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_12300 | 2026-01-01T00:00:00 | Tool calling, sandboxes, and CI integration | eval | expert | Task: eval
Topic: Tool calling, sandboxes, and CI integration
Difficulty: expert
Target language: Bash
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
| [] | {
"target_language": "Bash",
"developer_needs": [
"evaluation_metrics",
"tests_are_truth",
"reproducibility",
"security_gates"
],
"moe_experts": [
"performance_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 50cb0f89adff092882933244d434124344b24f2e | |
train_12301 | 2026-01-01T00:00:00 | Dataset curation pipelines (filter, dedupe, quality) | design | intermediate | Task: design
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: intermediate
Target language: SQL
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "SQL",
"developer_needs": [
"evaluation_metrics",
"governance",
"reproducibility",
"ci_integration"
],
"moe_experts": [
"performance_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 4f1b897e879dbbf594e463f317efc9460c3d3800 | |
train_12302 | 2026-01-01T00:00:00 | Code-specialized model families and sizing tradeoffs | design | advanced | Task: design
Topic: Code-specialized model families and sizing tradeoffs
Difficulty: advanced
Target language: C#
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "C#",
"developer_needs": [
"repo_scale_reasoning",
"security_gates",
"cost_latency_tradeoffs",
"evaluation_metrics"
],
"moe_experts": [
"performance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 546b92fcf93d9a0f4cbbcdcb854d0953d6208aff | |
train_12303 | 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: 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.
Loop: Plan → Edit → Test → Reflect → Human gate
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Bash",
"developer_needs": [
"auditability",
"reproducibility",
"ci_integration",
"governance"
],
"moe_experts": [
"security_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | ce28b4ec839756b4f5292c90db2ee522a059ee3c | |
train_12304 | 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: 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": [
"tests_are_truth",
"cost_latency_tradeoffs",
"documentation",
"governance"
],
"moe_experts": [
"data_curation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 385d309ddd322c74a7802a28329bbad05c43a855 | |
train_12305 | 2026-01-01T00:00:00 | Code-specialized model families and sizing tradeoffs | compare | intermediate | Task: compare
Topic: Code-specialized model families and sizing tradeoffs
Difficulty: intermediate
Target language: 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": [
"tooling",
"tests_are_truth",
"auditability",
"cost_latency_tradeoffs"
],
"moe_experts": [
"performance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 8d22d18d70eb7d30203a762dc0de53b1a7767df7 | |
train_12306 | 2026-01-01T00:00:00 | Self-improving agents and feedback loops | data_pipeline | advanced | Task: data_pipeline
Topic: Self-improving agents and feedback loops
Difficulty: advanced
Target language: 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": [
"documentation",
"tooling",
"evaluation_metrics",
"tests_are_truth"
],
"moe_experts": [
"data_curation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | e22fea428835534d1a0460d139d1198319a3f46b | |
train_12307 | 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: SQL
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
| [] | {
"target_language": "SQL",
"developer_needs": [
"governance",
"reproducibility",
"tests_are_truth",
"evaluation_metrics"
],
"moe_experts": [
"agentic_systems_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | ba92fb3e5c4d76def32cc8e57c6dce4e9c28294e | |
train_12308 | 2026-01-01T00:00:00 | Mixture-of-Experts (MoE) for code | patch_diff | intermediate | Task: patch_diff
Topic: Mixture-of-Experts (MoE) for code
Difficulty: intermediate
Target language: 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.
Patch (diff-style):
```diff
- if x == 0:
- return 1/x
+ if x == 0:
+ raise ValueError('division by zero')
```
Acceptance:
- Tests pass
- No new regressions
| [] | {
"target_language": "Go",
"developer_needs": [
"evaluation_metrics",
"repo_scale_reasoning",
"reproducibility",
"auditability"
],
"moe_experts": [
"security_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 1e9a1e3f27f977d2c8c69b4de815bc30a84c3b46 | |
train_12309 | 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: 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": [
"security_gates",
"evaluation_metrics",
"tooling",
"governance"
],
"moe_experts": [
"agentic_systems_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 2ad33d3d232cd737e1e6ec7f6f79b17eb225563a | |
train_12310 | 2026-01-01T00:00:00 | Secure code generation and policy gates | agent_loop | advanced | Task: agent_loop
Topic: Secure code generation and policy gates
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.
