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_34800 | 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: C#
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "C#",
"developer_needs": [
"tests_are_truth",
"tooling",
"governance",
"evaluation_metrics"
],
"moe_experts": [
"security_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 2689b65890e287481adde83922e73aaeef7f95ba | |
train_34801 | 2026-01-01T00:00:00 | Dataset curation pipelines (filter, dedupe, quality) | data_pipeline | intermediate | Task: data_pipeline
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: intermediate
Target language: Go
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
| [] | {
"target_language": "Go",
"developer_needs": [
"evaluation_metrics",
"governance",
"security_gates",
"reproducibility"
],
"moe_experts": [
"agentic_systems_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 99b30b37c92f66a2cdf80dc239b765f38b0d7d4b | |
train_34802 | 2026-01-01T00:00:00 | SWE-bench style real-repo evaluation | data_pipeline | intermediate | Task: data_pipeline
Topic: SWE-bench style real-repo evaluation
Difficulty: intermediate
Target language: Go
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
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": [
"auditability",
"tooling",
"tests_are_truth",
"documentation"
],
"moe_experts": [
"evaluation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 8b79b415072248dd73d8991d6e75503a5dc9d85f | |
train_34803 | 2026-01-01T00:00:00 | Multimodal dev workflows (docs, diagrams, traces) | explain | expert | Task: explain
Topic: Multimodal dev workflows (docs, diagrams, traces)
Difficulty: expert
Target language: 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.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "Java",
"developer_needs": [
"documentation",
"auditability",
"cost_latency_tradeoffs",
"reproducibility"
],
"moe_experts": [
"performance_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 3b41522eed59c4d83111f0da4d152b3a3e1f6f7c | |
train_34804 | 2026-01-01T00:00:00 | Code-specialized model families and sizing tradeoffs | compare | advanced | Task: compare
Topic: Code-specialized model families and sizing tradeoffs
Difficulty: advanced
Target language: C#
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
| [] | {
"target_language": "C#",
"developer_needs": [
"governance",
"reproducibility",
"tests_are_truth",
"evaluation_metrics"
],
"moe_experts": [
"coding_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | c55c493b5c529d53d7dceb34ed0f3b0eb015ea79 | |
train_34805 | 2026-01-01T00:00:00 | Multimodal dev workflows (docs, diagrams, traces) | explain | advanced | Task: explain
Topic: Multimodal dev workflows (docs, diagrams, traces)
Difficulty: advanced
Target language: Java
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "Java",
"developer_needs": [
"repo_scale_reasoning",
"reproducibility",
"tooling",
"security_gates"
],
"moe_experts": [
"coding_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 905ce2261772d7f2029fea94179f642912b9d8c6 | |
train_34806 | 2026-01-01T00:00:00 | Mixture-of-Experts (MoE) for code | eval | advanced | Task: eval
Topic: Mixture-of-Experts (MoE) for code
Difficulty: advanced
Target language: JavaScript
Context: 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": "JavaScript",
"developer_needs": [
"documentation",
"auditability",
"cost_latency_tradeoffs",
"security_gates"
],
"moe_experts": [
"agentic_systems_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | f65c14c4225bd14d1150bbf390e2fc8913e54a6f | |
train_34807 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | code | advanced | Task: code
Topic: Latency, cost, and reliability optimization
Difficulty: advanced
Target language: Python
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
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": [
"evaluation_metrics",
"governance",
"ci_integration",
"tests_are_truth"
],
"moe_experts": [
"agentic_systems_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 99542cca70308c9466dc68c7c2a2165295f93cef | |
train_34808 | 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: Java
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Java",
"developer_needs": [
"reproducibility",
"tooling",
"ci_integration",
"governance"
],
"moe_experts": [
"agentic_systems_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | c2acdb6593480244b13f0c63e8a04bd40b4ecf33 | |
train_34809 | 2026-01-01T00:00:00 | Tool calling, sandboxes, and CI integration | agent_loop | intermediate | Task: agent_loop
Topic: Tool calling, sandboxes, and CI integration
Difficulty: intermediate
Target language: Bash
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
| [] | {
"target_language": "Bash",
"developer_needs": [
"repo_scale_reasoning",
"security_gates",
"tests_are_truth",
"tooling"
],
"moe_experts": [
"governance_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | deca62b04555731a07efb421035237395e0b9cfc | |
train_34810 | 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: TypeScript
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
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": [
"reproducibility",
"auditability",
"evaluation_metrics",
"security_gates"
],
"moe_experts": [
"data_curation_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | f1d7d31c6fcb745053f4e214aeab096c5ee109eb | |
train_34811 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | eval | expert | Task: eval
Topic: Latency, cost, and reliability optimization
Difficulty: expert
Target language: JavaScript
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
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",
"ci_integration",
"evaluation_metrics",
"auditability"
],
"moe_experts": [
"agentic_systems_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 14173828efc97cd28bce41a172b301ecac064995 | |
train_34812 | 2026-01-01T00:00:00 | Self-improving agents and feedback loops | patch_diff | expert | Task: patch_diff
Topic: Self-improving agents and feedback loops
Difficulty: expert
Target language: Bash
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Patch (diff-style):
```diff
- if x == 0:
- return 1/x
+ if x == 0:
+ raise ValueError('division by zero')
```
Acceptance:
- Tests pass
- No new regressions
| [] | {
"target_language": "Bash",
"developer_needs": [
"cost_latency_tradeoffs",
"ci_integration",
"auditability",
"security_gates"
],
"moe_experts": [
