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_02200 | 2026-01-01T00:00:00 | Secure code generation and policy gates | code | expert | Task: code
Topic: Secure code generation and policy gates
Difficulty: expert
Target language: SQL
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "SQL",
"developer_needs": [
"reproducibility",
"cost_latency_tradeoffs",
"ci_integration",
"security_gates"
],
"moe_experts": [
"performance_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 83c35ba9bc239b65352df66df7168599f51c2f2a | |
train_02201 | 2026-01-01T00:00:00 | Mixture-of-Experts (MoE) for code | design | expert | Task: design
Topic: Mixture-of-Experts (MoE) for code
Difficulty: expert
Target language: 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
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Bash",
"developer_needs": [
"auditability",
"security_gates",
"tooling",
"tests_are_truth"
],
"moe_experts": [
"evaluation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 03fb2111c0beefdf3aac5b3dd5e769c4280118cd | |
train_02202 | 2026-01-01T00:00:00 | Dataset curation pipelines (filter, dedupe, quality) | design | advanced | Task: design
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: advanced
Target language: 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": [
"cost_latency_tradeoffs",
"evaluation_metrics",
"documentation",
"repo_scale_reasoning"
],
"moe_experts": [
"coding_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | b0cca1f995efcd6694e0a1ceb22c16e071e64e7f | |
train_02203 | 2026-01-01T00:00:00 | Model merging, distillation, and continued pretraining | patch_diff | intermediate | Task: patch_diff
Topic: Model merging, distillation, and continued pretraining
Difficulty: intermediate
Target language: 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
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Bash",
"developer_needs": [
"evaluation_metrics",
"reproducibility",
"tooling",
"cost_latency_tradeoffs"
],
"moe_experts": [
"data_curation_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | c7577e1e83a587bb9404c9bbef1183e66bb4079a | |
train_02204 | 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: TypeScript
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "TypeScript",
"developer_needs": [
"security_gates",
"reproducibility",
"ci_integration",
"evaluation_metrics"
],
"moe_experts": [
"coding_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 2cf3b640d28f27a3d0e1feff2db768e5d9efa6bb | |
train_02205 | 2026-01-01T00:00:00 | Extended context and repo-scale understanding | design | advanced | Task: design
Topic: Extended context and repo-scale understanding
Difficulty: advanced
Target language: C#
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "C#",
"developer_needs": [
"evaluation_metrics",
"ci_integration",
"governance",
"tooling"
],
"moe_experts": [
"data_curation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | f9eb5cb84cab97ea1cd358f8c21339bcbf5fc5cd | |
train_02206 | 2026-01-01T00:00:00 | SWE-bench style real-repo evaluation | eval | expert | Task: eval
Topic: SWE-bench style real-repo evaluation
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.
Eval:
pass@k, time-to-green, regressions, diff size
| [] | {
"target_language": "Go",
"developer_needs": [
"security_gates",
"evaluation_metrics",
"tooling",
"reproducibility"
],
"moe_experts": [
"evaluation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 313e38f25d8895bece5286c465f5589f6860b71c | |
train_02207 | 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: 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": [
"governance",
"documentation",
"tests_are_truth",
"repo_scale_reasoning"
],
"moe_experts": [
"evaluation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 112ff6ad8476e8e954ab8ffa67f24bf7c4a4b14b | |
train_02208 | 2026-01-01T00:00:00 | Dataset curation pipelines (filter, dedupe, quality) | compare | expert | Task: compare
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: expert
Target language: Bash
Context: 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": "Bash",
"developer_needs": [
"tests_are_truth",
"repo_scale_reasoning",
"auditability",
"security_gates"
],
"moe_experts": [
"coding_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 12188c90dff3e009d85b9745cb863729fb899342 | |
train_02209 | 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: C#
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "C#",
"developer_needs": [
"tests_are_truth",
"reproducibility",
"evaluation_metrics",
"documentation"
],
"moe_experts": [
"coding_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | e648df8cdf5eb288e661db08a730d0084c84b7c4 | |
train_02210 | 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: 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.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
| [] | {
"target_language": "Bash",
"developer_needs": [
"documentation",
"security_gates",
"governance",
"ci_integration"
],
"moe_experts": [
"performance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 4e1a10dabd06958be9ee99bf1d92fd5a1d8eaa9d | |
train_02211 | 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": [
"tests_are_truth",
"ci_integration",
"auditability",
"documentation"
],
"moe_experts": [
"security_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 99542cca70308c9466dc68c7c2a2165295f93cef | |
train_02212 | 2026-01-01T00:00:00 | Tool calling, sandboxes, and CI integration | compare | advanced | Task: compare
Topic: Tool calling, sandboxes, and CI integration
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.