Loop: Plan → Edit → Test → Reflect → Human gate
| [] | {
"target_language": "Python",
"developer_needs": [
"cost_latency_tradeoffs",
"ci_integration",
"governance",
"tooling"
],
"moe_experts": [
"coding_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | efffe8da8e3be507c5eb872fa633a47179843c01 | |
train_12311 | 2026-01-01T00:00:00 | SWE-bench style real-repo evaluation | explain | intermediate | Task: explain
Topic: SWE-bench style real-repo evaluation
Difficulty: intermediate
Target language: 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": [
"evaluation_metrics",
"security_gates",
"tests_are_truth",
"documentation"
],
"moe_experts": [
"data_curation_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | aaa959ad798b512bbcc47e8f22c4db27ff206b79 | |
train_12312 | 2026-01-01T00:00:00 | Multimodal dev workflows (docs, diagrams, traces) | patch_diff | intermediate | Task: patch_diff
Topic: Multimodal dev workflows (docs, diagrams, traces)
Difficulty: intermediate
Target language: Rust
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Patch (diff-style):
```diff
- if x == 0:
- return 1/x
+ if x == 0:
+ raise ValueError('division by zero')
```
Acceptance:
- Tests pass
- No new regressions
| [] | {
"target_language": "Rust",
"developer_needs": [
"tooling",
"tests_are_truth",
"governance",
"auditability"
],
"moe_experts": [
"governance_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 1a52421a5a5d7da51c2d53ef7f1d404fd9f80428 | |
train_12313 | 2026-01-01T00:00:00 | Code-specialized model families and sizing tradeoffs | eval | intermediate | Task: eval
Topic: Code-specialized model families and sizing tradeoffs
Difficulty: intermediate
Target language: Java
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Java",
"developer_needs": [
"documentation",
"evaluation_metrics",
"ci_integration",
"governance"
],
"moe_experts": [
"security_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | c22e92e7e8634a90dd79b4ae7b2565b98829822a | |
train_12314 | 2026-01-01T00:00:00 | Tool calling, sandboxes, and CI integration | design | expert | Task: design
Topic: Tool calling, sandboxes, and CI integration
Difficulty: expert
Target language: Rust
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "Rust",
"developer_needs": [
"documentation",
"evaluation_metrics",
"tooling",
"cost_latency_tradeoffs"
],
"moe_experts": [
"agentic_systems_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 7ee5a05912df57f1fb8cb738d6bee5c04ef09c24 | |
train_12315 | 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: 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.
Compare: capability, cost, latency, reliability
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "C#",
"developer_needs": [
"auditability",
"repo_scale_reasoning",
"documentation",
"cost_latency_tradeoffs"
],
"moe_experts": [
"data_curation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 84c2ceb1f1d5cf8323885643db6c9e9d5d248933 | |
train_12316 | 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
| [] | {
"target_language": "Python",
"developer_needs": [
"cost_latency_tradeoffs",
"tooling",
"tests_are_truth",
"evaluation_metrics"
],
"moe_experts": [
"governance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 049594df47c84809364b96b777dd2d9ad7de460d | |
train_12317 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | explain | advanced | Task: explain
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.
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": [
"ci_integration",
"documentation",
"tests_are_truth",
"tooling"
],
"moe_experts": [
"data_curation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 5d3e7461e35d01a17637fb6e8257748c9ca61688 | |
train_12318 | 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: 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": [
"governance",
"evaluation_metrics",
"auditability",
"reproducibility"
],
"moe_experts": [
"data_curation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | b8c346b5bbd029a4d526e0b5d5150bc88b637a1b | |
train_12319 | 2026-01-01T00:00:00 | SWE-bench style real-repo evaluation | explain | intermediate | Task: explain
Topic: SWE-bench style real-repo evaluation
Difficulty: intermediate
Target language: JavaScript
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "JavaScript",
"developer_needs": [
"cost_latency_tradeoffs",
"documentation",
"tooling",
"repo_scale_reasoning"
],
"moe_experts": [
"security_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | aaa959ad798b512bbcc47e8f22c4db27ff206b79 | |
train_12320 | 2026-01-01T00:00:00 | Governance, provenance, and licensing for code data | compare | advanced | Task: compare
Topic: Governance, provenance, and licensing for code data
Difficulty: advanced
Target language: Bash
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
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": [
"auditability",
"cost_latency_tradeoffs",
"governance",
"repo_scale_reasoning"
],
"moe_experts": [
"data_curation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 3c94384a05b578e128da8b4f181255539fac94ae | |
train_12321 | 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: Python
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Python",
"developer_needs": [
"reproducibility",
"auditability",
"documentation",
"tooling"
],
"moe_experts": [
"performance_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 57c01bad7c8e7b743bc95422304f979269b81d0b | |
train_12322 | 2026-01-01T00:00:00 | Multimodal dev workflows (docs, diagrams, traces) | design | intermediate | Task: design
Topic: Multimodal dev workflows (docs, diagrams, traces)
Difficulty: intermediate
Target language: JavaScript
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
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",
"cost_latency_tradeoffs",
"reproducibility"
],
"moe_experts": [
"performance_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | f9e7e71fd27280bcf0da0c9f2f6355cd598b1528 | |
train_12323 | 2026-01-01T00:00:00 | Mixture-of-Experts (MoE) for code | eval | expert | Task: eval
Topic: Mixture-of-Experts (MoE) for code
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.
