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_31400 | 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: 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.
Compare: capability, cost, latency, reliability
| [] | {
"target_language": "Python",
"developer_needs": [
"auditability",
"repo_scale_reasoning",
"governance",
"documentation"
],
"moe_experts": [
"coding_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | e281a8308799d381215fa2a733e7c1810dd9b67d | |
train_31401 | 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: 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
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Bash",
"developer_needs": [
"cost_latency_tradeoffs",
"tooling",
"ci_integration",
"reproducibility"
],
"moe_experts": [
"data_curation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | dd98a3de83f86097aa7dca7b27160f786abe90dc | |
train_31402 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | agent_loop | intermediate | Task: agent_loop
Topic: Latency, cost, and reliability optimization
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.
Loop: Plan → Edit → Test → Reflect → Human gate
| [] | {
"target_language": "JavaScript",
"developer_needs": [
"repo_scale_reasoning",
"security_gates",
"auditability",
"reproducibility"
],
"moe_experts": [
"data_curation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | cb8e00d9f6445a289737ee2de235e1abca01b878 | |
train_31403 | 2026-01-01T00:00:00 | Model merging, distillation, and continued pretraining | review | expert | Task: review
Topic: Model merging, distillation, and continued pretraining
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.
Review: correctness, security, performance, governance
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Python",
"developer_needs": [
"repo_scale_reasoning",
"ci_integration",
"auditability",
"documentation"
],
"moe_experts": [
"governance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | ca1f8c24f8a676cccb7963dbdc71471aae4246e0 | |
train_31404 | 2026-01-01T00:00:00 | Governance, provenance, and licensing for code data | review | expert | Task: review
Topic: Governance, provenance, and licensing for code data
Difficulty: expert
Target language: 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
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "C#",
"developer_needs": [
"tooling",
"reproducibility",
"repo_scale_reasoning",
"auditability"
],
"moe_experts": [
"security_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 5f740b259d0cbf946d86b10f1bd805c985336926 | |
train_31405 | 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: 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": [
"ci_integration",
"governance",
"repo_scale_reasoning",
"tooling"
],
"moe_experts": [
"performance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 69d796a41004677faedb4fea85996b381fe1eee4 | |
train_31406 | 2026-01-01T00:00:00 | Agentic coding systems (plan→edit→test→reflect) | eval | advanced | Task: eval
Topic: Agentic coding systems (plan→edit→test→reflect)
Difficulty: advanced
Target language: Go
Context: 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": [
"cost_latency_tradeoffs",
"repo_scale_reasoning",
"tooling",
"ci_integration"
],
"moe_experts": [
"governance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | d3c5d0603bcd2cf1a93edbbca40983e6373e46c0 | |
train_31407 | 2026-01-01T00:00:00 | Mixture-of-Experts (MoE) for code | failure_analysis | intermediate | Task: failure_analysis
Topic: Mixture-of-Experts (MoE) for code
Difficulty: intermediate
Target language: 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.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
| [] | {
"target_language": "SQL",
"developer_needs": [
"security_gates",
"documentation",
"tests_are_truth",
"governance"
],
"moe_experts": [
"agentic_systems_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 4319687a01d7d0888f39381fe904c365e99dd822 | |
train_31408 | 2026-01-01T00:00:00 | Code-specialized model families and sizing tradeoffs | explain | expert | Task: explain
Topic: Code-specialized model families and sizing tradeoffs
Difficulty: expert
Target language: TypeScript
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "TypeScript",
"developer_needs": [
"tests_are_truth",
"evaluation_metrics",
"tooling",
"auditability"
],
"moe_experts": [
"data_curation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 084bd250e639e3e9ee8714794cd3886dd3426a0c | |
train_31409 | 2026-01-01T00:00:00 | Governance, provenance, and licensing for code data | code | advanced | Task: code
Topic: Governance, provenance, and licensing for code data
Difficulty: advanced
Target language: 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": [
"security_gates",
"tooling",
"auditability",
"governance"
],
"moe_experts": [
"governance_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | f0021e01c8987ccf52ddf0ae3fb0eb5f50c58112 | |
train_31410 | 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: Java
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Java",
"developer_needs": [
"governance",
"reproducibility",
"repo_scale_reasoning",
"ci_integration"
],
"moe_experts": [
"evaluation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 458084efc9c41289077127267a478f75ad30ac24 | |
train_31411 | 2026-01-01T00:00:00 | Reasoning-first coding models and tunable deliberation | eval | expert | Task: eval
Topic: Reasoning-first coding models and tunable deliberation
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.