"performance_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | d57cdd8dce58598d4793fa4429a103c69da9c13a | |
train_34813 | 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: Java
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
| [] | {
"target_language": "Java",
"developer_needs": [
"tests_are_truth",
"documentation",
"cost_latency_tradeoffs",
"tooling"
],
"moe_experts": [
"data_curation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 2790d0bfed6e4b41104596aa1c6a44048470eb9d | |
train_34814 | 2026-01-01T00:00:00 | Secure code generation and policy gates | failure_analysis | intermediate | Task: failure_analysis
Topic: Secure code generation and policy gates
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.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Rust",
"developer_needs": [
"evaluation_metrics",
"security_gates",
"ci_integration",
"auditability"
],
"moe_experts": [
"security_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 945229df81d9803976ccd7ee88a1b0cd865d38f9 | |
train_34815 | 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: Java
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "Java",
"developer_needs": [
"documentation",
"auditability",
"cost_latency_tradeoffs",
"repo_scale_reasoning"
],
"moe_experts": [
"security_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | e339e4d58ad21be824abb49000a294e707201fb8 | |
train_34816 | 2026-01-01T00:00:00 | Extended context and repo-scale understanding | explain | intermediate | Task: explain
Topic: Extended context and repo-scale understanding
Difficulty: intermediate
Target language: Python
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "Python",
"developer_needs": [
"tests_are_truth",
"ci_integration",
"evaluation_metrics",
"reproducibility"
],
"moe_experts": [
"performance_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 9b8727937fc2f7abb8533d971ba41ae703dd20f8 | |
train_34817 | 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: 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.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "SQL",
"developer_needs": [
"governance",
"security_gates",
"evaluation_metrics",
"repo_scale_reasoning"
],
"moe_experts": [
"performance_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 662e7e6c9b62039571294d6ef5d93b7cea61e5b8 | |
train_34818 | 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: 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
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "TypeScript",
"developer_needs": [
"tooling",
"security_gates",
"auditability",
"tests_are_truth"
],
"moe_experts": [
"governance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 4a3f1256d331a9c4f3ecdce51ee94708eb14d053 | |
train_34819 | 2026-01-01T00:00:00 | Self-improving agents and feedback loops | design | intermediate | Task: design
Topic: Self-improving agents and feedback loops
Difficulty: intermediate
Target language: 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": [
"repo_scale_reasoning",
"documentation",
"ci_integration",
"reproducibility"
],
"moe_experts": [
"evaluation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 08d21b3e5456356cf04fd4e3527700eea5d55af3 | |
train_34820 | 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: 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
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Python",
"developer_needs": [
"governance",
"documentation",
"evaluation_metrics",
"cost_latency_tradeoffs"
],
"moe_experts": [
"data_curation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 075299a03394a92f53b340537081191de8ce17b0 | |
train_34821 | 2026-01-01T00:00:00 | SWE-bench style real-repo evaluation | eval | advanced | Task: eval
Topic: SWE-bench style real-repo evaluation
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.
Eval:
pass@k, time-to-green, regressions, diff size
| [] | {
"target_language": "C#",
"developer_needs": [
"repo_scale_reasoning",
"governance",
"evaluation_metrics",
"tooling"
],
"moe_experts": [
"data_curation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | ffb640a62586ab1c908c112eb030526dbc63ee24 | |
train_34822 | 2026-01-01T00:00:00 | Self-improving agents and feedback loops | code | advanced | Task: code
Topic: Self-improving agents and feedback loops
Difficulty: advanced
Target language: Bash
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "Bash",
"developer_needs": [
"evaluation_metrics",
"repo_scale_reasoning",
"tests_are_truth",
"auditability"
],
"moe_experts": [
"data_curation_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | a17e3e7f14f01fd17245ed92a6d4fece9df448d5 | |
train_34823 | 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: 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": "Bash",
"developer_needs": [
"tests_are_truth",
"reproducibility",
"documentation",
"auditability"
],
"moe_experts": [
"evaluation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 6eec659b3a55da3716691bafbe71f3533aa2f643 | |
train_34824 | 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: 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": [
"documentation",
"tests_are_truth",
"reproducibility",
"repo_scale_reasoning"
],
"moe_experts": [
"agentic_systems_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | d23731ada95401261bfe3eb77bf7a801471128ed | |
train_34825 | 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: Java
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Java",
"developer_needs": [
"security_gates",
"repo_scale_reasoning",
"ci_integration",
"reproducibility"
],
"moe_experts": [
"evaluation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 8e87bc0fd39b1875726db13d278c6e891cd39265 | |
train_34826 | 2026-01-01T00:00:00 | Dataset curation pipelines (filter, dedupe, quality) | data_pipeline | intermediate | Task: data_pipeline
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: intermediate
Target language: 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": [
"reproducibility",
"cost_latency_tradeoffs",
"governance",
"repo_scale_reasoning"
],
"moe_experts": [
"governance_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 1b19cb36bf4519ebeb4afea455881524972b44c6 | |
train_34827 | 2026-01-01T00:00:00 | Governance, provenance, and licensing for code data | code | advanced | Task: code
Topic: Governance, provenance, and licensing for code data
Difficulty: advanced
Target language: Python
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Scaffold:
```python
def agent_loop(plan, edit, test, issue, max_iters=4):