Compare: capability, cost, latency, reliability
| [] | {
"target_language": "Java",
"developer_needs": [
"tests_are_truth",
"repo_scale_reasoning",
"auditability",
"ci_integration"
],
"moe_experts": [
"coding_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | ebdf2da374b96f062706d6b58f048b0468ec5a95 | |
train_02213 | 2026-01-01T00:00:00 | Agentic coding systems (plan→edit→test→reflect) | agent_loop | expert | Task: agent_loop
Topic: Agentic coding systems (plan→edit→test→reflect)
Difficulty: expert
Target language: SQL
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
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": [
"security_gates",
"cost_latency_tradeoffs",
"auditability",
"repo_scale_reasoning"
],
"moe_experts": [
"security_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | a62bc769854c3df5fde7f0c9abed1e8df341508a | |
train_02214 | 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: 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": [
"governance",
"ci_integration",
"reproducibility",
"cost_latency_tradeoffs"
],
"moe_experts": [
"governance_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 08d517b3b53f278623901f963f3c5ba7a65e17e8 | |
train_02215 | 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: 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": [
"repo_scale_reasoning",
"governance",
"reproducibility",
"cost_latency_tradeoffs"
],
"moe_experts": [
"data_curation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 4e57c4265c8c7844e06cd0577c05cde1e5518983 | |
train_02216 | 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: TypeScript
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
| [] | {
"target_language": "TypeScript",
"developer_needs": [
"tooling",
"tests_are_truth",
"documentation",
"repo_scale_reasoning"
],
"moe_experts": [
"coding_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | f22a10b48336a687494e825b606ccd7e768020d2 | |
train_02217 | 2026-01-01T00:00:00 | Self-improving agents and feedback loops | compare | expert | Task: compare
Topic: Self-improving agents and feedback loops
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.
Compare: capability, cost, latency, reliability
| [] | {
"target_language": "Bash",
"developer_needs": [
"documentation",
"evaluation_metrics",
"tooling",
"cost_latency_tradeoffs"
],
"moe_experts": [
"performance_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 861372f45563d49d95a880e7cfcb750d7031792f | |
train_02218 | 2026-01-01T00:00:00 | Tool calling, sandboxes, and CI integration | data_pipeline | intermediate | Task: data_pipeline
Topic: Tool calling, sandboxes, and CI integration
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.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
| [] | {
"target_language": "Java",
"developer_needs": [
"governance",
"ci_integration",
"security_gates",
"tests_are_truth"
],
"moe_experts": [
"security_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 5136f4f035e7c487a4433fb55c0a8f969fa82ae1 | |
train_02219 | 2026-01-01T00:00:00 | Tool calling, sandboxes, and CI integration | compare | expert | Task: compare
Topic: Tool calling, sandboxes, and CI integration
Difficulty: expert
Target language: 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.
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": [
"auditability",
"evaluation_metrics",
"documentation",
"cost_latency_tradeoffs"
],
"moe_experts": [
"governance_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | b0fa2aba56899e7b3fca9b08fb527e9fdd75594d | |
train_02220 | 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: Python
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Python",
"developer_needs": [
"tests_are_truth",
"reproducibility",
"security_gates",
"tooling"
],
"moe_experts": [
"coding_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 098d23dd976c463521dd60ab14847b5dd8d38853 | |
train_02221 | 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: 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.
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": [
"cost_latency_tradeoffs",
"tests_are_truth",
"reproducibility",
"repo_scale_reasoning"
],
"moe_experts": [
"agentic_systems_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 5dccc9285dbfc53981f4acaa9ba114ed056579f9 | |
train_02222 | 2026-01-01T00:00:00 | SWE-bench style real-repo evaluation | design | advanced | Task: design
Topic: SWE-bench style real-repo evaluation
Difficulty: advanced
Target language: Python
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "Python",
"developer_needs": [
"cost_latency_tradeoffs",
"documentation",
"evaluation_metrics",
"reproducibility"
],
"moe_experts": [
"governance_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | a0b4ec6a57829bb98cca743860c53b4e3152fc9b | |
train_02223 | 2026-01-01T00:00:00 | Multimodal dev workflows (docs, diagrams, traces) | data_pipeline | advanced | Task: data_pipeline
Topic: Multimodal dev workflows (docs, diagrams, traces)
Difficulty: advanced
Target language: Go
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Go",
"developer_needs": [
"evaluation_metrics",
"ci_integration",
"security_gates",
"repo_scale_reasoning"
],
"moe_experts": [
"coding_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | bad4aac8e328ef35b756680fadd16858311e9e4e | |
train_02224 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | code | advanced | Task: code
Topic: Latency, cost, and reliability optimization
Difficulty: advanced
Target language: Bash
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "Bash",
"developer_needs": [
"documentation",
"tooling",
"repo_scale_reasoning",
"ci_integration"
],
"moe_experts": [
"security_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 0497ae48ebc4d4f488c9d18ca74e135f3fc755fd | |
train_02225 | 2026-01-01T00:00:00 | Secure code generation and policy gates | data_pipeline | intermediate | Task: data_pipeline
Topic: Secure code generation and policy gates
Difficulty: intermediate
Target language: Java
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
| [] | {
"target_language": "Java",
"developer_needs": [
"auditability",
"ci_integration",
"evaluation_metrics",
"repo_scale_reasoning"
],
"moe_experts": [
"agentic_systems_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | ad1bc191f2ad801cff55ddc09db44e0e44c40a8d | |
train_02226 | 2026-01-01T00:00:00 | SWE-bench style real-repo evaluation | review | advanced | Task: review
Topic: SWE-bench style real-repo evaluation
Difficulty: advanced
Target language: Go
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Review: correctness, security, performance, governance
| [] | {
"target_language": "Go",
"developer_needs": [
"reproducibility",
"tooling",
"security_gates",
"documentation"
],
"moe_experts": [
"evaluation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 042e7a645ab11133703c8d67a7b73f3ba38835e0 | |
train_02227 | 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: 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": [
"governance",
"repo_scale_reasoning",
"auditability",
"evaluation_metrics"
],
"moe_experts": [
"performance_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 5f1a82a4a56f25b25ec1aad06ca17987995101a0 | |
train_02228 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | compare | advanced | Task: compare
Topic: Latency, cost, and reliability optimization
Difficulty: advanced
Target language: Rust
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
| [] | {
"target_language": "Rust",
"developer_needs": [
"auditability",
"governance",
"cost_latency_tradeoffs",
"reproducibility"
],
"moe_experts": [
"evaluation_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 49215e6c7fb5a554bd1c072c802424182587d8d8 | |
train_02229 | 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: 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.