Eval:
pass@k, time-to-green, regressions, diff size
| [] | {
"target_language": "Go",
"developer_needs": [
"tests_are_truth",
"repo_scale_reasoning",
"auditability",
"reproducibility"
],
"moe_experts": [
"evaluation_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 925c5bb6ce92b69909db0ff6b1aeb7157b54053f | |
train_31412 | 2026-01-01T00:00:00 | Secure code generation and policy gates | review | intermediate | Task: review
Topic: Secure code generation and policy gates
Difficulty: intermediate
Target language: 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
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "C#",
"developer_needs": [
"security_gates",
"evaluation_metrics",
"auditability",
"documentation"
],
"moe_experts": [
"coding_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 006387ceb4bc165c398f216dc92dc6fdbfe3030d | |
train_31413 | 2026-01-01T00:00:00 | Secure code generation and policy gates | data_pipeline | advanced | Task: data_pipeline
Topic: Secure code generation and policy gates
Difficulty: advanced
Target language: Bash
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Bash",
"developer_needs": [
"cost_latency_tradeoffs",
"security_gates",
"auditability",
"repo_scale_reasoning"
],
"moe_experts": [
"security_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 0643683fafb87f11298457b5b759bd870ef0aff7 | |
train_31414 | 2026-01-01T00:00:00 | Extended context and repo-scale understanding | eval | expert | Task: eval
Topic: Extended context and repo-scale understanding
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
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Bash",
"developer_needs": [
"security_gates",
"tooling",
"auditability",
"tests_are_truth"
],
"moe_experts": [
"performance_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 22a63634bfe2d5f55e2843e7b5f4764188254f20 | |
train_31415 | 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: TypeScript
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "TypeScript",
"developer_needs": [
"tests_are_truth",
"security_gates",
"auditability",
"repo_scale_reasoning"
],
"moe_experts": [
"coding_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 9452c9657db433ed982d422e4fcd1cd91b3bf541 | |
train_31416 | 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: 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": [
"ci_integration",
"repo_scale_reasoning",
"evaluation_metrics",
"documentation"
],
"moe_experts": [
"data_curation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 6bc9ed12ff71c364809defe21a623a16abef67c9 | |
train_31417 | 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: Python
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
| [] | {
"target_language": "Python",
"developer_needs": [
"tests_are_truth",
"ci_integration",
"reproducibility",
"documentation"
],
"moe_experts": [
"agentic_systems_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | dbfb42d14d843819b5bff66f9f35a69cfaac56c7 | |
train_31418 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | explain | intermediate | Task: explain
Topic: Latency, cost, and reliability optimization
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.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "Java",
"developer_needs": [
"security_gates",
"auditability",
"reproducibility",
"evaluation_metrics"
],
"moe_experts": [
"data_curation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | a350356fee6a2f3e3e19ed44c28a4cbc7684a296 | |
train_31419 | 2026-01-01T00:00:00 | Dataset curation pipelines (filter, dedupe, quality) | code | expert | Task: code
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: expert
Target language: Bash
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
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": [
"repo_scale_reasoning",
"reproducibility",
"governance",
"documentation"
],
"moe_experts": [
"governance_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 473c70a7f2f0c744b2f86dda9ecc3483d5050a21 | |
train_31420 | 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: 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.
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": [
"documentation",
"tests_are_truth",
"cost_latency_tradeoffs",
"ci_integration"
],
"moe_experts": [
"governance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 90385f2c57a52f1af68ef7b4dcab5bba1c1a2300 | |
train_31421 | 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: 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": [
"reproducibility",
"evaluation_metrics",
"documentation",
"tooling"
],
"moe_experts": [
"agentic_systems_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 0787d938ea72f522772990c02ca87f1c5280c738 | |
train_31422 | 2026-01-01T00:00:00 | Extended context and repo-scale understanding | code | expert | Task: code
Topic: Extended context and repo-scale understanding
Difficulty: expert
Target language: C#
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "C#",
"developer_needs": [
"auditability",
"tests_are_truth",
"cost_latency_tradeoffs",
"security_gates"
],
"moe_experts": [
"performance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | d131bb3522c1ff551a7bf3ec74d60337b8092183 | |
train_31423 | 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: SQL
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "SQL",
"developer_needs": [
"cost_latency_tradeoffs",
"tooling",
"evaluation_metrics",
"repo_scale_reasoning"
],
"moe_experts": [
"data_curation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 7647694813bf84062ee6a76e8fe3f5540a2b9c76 | |
train_31424 | 2026-01-01T00:00:00 | Mixture-of-Experts (MoE) for code | eval | intermediate | Task: eval
Topic: Mixture-of-Experts (MoE) for code
Difficulty: intermediate
Target language: Rust
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Rust",
"developer_needs": [
"documentation",
"security_gates",
"reproducibility",
"tooling"
],
"moe_experts": [