history = []
p = plan(issue)
for _ in range(max_iters):
patch = edit(issue, p)
ok, report = test(patch)
history.append({"plan": p, "ok": ok})
if ok:
return patch, history
p = p + " | refine"
return patch, history
```
| [] | {
"target_language": "Python",
"developer_needs": [
"auditability",
"security_gates",
"repo_scale_reasoning",
"tooling"
],
"moe_experts": [
"performance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | e26b7f0f952965016947597509a90856231ef3fb | |
train_34828 | 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: SQL
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "SQL",
"developer_needs": [
"security_gates",
"reproducibility",
"auditability",
"ci_integration"
],
"moe_experts": [
"governance_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | fa6f3ce8db353147f1794a2e0fa71a99ffc1d5c8 | |
train_34829 | 2026-01-01T00:00:00 | SWE-bench style real-repo evaluation | agent_loop | advanced | Task: agent_loop
Topic: SWE-bench style real-repo evaluation
Difficulty: advanced
Target language: SQL
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "SQL",
"developer_needs": [
"tooling",
"governance",
"security_gates",
"documentation"
],
"moe_experts": [
"agentic_systems_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 2dd0fa5de465a1d54bd2e93a3892adde24c0a9b9 | |
train_34830 | 2026-01-01T00:00:00 | Agentic coding systems (plan→edit→test→reflect) | eval | advanced | Task: eval
Topic: Agentic coding systems (plan→edit→test→reflect)
Difficulty: advanced
Target language: Go
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
| [] | {
"target_language": "Go",
"developer_needs": [
"evaluation_metrics",
"tests_are_truth",
"tooling",
"reproducibility"
],
"moe_experts": [
"security_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 695ac3cfa5c8d7b2aaf6ad107183be0461fa3457 | |
train_34831 | 2026-01-01T00:00:00 | Self-improving agents and feedback loops | design | intermediate | Task: design
Topic: Self-improving agents and feedback loops
Difficulty: intermediate
Target language: Java
Context: 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": [
"documentation",
"reproducibility",
"cost_latency_tradeoffs",
"tooling"
],
"moe_experts": [
"security_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | cb2a9301b8ac14b50ea16fbf2a0837c6f65998b9 | |
train_34832 | 2026-01-01T00:00:00 | Dataset curation pipelines (filter, dedupe, quality) | compare | intermediate | Task: compare
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: intermediate
Target language: 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": [
"reproducibility",
"cost_latency_tradeoffs",
"ci_integration",
"repo_scale_reasoning"
],
"moe_experts": [
"evaluation_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | e9866063ab6397c4352e47154d5e6de318bb92cf | |
train_34833 | 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: 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": [
"evaluation_metrics",
"repo_scale_reasoning",
"reproducibility",
"tooling"
],
"moe_experts": [
"evaluation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | d568b07f9d2d6c1f636a28b1e8f4e76cf92e43d1 | |
train_34834 | 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: C#
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "C#",
"developer_needs": [
"tests_are_truth",
"tooling",
"security_gates",
"evaluation_metrics"
],
"moe_experts": [
"data_curation_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 88a3a82259c3ed83f5f3b77bd9d030d1bc23f4af | |
train_34835 | 2026-01-01T00:00:00 | Tool calling, sandboxes, and CI integration | agent_loop | expert | Task: agent_loop
Topic: Tool calling, sandboxes, and CI integration
Difficulty: expert
Target language: Python
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
| [] | {
"target_language": "Python",
"developer_needs": [
"reproducibility",
"cost_latency_tradeoffs",
"evaluation_metrics",
"tests_are_truth"
],
"moe_experts": [
"agentic_systems_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 8a4648ce14272fe09995680aa6600fa855db38cf | |
train_34836 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | data_pipeline | advanced | Task: data_pipeline
Topic: Latency, cost, and reliability optimization
Difficulty: advanced
Target language: TypeScript
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
| [] | {
"target_language": "TypeScript",
"developer_needs": [
"governance",
"auditability",
"evaluation_metrics",
"cost_latency_tradeoffs"
],
"moe_experts": [
"data_curation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | c4d28bcfa7bc9b0226c32b9895f00b3def4a92d7 | |
train_34837 | 2026-01-01T00:00:00 | Code-specialized model families and sizing tradeoffs | failure_analysis | expert | Task: failure_analysis
Topic: Code-specialized model families and sizing tradeoffs
Difficulty: expert
Target language: Go
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
| [] | {
"target_language": "Go",
"developer_needs": [
"cost_latency_tradeoffs",
"reproducibility",
"governance",
"evaluation_metrics"
],
"moe_experts": [
"performance_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 07038c98bc88d7ebf3e436a223d3de55db257fc0 | |
train_34838 | 2026-01-01T00:00:00 | Governance, provenance, and licensing for code data | design | intermediate | Task: design
Topic: Governance, provenance, and licensing for code data
Difficulty: intermediate
Target language: Rust
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "Rust",
"developer_needs": [
"reproducibility",
"evaluation_metrics",
"cost_latency_tradeoffs",
"ci_integration"
],
"moe_experts": [
"coding_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 2cc92dedf1f08512af6d4d27f027921f071a52f2 | |
train_34839 | 2026-01-01T00:00:00 | Model merging, distillation, and continued pretraining | design | expert | Task: design
Topic: Model merging, distillation, and continued pretraining
Difficulty: expert
Target language: JavaScript
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "JavaScript",
"developer_needs": [
"ci_integration",
"evaluation_metrics",
"cost_latency_tradeoffs",
"auditability"
],
"moe_experts": [
"performance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 235b968d3c49bb14166464265ec8165034f496ff | |
train_34840 | 2026-01-01T00:00:00 | Code-specialized model families and sizing tradeoffs | compare | advanced | Task: compare
Topic: Code-specialized model families and sizing tradeoffs
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.