Eval:
pass@k, time-to-green, regressions, diff size
| [] | {
"target_language": "Bash",
"developer_needs": [
"documentation",
"security_gates",
"repo_scale_reasoning",
"reproducibility"
],
"moe_experts": [
"evaluation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 8830313816679601f3e405e469cfe5fcde35e5b7 | |
train_12324 | 2026-01-01T00:00:00 | Self-improving agents and feedback loops | code | intermediate | Task: code
Topic: Self-improving agents and feedback loops
Difficulty: intermediate
Target language: SQL
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "SQL",
"developer_needs": [
"documentation",
"evaluation_metrics",
"governance",
"cost_latency_tradeoffs"
],
"moe_experts": [
"coding_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 4a8ae04281e155ae19c125698c2511f47e0751ee | |
train_12325 | 2026-01-01T00:00:00 | Dataset curation pipelines (filter, dedupe, quality) | explain | intermediate | Task: explain
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: intermediate
Target language: 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": [
"documentation",
"governance",
"ci_integration",
"cost_latency_tradeoffs"
],
"moe_experts": [
"data_curation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 4b9efda42661b6fda9df58abddef68e7577686b2 | |
train_12326 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | agent_loop | advanced | Task: agent_loop
Topic: Latency, cost, and reliability optimization
Difficulty: advanced
Target language: Go
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
| [] | {
"target_language": "Go",
"developer_needs": [
"tests_are_truth",
"documentation",
"evaluation_metrics",
"reproducibility"
],
"moe_experts": [
"data_curation_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | f2ceeadaa207f0c19e71e34144cbcf2066334d78 | |
train_12327 | 2026-01-01T00:00:00 | Reasoning-first coding models and tunable deliberation | patch_diff | intermediate | Task: patch_diff
Topic: Reasoning-first coding models and tunable deliberation
Difficulty: intermediate
Target language: Go
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Patch (diff-style):
```diff
- if x == 0:
- return 1/x
+ if x == 0:
+ raise ValueError('division by zero')
```
Acceptance:
- Tests pass
- No new regressions
| [] | {
"target_language": "Go",
"developer_needs": [
"tooling",
"cost_latency_tradeoffs",
"evaluation_metrics",
"governance"
],
"moe_experts": [
"coding_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | fae07c998dcd3a04f42d83360229b5bcedf5afd1 | |
train_12328 | 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: 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.
Loop: Plan → Edit → Test → Reflect → Human gate
| [] | {
"target_language": "Go",
"developer_needs": [
"reproducibility",
"documentation",
"repo_scale_reasoning",
"ci_integration"
],
"moe_experts": [
"data_curation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | c2505951791972a711415e22f95407951e9d76d0 | |
train_12329 | 2026-01-01T00:00:00 | Model merging, distillation, and continued pretraining | code | advanced | Task: code
Topic: Model merging, distillation, and continued pretraining
Difficulty: advanced
Target language: JavaScript
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "JavaScript",
"developer_needs": [
"governance",
"tooling",
"cost_latency_tradeoffs",
"security_gates"
],
"moe_experts": [
"evaluation_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | a186e87ba5b6351d53019a599bc1d7626f1b6f93 | |
train_12330 | 2026-01-01T00:00:00 | Agentic coding systems (plan→edit→test→reflect) | data_pipeline | advanced | Task: data_pipeline
Topic: Agentic coding systems (plan→edit→test→reflect)
Difficulty: advanced
Target language: Rust
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
| [] | {
"target_language": "Rust",
"developer_needs": [
"security_gates",
"ci_integration",
"repo_scale_reasoning",
"tests_are_truth"
],
"moe_experts": [
"evaluation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 7310ef5138590bf7838b262b541610cb4fc1b85a | |
train_12331 | 2026-01-01T00:00:00 | SWE-bench style real-repo evaluation | agent_loop | expert | Task: agent_loop
Topic: SWE-bench style real-repo evaluation
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": [
"repo_scale_reasoning",
"cost_latency_tradeoffs",
"reproducibility",
"governance"
],
"moe_experts": [
"evaluation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | f7fb38abfd82faac7f45c2132b9a5c333760c794 | |
train_12332 | 2026-01-01T00:00:00 | Secure code generation and policy gates | explain | advanced | Task: explain
Topic: Secure code generation and policy gates
Difficulty: advanced
Target language: TypeScript
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "TypeScript",
"developer_needs": [
"repo_scale_reasoning",
"cost_latency_tradeoffs",
"governance",
"documentation"
],
"moe_experts": [
"data_curation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | d26a917da257fbec4600bc9d2ff775b78de2ca38 | |
train_12333 | 2026-01-01T00:00:00 | SWE-bench style real-repo evaluation | failure_analysis | expert | Task: failure_analysis
Topic: SWE-bench style real-repo evaluation
Difficulty: expert
Target language: Bash
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Bash",
"developer_needs": [
"evaluation_metrics",
"auditability",
"tests_are_truth",
"cost_latency_tradeoffs"
],
"moe_experts": [
"governance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 49c3a2f6c32ecdc9f7264fc3afffc68b638f72b2 | |
train_12334 | 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: 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.
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": [
"tests_are_truth",
"cost_latency_tradeoffs",
"tooling",
"documentation"
],
"moe_experts": [
"security_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 010d23b9c5e4b4ecb9baa878b64a0d9903b5f34b | |
train_12335 | 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: Java
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Java",
"developer_needs": [
"ci_integration",
"cost_latency_tradeoffs",
"tests_are_truth",
"security_gates"
],
"moe_experts": [
"coding_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 84a38e78494a3a6b95ddc9a828305ae6286a202c | |
train_12336 | 2026-01-01T00:00:00 | Model merging, distillation, and continued pretraining | compare | advanced | Task: compare
Topic: Model merging, distillation, and continued pretraining
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.