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",
"tests_are_truth",
"governance",
"auditability"
],
"moe_experts": [
"coding_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 34d726b2648eb29dea639058c967fbc4295d76a2 | |
train_02230 | 2026-01-01T00:00:00 | SWE-bench style real-repo evaluation | design | intermediate | Task: design
Topic: SWE-bench style real-repo evaluation
Difficulty: intermediate
Target language: 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": [
"tests_are_truth",
"governance",
"repo_scale_reasoning",
"documentation"
],
"moe_experts": [
"governance_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 838847b678bb9a097cb4ad91188e85d54e4f730b | |
train_02231 | 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: 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": [
"ci_integration",
"repo_scale_reasoning",
"tooling",
"governance"
],
"moe_experts": [
"security_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | da277eafc9ae803f9ddc84e0a9646f198c2d4512 | |
train_02232 | 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: 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": [
"documentation",
"repo_scale_reasoning",
"evaluation_metrics",
"ci_integration"
],
"moe_experts": [
"evaluation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 9dc5317574ed5cee21e721ebab6064b7c6a91036 | |
train_02233 | 2026-01-01T00:00:00 | Self-improving agents and feedback loops | eval | intermediate | Task: eval
Topic: Self-improving agents and feedback loops
Difficulty: intermediate
Target language: 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
| [
"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",
"documentation",
"tooling",
"auditability"
],
"moe_experts": [
"security_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | fcb4f3d795176c651478b644755fb48e33d4d7d1 | |
train_02234 | 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: 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": [
"auditability",
"tests_are_truth",
"reproducibility",
"cost_latency_tradeoffs"
],
"moe_experts": [
"agentic_systems_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | a51c9dd11d5ef6f9ccafc46ff751169affb39dd2 | |
train_02235 | 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: 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": [
"documentation",
"auditability",
"ci_integration",
"security_gates"
],
"moe_experts": [
"coding_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 31d75345c63c5eef815550af1af0de712b0c1ed4 | |
train_02236 | 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: SQL
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
| [] | {
"target_language": "SQL",
"developer_needs": [
"tooling",
"governance",
"documentation",
"repo_scale_reasoning"
],
"moe_experts": [
"data_curation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | d36d17606321f4b601195ffe150df8001d382da0 | |
train_02237 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | agent_loop | expert | Task: agent_loop
Topic: Latency, cost, and reliability optimization
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
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Python",
"developer_needs": [
"ci_integration",
"security_gates",
"reproducibility",
"auditability"
],
"moe_experts": [
"performance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | c9671b66ab56c51f7fceb59c4f93f9b09ce4bc4e | |
train_02238 | 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: 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
| [] | {
"target_language": "Bash",
"developer_needs": [
"tooling",
"cost_latency_tradeoffs",
"evaluation_metrics",
"governance"
],
"moe_experts": [
"agentic_systems_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 8e40e82949b17b905d58b01519bc31757b7c031c | |
train_02239 | 2026-01-01T00:00:00 | Reasoning-first coding models and tunable deliberation | review | intermediate | Task: review
Topic: Reasoning-first coding models and tunable deliberation
Difficulty: intermediate
Target language: 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.
Review: correctness, security, performance, governance
| [] | {
"target_language": "Python",
"developer_needs": [
"cost_latency_tradeoffs",
"governance",
"documentation",
"auditability"
],
"moe_experts": [
"data_curation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 8bf5e786a5c18d4b47b282b8960a4da1312c9929 | |
train_02240 | 2026-01-01T00:00:00 | Agentic coding systems (plan→edit→test→reflect) | compare | advanced | Task: compare
Topic: Agentic coding systems (plan→edit→test→reflect)
Difficulty: advanced
Target language: 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.
