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_25200 | 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: 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": [
"governance",
"evaluation_metrics",
"security_gates",
"documentation"
],
"moe_experts": [
"data_curation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 25fedcb43c39d99c038d0f3bb17f6204f6ccb2fa | |
train_25201 | 2026-01-01T00:00:00 | Model merging, distillation, and continued pretraining | data_pipeline | advanced | Task: data_pipeline
Topic: Model merging, distillation, and continued pretraining
Difficulty: advanced
Target language: C#
Context: 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": "C#",
"developer_needs": [
"cost_latency_tradeoffs",
"tooling",
"tests_are_truth",
"auditability"
],
"moe_experts": [
"performance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 65d4ce49368bc0a34050524cadd631f80ce6b4d5 | |
train_25202 | 2026-01-01T00:00:00 | Agentic coding systems (plan→edit→test→reflect) | patch_diff | intermediate | Task: patch_diff
Topic: Agentic coding systems (plan→edit→test→reflect)
Difficulty: intermediate
Target language: 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": [
"evaluation_metrics",
"security_gates",
"cost_latency_tradeoffs",
"tooling"
],
"moe_experts": [
"coding_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 2ee1e0b444da60df9208d10b361605b76cc573b9 | |
train_25203 | 2026-01-01T00:00:00 | Mixture-of-Experts (MoE) for code | failure_analysis | expert | Task: failure_analysis
Topic: Mixture-of-Experts (MoE) for code
Difficulty: expert
Target language: 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
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "TypeScript",
"developer_needs": [
"security_gates",
"auditability",
"ci_integration",
"tests_are_truth"
],
"moe_experts": [
"data_curation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 5d745f842aaff0cb53bb09e8335cd46e025ae338 | |
train_25204 | 2026-01-01T00:00:00 | Model merging, distillation, and continued pretraining | agent_loop | intermediate | Task: agent_loop
Topic: Model merging, distillation, and continued pretraining
Difficulty: intermediate
Target language: JavaScript
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
| [] | {
"target_language": "JavaScript",
"developer_needs": [
"cost_latency_tradeoffs",
"reproducibility",
"repo_scale_reasoning",
"security_gates"
],
"moe_experts": [
"coding_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 9e43dfccee5e212289090c26e78a16685ff34286 | |
train_25205 | 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: Python
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
| [] | {
"target_language": "Python",
"developer_needs": [
"tooling",
"security_gates",
"repo_scale_reasoning",
"reproducibility"
],
"moe_experts": [
"performance_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | d64c37c649623f50ab92a59fb5c64b6549cc7ddc | |
train_25206 | 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: TypeScript
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "TypeScript",
"developer_needs": [
"reproducibility",
"tooling",
"evaluation_metrics",
"documentation"
],
"moe_experts": [
"evaluation_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 430ac51fb43768786d31b3acbb6ef2968930c4e5 | |
train_25207 | 2026-01-01T00:00:00 | Secure code generation and policy gates | patch_diff | expert | Task: patch_diff
Topic: Secure code generation and policy gates
Difficulty: expert
Target language: SQL
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
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": "SQL",
"developer_needs": [
"ci_integration",
"governance",
"cost_latency_tradeoffs",
"reproducibility"
],
"moe_experts": [
"performance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 4a8edc969e135cbbe381c1516598c9add456b07c | |
train_25208 | 2026-01-01T00:00:00 | Agentic coding systems (plan→edit→test→reflect) | failure_analysis | intermediate | Task: failure_analysis
Topic: Agentic coding systems (plan→edit→test→reflect)
Difficulty: intermediate
Target language: 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": [
"ci_integration",
"documentation",
"tooling",
"reproducibility"
],
"moe_experts": [
"data_curation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 79f3dfe8aab2df1d277713dccc8d4049d959cd91 | |
train_25209 | 2026-01-01T00:00:00 | Multimodal dev workflows (docs, diagrams, traces) | design | expert | Task: design
Topic: Multimodal dev workflows (docs, diagrams, traces)
Difficulty: expert
Target language: SQL
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
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": [
"ci_integration",
"tooling",
"cost_latency_tradeoffs",
"evaluation_metrics"
],
"moe_experts": [
"coding_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 171e505407c5afed592eff06dfcdf1019ebecb86 | |
train_25210 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | review | expert | Task: review
Topic: Latency, cost, and reliability optimization
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.