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": [
"security_gates",
"cost_latency_tradeoffs",
"repo_scale_reasoning",
"reproducibility"
],
"moe_experts": [
"security_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 3c510acc8647790680160e02d240281c52a95935 | |
train_12337 | 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: 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": [
"reproducibility",
"security_gates",
"cost_latency_tradeoffs",
"ci_integration"
],
"moe_experts": [
"evaluation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 8b5239705efeea75686c312f7359dffc757f2746 | |
train_12338 | 2026-01-01T00:00:00 | SWE-bench style real-repo evaluation | data_pipeline | expert | Task: data_pipeline
Topic: SWE-bench style real-repo evaluation
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.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Go",
"developer_needs": [
"governance",
"cost_latency_tradeoffs",
"auditability",
"repo_scale_reasoning"
],
"moe_experts": [
"governance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 92bf4c646873946335879df07261eb1aedf799d7 | |
train_12339 | 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: 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": [
"security_gates",
"reproducibility",
"evaluation_metrics",
"documentation"
],
"moe_experts": [
"data_curation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 9187ebd929618d15a55f1a1799c262c83b4e549c | |
train_12340 | 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: 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": [
"governance",
"reproducibility",
"ci_integration",
"tests_are_truth"
],
"moe_experts": [
"data_curation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 37c6b36f517ecdf56377c28d9ff027bc1f8aa499 | |
train_12341 | 2026-01-01T00:00:00 | Code-specialized model families and sizing tradeoffs | data_pipeline | intermediate | Task: data_pipeline
Topic: Code-specialized model families and sizing tradeoffs
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.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
| [] | {
"target_language": "Go",
"developer_needs": [
"documentation",
"security_gates",
"ci_integration",
"cost_latency_tradeoffs"
],
"moe_experts": [
"performance_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 406404c9556cc3faf204c06a20646226c6048480 | |
train_12342 | 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: 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": [
"documentation",
"governance",
"auditability",
"cost_latency_tradeoffs"
],
"moe_experts": [
"agentic_systems_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | d240faeb3c72a5f27ff77b30323bfb7ff8c99d21 | |
train_12343 | 2026-01-01T00:00:00 | Code-specialized model families and sizing tradeoffs | agent_loop | advanced | Task: agent_loop
Topic: Code-specialized model families and sizing tradeoffs
Difficulty: advanced
Target language: 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": [
"ci_integration",
"documentation",
"cost_latency_tradeoffs",
"tooling"
],
"moe_experts": [
"security_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 6fcc51af2281ae592c4c62d52b28701dce601db3 | |
train_12344 | 2026-01-01T00:00:00 | Governance, provenance, and licensing for code data | design | expert | Task: design
Topic: Governance, provenance, and licensing for code data
Difficulty: expert
Target language: Go
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "Go",
"developer_needs": [
"reproducibility",
"ci_integration",
"repo_scale_reasoning",
"documentation"
],
"moe_experts": [
"security_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 1d0dbad9aa2a6a78b18fe2a8494632fd1916cbda | |
train_12345 | 2026-01-01T00:00:00 | Agentic coding systems (plan→edit→test→reflect) | review | expert | Task: review
Topic: Agentic coding systems (plan→edit→test→reflect)
Difficulty: expert
Target language: Go
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Review: correctness, security, performance, governance
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Go",
"developer_needs": [
"documentation",
"tooling",
"repo_scale_reasoning",
"reproducibility"
],
"moe_experts": [
"coding_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | c3bb4e14cfb68f9d7ae011f14f2ceecacf186439 | |
train_12346 | 2026-01-01T00:00:00 | Multimodal dev workflows (docs, diagrams, traces) | data_pipeline | intermediate | Task: data_pipeline
Topic: Multimodal dev workflows (docs, diagrams, traces)
Difficulty: intermediate
Target language: JavaScript
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
| [] | {
"target_language": "JavaScript",
"developer_needs": [
"evaluation_metrics",
"tests_are_truth",
"auditability",
"reproducibility"
],
"moe_experts": [
"performance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 780ceaea8e36251df5cfa77123a5fa9065e5c4f9 | |
train_12347 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | review | advanced | Task: review
Topic: Latency, cost, and reliability optimization
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.
Review: correctness, security, performance, governance
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Java",
"developer_needs": [
"security_gates",
"reproducibility",
"ci_integration",
"tooling"
],
"moe_experts": [
"security_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 3a860e9af1c98575d8ca84c20be1f0a3cc4c05a4 | |
train_12348 | 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: 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
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Python",
"developer_needs": [
"evaluation_metrics",
"repo_scale_reasoning",
"tooling",
"governance"
],
"moe_experts": [
"data_curation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 16ee4b6aa4333295046bc13a9fc64d0605c61a46 | |
train_12349 | 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: 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.
Eval:
pass@k, time-to-green, regressions, diff size
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "JavaScript",
"developer_needs": [
"reproducibility",
"tooling",
"evaluation_metrics",
"tests_are_truth"
],
"moe_experts": [
"agentic_systems_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 72a7e05877aac70ee56781bc10d1b0365024454a | |
train_12350 | 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: 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.
