentation",
"auditability"
],
"moe_experts": [
"governance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 1b6b6bc53168ace5ec085c2ee979d660afcf0c69 | |
train_02481 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | data_pipeline | advanced | Task: data_pipeline
Topic: Latency, cost, and reliability optimization
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
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Python",
"developer_needs": [
"evaluation_metrics",
"governance",
"reproducibility",
"tests_are_truth"
],
"moe_experts": [
"coding_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 102b6daf77804c346fc7f161d82504ec3f027511 | |
train_02482 | 2026-01-01T00:00:00 | Mixture-of-Experts (MoE) for code | patch_diff | intermediate | Task: patch_diff
Topic: Mixture-of-Experts (MoE) for code
Difficulty: intermediate
Target language: 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.
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": [
"evaluation_metrics",
"auditability",
"tooling",
"reproducibility"
],
"moe_experts": [
"security_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 007042f515a3ddf82139884b1a32df200c0f0ae1 | |
train_02483 | 2026-01-01T00:00:00 | Code-specialized model families and sizing tradeoffs | agent_loop | expert | Task: agent_loop
Topic: Code-specialized model families and sizing tradeoffs
Difficulty: expert
Target language: TypeScript
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
| [] | {
"target_language": "TypeScript",
"developer_needs": [
"repo_scale_reasoning",
"tooling",
"evaluation_metrics",
"security_gates"
],
"moe_experts": [
"performance_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | d6053af3a6aad0f26a851e245b7a1d7e957f16f6 | |
train_02484 | 2026-01-01T00:00:00 | Multimodal dev workflows (docs, diagrams, traces) | compare | intermediate | Task: compare
Topic: Multimodal dev workflows (docs, diagrams, traces)
Difficulty: intermediate
Target language: 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.
Compare: capability, cost, latency, reliability
| [] | {
"target_language": "Rust",
"developer_needs": [
"reproducibility",
"tests_are_truth",
"repo_scale_reasoning",
"tooling"
],
"moe_experts": [
"evaluation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 53cffc2f29065bfd0992927ad22579fd2e63f0cd | |
train_02485 | 2026-01-01T00:00:00 | Multimodal dev workflows (docs, diagrams, traces) | agent_loop | expert | Task: agent_loop
Topic: Multimodal dev workflows (docs, diagrams, traces)
Difficulty: expert
Target language: Go
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
| [] | {
"target_language": "Go",
"developer_needs": [
"security_gates",
"cost_latency_tradeoffs",
"documentation",
"auditability"
],
"moe_experts": [
"coding_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 41f29ddd86a3147e3022b14f328be81de744945a | |
train_02486 | 2026-01-01T00:00:00 | SWE-bench style real-repo evaluation | design | expert | Task: design
Topic: SWE-bench style real-repo evaluation
Difficulty: expert
Target language: JavaScript
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "JavaScript",
"developer_needs": [
"tooling",
"repo_scale_reasoning",
"cost_latency_tradeoffs",
"reproducibility"
],
"moe_experts": [
"governance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 29b021e0fdbf7b15864382b1729991b26484f94a | |
train_02487 | 2026-01-01T00:00:00 | Dataset curation pipelines (filter, dedupe, quality) | compare | expert | Task: compare
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: expert
Target language: 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.
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": [
"tests_are_truth",
"tooling",
"auditability",
"documentation"
],
"moe_experts": [
"security_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 16f642c4804837577fc607d942cf0428fdf85643 | |
train_02488 | 2026-01-01T00:00:00 | Secure code generation and policy gates | compare | intermediate | Task: compare
Topic: Secure code generation and policy gates
Difficulty: intermediate
Target language: SQL
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
| [] | {
"target_language": "SQL",
"developer_needs": [
"security_gates",
"ci_integration",
"tooling",
"documentation"
],
"moe_experts": [
"agentic_systems_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 8d99606b0cb9adf70735f0f29f668326f324febf | |
train_02489 | 2026-01-01T00:00:00 | Code-specialized model families and sizing tradeoffs | code | intermediate | Task: code
Topic: Code-specialized model families and sizing tradeoffs
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.
Design with risks, metrics, acceptance criteria
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "TypeScript",
"developer_needs": [
"reproducibility",
"ci_integration",
"evaluation_metrics",
"cost_latency_tradeoffs"
],
"moe_experts": [
"security_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | b894a80931d30687b7a5c050b5947a83f2c8feca | |
train_02490 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | design | intermediate | Task: design
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.