Review: correctness, security, performance, governance
| [] | {
"target_language": "Bash",
"developer_needs": [
"tests_are_truth",
"repo_scale_reasoning",
"tooling",
"reproducibility"
],
"moe_experts": [
"coding_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 5e8c0772a9436d01ce445490e1675a82d1d14dfa | |
train_25211 | 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: 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.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
| [] | {
"target_language": "Java",
"developer_needs": [
"repo_scale_reasoning",
"evaluation_metrics",
"governance",
"ci_integration"
],
"moe_experts": [
"governance_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 4ecc021ea9077fff67b53209d856a580b376e0cb | |
train_25212 | 2026-01-01T00:00:00 | Extended context and repo-scale understanding | patch_diff | expert | Task: patch_diff
Topic: Extended context and repo-scale understanding
Difficulty: expert
Target language: Rust
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Patch (diff-style):
```diff
- if x == 0:
- return 1/x
+ if x == 0:
+ raise ValueError('division by zero')
```
Acceptance:
- Tests pass
- No new regressions
| [] | {
"target_language": "Rust",
"developer_needs": [
"cost_latency_tradeoffs",
"tooling",
"evaluation_metrics",
"reproducibility"
],
"moe_experts": [
"coding_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 8f7fe2d3e650bc3c51dfbe087d627e649b5f3b05 | |
train_25213 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | eval | expert | Task: eval
Topic: Latency, cost, and reliability optimization
Difficulty: expert
Target language: Bash
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
| [] | {
"target_language": "Bash",
"developer_needs": [
"cost_latency_tradeoffs",
"repo_scale_reasoning",
"ci_integration",
"security_gates"
],
"moe_experts": [
"coding_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 54bcd8e3b42da83f28bf0bb492be083698f9320f | |
train_25214 | 2026-01-01T00:00:00 | Extended context and repo-scale understanding | review | intermediate | Task: review
Topic: Extended context and repo-scale understanding
Difficulty: intermediate
Target language: Bash
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Review: correctness, security, performance, governance
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Bash",
"developer_needs": [
"security_gates",
"governance",
"tooling",
"cost_latency_tradeoffs"
],
"moe_experts": [
"data_curation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 3503ec72039620337fc9ed147c63174c302d3f1d | |
train_25215 | 2026-01-01T00:00:00 | Dataset curation pipelines (filter, dedupe, quality) | agent_loop | advanced | Task: agent_loop
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: advanced
Target language: Java
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Java",
"developer_needs": [
"evaluation_metrics",
"repo_scale_reasoning",
"tests_are_truth",
"governance"
],
"moe_experts": [
"governance_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 3410bdf4813ccd73c3a15fd3fa499faec3640ef4 | |
train_25216 | 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: 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
| [] | {
"target_language": "Java",
"developer_needs": [
"reproducibility",
"ci_integration",
"tooling",
"security_gates"
],
"moe_experts": [
"agentic_systems_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | d2b3c1fb17628ea819a697d66f9294a7d06680e1 | |
train_25217 | 2026-01-01T00:00:00 | Extended context and repo-scale understanding | explain | advanced | Task: explain
Topic: Extended context and repo-scale understanding
Difficulty: advanced
Target language: JavaScript
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "JavaScript",
"developer_needs": [
"documentation",
"governance",
"ci_integration",
"security_gates"
],
"moe_experts": [
"performance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | b3a08f1dd50f3c377942a20314433fcfbabdb19f | |
train_25218 | 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": [
"reproducibility",
"cost_latency_tradeoffs",
"documentation",
"evaluation_metrics"
],
"moe_experts": [
"security_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | d7abc592e759cdbabe7849351af296020556de1c | |
train_25219 | 2026-01-01T00:00:00 | Dataset curation pipelines (filter, dedupe, quality) | design | intermediate | Task: design
Topic: Dataset curation pipelines (filter, dedupe, quality)
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",
"reproducibility",
"evaluation_metrics",
"tests_are_truth"
],
"moe_experts": [
"performance_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | ce1c12f977f3f3420e858356ccbebccc95d59f49 | |
train_25220 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | compare | intermediate | Task: compare
Topic: Latency, cost, and reliability optimization
Difficulty: intermediate
Target language: SQL
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
| [] | {
"target_language": "SQL",
"developer_needs": [
"ci_integration",
"documentation",
"governance",
"cost_latency_tradeoffs"
],
"moe_experts": [
"performance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | c9aa0a7a75707a078534560c5cb3a28646163d2f | |
train_25221 | 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: Python
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
| [] | {
"target_language": "Python",
"developer_needs": [
"evaluation_metrics",
"reproducibility",
"cost_latency_tradeoffs",
"governance"
],
"moe_experts": [
"governance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | a80586b1ae8934e275fb65c690364e34e1cb903e | |
train_25222 | 2026-01-01T00:00:00 | Agentic coding systems (plan→edit→test→reflect) | code | advanced | Task: code
Topic: Agentic coding systems (plan→edit→test→reflect)
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.
Scaffold:
```python
def agent_loop(plan, edit, test, issue, max_iters=4):
history = []
p = plan(issue)
for _ in range(max_iters):
patch = edit(issue, p)
ok, report = test(patch)
history.append({"plan": p, "ok": ok})
if ok:
return patch, history
p = p + " | refine"
return patch, history
```
| [] | {
"target_language": "Python",
"developer_needs": [
"reproducibility",
"security_gates",
"evaluation_metrics",
"tooling"
],
"moe_experts": [
"coding_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 8d3604c54058af138163f6b338c30080545c44f6 | |
train_25223 | 2026-01-01T00:00:00 | Mixture-of-Experts (MoE) for code | eval | advanced | Task: eval
Topic: Mixture-of-Experts (MoE) for code
Difficulty: advanced
Target language: 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.