Patch (diff-style):
```diff
- if x == 0:
- return 1/x
+ if x == 0:
+ raise ValueError('division by zero')
```
Acceptance:
- Tests pass
- No new regressions
| [] | {
"target_language": "Go",
"developer_needs": [
"reproducibility",
"ci_integration",
"documentation",
"security_gates"
],
"moe_experts": [
"coding_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | a5fdbed797bc051134daaf3254bcef9e137a2731 | |
train_12351 | 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: TypeScript
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Patch (diff-style):
```diff
- if x == 0:
- return 1/x
+ if x == 0:
+ raise ValueError('division by zero')
```
Acceptance:
- Tests pass
- No new regressions
| [] | {
"target_language": "TypeScript",
"developer_needs": [
"reproducibility",
"security_gates",
"repo_scale_reasoning",
"cost_latency_tradeoffs"
],
"moe_experts": [
"governance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 42e963f016de6732bb45009e463d598cf66389ce | |
train_12352 | 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: SQL
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "SQL",
"developer_needs": [
"repo_scale_reasoning",
"security_gates",
"governance",
"tests_are_truth"
],
"moe_experts": [
"data_curation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | f9a62765f1e7aea704ce24261f8d9a07f26679ff | |
train_12353 | 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: Bash
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
| [] | {
"target_language": "Bash",
"developer_needs": [
"repo_scale_reasoning",
"reproducibility",
"governance",
"tooling"
],
"moe_experts": [
"evaluation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | fe4641cf61da7a68ebe948213223163d32c6765c | |
train_12354 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | design | intermediate | Task: design
Topic: Latency, cost, and reliability optimization
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.
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": [
"documentation",
"tests_are_truth",
"governance",
"auditability"
],
"moe_experts": [
"coding_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 6231a0e74670fa4faeae93e286d23d238ab483fd | |
train_12355 | 2026-01-01T00:00:00 | Secure code generation and policy gates | agent_loop | advanced | Task: agent_loop
Topic: Secure code generation and policy gates
Difficulty: advanced
Target language: Bash
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
| [] | {
"target_language": "Bash",
"developer_needs": [
"auditability",
"evaluation_metrics",
"ci_integration",
"security_gates"
],
"moe_experts": [
"agentic_systems_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | c13a610f9e79b03bfaf668fc94c25ad6c046d906 | |
train_12356 | 2026-01-01T00:00:00 | Extended context and repo-scale understanding | agent_loop | advanced | Task: agent_loop
Topic: Extended context and repo-scale understanding
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.
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": "Rust",
"developer_needs": [
"security_gates",
"auditability",
"tooling",
"evaluation_metrics"
],
"moe_experts": [
"agentic_systems_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | bec6b4985734b85e1d243cf915bb3c35889704e0 | |
train_12357 | 2026-01-01T00:00:00 | Tool calling, sandboxes, and CI integration | failure_analysis | expert | Task: failure_analysis
Topic: Tool calling, sandboxes, and CI integration
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.
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",
"evaluation_metrics",
"security_gates",
"repo_scale_reasoning"
],
"moe_experts": [
"coding_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 546e1744ad7444806b8225d5d4ed4e925fb0f080 | |
train_12358 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | eval | advanced | Task: eval
Topic: Latency, cost, and reliability optimization
Difficulty: advanced
Target language: Java
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
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": [
"ci_integration",
"tests_are_truth",
"auditability",
"tooling"
],
"moe_experts": [
"data_curation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | e77f4b06192622f3da84c2b2c2738c50dcd59ce9 | |
train_12359 | 2026-01-01T00:00:00 | Code-specialized model families and sizing tradeoffs | agent_loop | expert | Task: agent_loop
Topic: Code-specialized model families and sizing tradeoffs
Difficulty: expert
Target language: JavaScript
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
| [] | {
"target_language": "JavaScript",
"developer_needs": [
"ci_integration",
"repo_scale_reasoning",
"cost_latency_tradeoffs",
"documentation"
],
"moe_experts": [
"governance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 12a4b35f6557a636cf0cf05750a055fdb604416e | |
train_12360 | 2026-01-01T00:00:00 | Extended context and repo-scale understanding | data_pipeline | expert | Task: data_pipeline
Topic: Extended context and repo-scale understanding
Difficulty: expert
Target language: 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.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
| [] | {
"target_language": "C#",
"developer_needs": [
"tests_are_truth",
"security_gates",
"auditability",
"governance"
],
"moe_experts": [
"evaluation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | ff9011851087891713931bb00b9ab426b96422b1 | |
train_12361 | 2026-01-01T00:00:00 | Extended context and repo-scale understanding | explain | advanced | Task: explain
Topic: Extended context and repo-scale understanding
Difficulty: advanced
Target language: 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": [
"cost_latency_tradeoffs",
"evaluation_metrics",
"tooling",
"repo_scale_reasoning"
],
"moe_experts": [
"evaluation_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 7550deb1cc5f93e94e368506ec81e522ab055690 | |
train_12362 | 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: 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
| [] | {
"target_language": "TypeScript",
"developer_needs": [
"governance",
"evaluation_metrics",
"repo_scale_reasoning",
"security_gates"
],
"moe_experts": [
"agentic_systems_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 9357ab97ec96cee1e0801bf50cf85d26d2f9a210 | |
train_12363 | 2026-01-01T00:00:00 | Agentic coding systems (plan→edit→test→reflect) | design | expert | Task: design
Topic: Agentic coding systems (plan→edit→test→reflect)
Difficulty: expert
Target language: 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": [
"tooling",
"cost_latency_tradeoffs",
"documentation",
"tests_are_truth"
],
"moe_experts": [
"coding_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 963702baf8d86ab6fb3adea400b82ef0cc2204bf | |
train_12364 | 2026-01-01T00:00:00 | Multimodal dev workflows (docs, diagrams, traces) | agent_loop | intermediate | Task: agent_loop
Topic: Multimodal dev workflows (docs, diagrams, traces)
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.