Compare: capability, cost, latency, reliability
| [] | {
"target_language": "TypeScript",
"developer_needs": [
"auditability",
"tests_are_truth",
"documentation",
"ci_integration"
],
"moe_experts": [
"coding_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 4465e0e68ab0c1d3e49b9509684f03e638890a38 | |
train_02241 | 2026-01-01T00:00:00 | Agentic coding systems (plan→edit→test→reflect) | agent_loop | intermediate | Task: agent_loop
Topic: Agentic coding systems (plan→edit→test→reflect)
Difficulty: intermediate
Target language: 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.
Loop: Plan → Edit → Test → Reflect → Human gate
| [] | {
"target_language": "Python",
"developer_needs": [
"repo_scale_reasoning",
"evaluation_metrics",
"cost_latency_tradeoffs",
"tooling"
],
"moe_experts": [
"evaluation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 339ecdbc2ca38fdc9c300b8ce8dbb8fe7feac0c9 | |
train_02242 | 2026-01-01T00:00:00 | Self-improving agents and feedback loops | review | expert | Task: review
Topic: Self-improving agents and feedback loops
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.
Review: correctness, security, performance, governance
| [] | {
"target_language": "TypeScript",
"developer_needs": [
"tests_are_truth",
"tooling",
"ci_integration",
"evaluation_metrics"
],
"moe_experts": [
"performance_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | fd3353fd2a27f5b60ef8a6074b00007c906c6530 | |
train_02243 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | failure_analysis | advanced | Task: failure_analysis
Topic: Latency, cost, and reliability optimization
Difficulty: advanced
Target language: Bash
Context: 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": "Bash",
"developer_needs": [
"tests_are_truth",
"reproducibility",
"auditability",
"tooling"
],
"moe_experts": [
"performance_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 00e6a6c0eede6038c05876621b8b0daecc710d5f | |
train_02244 | 2026-01-01T00:00:00 | Model merging, distillation, and continued pretraining | data_pipeline | intermediate | Task: data_pipeline
Topic: Model merging, distillation, and continued pretraining
Difficulty: intermediate
Target language: Python
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
| [] | {
"target_language": "Python",
"developer_needs": [
"governance",
"security_gates",
"tooling",
"ci_integration"
],
"moe_experts": [
"performance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 672c74641191544321e4cc08f0f39f4150a9ad03 | |
train_02245 | 2026-01-01T00:00:00 | Multimodal dev workflows (docs, diagrams, traces) | explain | intermediate | Task: explain
Topic: Multimodal dev workflows (docs, diagrams, traces)
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
| [
"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",
"ci_integration",
"cost_latency_tradeoffs"
],
"moe_experts": [
"coding_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 14b0b5f3da3d0f388ef8efe7078c7209fc06d1ee | |
train_02246 | 2026-01-01T00:00:00 | Code-specialized model families and sizing tradeoffs | eval | advanced | Task: eval
Topic: Code-specialized model families and sizing tradeoffs
Difficulty: advanced
Target language: Bash
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
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": [
"repo_scale_reasoning",
"tooling",
"auditability",
"security_gates"
],
"moe_experts": [
"performance_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | e832c9f95ab85484a80cb3852f946debfee2f631 | |
train_02247 | 2026-01-01T00:00:00 | Governance, provenance, and licensing for code data | patch_diff | advanced | Task: patch_diff
Topic: Governance, provenance, and licensing for code data
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.
Patch (diff-style):
```diff
- if x == 0:
- return 1/x
+ if x == 0:
+ raise ValueError('division by zero')
```
Acceptance:
- Tests pass
- No new regressions
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "C#",
"developer_needs": [
"repo_scale_reasoning",
"reproducibility",
"auditability",
"cost_latency_tradeoffs"
],
"moe_experts": [
"data_curation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 66b1ecb6492c7da4cc1d7362ebcdf8f69b0c1062 | |
train_02248 | 2026-01-01T00:00:00 | Secure code generation and policy gates | compare | advanced | Task: compare
Topic: Secure code generation and policy gates
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.
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": [
"cost_latency_tradeoffs",
"tests_are_truth",
"documentation",
"ci_integration"
],
"moe_experts": [
"agentic_systems_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 0a2b0e5deb1645b93165858a30f0a426cc4bef21 | |
train_02249 | 2026-01-01T00:00:00 | Reasoning-first coding models and tunable deliberation | explain | expert | Task: explain
Topic: Reasoning-first coding models and tunable deliberation
Difficulty: expert
Target language: Bash
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Bash",
"developer_needs": [
"auditability",
"cost_latency_tradeoffs",
"ci_integration",
"governance"
],
"moe_experts": [
"performance_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 3166df9a678c95bfbe651947d3e9ec74865d1516 | |
train_02250 | 2026-01-01T00:00:00 | Agentic coding systems (plan→edit→test→reflect) | design | advanced | Task: design
Topic: Agentic coding systems (plan→edit→test→reflect)
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": [
"reproducibility",
"tooling",
"security_gates",
"auditability"
],
"moe_experts": [
"governance_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 1cfd3a085c6747710841efe0b4d62809c8f260b6 | |
train_02251 | 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: 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.