Eval:
pass@k, time-to-green, regressions, diff size
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "TypeScript",
"developer_needs": [
"repo_scale_reasoning",
"ci_integration",
"reproducibility",
"evaluation_metrics"
],
"moe_experts": [
"evaluation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | af2b8c3eb6353ad82adb36b01da55cc52bf6c05d | |
train_25224 | 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: SQL
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "SQL",
"developer_needs": [
"ci_integration",
"governance",
"documentation",
"repo_scale_reasoning"
],
"moe_experts": [
"agentic_systems_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 799c0715ce6ecaa5726731fb40e3c23b9246ca6e | |
train_25225 | 2026-01-01T00:00:00 | Dataset curation pipelines (filter, dedupe, quality) | code | intermediate | Task: code
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: intermediate
Target language: 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": [
"evaluation_metrics",
"tests_are_truth",
"documentation",
"governance"
],
"moe_experts": [
"evaluation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 3de822988aef77719f3d8ef9696707e5c954b158 | |
train_25226 | 2026-01-01T00:00:00 | Code-specialized model families and sizing tradeoffs | compare | intermediate | Task: compare
Topic: Code-specialized model families and sizing tradeoffs
Difficulty: intermediate
Target language: SQL
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "SQL",
"developer_needs": [
"reproducibility",
"auditability",
"cost_latency_tradeoffs",
"security_gates"
],
"moe_experts": [
"governance_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | c664aa6c34aecce523195e770907f4f918333981 | |
train_25227 | 2026-01-01T00:00:00 | Tool calling, sandboxes, and CI integration | data_pipeline | advanced | Task: data_pipeline
Topic: Tool calling, sandboxes, and CI integration
Difficulty: advanced
Target language: Bash
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
| [] | {
"target_language": "Bash",
"developer_needs": [
"repo_scale_reasoning",
"governance",
"evaluation_metrics",
"documentation"
],
"moe_experts": [
"security_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | b06430161e2317c9009b2f5cf0189e803dd5caac | |
train_25228 | 2026-01-01T00:00:00 | Mixture-of-Experts (MoE) for code | code | intermediate | Task: code
Topic: Mixture-of-Experts (MoE) for code
Difficulty: intermediate
Target language: C#
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "C#",
"developer_needs": [
"auditability",
"documentation",
"repo_scale_reasoning",
"governance"
],
"moe_experts": [
"evaluation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 735db2e5f6c2c3163491b5bc41dc3b7e0b91e178 | |
train_25229 | 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: 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": [
"evaluation_metrics",
"documentation",
"tests_are_truth",
"security_gates"
],
"moe_experts": [
"coding_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 95831d0943ed9c3249ddaeb518e669091b7d6e2d | |
train_25230 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | explain | expert | Task: explain
Topic: Latency, cost, and reliability optimization
Difficulty: expert
Target language: Rust
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "Rust",
"developer_needs": [
"documentation",
"reproducibility",
"auditability",
"ci_integration"
],
"moe_experts": [
"performance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 08a2735969fd5a48b884a2375561c1cb670e6913 | |
train_25231 | 2026-01-01T00:00:00 | Reasoning-first coding models and tunable deliberation | compare | advanced | Task: compare
Topic: Reasoning-first coding models and tunable deliberation
Difficulty: advanced
Target language: 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
| [] | {
"target_language": "TypeScript",
"developer_needs": [
"evaluation_metrics",
"repo_scale_reasoning",
"security_gates",
"auditability"
],
"moe_experts": [
"agentic_systems_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 35e6a216b43b3b95d8577579bac06fc462c03860 | |
train_25232 | 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: 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.
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": [
"ci_integration",
"repo_scale_reasoning",
"tests_are_truth",
"reproducibility"
],
"moe_experts": [
"performance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | e6afa89f26fdf7d672192fdb27510abf122df5cf | |
train_25233 | 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: TypeScript
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "TypeScript",
"developer_needs": [
"governance",
"tooling",
"tests_are_truth",
"cost_latency_tradeoffs"
],
"moe_experts": [
"security_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | b8429ce5474fc873c471de1290811584af614c6c | |
train_25234 | 2026-01-01T00:00:00 | Mixture-of-Experts (MoE) for code | eval | advanced | Task: eval
Topic: Mixture-of-Experts (MoE) for code
Difficulty: advanced
Target language: Bash
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Bash",
"developer_needs": [
"ci_integration",
"auditability",
"cost_latency_tradeoffs",
"governance"
],
"moe_experts": [
"evaluation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 149e173e194bd55408d1444ce9690b9c96e1a483 | |
train_25235 | 2026-01-01T00:00:00 | Secure code generation and policy gates | explain | advanced | Task: explain
Topic: Secure code generation and policy gates
Difficulty: advanced
Target language: C#
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "C#",
"developer_needs": [
"tests_are_truth",
"tooling",
"cost_latency_tradeoffs",
"governance"
],
"moe_experts": [
"evaluation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | a3334bdf333275da1beb240d259644e142e43957 | |
train_25236 | 2026-01-01T00:00:00 | Code-specialized model families and sizing tradeoffs | code | advanced | Task: code
Topic: Code-specialized model families and sizing tradeoffs
Difficulty: advanced
Target language: Java
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Java",
"developer_needs": [
"repo_scale_reasoning",
"ci_integration",
"governance",
"reproducibility"
],
"moe_experts": [
"governance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 7fff6cf3ebcd787e5c9b45619047ae2a6e18cb4b | |
train_25237 | 2026-01-01T00:00:00 | Agentic coding systems (plan→edit→test→reflect) | failure_analysis | intermediate | Task: failure_analysis
Topic: Agentic coding systems (plan→edit→test→reflect)
Difficulty: intermediate
Target language: 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
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Python",
"developer_needs": [
"reproducibility",
"auditability",
"evaluation_metrics",
"governance"
],
"moe_experts": [
"coding_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 72bd93b8baeba8dcfc4d19118bdcb61d3407fd43 | |
train_25238 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | compare | intermediate | Task: compare
Topic: Latency, cost, and reliability optimization
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": [
"documentation",
"tests_are_truth",
"ci_integration",
"tooling"
],
"moe_experts": [
"data_curation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | e349b3de38c77b62dc52c3890cb5a2e55a3b4232 | |
train_25239 | 2026-01-01T00:00:00 | Reasoning-first coding models and tunable deliberation | data_pipeline | advanced | Task: data_pipeline
Topic: Reasoning-first coding models and tunable deliberation
Difficulty: advanced
Target language: 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.