Loop: Plan → Edit → Test → Reflect → Human gate
| [] | {
"target_language": "Java",
"developer_needs": [
"evaluation_metrics",
"cost_latency_tradeoffs",
"repo_scale_reasoning",
"security_gates"
],
"moe_experts": [
"governance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | c13aa6a977353f9b75808936394791a47e1660ae | |
train_12365 | 2026-01-01T00:00:00 | Model merging, distillation, and continued pretraining | review | intermediate | Task: review
Topic: Model merging, distillation, and continued pretraining
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.
Review: correctness, security, performance, governance
| [] | {
"target_language": "Java",
"developer_needs": [
"repo_scale_reasoning",
"cost_latency_tradeoffs",
"evaluation_metrics",
"documentation"
],
"moe_experts": [
"coding_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 828c20ce5b6619eb48714b1917c4382492c8f3d2 | |
train_12366 | 2026-01-01T00:00:00 | Extended context and repo-scale understanding | agent_loop | advanced | Task: agent_loop
Topic: Extended context and repo-scale understanding
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.
Loop: Plan → Edit → Test → Reflect → Human gate
| [] | {
"target_language": "Go",
"developer_needs": [
"security_gates",
"cost_latency_tradeoffs",
"reproducibility",
"tests_are_truth"
],
"moe_experts": [
"coding_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 52817542c23032420f74675680881574bf5eed9d | |
train_12367 | 2026-01-01T00:00:00 | Secure code generation and policy gates | compare | intermediate | Task: compare
Topic: Secure code generation and policy gates
Difficulty: intermediate
Target language: 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.
Compare: capability, cost, latency, reliability
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "C#",
"developer_needs": [
"documentation",
"ci_integration",
"auditability",
"repo_scale_reasoning"
],
"moe_experts": [
"agentic_systems_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | c9e0bcb9e45869ebebdee7bae09effa322315bf2 | |
train_12368 | 2026-01-01T00:00:00 | Dataset curation pipelines (filter, dedupe, quality) | compare | advanced | Task: compare
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: advanced
Target language: C#
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
| [] | {
"target_language": "C#",
"developer_needs": [
"tests_are_truth",
"documentation",
"security_gates",
"reproducibility"
],
"moe_experts": [
"governance_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 05c9bbf913a8a84e86550e798a56e0846900282d | |
train_12369 | 2026-01-01T00:00:00 | Multimodal dev workflows (docs, diagrams, traces) | compare | intermediate | Task: compare
Topic: Multimodal dev workflows (docs, diagrams, traces)
Difficulty: intermediate
Target language: 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.
Compare: capability, cost, latency, reliability
| [] | {
"target_language": "C#",
"developer_needs": [
"cost_latency_tradeoffs",
"documentation",
"ci_integration",
"tests_are_truth"
],
"moe_experts": [
"security_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 81247da0ecc710ac8e2ac24dbdb1bc4cc8903f64 | |
train_12370 | 2026-01-01T00:00:00 | Agentic coding systems (plan→edit→test→reflect) | data_pipeline | expert | Task: data_pipeline
Topic: Agentic coding systems (plan→edit→test→reflect)
Difficulty: expert
Target language: 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.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
| [] | {
"target_language": "C#",
"developer_needs": [
"tooling",
"cost_latency_tradeoffs",
"auditability",
"repo_scale_reasoning"
],
"moe_experts": [
"data_curation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 7fc0357265032fa6155d1933ef7eecc8a73858df | |
train_12371 | 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: 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": [
"auditability",
"repo_scale_reasoning",
"tests_are_truth",
"cost_latency_tradeoffs"
],
"moe_experts": [
"evaluation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 46f91f01f1691ec4555dc1ebe06ecee8b89fa38f | |
train_12372 | 2026-01-01T00:00:00 | Governance, provenance, and licensing for code data | code | expert | Task: code
Topic: Governance, provenance, and licensing for code data
Difficulty: expert
Target language: Python
Context: 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.
Scaffold:
```python
def agent_loop(plan, edit, test, issue, max_iters=4):
history = []
p = plan(issue)
for _ in range(max_iters):
patch = edit(issue, p)
ok, report = test(patch)
history.append({"plan": p, "ok": ok})
if ok:
return patch, history
p = p + " | refine"
return patch, history
```
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Python",
"developer_needs": [
"documentation",
"auditability",
"repo_scale_reasoning",
"security_gates"
],
"moe_experts": [
"governance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 54dfe0e3b8df5c3897486d435860458015ea8bbe | |
train_12373 | 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: 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.