Compare: capability, cost, latency, reliability
| [] | {
"target_language": "Python",
"developer_needs": [
"governance",
"documentation",
"cost_latency_tradeoffs",
"tooling"
],
"moe_experts": [
"data_curation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | f75796afbd69ad839a014586c13401988eb59122 | |
train_34841 | 2026-01-01T00:00:00 | Extended context and repo-scale understanding | failure_analysis | expert | Task: failure_analysis
Topic: Extended context and repo-scale understanding
Difficulty: expert
Target language: 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.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "JavaScript",
"developer_needs": [
"security_gates",
"documentation",
"governance",
"cost_latency_tradeoffs"
],
"moe_experts": [
"agentic_systems_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | dbba1ebcb16f6c26cba387f00fa44fe09ff5688b | |
train_34842 | 2026-01-01T00:00:00 | Self-improving agents and feedback loops | compare | advanced | Task: compare
Topic: Self-improving agents and feedback loops
Difficulty: advanced
Target language: Python
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
| [] | {
"target_language": "Python",
"developer_needs": [
"governance",
"documentation",
"tests_are_truth",
"tooling"
],
"moe_experts": [
"security_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | afda002eb12abb36cf6ed25c332f88d6252463af | |
train_34843 | 2026-01-01T00:00:00 | Model merging, distillation, and continued pretraining | eval | expert | Task: eval
Topic: Model merging, distillation, and continued pretraining
Difficulty: expert
Target language: Java
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Java",
"developer_needs": [
"tests_are_truth",
"evaluation_metrics",
"ci_integration",
"repo_scale_reasoning"
],
"moe_experts": [
"governance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 37ac29b012721f565722cd3b520d428b096163b0 | |
train_34844 | 2026-01-01T00:00:00 | Reasoning-first coding models and tunable deliberation | failure_analysis | intermediate | Task: failure_analysis
Topic: Reasoning-first coding models and tunable deliberation
Difficulty: intermediate
Target language: Go
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
| [] | {
"target_language": "Go",
"developer_needs": [
"tooling",
"cost_latency_tradeoffs",
"documentation",
"security_gates"
],
"moe_experts": [
"performance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | b0551ea1e481548ae2a2e8938806bdc450461321 | |
train_34845 | 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: 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.
Compare: capability, cost, latency, reliability
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Python",
"developer_needs": [
"documentation",
"auditability",
"repo_scale_reasoning",
"ci_integration"
],
"moe_experts": [
"performance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 049594df47c84809364b96b777dd2d9ad7de460d | |
train_34846 | 2026-01-01T00:00:00 | Self-improving agents and feedback loops | patch_diff | intermediate | Task: patch_diff
Topic: Self-improving agents and feedback loops
Difficulty: intermediate
Target language: 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.
Patch (diff-style):
```diff
- if x == 0:
- return 1/x
+ if x == 0:
+ raise ValueError('division by zero')
```
Acceptance:
- Tests pass
- No new regressions
| [] | {
"target_language": "Bash",
"developer_needs": [
"tests_are_truth",
"ci_integration",
"auditability",
"evaluation_metrics"
],
"moe_experts": [
"coding_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 375af0e27b9c2766945eedbc5b54fffe5ca0808a | |
train_34847 | 2026-01-01T00:00:00 | Extended context and repo-scale understanding | compare | advanced | Task: compare
Topic: Extended context and repo-scale understanding
Difficulty: advanced
Target language: JavaScript
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
| [] | {
"target_language": "JavaScript",
"developer_needs": [
"governance",
"security_gates",
"ci_integration",
"auditability"
],
"moe_experts": [
"agentic_systems_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | f6fb37a3e7403955dbd3c57fba503503bb0a56a5 | |
train_34848 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | review | intermediate | Task: review
Topic: Latency, cost, and reliability optimization
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.