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": "Go",
"developer_needs": [
"governance",
"reproducibility",
"repo_scale_reasoning",
"security_gates"
],
"moe_experts": [
"agentic_systems_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 05b4372a165005a125c583f79523c10db14aa113 | |
train_25240 | 2026-01-01T00:00:00 | SWE-bench style real-repo evaluation | compare | intermediate | Task: compare
Topic: SWE-bench style real-repo evaluation
Difficulty: intermediate
Target language: TypeScript
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
| [] | {
"target_language": "TypeScript",
"developer_needs": [
"reproducibility",
"tooling",
"ci_integration",
"documentation"
],
"moe_experts": [
"agentic_systems_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | f103eea38dce3e1ffb4b6b5218329b089d641d88 | |
train_25241 | 2026-01-01T00:00:00 | Self-improving agents and feedback loops | data_pipeline | intermediate | Task: data_pipeline
Topic: Self-improving agents and feedback loops
Difficulty: intermediate
Target language: JavaScript
Context: 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": "JavaScript",
"developer_needs": [
"security_gates",
"cost_latency_tradeoffs",
"tooling",
"evaluation_metrics"
],
"moe_experts": [
"performance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 99347eb5719ed3678b5ba6ad5eb0fc72a788229b | |
train_25242 | 2026-01-01T00:00:00 | Agentic coding systems (plan→edit→test→reflect) | code | advanced | Task: code
Topic: Agentic coding systems (plan→edit→test→reflect)
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": [
"ci_integration",
"repo_scale_reasoning",
"tests_are_truth",
"tooling"
],
"moe_experts": [
"security_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 0592571c7cd1591ab65fc8b4c4ef74be48d4df51 | |
train_25243 | 2026-01-01T00:00:00 | Multimodal dev workflows (docs, diagrams, traces) | failure_analysis | expert | Task: failure_analysis
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.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Go",
"developer_needs": [
"security_gates",
"ci_integration",
"evaluation_metrics",
"auditability"
],
"moe_experts": [
"agentic_systems_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 0e583d6d68db0b36fc72a170b3ba1546a7d6299d | |
train_25244 | 2026-01-01T00:00:00 | Reasoning-first coding models and tunable deliberation | code | intermediate | Task: code
Topic: Reasoning-first coding models and tunable deliberation
Difficulty: intermediate
Target language: 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": [
"auditability",
"documentation",
"ci_integration",
"tests_are_truth"
],
"moe_experts": [
"performance_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 70d49472173972e6f615e65e89f0cf4c9c287d60 | |
train_25245 | 2026-01-01T00:00:00 | Code-specialized model families and sizing tradeoffs | failure_analysis | intermediate | Task: failure_analysis
Topic: Code-specialized model families and sizing tradeoffs
Difficulty: intermediate
Target language: 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.
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": "TypeScript",
"developer_needs": [
"ci_integration",
"tooling",
"cost_latency_tradeoffs",
"security_gates"
],
"moe_experts": [
"governance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 5cacee1c5ebbb9be660b7fb96e6d5c14adaf382d | |
train_25246 | 2026-01-01T00:00:00 | Governance, provenance, and licensing for code data | agent_loop | expert | Task: agent_loop
Topic: Governance, provenance, and licensing for code data
Difficulty: expert
Target language: Java
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
| [] | {
"target_language": "Java",
"developer_needs": [
"documentation",
"security_gates",
"governance",
"repo_scale_reasoning"
],
"moe_experts": [
"performance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | b68dd0f37c27fcc29356f00ab9206b84ebce4e28 | |
train_25247 | 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: 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",
"ci_integration",
"reproducibility",
"auditability"
],
"moe_experts": [
"governance_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 51faeb5f95af49f8ede37d822c2bec527d869f11 | |
train_25248 | 2026-01-01T00:00:00 | Dataset curation pipelines (filter, dedupe, quality) | compare | advanced | Task: compare
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: advanced
Target language: 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": [
"reproducibility",
"auditability",
"tooling",
"governance"
],
"moe_experts": [
"security_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 743c3b3ae1be84e14a930963c964e85a2e1ffcc3 | |
train_25249 | 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: 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": [
"ci_integration",
"cost_latency_tradeoffs",
"evaluation_metrics",
"governance"
],
"moe_experts": [
"security_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 8e17a7c94072f09423ba0bc7e195db3903211c0c | |
train_25250 | 2026-01-01T00:00:00 | Model merging, distillation, and continued pretraining | patch_diff | advanced | Task: patch_diff
Topic: Model merging, distillation, and continued pretraining
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.