Review: correctness, security, performance, governance
| [] | {
"target_language": "Rust",
"developer_needs": [
"auditability",
"repo_scale_reasoning",
"tests_are_truth",
"evaluation_metrics"
],
"moe_experts": [
"agentic_systems_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | c2719cd16f51fac6666f69196f71bc158c90838b | |
train_12374 | 2026-01-01T00:00:00 | SWE-bench style real-repo evaluation | failure_analysis | intermediate | Task: failure_analysis
Topic: SWE-bench style real-repo evaluation
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.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
| [] | {
"target_language": "C#",
"developer_needs": [
"tooling",
"repo_scale_reasoning",
"governance",
"security_gates"
],
"moe_experts": [
"performance_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 73f60dcf6ea236f13915295e4e0f4cd73759ba66 | |
train_12375 | 2026-01-01T00:00:00 | Multimodal dev workflows (docs, diagrams, traces) | code | advanced | Task: code
Topic: Multimodal dev workflows (docs, diagrams, traces)
Difficulty: advanced
Target language: Bash
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "Bash",
"developer_needs": [
"cost_latency_tradeoffs",
"auditability",
"security_gates",
"documentation"
],
"moe_experts": [
"coding_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 91d1c0b10d65da75696c7a5e94b35e41fc0ee4e6 | |
train_12376 | 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: 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.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Rust",
"developer_needs": [
"evaluation_metrics",
"cost_latency_tradeoffs",
"tooling",
"documentation"
],
"moe_experts": [
"agentic_systems_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 52c48b33267de16d2f2648633d8bc3d5ab9dec35 | |
train_12377 | 2026-01-01T00:00:00 | Model merging, distillation, and continued pretraining | patch_diff | expert | Task: patch_diff
Topic: Model merging, distillation, and continued pretraining
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.
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": [
"tooling",
"tests_are_truth",
"repo_scale_reasoning",
"auditability"
],
"moe_experts": [
"coding_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 1fce3fd40fb2271c83baab7a401775ad62ac43e3 | |
train_12378 | 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: 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.
Review: correctness, security, performance, governance
| [] | {
"target_language": "JavaScript",
"developer_needs": [
"governance",
"auditability",
"tests_are_truth",
"cost_latency_tradeoffs"
],
"moe_experts": [
"performance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | b76447f282f1d2af20893a68a1fb46280050e0c7 | |
train_12379 | 2026-01-01T00:00:00 | Governance, provenance, and licensing for code data | patch_diff | expert | Task: patch_diff
Topic: Governance, provenance, and licensing for code data
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
| [
"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",
"security_gates",
"ci_integration",
"auditability"
],
"moe_experts": [
"performance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 37ea2bf8f81bfa979cefc7a95cd467749c329681 | |
train_12380 | 2026-01-01T00:00:00 | Code-specialized model families and sizing tradeoffs | patch_diff | expert | Task: patch_diff
Topic: Code-specialized model families and sizing tradeoffs
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": [
"ci_integration",
"tests_are_truth",
"repo_scale_reasoning",
"evaluation_metrics"
],
"moe_experts": [
"security_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | f9a5d0bb087729b48fd66fd3d6ff28744ab0f675 | |
train_12381 | 2026-01-01T00:00:00 | Dataset curation pipelines (filter, dedupe, quality) | explain | advanced | Task: explain
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: advanced
Target language: Go
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Go",
"developer_needs": [
"cost_latency_tradeoffs",
"repo_scale_reasoning",
"auditability",
"ci_integration"
],
"moe_experts": [
"governance_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 162cc83408e6da7706d56ba31e8a0b61d15a431e | |
train_12382 | 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: 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.
Eval:
pass@k, time-to-green, regressions, diff size
| [] | {
"target_language": "TypeScript",
"developer_needs": [
"ci_integration",
"security_gates",
"repo_scale_reasoning",
"tooling"
],
"moe_experts": [
"evaluation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 088f62e5df002ddc01970f7b396c196812bb85c9 | |
train_12383 | 2026-01-01T00:00:00 | Secure code generation and policy gates | explain | advanced | Task: explain
Topic: Secure code generation and policy gates
Difficulty: advanced
Target language: 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": [
"governance",
"reproducibility",
"tests_are_truth",
"repo_scale_reasoning"
],
"moe_experts": [
"security_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 249cfddbecb2a0a2f6b32b7921d71dc428e0b9d6 | |
train_12384 | 2026-01-01T00:00:00 | Dataset curation pipelines (filter, dedupe, quality) | eval | intermediate | Task: eval
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: intermediate
Target language: 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
| [] | {
"target_language": "Bash",
"developer_needs": [
"cost_latency_tradeoffs",
"auditability",
"evaluation_metrics",
"ci_integration"
],
"moe_experts": [
"performance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 26ef1b976690417c5409fbd5cece2527b282ae75 | |
train_12385 | 2026-01-01T00:00:00 | Code-specialized model families and sizing tradeoffs | design | advanced | Task: design
Topic: Code-specialized model families and sizing tradeoffs
Difficulty: advanced
Target language: Python
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "Python",
"developer_needs": [
"governance",
"tests_are_truth",
"security_gates",
"ci_integration"
],
"moe_experts": [
"agentic_systems_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | fd06a59dc9445b512857c9e9922c05f57f984205 | |
train_12386 | 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: 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": [
"governance",
"repo_scale_reasoning",
"evaluation_metrics",
"cost_latency_tradeoffs"
],
"moe_experts": [
"security_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 1e17ee16e39a02049524db9a6fafda50b1c43d02 | |
train_12387 | 2026-01-01T00:00:00 | Agentic coding systems (plan→edit→test→reflect) | review | advanced | Task: review
Topic: Agentic coding systems (plan→edit→test→reflect)
Difficulty: advanced
Target language: 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.