Design with risks, metrics, acceptance criteria
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "TypeScript",
"developer_needs": [
"auditability",
"security_gates",
"tests_are_truth",
"cost_latency_tradeoffs"
],
"moe_experts": [
"performance_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 305ab2356b5ecfaf2a798c8107c0dd075366bf08 | |
train_02491 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | review | intermediate | Task: review
Topic: Latency, cost, and reliability optimization
Difficulty: intermediate
Target language: SQL
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Review: correctness, security, performance, governance
| [] | {
"target_language": "SQL",
"developer_needs": [
"reproducibility",
"tooling",
"evaluation_metrics",
"tests_are_truth"
],
"moe_experts": [
"data_curation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 0fa6322716f4bada2d48159626da4f077f3f9e7b | |
train_02492 | 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: Go
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "Go",
"developer_needs": [
"tooling",
"repo_scale_reasoning",
"evaluation_metrics",
"tests_are_truth"
],
"moe_experts": [
"security_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | db27318f5603c7ebf1e3605ab1fe3ec5ec8549da | |
train_02493 | 2026-01-01T00:00:00 | Agentic coding systems (plan→edit→test→reflect) | compare | expert | Task: compare
Topic: Agentic coding systems (plan→edit→test→reflect)
Difficulty: expert
Target language: 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.
Compare: capability, cost, latency, reliability
| [] | {
"target_language": "Python",
"developer_needs": [
"auditability",
"documentation",
"reproducibility",
"repo_scale_reasoning"
],
"moe_experts": [
"performance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | bb08ec9fbc2e660b779b219ccdef22b1e03d83ff | |
train_02494 | 2026-01-01T00:00:00 | Mixture-of-Experts (MoE) for code | agent_loop | intermediate | Task: agent_loop
Topic: Mixture-of-Experts (MoE) for code
Difficulty: intermediate
Target language: Bash
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Bash",
"developer_needs": [
"reproducibility",
"tooling",
"tests_are_truth",
"auditability"
],
"moe_experts": [
"performance_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 1e5fc722aa7151bf3688c1e75aa339c94b606d73 | |
train_02495 | 2026-01-01T00:00:00 | Governance, provenance, and licensing for code data | design | expert | Task: design
Topic: Governance, provenance, and licensing for code data
Difficulty: expert
Target language: TypeScript
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "TypeScript",
"developer_needs": [
"tests_are_truth",
"ci_integration",
"tooling",
"reproducibility"
],
"moe_experts": [
"coding_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 9f2272cf88f5e25eb300486054d70587c2164e3b | |
train_02496 | 2026-01-01T00:00:00 | Multimodal dev workflows (docs, diagrams, traces) | agent_loop | advanced | Task: agent_loop
Topic: Multimodal dev workflows (docs, diagrams, traces)
Difficulty: advanced
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.
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": [
"cost_latency_tradeoffs",
"auditability",
"ci_integration",
"tooling"
],
"moe_experts": [
"evaluation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 87cbbb13d885cd82396858f95f1328ebb0f2c20c | |
train_02497 | 2026-01-01T00:00:00 | SWE-bench style real-repo evaluation | explain | advanced | Task: explain
Topic: SWE-bench style real-repo evaluation
Difficulty: advanced
Target language: Rust
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Rust",
"developer_needs": [
"ci_integration",
"governance",
"repo_scale_reasoning",
"tooling"
],
"moe_experts": [
"performance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 53afac17f669932faded1300f904682bec59647d | |
train_02498 | 2026-01-01T00:00:00 | Dataset curation pipelines (filter, dedupe, quality) | design | advanced | Task: design
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: advanced
Target language: 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
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "SQL",
"developer_needs": [
"cost_latency_tradeoffs",
"evaluation_metrics",
"tooling",
"governance"
],
"moe_experts": [
"security_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 33b667b9666bc8d2263b173c20d3d8c71d748ad8 | |
train_02499 | 2026-01-01T00:00:00 | Multimodal dev workflows (docs, diagrams, traces) | code | intermediate | Task: code
Topic: Multimodal dev workflows (docs, diagrams, traces)
Difficulty: intermediate
Target language: Rust
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Rust",
"developer_needs": [
"ci_integration",
"tooling",
"documentation",
"reproducibility"
],
"moe_experts": [
"evaluation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 08ddaee0f4ae2db5a7058ca2f3ae0f246e45404e |
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