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": [
"evaluation_metrics",
"governance",
"repo_scale_reasoning",
"documentation"
],
"moe_experts": [
"agentic_systems_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 8db074de0d702d669228656a5406d34a0e626dc3 | |
train_25251 | 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: 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": [
"cost_latency_tradeoffs",
"repo_scale_reasoning",
"documentation",
"auditability"
],
"moe_experts": [
"security_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 529ef92d8d8b12f2347b70e48ec1447c53b2e9ed | |
train_25252 | 2026-01-01T00:00:00 | Governance, provenance, and licensing for code data | data_pipeline | advanced | Task: data_pipeline
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.
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": [
"evaluation_metrics",
"tooling",
"governance",
"repo_scale_reasoning"
],
"moe_experts": [
"governance_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | d3652099940251296d5f518991c8c963b2b61015 | |
train_25253 | 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: JavaScript
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Patch (diff-style):
```diff
- if x == 0:
- return 1/x
+ if x == 0:
+ raise ValueError('division by zero')
```
Acceptance:
- Tests pass
- No new regressions
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "JavaScript",
"developer_needs": [
"ci_integration",
"tests_are_truth",
"governance",
"repo_scale_reasoning"
],
"moe_experts": [
"evaluation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 293fd1f09857e73612b114fc7f76789899057c11 | |
train_25254 | 2026-01-01T00:00:00 | Tool calling, sandboxes, and CI integration | agent_loop | advanced | Task: agent_loop
Topic: Tool calling, sandboxes, and CI integration
Difficulty: advanced
Target language: Bash
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
| [] | {
"target_language": "Bash",
"developer_needs": [
"governance",
"reproducibility",
"repo_scale_reasoning",
"documentation"
],
"moe_experts": [
"governance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | d651ff4c0dc0eaf80178e370afb40fd4ef6dce14 | |
train_25255 | 2026-01-01T00:00:00 | Self-improving agents and feedback loops | review | intermediate | Task: review
Topic: Self-improving agents and feedback loops
Difficulty: intermediate
Target language: 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
| [] | {
"target_language": "SQL",
"developer_needs": [
"auditability",
"evaluation_metrics",
"tooling",
"reproducibility"
],
"moe_experts": [
"data_curation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 81fa390faeb47f215ce3820566122ffbeff20d51 | |
train_25256 | 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: 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": [
"documentation",
"reproducibility",
"tooling",
"tests_are_truth"
],
"moe_experts": [
"data_curation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 309ad33a443775214001c85b41571fd4248e06b0 | |
train_25257 | 2026-01-01T00:00:00 | Extended context and repo-scale understanding | patch_diff | intermediate | Task: patch_diff
Topic: Extended context and repo-scale understanding
Difficulty: intermediate
Target language: Java
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Patch (diff-style):
```diff
- if x == 0:
- return 1/x
+ if x == 0:
+ raise ValueError('division by zero')
```
Acceptance:
- Tests pass
- No new regressions
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Java",
"developer_needs": [
"auditability",
"cost_latency_tradeoffs",
"governance",
"security_gates"
],
"moe_experts": [
"coding_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | dd793e66ad8c1eca808e68235a97723a6942c070 | |
train_25258 | 2026-01-01T00:00:00 | Dataset curation pipelines (filter, dedupe, quality) | data_pipeline | advanced | Task: data_pipeline
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: advanced
Target language: Python
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
| [] | {
"target_language": "Python",
"developer_needs": [
"auditability",
"cost_latency_tradeoffs",
"tests_are_truth",
"ci_integration"
],
"moe_experts": [
"evaluation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 0a2dd49e4982d65c2e0f426227b18658233e8f1f | |
train_25259 | 2026-01-01T00:00:00 | Code-specialized model families and sizing tradeoffs | agent_loop | advanced | Task: agent_loop
Topic: Code-specialized model families and sizing tradeoffs
Difficulty: advanced
Target language: 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
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "JavaScript",
"developer_needs": [
"security_gates",
"repo_scale_reasoning",
"tests_are_truth",
"cost_latency_tradeoffs"
],
"moe_experts": [
"agentic_systems_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 5e7b5f0ba223b699c45ceca831e311e0803a5de1 | |
train_25260 | 2026-01-01T00:00:00 | Tool calling, sandboxes, and CI integration | code | advanced | Task: code
Topic: Tool calling, sandboxes, and CI integration
Difficulty: advanced
Target language: 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
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "TypeScript",
"developer_needs": [
"tests_are_truth",
"reproducibility",
"evaluation_metrics",
"tooling"
],
"moe_experts": [
"governance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 83e74998f54d30073e2cd7fd90ddd17e93eb396c | |
train_25261 | 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: 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": [
"ci_integration",
"repo_scale_reasoning",
"documentation",
"security_gates"
],
"moe_experts": [
"governance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | b31a3a41192fc71cd216d49a398d9c89546ec603 | |
train_25262 | 2026-01-01T00:00:00 | Agentic coding systems (plan→edit→test→reflect) | patch_diff | expert | Task: patch_diff
Topic: Agentic coding systems (plan→edit→test→reflect)
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.