Review: correctness, security, performance, governance
| [] | {
"target_language": "Go",
"developer_needs": [
"evaluation_metrics",
"repo_scale_reasoning",
"security_gates",
"tests_are_truth"
],
"moe_experts": [
"coding_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | a5b1b6c8afa5a95f410cc5051090b4b2b6130536 | |
train_12388 | 2026-01-01T00:00:00 | Extended context and repo-scale understanding | review | advanced | Task: review
Topic: Extended context and repo-scale understanding
Difficulty: advanced
Target language: 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.
Review: correctness, security, performance, governance
| [] | {
"target_language": "TypeScript",
"developer_needs": [
"governance",
"repo_scale_reasoning",
"tests_are_truth",
"cost_latency_tradeoffs"
],
"moe_experts": [
"security_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 6c071d8963d9e69daa97917228594b3d8fca1dc4 | |
train_12389 | 2026-01-01T00:00:00 | SWE-bench style real-repo evaluation | code | intermediate | Task: code
Topic: SWE-bench style real-repo evaluation
Difficulty: intermediate
Target language: 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",
"repo_scale_reasoning",
"tests_are_truth",
"documentation"
],
"moe_experts": [
"agentic_systems_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 64800b45698da54dd6d48831581900132cdc01f9 | |
train_12390 | 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: 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": [
"evaluation_metrics",
"governance",
"tooling",
"auditability"
],
"moe_experts": [
"data_curation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | adf25af28747d5e524d119ea3876201befa1ec8d | |
train_12391 | 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: 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",
"documentation",
"repo_scale_reasoning",
"tooling"
],
"moe_experts": [
"performance_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 5fc24c35717ea458b6c43fdccf210ddc1033d7d2 | |
train_12392 | 2026-01-01T00:00:00 | Mixture-of-Experts (MoE) for code | agent_loop | intermediate | Task: agent_loop
Topic: Mixture-of-Experts (MoE) for code
Difficulty: intermediate
Target language: Bash
Context: 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": "Bash",
"developer_needs": [
"tests_are_truth",
"auditability",
"evaluation_metrics",
"tooling"
],
"moe_experts": [
"evaluation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 1d9517708950cb874f507937c737418eaa167a4b | |
train_12393 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | data_pipeline | expert | Task: data_pipeline
Topic: Latency, cost, and reliability optimization
Difficulty: expert
Target language: Bash
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
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": "Bash",
"developer_needs": [
"auditability",
"security_gates",
"documentation",
"ci_integration"
],
"moe_experts": [
"security_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 3fb136d26a981b19f785c7a231021a49ace3ecee | |
train_12394 | 2026-01-01T00:00:00 | SWE-bench style real-repo evaluation | code | intermediate | Task: code
Topic: SWE-bench style real-repo evaluation
Difficulty: intermediate
Target language: Rust
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "Rust",
"developer_needs": [
"tests_are_truth",
"evaluation_metrics",
"documentation",
"ci_integration"
],
"moe_experts": [
"performance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | c96801179aec92efc1ba3b109e18aedc4afd1261 | |
train_12395 | 2026-01-01T00:00:00 | Governance, provenance, and licensing for code data | data_pipeline | intermediate | Task: data_pipeline
Topic: Governance, provenance, and licensing for code data
Difficulty: intermediate
Target language: Rust
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Rust",
"developer_needs": [
"auditability",
"documentation",
"governance",
"reproducibility"
],
"moe_experts": [
"security_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 30efd5b79bd76b2957ab26639b2147e36badd8ca | |
train_12396 | 2026-01-01T00:00:00 | Extended context and repo-scale understanding | code | intermediate | Task: code
Topic: Extended context and repo-scale understanding
Difficulty: intermediate
Target language: 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": [
"tooling",
"auditability",
"reproducibility",
"evaluation_metrics"
],
"moe_experts": [
"data_curation_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | a6b618306205e6534d285fbd95b71942c39acf80 | |
train_12397 | 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
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Go",
"developer_needs": [
"governance",
"tooling",
"ci_integration",
"evaluation_metrics"
],
"moe_experts": [
"coding_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 4abd6d6a3ded36956166150ae96e74834474d502 | |
train_12398 | 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: 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": [
"cost_latency_tradeoffs",
"auditability",
"documentation",
"tooling"
],
"moe_experts": [
"data_curation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | bcc0adc0e872f933044f7f4c96b9eddff947815a | |
train_12399 | 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: Rust
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Rust",
"developer_needs": [
"reproducibility",
"tests_are_truth",
"tooling",
"ci_integration"
],
"moe_experts": [
"agentic_systems_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | d830661d5fe51afce7963ad5bd084e2bffbc908d |
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