"data_curation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | a5c8b637cb8b3ac5633542199eb0043edc6e9d6c | |
train_31425 | 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: 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": [
"security_gates",
"governance",
"evaluation_metrics",
"tests_are_truth"
],
"moe_experts": [
"agentic_systems_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 9f924935010f376e2ca28ec2cb6fdfee788e2b18 | |
train_31426 | 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: 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.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
| [] | {
"target_language": "Bash",
"developer_needs": [
"security_gates",
"tests_are_truth",
"governance",
"documentation"
],
"moe_experts": [
"performance_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | e5307a9bf15eda34502890239eed11f8181731ea | |
train_31427 | 2026-01-01T00:00:00 | Multimodal dev workflows (docs, diagrams, traces) | design | advanced | Task: design
Topic: Multimodal dev workflows (docs, diagrams, traces)
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": [
"evaluation_metrics",
"auditability",
"reproducibility",
"security_gates"
],
"moe_experts": [
"performance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 8ef38aaf108529e931a59c4dfa2b775afdfc9a01 | |
train_31428 | 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: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "TypeScript",
"developer_needs": [
"security_gates",
"tooling",
"tests_are_truth",
"repo_scale_reasoning"
],
"moe_experts": [
"performance_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | d32d575d9595726d4eb22419ea0e079e037f11c9 | |
train_31429 | 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: TypeScript
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "TypeScript",
"developer_needs": [
"reproducibility",
"tests_are_truth",
"documentation",
"tooling"
],
"moe_experts": [
"security_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 67b73d21b9b164d3f7f39f851c258ea31c7cbd82 | |
train_31430 | 2026-01-01T00:00:00 | Secure code generation and policy gates | eval | expert | Task: eval
Topic: Secure code generation and policy gates
Difficulty: expert
Target language: Rust
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Rust",
"developer_needs": [
"auditability",
"evaluation_metrics",
"documentation",
"governance"
],
"moe_experts": [
"performance_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 3aeb0cbb224e6b8aec630233810f401f5615b1fc | |
train_31431 | 2026-01-01T00:00:00 | Tool calling, sandboxes, and CI integration | failure_analysis | advanced | Task: failure_analysis
Topic: Tool calling, sandboxes, and CI integration
Difficulty: advanced
Target language: JavaScript
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
| [] | {
"target_language": "JavaScript",
"developer_needs": [
"security_gates",
"documentation",
"ci_integration",
"reproducibility"
],
"moe_experts": [
"governance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 92836de901b0b72e00dbd20823751882dc488686 | |
train_31432 | 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: 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.
Patch (diff-style):
```diff
- if x == 0:
- return 1/x
+ if x == 0:
+ raise ValueError('division by zero')
```
Acceptance:
- Tests pass
- No new regressions
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "JavaScript",
"developer_needs": [
"governance",
"reproducibility",
"repo_scale_reasoning",
"evaluation_metrics"
],
"moe_experts": [
"governance_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 9d008e18e21e62705d8398da94f47dad02bd5705 | |
train_31433 | 2026-01-01T00:00:00 | Agentic coding systems (plan→edit→test→reflect) | code | intermediate | Task: code
Topic: Agentic coding systems (plan→edit→test→reflect)
Difficulty: intermediate
Target language: Python
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Scaffold:
```python
def agent_loop(plan, edit, test, issue, max_iters=4):
history = []
p = plan(issue)
for _ in range(max_iters):
patch = edit(issue, p)
ok, report = test(patch)
history.append({"plan": p, "ok": ok})
if ok:
return patch, history
p = p + " | refine"
return patch, history
```
| [] | {
"target_language": "Python",
"developer_needs": [
"evaluation_metrics",
"ci_integration",
"reproducibility",
"tests_are_truth"
],
"moe_experts": [
"coding_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | ee11923a4737b2c062dd2c1ef26a3a8864e2ee0b | |
train_31434 | 2026-01-01T00:00:00 | Reasoning-first coding models and tunable deliberation | failure_analysis | expert | Task: failure_analysis
Topic: Reasoning-first coding models and tunable deliberation
Difficulty: expert
Target language: C#
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
| [] | {
"target_language": "C#",
"developer_needs": [
"governance",
"auditability",
"documentation",
"cost_latency_tradeoffs"
],
"moe_experts": [
"governance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | bd439e093f587f53dace6ba5ed12e330ae92ad81 | |
train_31435 | 2026-01-01T00:00:00 | Code-specialized model families and sizing tradeoffs | explain | intermediate | Task: explain
Topic: Code-specialized model families and sizing tradeoffs
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
| [] | {
"target_language": "C#",
"developer_needs": [
"tooling",
"cost_latency_tradeoffs",
"ci_integration",
"security_gates"
],
"moe_experts": [
"agentic_systems_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | a28580e3db23259bf9532f6a18a0ee599328f7f3 | |
train_31436 | 2026-01-01T00:00:00 | Reasoning-first coding models and tunable deliberation | review | expert | Task: review
Topic: Reasoning-first coding models and tunable deliberation
Difficulty: expert
Target language: 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": [
"security_gates",
"reproducibility",
"evaluation_metrics",
"tests_are_truth"
],
"moe_experts": [