Patch (diff-style):
```diff
- if x == 0:
- return 1/x
+ if x == 0:
+ raise ValueError('division by zero')
```
Acceptance:
- Tests pass
- No new regressions
| [] | {
"target_language": "Java",
"developer_needs": [
"evaluation_metrics",
"governance",
"security_gates",
"tooling"
],
"moe_experts": [
"agentic_systems_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 1699741cd7d69cf307f02465b33dc5591b0b8fd8 | |
train_25263 | 2026-01-01T00:00:00 | Agentic coding systems (plan→edit→test→reflect) | explain | intermediate | Task: explain
Topic: Agentic coding systems (plan→edit→test→reflect)
Difficulty: intermediate
Target language: Rust
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Rust",
"developer_needs": [
"auditability",
"tooling",
"repo_scale_reasoning",
"reproducibility"
],
"moe_experts": [
"governance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 461df607e26b8404a531eb9a67314cd1ab6b2b76 | |
train_25264 | 2026-01-01T00:00:00 | Model merging, distillation, and continued pretraining | explain | advanced | Task: explain
Topic: Model merging, distillation, and continued pretraining
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.
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": [
"auditability",
"governance",
"cost_latency_tradeoffs",
"security_gates"
],
"moe_experts": [
"performance_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 485d828bf67124f2557a8c1ebc235d6dad718021 | |
train_25265 | 2026-01-01T00:00:00 | Multimodal dev workflows (docs, diagrams, traces) | eval | expert | Task: eval
Topic: Multimodal dev workflows (docs, diagrams, traces)
Difficulty: expert
Target language: 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.
Eval:
pass@k, time-to-green, regressions, diff size
| [] | {
"target_language": "Rust",
"developer_needs": [
"repo_scale_reasoning",
"governance",
"ci_integration",
"security_gates"
],
"moe_experts": [
"performance_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 28652e6ec20121ddc207e4c3c1010182a81e6f18 | |
train_25266 | 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: 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": [
"reproducibility",
"cost_latency_tradeoffs",
"auditability",
"documentation"
],
"moe_experts": [
"performance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 4194cc17c76059096ad81d098cd4fe4902145717 | |
train_25267 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | code | expert | Task: code
Topic: Latency, cost, and reliability optimization
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": [
"tooling",
"tests_are_truth",
"cost_latency_tradeoffs",
"governance"
],
"moe_experts": [
"data_curation_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | eade6756869cfd35c0cc1a11548e5b9561126a69 | |
train_25268 | 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: 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
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "TypeScript",
"developer_needs": [
"tooling",
"documentation",
"evaluation_metrics",
"security_gates"
],
"moe_experts": [
"governance_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | dd44c1a41d606beda4890f1b0e93fd8ac006c86f | |
train_25269 | 2026-01-01T00:00:00 | Dataset curation pipelines (filter, dedupe, quality) | explain | advanced | Task: explain
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: advanced
Target language: Rust
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Rust",
"developer_needs": [
"tooling",
"governance",
"documentation",
"evaluation_metrics"
],
"moe_experts": [
"evaluation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | a1c926ea1a1fdc13feb9fbbe3d42d4289578efc1 | |
train_25270 | 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: 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
| [] | {
"target_language": "Rust",
"developer_needs": [
"auditability",
"evaluation_metrics",
"reproducibility",
"tests_are_truth"
],
"moe_experts": [
"data_curation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | f2f7525399ac91902a9285a4566e2ec0bcaa0d4b | |
train_25271 | 2026-01-01T00:00:00 | Governance, provenance, and licensing for code data | patch_diff | intermediate | Task: patch_diff
Topic: Governance, provenance, and licensing for code data
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
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "TypeScript",
"developer_needs": [
"ci_integration",
"cost_latency_tradeoffs",
"auditability",
"security_gates"
],
"moe_experts": [
"data_curation_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | ef9d782e1487984774d5abf4a6579dbcfef14fc0 | |
train_25272 | 2026-01-01T00:00:00 | Multimodal dev workflows (docs, diagrams, traces) | failure_analysis | advanced | Task: failure_analysis
Topic: Multimodal dev workflows (docs, diagrams, traces)
Difficulty: advanced
Target language: Java
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Java",
"developer_needs": [
"repo_scale_reasoning",
"security_gates",
"tests_are_truth",
"documentation"
],
"moe_experts": [
"agentic_systems_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | f3ef2b878c0ccbf9bf33c555a67016c7cc9929fa | |
train_25273 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | data_pipeline | intermediate | Task: data_pipeline
Topic: Latency, cost, and reliability optimization
Difficulty: intermediate
Target language: SQL
Context: 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": "SQL",
"developer_needs": [
"reproducibility",
"cost_latency_tradeoffs",
"tests_are_truth",
"evaluation_metrics"
],
"moe_experts": [
"coding_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | b14323814b70802425ae53c56b6c482e2f593aee | |
train_25274 | 2026-01-01T00:00:00 | Mixture-of-Experts (MoE) for code | failure_analysis | expert | Task: failure_analysis
Topic: Mixture-of-Experts (MoE) for code
Difficulty: expert
Target language: 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.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
| [] | {
"target_language": "TypeScript",
"developer_needs": [
"repo_scale_reasoning",
"cost_latency_tradeoffs",
"governance",
"reproducibility"
],
"moe_experts": [
"evaluation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | e63453eae1f4e361710e21f6aa3ad8793d77cb27 | |
train_25275 | 2026-01-01T00:00:00 | Secure code generation and policy gates | eval | intermediate | Task: eval
Topic: Secure code generation and policy gates
Difficulty: intermediate
Target language: JavaScript
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "JavaScript",
"developer_needs": [
"documentation",
"repo_scale_reasoning",
"evaluation_metrics",
"tooling"
],
"moe_experts": [
"security_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 372a594efe0dc214730492ffe4a5caf6828c19d3 | |
train_25276 | 2026-01-01T00:00:00 | Secure code generation and policy gates | agent_loop | intermediate | Task: agent_loop
Topic: Secure code generation and policy gates
Difficulty: intermediate
Target language: 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.