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": [
"tooling",
"evaluation_metrics",
"security_gates",
"governance"
],
"moe_experts": [
"evaluation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | e1b3716a1357a90fbb88f24a811bb16ecd76d07c | |
train_02252 | 2026-01-01T00:00:00 | Multimodal dev workflows (docs, diagrams, traces) | code | expert | Task: code
Topic: Multimodal dev workflows (docs, diagrams, traces)
Difficulty: expert
Target language: Bash
Context: 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": "Bash",
"developer_needs": [
"auditability",
"cost_latency_tradeoffs",
"documentation",
"evaluation_metrics"
],
"moe_experts": [
"agentic_systems_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 16f33fb57db0d4f2809d7d3a9b214c13856d405a | |
train_02253 | 2026-01-01T00:00:00 | Governance, provenance, and licensing for code data | failure_analysis | advanced | Task: failure_analysis
Topic: Governance, provenance, and licensing for code data
Difficulty: advanced
Target language: 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.
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": "C#",
"developer_needs": [
"ci_integration",
"tests_are_truth",
"documentation",
"security_gates"
],
"moe_experts": [
"coding_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | bf947b5b23140f80e80522f861a5af8ca15755e3 | |
train_02254 | 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: 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.
Patch (diff-style):
```diff
- if x == 0:
- return 1/x
+ if x == 0:
+ raise ValueError('division by zero')
```
Acceptance:
- Tests pass
- No new regressions
| [] | {
"target_language": "Python",
"developer_needs": [
"auditability",
"security_gates",
"tooling",
"repo_scale_reasoning"
],
"moe_experts": [
"security_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 75b1b9d4ce67d3e2ac4d5d19c0fd5f4a8e8545ba | |
train_02255 | 2026-01-01T00:00:00 | SWE-bench style real-repo evaluation | data_pipeline | advanced | Task: data_pipeline
Topic: SWE-bench style real-repo evaluation
Difficulty: advanced
Target language: Go
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Go",
"developer_needs": [
"security_gates",
"governance",
"evaluation_metrics",
"tests_are_truth"
],
"moe_experts": [
"agentic_systems_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | e690abdfb8e8e7506207eb3f6abdbc8018fb00d0 | |
train_02256 | 2026-01-01T00:00:00 | Reasoning-first coding models and tunable deliberation | failure_analysis | advanced | Task: failure_analysis
Topic: Reasoning-first coding models and tunable deliberation
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.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
| [] | {
"target_language": "Python",
"developer_needs": [
"documentation",
"evaluation_metrics",
"auditability",
"governance"
],
"moe_experts": [
"data_curation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | e8842b35f24ef34e4728b46eff664c8fa4994e95 | |
train_02257 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | review | intermediate | Task: review
Topic: Latency, cost, and reliability optimization
Difficulty: intermediate
Target language: C#
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Review: correctness, security, performance, governance
| [] | {
"target_language": "C#",
"developer_needs": [
"ci_integration",
"tests_are_truth",
"documentation",
"evaluation_metrics"
],
"moe_experts": [
"agentic_systems_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | a551c75926c5c03ab7f269ac45b4d6bca59c9f46 | |
train_02258 | 2026-01-01T00:00:00 | Model merging, distillation, and continued pretraining | failure_analysis | advanced | Task: failure_analysis
Topic: Model merging, distillation, and continued pretraining
Difficulty: advanced
Target language: Rust
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
| [] | {
"target_language": "Rust",
"developer_needs": [
"reproducibility",
"auditability",
"security_gates",
"repo_scale_reasoning"
],
"moe_experts": [
"evaluation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | a0d49a1a8a2372251fa41ebd856ea8ff7c276fce | |
train_02259 | 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: 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.