Review: correctness, security, performance, governance
| [] | {
"target_language": "Rust",
"developer_needs": [
"ci_integration",
"tooling",
"auditability",
"cost_latency_tradeoffs"
],
"moe_experts": [
"coding_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | e4c08fcfed1d42236b874b767f4dcc73ec369154 | |
train_34849 | 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: 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": [
"repo_scale_reasoning",
"reproducibility",
"evaluation_metrics",
"governance"
],
"moe_experts": [
"evaluation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 24942ec508063fc7b42c07ec544bfc0169f706e5 | |
train_34850 | 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: Bash
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "Bash",
"developer_needs": [
"auditability",
"evaluation_metrics",
"tests_are_truth",
"security_gates"
],
"moe_experts": [
"governance_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | c53c8266a7b0582add953313b10cb3c193109e6f | |
train_34851 | 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: JavaScript
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
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": [
"governance",
"tests_are_truth",
"evaluation_metrics",
"auditability"
],
"moe_experts": [
"agentic_systems_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 3d034d330390626a79782c13cbeb6e3424c094a5 | |
train_34852 | 2026-01-01T00:00:00 | Self-improving agents and feedback loops | eval | advanced | Task: eval
Topic: Self-improving agents and feedback loops
Difficulty: advanced
Target language: JavaScript
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
| [] | {
"target_language": "JavaScript",
"developer_needs": [
"reproducibility",
"cost_latency_tradeoffs",
"documentation",
"tooling"
],
"moe_experts": [
"agentic_systems_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 40ae4012cd992fb696e443a1fca9962efa2c8e85 | |
train_34853 | 2026-01-01T00:00:00 | Multimodal dev workflows (docs, diagrams, traces) | compare | advanced | Task: compare
Topic: Multimodal dev workflows (docs, diagrams, traces)
Difficulty: advanced
Target language: JavaScript
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
| [] | {
"target_language": "JavaScript",
"developer_needs": [
"reproducibility",
"auditability",
"tests_are_truth",
"governance"
],
"moe_experts": [
"performance_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 9920232e4867bc256261860e2b64d6f8a0fd0275 | |
train_34854 | 2026-01-01T00:00:00 | Secure code generation and policy gates | eval | advanced | Task: eval
Topic: Secure code generation and policy gates
Difficulty: advanced
Target language: C#
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
| [] | {
"target_language": "C#",
"developer_needs": [
"tooling",
"tests_are_truth",
"cost_latency_tradeoffs",
"repo_scale_reasoning"
],
"moe_experts": [
"data_curation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 65a90dbc3d71b89d8bb82c34e2508cc2b48e4552 | |
train_34855 | 2026-01-01T00:00:00 | Agentic coding systems (plan→edit→test→reflect) | eval | expert | Task: eval
Topic: Agentic coding systems (plan→edit→test→reflect)
Difficulty: expert
Target language: Python
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
| [] | {
"target_language": "Python",
"developer_needs": [
"cost_latency_tradeoffs",
"security_gates",
"evaluation_metrics",
"tests_are_truth"
],
"moe_experts": [
"governance_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 95e6cf5a69b45016cf703ee9145ee6644f9b6b95 | |
train_34856 | 2026-01-01T00:00:00 | Dataset curation pipelines (filter, dedupe, quality) | compare | intermediate | Task: compare
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: intermediate
Target language: TypeScript
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "TypeScript",
"developer_needs": [
"ci_integration",
"tests_are_truth",
"tooling",
"auditability"
],
"moe_experts": [
"agentic_systems_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 5b81cad7912ec54d5cf01837d1956fae251482ce | |
train_34857 | 2026-01-01T00:00:00 | Tool calling, sandboxes, and CI integration | data_pipeline | expert | Task: data_pipeline
Topic: Tool calling, sandboxes, and CI integration
Difficulty: expert
Target language: JavaScript
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
| [] | {
"target_language": "JavaScript",
"developer_needs": [
"documentation",
"repo_scale_reasoning",
"tests_are_truth",
"auditability"
],
"moe_experts": [
"evaluation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | c95a1d888a2d095c431eab458d888ee867a6110c | |
train_34858 | 2026-01-01T00:00:00 | Reasoning-first coding models and tunable deliberation | explain | intermediate | Task: explain
Topic: Reasoning-first coding models and tunable deliberation
Difficulty: intermediate
Target language: JavaScript
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "JavaScript",
"developer_needs": [
"tooling",
"evaluation_metrics",
"auditability",
"reproducibility"
],
"moe_experts": [
"security_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | cf6003dff70abf96796778c9a6724cf3a6e4baa7 | |
train_34859 | 2026-01-01T00:00:00 | Multimodal dev workflows (docs, diagrams, traces) | review | advanced | Task: review
Topic: Multimodal dev workflows (docs, diagrams, traces)
Difficulty: advanced
Target language: Python
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Review: correctness, security, performance, governance
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Python",
"developer_needs": [
"evaluation_metrics",
"governance",
"cost_latency_tradeoffs",
"security_gates"
],
"moe_experts": [
"evaluation_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | faab8848fade1809ab4d4bcbe8b7568d2e63eb29 | |
train_34860 | 2026-01-01T00:00:00 | Mixture-of-Experts (MoE) for code | agent_loop | intermediate | Task: agent_loop
Topic: Mixture-of-Experts (MoE) for code
Difficulty: intermediate
Target language: Rust
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
| [] | {
"target_language": "Rust",
"developer_needs": [
"reproducibility",
"ci_integration",
"documentation",
"tests_are_truth"
],
"moe_experts": [
"agentic_systems_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | a4ab236d59fe5ca4962400fea149049ef195769c | |
train_34861 | 2026-01-01T00:00:00 | Multimodal dev workflows (docs, diagrams, traces) | compare | expert | Task: compare
Topic: Multimodal dev workflows (docs, diagrams, traces)
Difficulty: expert
Target language: 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.