Loop: Plan → Edit → Test → Reflect → Human gate
| [] | {
"target_language": "SQL",
"developer_needs": [
"governance",
"reproducibility",
"tests_are_truth",
"cost_latency_tradeoffs"
],
"moe_experts": [
"performance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | e4813247a3fed380c57db6ca848c101d46307f21 | |
train_25277 | 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: SQL
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "SQL",
"developer_needs": [
"security_gates",
"auditability",
"governance",
"repo_scale_reasoning"
],
"moe_experts": [
"agentic_systems_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 56bd5ec8d394785fe4413900efeb81309c7a773f | |
train_25278 | 2026-01-01T00:00:00 | Reasoning-first coding models and tunable deliberation | compare | intermediate | Task: compare
Topic: Reasoning-first coding models and tunable deliberation
Difficulty: intermediate
Target language: Python
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
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": [
"repo_scale_reasoning",
"evaluation_metrics",
"tests_are_truth",
"ci_integration"
],
"moe_experts": [
"performance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | fd608f4bc8d3799f3a1151e01489f225a55ac55d | |
train_25279 | 2026-01-01T00:00:00 | Secure code generation and policy gates | eval | expert | Task: eval
Topic: Secure code generation and policy gates
Difficulty: expert
Target language: 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.
Eval:
pass@k, time-to-green, regressions, diff size
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Rust",
"developer_needs": [
"tooling",
"repo_scale_reasoning",
"reproducibility",
"security_gates"
],
"moe_experts": [
"agentic_systems_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 3aeb0cbb224e6b8aec630233810f401f5615b1fc | |
train_25280 | 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: Python
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "Python",
"developer_needs": [
"auditability",
"repo_scale_reasoning",
"reproducibility",
"ci_integration"
],
"moe_experts": [
"performance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 02c1ffebfff5c97b1efb71334dad4cb2d5b4d865 | |
train_25281 | 2026-01-01T00:00:00 | Secure code generation and policy gates | design | intermediate | Task: design
Topic: Secure code generation and policy gates
Difficulty: intermediate
Target language: 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": [
"repo_scale_reasoning",
"tooling",
"reproducibility",
"cost_latency_tradeoffs"
],
"moe_experts": [
"agentic_systems_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | c400ebdba4e511ca70eba95f2423840c8b52423e | |
train_25282 | 2026-01-01T00:00:00 | Agentic coding systems (plan→edit→test→reflect) | data_pipeline | intermediate | Task: data_pipeline
Topic: Agentic coding systems (plan→edit→test→reflect)
Difficulty: intermediate
Target language: 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.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
| [] | {
"target_language": "Go",
"developer_needs": [
"ci_integration",
"auditability",
"tooling",
"evaluation_metrics"
],
"moe_experts": [
"agentic_systems_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 4e57d2f2b459c32d7f2994a3c12021c7421490a2 | |
train_25283 | 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: 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": [
"reproducibility",
"cost_latency_tradeoffs",
"evaluation_metrics",
"auditability"
],
"moe_experts": [
"governance_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | cfb6b78b4f393aaf8226ffac633354867c8d0fc8 | |
train_25284 | 2026-01-01T00:00:00 | Mixture-of-Experts (MoE) for code | code | expert | Task: code
Topic: Mixture-of-Experts (MoE) for code
Difficulty: expert
Target language: 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": [
"repo_scale_reasoning",
"evaluation_metrics",
"cost_latency_tradeoffs",
"tooling"
],
"moe_experts": [
"agentic_systems_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 2eb34dd2854c183863f631170e11933b6a10c4b9 | |
train_25285 | 2026-01-01T00:00:00 | Tool calling, sandboxes, and CI integration | agent_loop | advanced | Task: agent_loop
Topic: Tool calling, sandboxes, and CI integration
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.
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": [
"tests_are_truth",
"documentation",
"tooling",
"reproducibility"
],
"moe_experts": [
"security_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | da6b02e65b33df4683b1f7f1c4f9415208d1dce6 | |
train_25286 | 2026-01-01T00:00:00 | Code-specialized model families and sizing tradeoffs | compare | intermediate | Task: compare
Topic: Code-specialized model families and sizing tradeoffs
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.