Design with risks, metrics, acceptance criteria
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "C#",
"developer_needs": [
"governance",
"reproducibility",
"documentation",
"tooling"
],
"moe_experts": [
"evaluation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 54942d9c9bc0ecbbba042d28bc61b74dae0ac974 | |
train_02260 | 2026-01-01T00:00:00 | Self-improving agents and feedback loops | design | advanced | Task: design
Topic: Self-improving agents and feedback loops
Difficulty: advanced
Target language: SQL
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "SQL",
"developer_needs": [
"auditability",
"cost_latency_tradeoffs",
"ci_integration",
"tooling"
],
"moe_experts": [
"performance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 5f8cb4bca748ef1ef5e1102f6ae90f41bb48b764 | |
train_02261 | 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: TypeScript
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Patch (diff-style):
```diff
- if x == 0:
- return 1/x
+ if x == 0:
+ raise ValueError('division by zero')
```
Acceptance:
- Tests pass
- No new regressions
| [] | {
"target_language": "TypeScript",
"developer_needs": [
"documentation",
"repo_scale_reasoning",
"tooling",
"governance"
],
"moe_experts": [
"coding_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | c20f74b7c85e7d7e5817cb789e4ea896a920bf53 | |
train_02262 | 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: 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": [
"evaluation_metrics",
"tooling",
"security_gates",
"auditability"
],
"moe_experts": [
"governance_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 41fe188746bd8ea14673f36c3abd48f8eaf1bd10 | |
train_02263 | 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: 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": [
"auditability",
"reproducibility",
"evaluation_metrics",
"ci_integration"
],
"moe_experts": [
"coding_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | bfd5446ad75b418567355c28e5ba5cbf52dc7006 | |
train_02264 | 2026-01-01T00:00:00 | Extended context and repo-scale understanding | compare | expert | Task: compare
Topic: Extended context and repo-scale understanding
Difficulty: expert
Target language: JavaScript
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
| [] | {
"target_language": "JavaScript",
"developer_needs": [
"ci_integration",
"tooling",
"tests_are_truth",
"repo_scale_reasoning"
],
"moe_experts": [
"data_curation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 1087713866939887d947f06be605f1b69be33bbb | |
train_02265 | 2026-01-01T00:00:00 | Self-improving agents and feedback loops | agent_loop | intermediate | Task: agent_loop
Topic: Self-improving agents and feedback loops
Difficulty: intermediate
Target language: 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.
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": "Python",
"developer_needs": [
"governance",
"tooling",
"documentation",
"repo_scale_reasoning"
],
"moe_experts": [
"performance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | a25badcf5883972223371731e3aca4e0b2fef08b | |
train_02266 | 2026-01-01T00:00:00 | Secure code generation and policy gates | explain | intermediate | Task: explain
Topic: Secure code generation and policy gates
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": [
"evaluation_metrics",
"auditability",
"reproducibility",
"security_gates"
],
"moe_experts": [
"governance_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 6668298056bb64c5197d13fdaa1af40d92419ea6 | |
train_02267 | 2026-01-01T00:00:00 | Multimodal dev workflows (docs, diagrams, traces) | code | expert | Task: code
Topic: Multimodal dev workflows (docs, diagrams, traces)
Difficulty: expert
Target language: JavaScript
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "JavaScript",
"developer_needs": [
"governance",
"tests_are_truth",
"ci_integration",
"tooling"
],
"moe_experts": [
"security_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 4522bed8aff81b3f3cd80f2222f96ea09cf6a510 | |
train_02268 | 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: 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": [
"ci_integration",
"security_gates",
"cost_latency_tradeoffs",
"reproducibility"
],
"moe_experts": [
"performance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 38312eeb1577296c5e31d3d04fbcce71f4568edc | |
train_02269 | 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: 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": "Go",
"developer_needs": [
"tests_are_truth",
"security_gates",
"auditability",
"tooling"
],
"moe_experts": [
"evaluation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 67af70d06b292b3d211f158d1825a8dafe137bf8 | |
train_02270 | 2026-01-01T00:00:00 | SWE-bench style real-repo evaluation | patch_diff | expert | Task: patch_diff
Topic: SWE-bench style real-repo evaluation
Difficulty: expert
Target language: 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.
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": [
"auditability",
"security_gates",
"documentation",
"governance"
],
"moe_experts": [
"security_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 077a24815cf57ac380c4646a7762fb10a6318869 | |
train_02271 | 2026-01-01T00:00:00 | Self-improving agents and feedback loops | review | expert | Task: review
Topic: Self-improving agents and feedback loops
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.
Review: correctness, security, performance, governance
| [] | {
"target_language": "Bash",
"developer_needs": [
"security_gates",
"documentation",
"reproducibility",
"tests_are_truth"
],
"moe_experts": [
"security_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 68a694b82aab70114fefe3fd2bbf1cebed6ea09a | |
train_02272 | 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: 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": "Go",
"developer_needs": [
"security_gates",
"cost_latency_tradeoffs",
"tooling",
"evaluation_metrics"
],
"moe_experts": [
"governance_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 82f24ee5a4d8b78d5d5323cede4c68d897caa674 | |
train_02273 | 2026-01-01T00:00:00 | Governance, provenance, and licensing for code data | compare | expert | Task: compare
Topic: Governance, provenance, and licensing for code data
Difficulty: expert
Target language: 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": [
"governance",
"evaluation_metrics",
"tooling",
"auditability"
],
"moe_experts": [
"coding_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 01c6a988f94d03b97450b4059c38940ecd5872a3 | |
train_02274 | 2026-01-01T00:00:00 | Secure code generation and policy gates | compare | expert | Task: compare
Topic: Secure code generation and policy gates
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.