Compare: capability, cost, latency, reliability
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Go",
"developer_needs": [
"evaluation_metrics",
"auditability",
"repo_scale_reasoning",
"documentation"
],
"moe_experts": [
"agentic_systems_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | cb76e16184c1905922b362bc24618566c01513da | |
train_34862 | 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: C#
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
| [] | {
"target_language": "C#",
"developer_needs": [
"auditability",
"repo_scale_reasoning",
"documentation",
"security_gates"
],
"moe_experts": [
"security_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | a7c45e993d157b240c9a14195691f575c9f23fe1 | |
train_34863 | 2026-01-01T00:00:00 | Mixture-of-Experts (MoE) for code | design | advanced | Task: design
Topic: Mixture-of-Experts (MoE) for code
Difficulty: advanced
Target language: TypeScript
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "TypeScript",
"developer_needs": [
"repo_scale_reasoning",
"reproducibility",
"auditability",
"documentation"
],
"moe_experts": [
"coding_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | a90c68956a153c7b15089ef1e5bd03735e19ba13 | |
train_34864 | 2026-01-01T00:00:00 | SWE-bench style real-repo evaluation | failure_analysis | advanced | Task: failure_analysis
Topic: SWE-bench style real-repo evaluation
Difficulty: advanced
Target language: TypeScript
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
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": [
"documentation",
"security_gates",
"auditability",
"cost_latency_tradeoffs"
],
"moe_experts": [
"evaluation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | ea573220cff5494d14d33da02432bbac65eb8842 | |
train_34865 | 2026-01-01T00:00:00 | Reasoning-first coding models and tunable deliberation | agent_loop | advanced | Task: agent_loop
Topic: Reasoning-first coding models and tunable deliberation
Difficulty: advanced
Target language: Go
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
| [] | {
"target_language": "Go",
"developer_needs": [
"repo_scale_reasoning",
"tests_are_truth",
"auditability",
"evaluation_metrics"
],
"moe_experts": [
"governance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | bba29bcdfde2553444371523af9a613be09589fb | |
train_34866 | 2026-01-01T00:00:00 | Dataset curation pipelines (filter, dedupe, quality) | eval | advanced | Task: eval
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: advanced
Target language: Python
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Python",
"developer_needs": [
"reproducibility",
"tooling",
"auditability",
"security_gates"
],
"moe_experts": [
"security_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | d3225d57a21649fab1b05e6e7cf5ec82ebee88a3 | |
train_34867 | 2026-01-01T00:00:00 | Reasoning-first coding models and tunable deliberation | eval | advanced | Task: eval
Topic: Reasoning-first coding models and tunable deliberation
Difficulty: advanced
Target language: Go
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
| [] | {
"target_language": "Go",
"developer_needs": [
"governance",
"ci_integration",
"auditability",
"tests_are_truth"
],
"moe_experts": [
"data_curation_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 65c5c4bd22654a2923f38a09babe0bd0b36e7a22 | |
train_34868 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | explain | intermediate | Task: explain
Topic: Latency, cost, and reliability optimization
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
| [] | {
"target_language": "Rust",
"developer_needs": [
"security_gates",
"evaluation_metrics",
"tooling",
"reproducibility"
],
"moe_experts": [
"performance_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 7b025663d8e832fa6e7363f6d1ddd4f7f424e25d | |
train_34869 | 2026-01-01T00:00:00 | Self-improving agents and feedback loops | explain | intermediate | Task: explain
Topic: Self-improving agents and feedback loops
Difficulty: intermediate
Target language: Go
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "Go",
"developer_needs": [
"tests_are_truth",
"evaluation_metrics",
"cost_latency_tradeoffs",
"reproducibility"
],
"moe_experts": [
"evaluation_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 3de555f230bc051c7b925b94d9c3ce8083e34fd4 | |
train_34870 | 2026-01-01T00:00:00 | Agentic coding systems (plan→edit→test→reflect) | code | expert | Task: code
Topic: Agentic coding systems (plan→edit→test→reflect)
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
| [] | {
"target_language": "Go",
"developer_needs": [
"auditability",
"governance",
"tests_are_truth",
"documentation"
],
"moe_experts": [
"performance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 73101921169c5ce7b7673407e4e62e000d5db79c | |
train_34871 | 2026-01-01T00:00:00 | Dataset curation pipelines (filter, dedupe, quality) | agent_loop | intermediate | Task: agent_loop
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: intermediate
Target language: C#
Context: 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": "C#",
"developer_needs": [
"documentation",
"ci_integration",
"tests_are_truth",
"cost_latency_tradeoffs"
],
"moe_experts": [
"performance_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | bee3f650345c67566576331d2e2070fc27cc07e9 | |
train_34872 | 2026-01-01T00:00:00 | SWE-bench style real-repo evaluation | review | intermediate | Task: review
Topic: SWE-bench style real-repo evaluation
Difficulty: intermediate
Target language: C#
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Review: correctness, security, performance, governance
| [] | {
"target_language": "C#",
"developer_needs": [
"cost_latency_tradeoffs",
"tooling",
"governance",
"auditability"
],
"moe_experts": [
"governance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 53d847bf7cb7b09b1d3a6596988f54eb84266e49 | |
train_34873 | 2026-01-01T00:00:00 | Model merging, distillation, and continued pretraining | agent_loop | expert | Task: agent_loop
Topic: Model merging, distillation, and continued pretraining
Difficulty: expert
Target language: Bash
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
| [] | {
"target_language": "Bash",
"developer_needs": [
"auditability",
"ci_integration",
"tooling",
"documentation"
],
"moe_experts": [