Compare: capability, cost, latency, reliability
| [] | {
"target_language": "JavaScript",
"developer_needs": [
"repo_scale_reasoning",
"cost_latency_tradeoffs",
"reproducibility",
"evaluation_metrics"
],
"moe_experts": [
"agentic_systems_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | c20f997b1401dcd338e80eb92db670094d795ea6 | |
train_25287 | 2026-01-01T00:00:00 | Extended context and repo-scale understanding | data_pipeline | expert | Task: data_pipeline
Topic: Extended context and repo-scale understanding
Difficulty: expert
Target language: 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.
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": "Go",
"developer_needs": [
"security_gates",
"reproducibility",
"ci_integration",
"governance"
],
"moe_experts": [
"coding_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 2750524268a79692ffe21dd8880276942ac8d15f | |
train_25288 | 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: 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": [
"evaluation_metrics",
"tests_are_truth",
"repo_scale_reasoning",
"reproducibility"
],
"moe_experts": [
"data_curation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 62e68d8da4a2c5627784ff1e6898a9174697a401 | |
train_25289 | 2026-01-01T00:00:00 | Code-specialized model families and sizing tradeoffs | patch_diff | advanced | Task: patch_diff
Topic: Code-specialized model families and sizing tradeoffs
Difficulty: advanced
Target language: Java
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
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",
"evaluation_metrics",
"repo_scale_reasoning",
"governance"
],
"moe_experts": [
"coding_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | ecd0137f69c9c0bc25f4b08cdf161d0f1ba7fd65 | |
train_25290 | 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: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "JavaScript",
"developer_needs": [
"auditability",
"cost_latency_tradeoffs",
"tests_are_truth",
"governance"
],
"moe_experts": [
"evaluation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | eb93e94173c66a825c2216e96ed00f05139c4cc4 | |
train_25291 | 2026-01-01T00:00:00 | Reasoning-first coding models and tunable deliberation | review | expert | Task: review
Topic: Reasoning-first coding models and tunable deliberation
Difficulty: expert
Target language: 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.
Review: correctness, security, performance, governance
| [] | {
"target_language": "Rust",
"developer_needs": [
"tests_are_truth",
"ci_integration",
"documentation",
"reproducibility"
],
"moe_experts": [
"data_curation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | eb85fe00a36b5327f047ae1fc46a70a5aced700f | |
train_25292 | 2026-01-01T00:00:00 | Dataset curation pipelines (filter, dedupe, quality) | data_pipeline | advanced | Task: data_pipeline
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: advanced
Target language: Rust
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
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": [
"reproducibility",
"auditability",
"evaluation_metrics",
"security_gates"
],
"moe_experts": [
"coding_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 13fd302eef0c3b838180f7c954249cb01e9a8dec | |
train_25293 | 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: Bash
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Review: correctness, security, performance, governance
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Bash",
"developer_needs": [
"documentation",
"repo_scale_reasoning",
"evaluation_metrics",
"security_gates"
],
"moe_experts": [
"coding_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 78a4aa99c55faf3898bdcdcd8d467e6ed7aa0fd8 | |
train_25294 | 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: C#
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
| [] | {
"target_language": "C#",
"developer_needs": [
"governance",
"auditability",
"reproducibility",
"documentation"
],
"moe_experts": [
"evaluation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 36b356357d58e97e6feea84bf0bafd9d317d8791 | |
train_25295 | 2026-01-01T00:00:00 | Self-improving agents and feedback loops | explain | expert | Task: explain
Topic: Self-improving agents and feedback loops
Difficulty: expert
Target language: SQL
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "SQL",
"developer_needs": [
"cost_latency_tradeoffs",
"auditability",
"ci_integration",
"evaluation_metrics"
],
"moe_experts": [
"data_curation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 56e1a672b6dfac59e8156153177d9cc70bd546ae | |
train_25296 | 2026-01-01T00:00:00 | Secure code generation and policy gates | design | expert | Task: design
Topic: Secure code generation and policy gates
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.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "TypeScript",
"developer_needs": [
"tooling",
"evaluation_metrics",
"tests_are_truth",
"repo_scale_reasoning"
],
"moe_experts": [
"data_curation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 2da64523162fb97069eb8a82cd6f60ff392a44bc | |
train_25297 | 2026-01-01T00:00:00 | Model merging, distillation, and continued pretraining | failure_analysis | expert | Task: failure_analysis
Topic: Model merging, distillation, and continued pretraining
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.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
| [] | {
"target_language": "Python",
"developer_needs": [
"reproducibility",
"tooling",
"governance",
"repo_scale_reasoning"
],
"moe_experts": [
"evaluation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 022ab8a5f14dccbeb2685bd6cbb03e6503b33566 | |
train_25298 | 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: 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": [
"tests_are_truth",
"governance",
"reproducibility",
"ci_integration"
],
"moe_experts": [
"security_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 954fb11364ad4edf2da543875fb4876846bdd6c8 | |
train_25299 | 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: Bash
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Review: correctness, security, performance, governance
| [] | {
"target_language": "Bash",
"developer_needs": [
"security_gates",
"reproducibility",
"auditability",
"repo_scale_reasoning"
],
"moe_experts": [
"security_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 704fb6215c894c356c1abe7f0e41fa54b7d1f336 |
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