"performance_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | a99926b5e46c1508dd68415f9adaa5a257659e2b | |
train_31437 | 2026-01-01T00:00:00 | Model merging, distillation, and continued pretraining | compare | intermediate | Task: compare
Topic: Model merging, distillation, and continued pretraining
Difficulty: intermediate
Target language: Java
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
| [] | {
"target_language": "Java",
"developer_needs": [
"evaluation_metrics",
"security_gates",
"auditability",
"reproducibility"
],
"moe_experts": [
"governance_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | c36bf0b2bae83f3b41b0cb5d1f7e15436e180964 | |
train_31438 | 2026-01-01T00:00:00 | Multimodal dev workflows (docs, diagrams, traces) | agent_loop | expert | Task: agent_loop
Topic: Multimodal dev workflows (docs, diagrams, traces)
Difficulty: expert
Target language: Java
Context: 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": "Java",
"developer_needs": [
"repo_scale_reasoning",
"security_gates",
"ci_integration",
"cost_latency_tradeoffs"
],
"moe_experts": [
"coding_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 9d1df00035210c4253cf8722595886b6c878d3fc | |
train_31439 | 2026-01-01T00:00:00 | Governance, provenance, and licensing for code data | failure_analysis | intermediate | Task: failure_analysis
Topic: Governance, provenance, and licensing for code data
Difficulty: intermediate
Target language: 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.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
| [] | {
"target_language": "C#",
"developer_needs": [
"cost_latency_tradeoffs",
"documentation",
"auditability",
"tests_are_truth"
],
"moe_experts": [
"security_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | cc1943f4f0020339fe9fc6b7caa014c0da3591e2 | |
train_31440 | 2026-01-01T00:00:00 | Mixture-of-Experts (MoE) for code | review | advanced | Task: review
Topic: Mixture-of-Experts (MoE) for code
Difficulty: advanced
Target language: Go
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Review: correctness, security, performance, governance
| [] | {
"target_language": "Go",
"developer_needs": [
"auditability",
"documentation",
"ci_integration",
"evaluation_metrics"
],
"moe_experts": [
"performance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 617d91b037191add1855ce9f42b1a746f1cdb2e1 | |
train_31441 | 2026-01-01T00:00:00 | Multimodal dev workflows (docs, diagrams, traces) | review | advanced | Task: review
Topic: Multimodal dev workflows (docs, diagrams, traces)
Difficulty: advanced
Target language: 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.
Review: correctness, security, performance, governance
| [] | {
"target_language": "JavaScript",
"developer_needs": [
"documentation",
"reproducibility",
"repo_scale_reasoning",
"evaluation_metrics"
],
"moe_experts": [
"performance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 98585192604c9aad53e27b96181cef02ad3d1932 | |
train_31442 | 2026-01-01T00:00:00 | Dataset curation pipelines (filter, dedupe, quality) | failure_analysis | advanced | Task: failure_analysis
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: advanced
Target language: JavaScript
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "JavaScript",
"developer_needs": [
"repo_scale_reasoning",
"governance",
"tests_are_truth",
"auditability"
],
"moe_experts": [
"security_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 5ecab89c35f8ed1d7e805519f57961eabcc9e39a | |
train_31443 | 2026-01-01T00:00:00 | Reasoning-first coding models and tunable deliberation | design | expert | Task: design
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
| [] | {
"target_language": "Bash",
"developer_needs": [
"governance",
"reproducibility",
"evaluation_metrics",
"cost_latency_tradeoffs"
],
"moe_experts": [
"evaluation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 403c9095ce4146e5f39e2cab60e8e69894383749 | |
train_31444 | 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: C#
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "C#",
"developer_needs": [
"ci_integration",
"governance",
"repo_scale_reasoning",
"tests_are_truth"
],
"moe_experts": [
"data_curation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 3a8c6c0f6adf28ac248922d79d0e298656f156df | |
train_31445 | 2026-01-01T00:00:00 | Agentic coding systems (plan→edit→test→reflect) | explain | advanced | Task: explain
Topic: Agentic coding systems (plan→edit→test→reflect)
Difficulty: advanced
Target language: Python
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "Python",
"developer_needs": [
"auditability",
"security_gates",
"cost_latency_tradeoffs",
"tooling"
],
"moe_experts": [
"security_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 02295434d1b40aaa5926a714c8b03a9de9f9d275 | |
train_31446 | 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: 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.
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": [
"evaluation_metrics",
"auditability",
"tooling",
"reproducibility"
],
"moe_experts": [
"evaluation_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 4c35ac634f30646b886b51897ebabc6752a5629d | |
train_31447 | 2026-01-01T00:00:00 | Code-specialized model families and sizing tradeoffs | compare | expert | Task: compare
Topic: Code-specialized model families and sizing tradeoffs
Difficulty: expert
Target language: Bash
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
| [] | {
"target_language": "Bash",
"developer_needs": [
"evaluation_metrics",
"ci_integration",
"documentation",
"repo_scale_reasoning"
],
"moe_experts": [
"security_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 6c07acf296451868c58d692b1d6157a770314e35 | |
train_31448 | 2026-01-01T00:00:00 | Governance, provenance, and licensing for code data | agent_loop | intermediate | Task: agent_loop
Topic: Governance, provenance, and licensing for code data
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.