Compare: capability, cost, latency, reliability
| [] | {
"target_language": "Bash",
"developer_needs": [
"reproducibility",
"tests_are_truth",
"documentation",
"repo_scale_reasoning"
],
"moe_experts": [
"coding_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | ba35ea621a2d76c72cbd5936dd46daac1f469b2a | |
train_02275 | 2026-01-01T00:00:00 | Dataset curation pipelines (filter, dedupe, quality) | failure_analysis | intermediate | Task: failure_analysis
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: intermediate
Target language: Go
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
| [] | {
"target_language": "Go",
"developer_needs": [
"cost_latency_tradeoffs",
"evaluation_metrics",
"auditability",
"documentation"
],
"moe_experts": [
"governance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 4abd6d6a3ded36956166150ae96e74834474d502 | |
train_02276 | 2026-01-01T00:00:00 | Self-improving agents and feedback loops | agent_loop | intermediate | Task: agent_loop
Topic: Self-improving agents and feedback loops
Difficulty: intermediate
Target language: 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.
Loop: Plan → Edit → Test → Reflect → Human gate
| [] | {
"target_language": "Rust",
"developer_needs": [
"reproducibility",
"tests_are_truth",
"auditability",
"governance"
],
"moe_experts": [
"coding_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 85d38e0f51a7dbfc07e874f4553e03dc65e8bb44 | |
train_02277 | 2026-01-01T00:00:00 | Reasoning-first coding models and tunable deliberation | design | intermediate | Task: design
Topic: Reasoning-first coding models and tunable deliberation
Difficulty: intermediate
Target language: Java
Context: 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": "Java",
"developer_needs": [
"ci_integration",
"documentation",
"tooling",
"cost_latency_tradeoffs"
],
"moe_experts": [
"data_curation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 6873812fa69b1cbc6e603c16830743fd15ab21cf | |
train_02278 | 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: 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
| [] | {
"target_language": "SQL",
"developer_needs": [
"documentation",
"repo_scale_reasoning",
"tooling",
"governance"
],
"moe_experts": [
"evaluation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | bf9af4b22c77dfde85d3ef57664083a4b72d66a4 | |
train_02279 | 2026-01-01T00:00:00 | Self-improving agents and feedback loops | patch_diff | advanced | Task: patch_diff
Topic: Self-improving agents and feedback loops
Difficulty: advanced
Target language: 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
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Rust",
"developer_needs": [
"security_gates",
"tooling",
"cost_latency_tradeoffs",
"evaluation_metrics"
],
"moe_experts": [
"governance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 1558f4e2afa32fd0ef5c767a02ea7f20a5115159 | |
train_02280 | 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: 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.
Eval:
pass@k, time-to-green, regressions, diff size
| [] | {
"target_language": "SQL",
"developer_needs": [
"repo_scale_reasoning",
"ci_integration",
"cost_latency_tradeoffs",
"tooling"
],
"moe_experts": [
"data_curation_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 309e738d632b52c97b7016396b4f6288aaeea831 | |
train_02281 | 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: SQL
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "SQL",
"developer_needs": [
"repo_scale_reasoning",
"security_gates",
"auditability",
"evaluation_metrics"
],
"moe_experts": [
"security_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | fac310d7d385e1c4832e3d89be4f36d8e89194c2 | |
train_02282 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | failure_analysis | intermediate | Task: failure_analysis
Topic: Latency, cost, and reliability optimization
Difficulty: intermediate
Target language: 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": [
"governance",
"reproducibility",
"repo_scale_reasoning",
"ci_integration"
],
"moe_experts": [
"data_curation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | c8556c2808dbed540f43f545ba3751cc772d18c1 | |
train_02283 | 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: Bash
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "Bash",
"developer_needs": [
"security_gates",
"evaluation_metrics",
"cost_latency_tradeoffs",
"repo_scale_reasoning"
],
"moe_experts": [
"security_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | f9600a66c85af994b364f010ae2809a3fce3e8a9 | |
train_02284 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | patch_diff | intermediate | Task: patch_diff
Topic: Latency, cost, and reliability optimization
Difficulty: intermediate
Target language: 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": [
"tests_are_truth",
"reproducibility",
"tooling",
"security_gates"
],
"moe_experts": [
"evaluation_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 407b9fb72debba701439306af977e0718726e2b2 | |
train_02285 | 2026-01-01T00:00:00 | Reasoning-first coding models and tunable deliberation | compare | expert | Task: compare
Topic: Reasoning-first coding models and tunable deliberation
Difficulty: expert
Target language: Python
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
| [] | {
"target_language": "Python",
"developer_needs": [
"governance",
"auditability",
"cost_latency_tradeoffs",
"ci_integration"
],
"moe_experts": [
"governance_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 39f85ead6ff16bb3772f87d3c3d66c2a3f7b5fe9 | |
train_02286 | 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: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Patch (diff-style):
```diff
- if x == 0:
- return 1/x
+ if x == 0:
+ raise ValueError('division by zero')
```
Acceptance:
- Tests pass
- No new regressions
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Java",
"developer_needs": [
"evaluation_metrics",
"tooling",
"cost_latency_tradeoffs",
"repo_scale_reasoning"
],
"moe_experts": [