"performance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 2dcc7dd4e77e13279ae51e82201a3d52d7f01cf9 | |
train_34874 | 2026-01-01T00:00:00 | SWE-bench style real-repo evaluation | compare | expert | Task: compare
Topic: SWE-bench style real-repo evaluation
Difficulty: expert
Target language: 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": [
"reproducibility",
"documentation",
"security_gates",
"cost_latency_tradeoffs"
],
"moe_experts": [
"agentic_systems_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | dd22fb91beedd626991fa006eb86b5f491efebe9 | |
train_34875 | 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: SQL
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "SQL",
"developer_needs": [
"documentation",
"repo_scale_reasoning",
"tooling",
"security_gates"
],
"moe_experts": [
"evaluation_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | fe12cc3492f49edb2ddc23dcbbcbb423c11d6230 | |
train_34876 | 2026-01-01T00:00:00 | Tool calling, sandboxes, and CI integration | code | expert | Task: code
Topic: Tool calling, sandboxes, and CI integration
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.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "Java",
"developer_needs": [
"ci_integration",
"governance",
"security_gates",
"repo_scale_reasoning"
],
"moe_experts": [
"security_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 98817e94fdf3d056da78f62dbb10caf0a32a897f | |
train_34877 | 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: 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
| [] | {
"target_language": "JavaScript",
"developer_needs": [
"evaluation_metrics",
"governance",
"documentation",
"tooling"
],
"moe_experts": [
"governance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 5678613f1b01eeb27e3654d09b33d09dfe3b7193 | |
train_34878 | 2026-01-01T00:00:00 | Reasoning-first coding models and tunable deliberation | agent_loop | expert | Task: agent_loop
Topic: Reasoning-first coding models and tunable deliberation
Difficulty: expert
Target language: TypeScript
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
| [] | {
"target_language": "TypeScript",
"developer_needs": [
"repo_scale_reasoning",
"auditability",
"reproducibility",
"documentation"
],
"moe_experts": [
"agentic_systems_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | ca905e5e0a2d2b5f204c4b5ace10612fec15e8ee | |
train_34879 | 2026-01-01T00:00:00 | Mixture-of-Experts (MoE) for code | patch_diff | advanced | Task: patch_diff
Topic: Mixture-of-Experts (MoE) for code
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.
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",
"repo_scale_reasoning",
"governance"
],
"moe_experts": [
"security_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | b7f930fdee283fd57890f75bd13384438ae81f2c | |
train_34880 | 2026-01-01T00:00:00 | Extended context and repo-scale understanding | compare | intermediate | Task: compare
Topic: Extended context and repo-scale understanding
Difficulty: intermediate
Target language: 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.
Compare: capability, cost, latency, reliability
| [] | {
"target_language": "Bash",
"developer_needs": [
"documentation",
"evaluation_metrics",
"ci_integration",
"repo_scale_reasoning"
],
"moe_experts": [
"data_curation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 4a5121faa79310d7b5a58cc758560e493f547227 | |
train_34881 | 2026-01-01T00:00:00 | Reasoning-first coding models and tunable deliberation | code | expert | Task: code
Topic: Reasoning-first coding models and tunable deliberation
Difficulty: expert
Target language: 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": [
"cost_latency_tradeoffs",
"auditability",
"evaluation_metrics",
"documentation"
],
"moe_experts": [
"evaluation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 59e572769cb84d17b227ef8a26d9d99d912d16d9 | |
train_34882 | 2026-01-01T00:00:00 | Reasoning-first coding models and tunable deliberation | patch_diff | expert | Task: patch_diff
Topic: Reasoning-first coding models and tunable deliberation
Difficulty: expert
Target language: 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": [
"tooling",
"tests_are_truth",
"auditability",
"security_gates"
],
"moe_experts": [
"evaluation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 5fc28f27c7e3e8471d18af774c0206a5b1bae241 | |
train_34883 | 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: Go
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Go",
"developer_needs": [
"reproducibility",
"ci_integration",
"repo_scale_reasoning",
"tooling"
],
"moe_experts": [
"evaluation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 31a84ea395e38af05635f908bd404d45507aa602 | |
train_34884 | 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: 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
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "TypeScript",
"developer_needs": [
"evaluation_metrics",
"ci_integration",
"reproducibility",
"auditability"
],
"moe_experts": [
"governance_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 89f98d9681640a5909cd900542957f3200956755 | |
train_34885 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | failure_analysis | advanced | Task: failure_analysis
Topic: Latency, cost, and reliability optimization
Difficulty: advanced
Target language: Rust
Context: 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": "Rust",
"developer_needs": [
"repo_scale_reasoning",
"security_gates",
"auditability",
"tooling"
],
"moe_experts": [
"governance_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 5360532ca720beb24781bd2b6885f6361849033e | |
train_34886 | 2026-01-01T00:00:00 | Extended context and repo-scale understanding | data_pipeline | advanced | Task: data_pipeline
Topic: Extended context and repo-scale understanding
Difficulty: advanced
Target language: SQL
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
| [] | {
"target_language": "SQL",
"developer_needs": [
"repo_scale_reasoning",
"auditability",
"ci_integration",
"evaluation_metrics"
],
"moe_experts": [
"governance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 01ee8f7c76adbec356b55a79e13ff8e5ff527dd6 | |
train_34887 | 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: 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.