Loop: Plan → Edit → Test → Reflect → Human gate
| [] | {
"target_language": "JavaScript",
"developer_needs": [
"auditability",
"documentation",
"security_gates",
"cost_latency_tradeoffs"
],
"moe_experts": [
"performance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 1d34b60b04ac2f65d17935f058bfce4c39c5fbda | |
train_31449 | 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: 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.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
| [] | {
"target_language": "SQL",
"developer_needs": [
"governance",
"security_gates",
"repo_scale_reasoning",
"cost_latency_tradeoffs"
],
"moe_experts": [
"agentic_systems_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | a5e41072f16b005b858d34a83462516c16fb6724 | |
train_31450 | 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: 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.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
| [] | {
"target_language": "Rust",
"developer_needs": [
"governance",
"reproducibility",
"repo_scale_reasoning",
"auditability"
],
"moe_experts": [
"coding_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 43b50ace4a02c8c99073670fd750b47f0c3d2003 | |
train_31451 | 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: 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": [
"evaluation_metrics",
"security_gates",
"tests_are_truth",
"reproducibility"
],
"moe_experts": [
"performance_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | b2cacd75e20657e429ee4dec3bb6638ba7a5bbe2 | |
train_31452 | 2026-01-01T00:00:00 | Extended context and repo-scale understanding | eval | intermediate | Task: eval
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.
Eval:
pass@k, time-to-green, regressions, diff size
| [] | {
"target_language": "Go",
"developer_needs": [
"evaluation_metrics",
"reproducibility",
"documentation",
"ci_integration"
],
"moe_experts": [
"performance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 0f5a1a9ba316cc36f22aa7eb7f4bc793d000d31c | |
train_31453 | 2026-01-01T00:00:00 | Reasoning-first coding models and tunable deliberation | data_pipeline | intermediate | Task: data_pipeline
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.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
| [] | {
"target_language": "Python",
"developer_needs": [
"auditability",
"reproducibility",
"tooling",
"security_gates"
],
"moe_experts": [
"data_curation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | e943a9a5a1c1a6127163d0fed30eb036bf3ecbb1 | |
train_31454 | 2026-01-01T00:00:00 | Secure code generation and policy gates | design | advanced | Task: design
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.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "Bash",
"developer_needs": [
"tests_are_truth",
"cost_latency_tradeoffs",
"repo_scale_reasoning",
"governance"
],
"moe_experts": [
"evaluation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 957087a20914085762c2cee7463a117d25cf080a | |
train_31455 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | agent_loop | intermediate | Task: agent_loop
Topic: Latency, cost, and reliability optimization
Difficulty: intermediate
Target language: Python
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
| [] | {
"target_language": "Python",
"developer_needs": [
"security_gates",
"governance",
"tooling",
"repo_scale_reasoning"
],
"moe_experts": [
"governance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | b0ef4ab8948ea24f89da6d132a2d7d4bc0c8f6dd | |
train_31456 | 2026-01-01T00:00:00 | Mixture-of-Experts (MoE) for code | data_pipeline | intermediate | Task: data_pipeline
Topic: Mixture-of-Experts (MoE) for code
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.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
| [] | {
"target_language": "JavaScript",
"developer_needs": [
"cost_latency_tradeoffs",
"security_gates",
"auditability",
"evaluation_metrics"
],
"moe_experts": [
"security_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 039b71644af2d8cd8226f469a05c79d4d6d03fa8 | |
train_31457 | 2026-01-01T00:00:00 | Governance, provenance, and licensing for code data | eval | expert | Task: eval
Topic: Governance, provenance, and licensing for code data
Difficulty: expert
Target language: Go
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
| [] | {
"target_language": "Go",
"developer_needs": [
"cost_latency_tradeoffs",
"security_gates",
"governance",
"auditability"
],
"moe_experts": [
"agentic_systems_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 8c5f1bdf8fb4f0879dac7cc24c8213e37267101a | |
train_31458 | 2026-01-01T00:00:00 | SWE-bench style real-repo evaluation | review | expert | Task: review
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.
Review: correctness, security, performance, governance
| [] | {
"target_language": "Go",
"developer_needs": [
"tests_are_truth",
"evaluation_metrics",
"tooling",
"governance"
],
"moe_experts": [
"coding_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 2c0cb02d2979ef213dd4ad360239e4eb79801b74 | |
train_31459 | 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: 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": [
"cost_latency_tradeoffs",
"reproducibility",
"evaluation_metrics",
"tooling"
],
"moe_experts": [
"data_curation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | dd6843281ee952a156ffe34cb9de205d66a5ed76 | |
train_31460 | 2026-01-01T00:00:00 | Secure code generation and policy gates | failure_analysis | expert | Task: failure_analysis
Topic: Secure code generation and policy gates
Difficulty: expert
Target language: 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": [
"ci_integration",
"cost_latency_tradeoffs",
"documentation",
"reproducibility"
],
"moe_experts": [
"evaluation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 820b251c2ea225ca4e3b8ef19f7d9daccab92031 | |
train_31461 | 2026-01-01T00:00:00 | Dataset curation pipelines (filter, dedupe, quality) | failure_analysis | expert | Task: failure_analysis
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: expert