"security_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 47919346305490f4fa9f26359ded7aa4ab98e462 | |
train_02287 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | eval | advanced | Task: eval
Topic: Latency, cost, and reliability optimization
Difficulty: advanced
Target language: Rust
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
| [] | {
"target_language": "Rust",
"developer_needs": [
"repo_scale_reasoning",
"tests_are_truth",
"auditability",
"security_gates"
],
"moe_experts": [
"performance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 71e29496cdba2867c2fe9ca0481ce2b9b06306b1 | |
train_02288 | 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: 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": [
"auditability",
"reproducibility",
"governance",
"cost_latency_tradeoffs"
],
"moe_experts": [
"data_curation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 13ba0ed0d6ba2b53cb33b1e54b295dc0218e9d36 | |
train_02289 | 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: Python
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Python",
"developer_needs": [
"cost_latency_tradeoffs",
"repo_scale_reasoning",
"reproducibility",
"auditability"
],
"moe_experts": [
"performance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | fab301c6d58bcc2446b890448abce64ea2dcb3ef | |
train_02290 | 2026-01-01T00:00:00 | Dataset curation pipelines (filter, dedupe, quality) | agent_loop | expert | Task: agent_loop
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: expert
Target language: C#
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "C#",
"developer_needs": [
"governance",
"tests_are_truth",
"documentation",
"auditability"
],
"moe_experts": [
"security_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 10e6bc6d048e41a011fa69c2b8d167c614e62b46 | |
train_02291 | 2026-01-01T00:00:00 | SWE-bench style real-repo evaluation | code | expert | Task: code
Topic: SWE-bench style real-repo evaluation
Difficulty: expert
Target language: SQL
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "SQL",
"developer_needs": [
"ci_integration",
"tests_are_truth",
"evaluation_metrics",
"governance"
],
"moe_experts": [
"governance_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | f8b6d9bcd59d8a010c8c3dad4b82d01c491fd39e | |
train_02292 | 2026-01-01T00:00:00 | Reasoning-first coding models and tunable deliberation | design | advanced | Task: design
Topic: Reasoning-first coding models and tunable deliberation
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.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "Bash",
"developer_needs": [
"tests_are_truth",
"evaluation_metrics",
"ci_integration",
"security_gates"
],
"moe_experts": [
"coding_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 19dc817ce69bb058b5d473a7e162d04d1eba1c0c | |
train_02293 | 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: 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": [
"tests_are_truth",
"evaluation_metrics",
"repo_scale_reasoning",
"ci_integration"
],
"moe_experts": [
"security_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 6f239373ce1f5c7ece1bbe8535d0c408954f9265 | |
train_02294 | 2026-01-01T00:00:00 | Model merging, distillation, and continued pretraining | design | intermediate | Task: design
Topic: Model merging, distillation, and continued pretraining
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": [
"tests_are_truth",
"tooling",
"auditability",
"security_gates"
],
"moe_experts": [
"governance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 36748c22f2c8c34fe1affd7d9b5a7e23d0982dac | |
train_02295 | 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: 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
| [] | {
"target_language": "JavaScript",
"developer_needs": [
"reproducibility",
"governance",
"tests_are_truth",
"evaluation_metrics"
],
"moe_experts": [
"data_curation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 888344fc78028f4d6d979f6b6ae16ef690ab8c84 | |
train_02296 | 2026-01-01T00:00:00 | Tool calling, sandboxes, and CI integration | patch_diff | intermediate | Task: patch_diff
Topic: Tool calling, sandboxes, and CI integration
Difficulty: intermediate
Target language: 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.
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": [
"evaluation_metrics",
"tests_are_truth",
"repo_scale_reasoning",
"tooling"
],
"moe_experts": [
"evaluation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 133ee636bb85b1697cca80272c3a367a66fb0d3e | |
train_02297 | 2026-01-01T00:00:00 | Extended context and repo-scale understanding | review | expert | Task: review
Topic: Extended context and repo-scale understanding
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.
Review: correctness, security, performance, governance
| [] | {
"target_language": "C#",
"developer_needs": [
"cost_latency_tradeoffs",
"tests_are_truth",
"governance",
"repo_scale_reasoning"
],
"moe_experts": [
"data_curation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 9056d08fd25b89b3e17fd6183d1cd2a2fee20003 | |
train_02298 | 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: JavaScript
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "JavaScript",
"developer_needs": [
"tests_are_truth",
"repo_scale_reasoning",
"security_gates",
"cost_latency_tradeoffs"
],
"moe_experts": [
"governance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | b060a80ff3b9f114b7ed02daec80233d33517eb0 | |
train_02299 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | review | intermediate | Task: review
Topic: Latency, cost, and reliability optimization
Difficulty: intermediate
Target language: C#
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Review: correctness, security, performance, governance
| [] | {
"target_language": "C#",
"developer_needs": [
"repo_scale_reasoning",
"governance",
"reproducibility",
"auditability"
],
"moe_experts": [
"data_curation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | a551c75926c5c03ab7f269ac45b4d6bca59c9f46 |
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