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": [
"repo_scale_reasoning",
"security_gates",
"tests_are_truth",
"evaluation_metrics"
],
"moe_experts": [
"performance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | b8c27f161fa5728631e4ff195cbdffcbbc25fd15 | |
train_34888 | 2026-01-01T00:00:00 | Mixture-of-Experts (MoE) for code | review | advanced | Task: review
Topic: Mixture-of-Experts (MoE) for code
Difficulty: advanced
Target language: C#
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Review: correctness, security, performance, governance
| [] | {
"target_language": "C#",
"developer_needs": [
"tooling",
"repo_scale_reasoning",
"security_gates",
"reproducibility"
],
"moe_experts": [
"performance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 0164646ede2931d81de8e1166bbaa2670910158e | |
train_34889 | 2026-01-01T00:00:00 | Extended context and repo-scale understanding | explain | expert | Task: explain
Topic: Extended context and repo-scale understanding
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.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "Java",
"developer_needs": [
"reproducibility",
"evaluation_metrics",
"ci_integration",
"governance"
],
"moe_experts": [
"security_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 0760ff22af4c5981abcfb93c05c3624979c45a99 | |
train_34890 | 2026-01-01T00:00:00 | Agentic coding systems (plan→edit→test→reflect) | explain | advanced | Task: explain
Topic: Agentic coding systems (plan→edit→test→reflect)
Difficulty: advanced
Target language: C#
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "C#",
"developer_needs": [
"evaluation_metrics",
"governance",
"ci_integration",
"security_gates"
],
"moe_experts": [
"evaluation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 0184b0fdf199fb200d1f0ed66c26118c2d14aa7a | |
train_34891 | 2026-01-01T00:00:00 | Reasoning-first coding models and tunable deliberation | failure_analysis | expert | Task: failure_analysis
Topic: Reasoning-first coding models and tunable deliberation
Difficulty: expert
Target language: C#
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
| [] | {
"target_language": "C#",
"developer_needs": [
"repo_scale_reasoning",
"documentation",
"tooling",
"ci_integration"
],
"moe_experts": [
"security_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | b3e78693f1280e25526350aaa742ba386e258583 | |
train_34892 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | compare | intermediate | Task: compare
Topic: Latency, cost, and reliability optimization
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
| [] | {
"target_language": "Python",
"developer_needs": [
"tooling",
"security_gates",
"governance",
"tests_are_truth"
],
"moe_experts": [
"governance_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 8667627c99ac36248210b22f79ade54631f9bbb7 | |
train_34893 | 2026-01-01T00:00:00 | Tool calling, sandboxes, and CI integration | eval | advanced | Task: eval
Topic: Tool calling, sandboxes, and CI integration
Difficulty: advanced
Target language: Rust
Context: 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": [
"security_gates",
"reproducibility",
"cost_latency_tradeoffs",
"auditability"
],
"moe_experts": [
"performance_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 2b699f9fcc7de4007e627cdb6ac932a8f34c8e09 | |
train_34894 | 2026-01-01T00:00:00 | Code-specialized model families and sizing tradeoffs | data_pipeline | advanced | Task: data_pipeline
Topic: Code-specialized model families and sizing tradeoffs
Difficulty: advanced
Target language: C#
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
| [] | {
"target_language": "C#",
"developer_needs": [
"reproducibility",
"auditability",
"documentation",
"governance"
],
"moe_experts": [
"governance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | fbe1267f2c8e6a34872e91045f2452b37391cce2 | |
train_34895 | 2026-01-01T00:00:00 | Dataset curation pipelines (filter, dedupe, quality) | compare | intermediate | Task: compare
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: intermediate
Target language: Go
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
| [] | {
"target_language": "Go",
"developer_needs": [
"evaluation_metrics",
"cost_latency_tradeoffs",
"tooling",
"repo_scale_reasoning"
],
"moe_experts": [
"data_curation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 7e20276d6a5b3d395f3ada81af8f1ac9a31223f6 | |
train_34896 | 2026-01-01T00:00:00 | Model merging, distillation, and continued pretraining | compare | expert | Task: compare
Topic: Model merging, distillation, and continued pretraining
Difficulty: expert
Target language: 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.
Compare: capability, cost, latency, reliability
| [] | {
"target_language": "Bash",
"developer_needs": [
"tooling",
"tests_are_truth",
"governance",
"auditability"
],
"moe_experts": [
"evaluation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | d27aebe97df48fe4ef3a6f0c777e405b064f9f99 | |
train_34897 | 2026-01-01T00:00:00 | Reasoning-first coding models and tunable deliberation | code | advanced | Task: code
Topic: Reasoning-first coding models and tunable deliberation
Difficulty: advanced
Target language: 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.
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": [
"documentation",
"tooling",
"ci_integration",
"evaluation_metrics"
],
"moe_experts": [
"coding_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 7e4a7c6a09573e6723935c58ef3fe77f5c84eab4 | |
train_34898 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | explain | intermediate | Task: explain
Topic: Latency, cost, and reliability optimization
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.
Design with risks, metrics, acceptance criteria
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "JavaScript",
"developer_needs": [
"security_gates",
"repo_scale_reasoning",
"reproducibility",
"governance"
],
"moe_experts": [
"data_curation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 2ce86311b13b4cecd4184dde0374ce3bcf1e50ff | |
train_34899 | 2026-01-01T00:00:00 | Dataset curation pipelines (filter, dedupe, quality) | patch_diff | expert | Task: patch_diff
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: expert
Target language: JavaScript
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Patch (diff-style):
```diff
- if x == 0:
- return 1/x
+ if x == 0:
+ raise ValueError('division by zero')
```
Acceptance:
- Tests pass
- No new regressions
| [] | {
"target_language": "JavaScript",
"developer_needs": [
"security_gates",
"governance",
"documentation",
"evaluation_metrics"
],
"moe_experts": [
"data_curation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 2b74eeafe7b6dfe0526f071fc04ea1e1e82be15e |
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