Target language: Python
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
| [] | {
"target_language": "Python",
"developer_needs": [
"ci_integration",
"repo_scale_reasoning",
"governance",
"auditability"
],
"moe_experts": [
"governance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 49d0a0fa4df641b8c2e641463f0a998a40343ed6 | |
train_31462 | 2026-01-01T00:00:00 | Self-improving agents and feedback loops | data_pipeline | intermediate | Task: data_pipeline
Topic: Self-improving agents and feedback loops
Difficulty: intermediate
Target language: 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
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Go",
"developer_needs": [
"repo_scale_reasoning",
"security_gates",
"documentation",
"cost_latency_tradeoffs"
],
"moe_experts": [
"agentic_systems_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | b9793adc0a22813f132c9862d38ac6f69b8678aa | |
train_31463 | 2026-01-01T00:00:00 | Mixture-of-Experts (MoE) for code | design | intermediate | Task: design
Topic: Mixture-of-Experts (MoE) for code
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": [
"reproducibility",
"auditability",
"security_gates",
"tests_are_truth"
],
"moe_experts": [
"security_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | c6fff7e70a55299b7c7ddacc04a1d646eb8038ce | |
train_31464 | 2026-01-01T00:00:00 | Model merging, distillation, and continued pretraining | agent_loop | advanced | Task: agent_loop
Topic: Model merging, distillation, and continued pretraining
Difficulty: advanced
Target language: Java
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Java",
"developer_needs": [
"ci_integration",
"governance",
"repo_scale_reasoning",
"documentation"
],
"moe_experts": [
"coding_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 40c57190b8a20ee1859a7e70cbc25044366b0ee8 | |
train_31465 | 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: 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": [
"security_gates",
"governance",
"tooling",
"auditability"
],
"moe_experts": [
"security_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 2910c0cd8e9ce0a987b7426743a9bee0048e5308 | |
train_31466 | 2026-01-01T00:00:00 | Reasoning-first coding models and tunable deliberation | eval | expert | Task: eval
Topic: Reasoning-first coding models and tunable deliberation
Difficulty: expert
Target language: JavaScript
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "JavaScript",
"developer_needs": [
"tooling",
"ci_integration",
"evaluation_metrics",
"security_gates"
],
"moe_experts": [
"performance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | bdb9a50a304db8029ba335bd7b18afa0ffe4acc4 | |
train_31467 | 2026-01-01T00:00:00 | Mixture-of-Experts (MoE) for code | agent_loop | expert | Task: agent_loop
Topic: Mixture-of-Experts (MoE) for code
Difficulty: expert
Target language: TypeScript
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
| [] | {
"target_language": "TypeScript",
"developer_needs": [
"cost_latency_tradeoffs",
"governance",
"security_gates",
"tests_are_truth"
],
"moe_experts": [
"governance_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | c24f8de6cb7ee029952159ab4d5df832565435ca | |
train_31468 | 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: 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": [
"reproducibility",
"cost_latency_tradeoffs",
"repo_scale_reasoning",
"governance"
],
"moe_experts": [
"performance_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 6f7b2f8730c8ce252fc697ff5f3aea7e498a08ea | |
train_31469 | 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: 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": [
"auditability",
"ci_integration",
"repo_scale_reasoning",
"governance"
],
"moe_experts": [
"security_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 2fc3a987c135b8a821435dc461a53faa75fc0888 | |
train_31470 | 2026-01-01T00:00:00 | Agentic coding systems (plan→edit→test→reflect) | explain | advanced | Task: explain
Topic: Agentic coding systems (plan→edit→test→reflect)
Difficulty: advanced
Target language: 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": [
"security_gates",
"reproducibility",
"tooling",
"cost_latency_tradeoffs"
],
"moe_experts": [
"security_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 44068dcfae007b8d831a195aca0f7d2e3f9fb93e | |
train_31471 | 2026-01-01T00:00:00 | Reasoning-first coding models and tunable deliberation | failure_analysis | expert | Task: failure_analysis
Topic: Reasoning-first coding models and tunable deliberation
Difficulty: expert
Target language: Java
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Java",
"developer_needs": [
"documentation",
"evaluation_metrics",
"cost_latency_tradeoffs",
"tests_are_truth"
],
"moe_experts": [
"agentic_systems_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 0fa463b899706d660c4c73d875476c3f09f29176 | |
train_31472 | 2026-01-01T00:00:00 | Mixture-of-Experts (MoE) for code | review | expert | Task: review
Topic: Mixture-of-Experts (MoE) for code
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.
Review: correctness, security, performance, governance
| [] | {
"target_language": "TypeScript",
"developer_needs": [
"reproducibility",
"security_gates",
"repo_scale_reasoning",
"governance"
],
"moe_experts": [
"agentic_systems_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | c24356ed90c4d13fa0a9ac6fe28b03d73685c279 | |
train_31473 | 2026-01-01T00:00:00 | Dataset curation pipelines (filter, dedupe, quality) | design | intermediate | Task: design
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: intermediate
Target language: Python
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "Python",
"developer_needs": [
"reproducibility",
"evaluation_metrics",
"tests_are_truth",
"auditability"
],
"moe_experts": [
"data_curation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | ce1c12f977f3f3420e858356ccbebccc95d59f49 | |
train_31474 | 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: 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.
Review: correctness, security, performance, governance
| [] | {
"target_language": "TypeScript",
"developer_needs": [
"cost_latency_tradeoffs",
"evaluation_metrics",
"tooling",
"security_gates"
],
"moe_experts": [
"governance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | f7542f51d3ce8145be64b5a8836c12cb4b4d8d2a | |
train_31475 | 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: 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
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "C#",
"developer_needs": [
"auditability",
"ci_integration",
"cost_latency_tradeoffs",
"evaluation_metrics"
],
"moe_experts": [
"evaluation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | ec406e0c25de17f98b5f4eba5d3c1077ad35a9ab | |
train_31476 | 2026-01-01T00:00:00 | Dataset curation pipelines (filter, dedupe, quality) | explain | expert | Task: explain
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: expert
Target language: Rust
Context: 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": "Rust",
"developer_needs": [
"security_gates",
"cost_latency_tradeoffs",
"ci_integration",
"repo_scale_reasoning"
],
"moe_experts": [
"governance_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 576f549bd241fdea166c8b91d68adef41d11c756 | |
train_31477 | 2026-01-01T00:00:00 | Code-specialized model families and sizing tradeoffs | review | expert | Task: review
Topic: Code-specialized model families and sizing tradeoffs
Difficulty: expert
Target language: 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": [
"repo_scale_reasoning",
"auditability",
"reproducibility",
"tooling"
],
"moe_experts": [
"evaluation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | e5970490cbaf4b0122c005fb02294771a7a074ec | |
train_31478 | 2026-01-01T00:00:00 | Mixture-of-Experts (MoE) for code | code | advanced | Task: code
Topic: Mixture-of-Experts (MoE) for code
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.
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",
"documentation",
"cost_latency_tradeoffs",
"security_gates"
],
"moe_experts": [
"coding_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | e95a2eeb833a19efd78a3174abeffe15c8a41595 | |
train_31479 | 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: 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
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "JavaScript",
"developer_needs": [
"evaluation_metrics",
"tooling",
"repo_scale_reasoning",
"governance"
],
"moe_experts": [
"evaluation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | efb37294514038a1167ad04ddfcb5737009f29ee | |
train_31480 | 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: Python
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Scaffold:
```python
def agent_loop(plan, edit, test, issue, max_iters=4):
history = []
p = plan(issue)
for _ in range(max_iters):
patch = edit(issue, p)
ok, report = test(patch)
history.append({"plan": p, "ok": ok})
if ok:
return patch, history
p = p + " | refine"
return patch, history
```
| [] | {
"target_language": "Python",
"developer_needs": [
"auditability",
"ci_integration",
"documentation",
"security_gates"
],
"moe_experts": [
"security_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 5c4690dadb6d8dc79094afda89b90afc9232b215 | |
train_31481 | 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: 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.
Loop: Plan → Edit → Test → Reflect → Human gate
| [] | {
"target_language": "Rust",
"developer_needs": [
"ci_integration",
"tooling",
"tests_are_truth",
"security_gates"
],
"moe_experts": [
"evaluation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 3780dc897a9fe4ce30ff1ae642254492d04fa545 | |
train_31482 | 2026-01-01T00:00:00 | Code-specialized model families and sizing tradeoffs | design | expert | Task: design
Topic: Code-specialized model families and sizing tradeoffs
Difficulty: expert
Target language: 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",
"reproducibility",
"evaluation_metrics",
"ci_integration"
],
"moe_experts": [
"security_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 7d1b79ce69f0976c0902477a48137372b026cc94 | |
train_31483 | 2026-01-01T00:00:00 | Reasoning-first coding models and tunable deliberation | code | expert | Task: code
Topic: Reasoning-first coding models and tunable deliberation
Difficulty: expert
Target language: 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": [
"governance",
"evaluation_metrics",
"cost_latency_tradeoffs",
"security_gates"
],
"moe_experts": [
"security_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 6557acfb47645b40ef455135f05f1df66ba914cc | |
train_31484 | 2026-01-01T00:00:00 | Extended context and repo-scale understanding | eval | expert | Task: eval
Topic: Extended context and repo-scale understanding
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.
Eval:
pass@k, time-to-green, regressions, diff size
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Go",
"developer_needs": [
"reproducibility",
"cost_latency_tradeoffs",
"ci_integration",
"tooling"
],
"moe_experts": [
"agentic_systems_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 278c9923152899982fe94ae7cb4461ab07958c25 | |
train_31485 | 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: 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": [
"ci_integration",
"auditability",
"security_gates",
"repo_scale_reasoning"
],
"moe_experts": [
"governance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 873f309633f9a81b8b64b2a2f11e7184ab44d48b | |
train_31486 | 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: 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.
Patch (diff-style):
```diff
- if x == 0:
- return 1/x
+ if x == 0:
+ raise ValueError('division by zero')
```
Acceptance:
- Tests pass
- No new regressions
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "JavaScript",
"developer_needs": [
"repo_scale_reasoning",
"cost_latency_tradeoffs",
"security_gates",
"tests_are_truth"
],
"moe_experts": [
"security_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | e899f432848221a42343c9e48e3ed4c77942012f | |
train_31487 | 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: 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.
Loop: Plan → Edit → Test → Reflect → Human gate
| [] | {
"target_language": "C#",
"developer_needs": [
"repo_scale_reasoning",
"cost_latency_tradeoffs",
"ci_integration",
"documentation"
],
"moe_experts": [
"performance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 8bb3ce4ab60df9a8b78a27b66674a48ef29dee73 | |
train_31488 | 2026-01-01T00:00:00 | Extended context and repo-scale understanding | design | expert | Task: design
Topic: Extended context and repo-scale understanding
Difficulty: expert
Target language: Java
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "Java",
"developer_needs": [
"repo_scale_reasoning",
"cost_latency_tradeoffs",
"security_gates",
"documentation"
],
"moe_experts": [
"coding_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | e6964c961a25298773032a46f27da07a434d9d55 | |
train_31489 | 2026-01-01T00:00:00 | Reasoning-first coding models and tunable deliberation | failure_analysis | intermediate | Task: failure_analysis
Topic: Reasoning-first coding models and tunable deliberation
Difficulty: intermediate
Target language: 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.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
| [] | {
"target_language": "Rust",
"developer_needs": [
"security_gates",
"repo_scale_reasoning",
"auditability",
"evaluation_metrics"
],
"moe_experts": [
"security_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 74ca802d8d97a49eee3638eeb8239b9c6061ddba | |
train_31490 | 2026-01-01T00:00:00 | Extended context and repo-scale understanding | compare | advanced | Task: compare
Topic: Extended context and repo-scale understanding
Difficulty: advanced
Target language: 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.
Compare: capability, cost, latency, reliability
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Go",
"developer_needs": [
"tooling",
"governance",
"auditability",
"repo_scale_reasoning"
],
"moe_experts": [
"security_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 866254a7dac49c99f9fe7da7d7b66ff5666f84e3 | |
train_31491 | 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: 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.
Compare: capability, cost, latency, reliability
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Rust",
"developer_needs": [
"ci_integration",
"repo_scale_reasoning",
"tests_are_truth",
"security_gates"
],
"moe_experts": [
"governance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 991f7b7ce2e0eef77abe3cf33c777ca48f9ed8a3 | |
train_31492 | 2026-01-01T00:00:00 | Agentic coding systems (plan→edit→test→reflect) | failure_analysis | advanced | Task: failure_analysis
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.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
| [] | {
"target_language": "TypeScript",
"developer_needs": [
"tooling",
"auditability",
"governance",
"reproducibility"
],
"moe_experts": [
"agentic_systems_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 1503c668802e80c3dc3354694ae756292a663d2a | |
train_31493 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | patch_diff | advanced | Task: patch_diff
Topic: Latency, cost, and reliability optimization
Difficulty: advanced
Target language: 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
| [
"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",
"documentation",
"tooling",
"tests_are_truth"
],
"moe_experts": [
"security_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 0f7cc4e754ae0786426633af7da8526733fc325a | |
train_31494 | 2026-01-01T00:00:00 | Secure code generation and policy gates | data_pipeline | expert | Task: data_pipeline
Topic: Secure code generation and policy gates
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.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "JavaScript",
"developer_needs": [
"tooling",
"repo_scale_reasoning",
"documentation",
"tests_are_truth"
],
"moe_experts": [
"evaluation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 711f4c8f6d590ad1b34bf338238de011ee88baa0 | |
train_31495 | 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: 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": [
"documentation",
"security_gates",
"cost_latency_tradeoffs",
"reproducibility"
],
"moe_experts": [
"security_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | f82170060a362f760611ef8ebd380298e57d6483 | |
train_31496 | 2026-01-01T00:00:00 | Tool calling, sandboxes, and CI integration | agent_loop | intermediate | Task: agent_loop
Topic: Tool calling, sandboxes, and CI integration
Difficulty: intermediate
Target language: 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",
"governance",
"evaluation_metrics"
],
"moe_experts": [
"coding_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 713db9e7e8644c87baa059325616b57308de7c43 | |
train_31497 | 2026-01-01T00:00:00 | Agentic coding systems (plan→edit→test→reflect) | failure_analysis | expert | Task: failure_analysis
Topic: Agentic coding systems (plan→edit→test→reflect)
Difficulty: expert
Target language: 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": [
"repo_scale_reasoning",
"ci_integration",
"governance",
"auditability"
],
"moe_experts": [
"evaluation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 3ad42e3376f53f8d708bfb84f97c8708cea3f547 | |
train_31498 | 2026-01-01T00:00:00 | Model merging, distillation, and continued pretraining | eval | advanced | Task: eval
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.
Eval:
pass@k, time-to-green, regressions, diff size
| [] | {
"target_language": "Python",
"developer_needs": [
"security_gates",
"ci_integration",
"auditability",
"evaluation_metrics"
],
"moe_experts": [
"evaluation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 3598eb91445c31ad563aa91e2cd49d4dc81ae648 | |
train_31499 | 2026-01-01T00:00:00 | Dataset curation pipelines (filter, dedupe, quality) | code | intermediate | Task: code
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: intermediate
Target language: C#
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "C#",
"developer_needs": [
"auditability",
"documentation",
"reproducibility",
"repo_scale_reasoning"
],
"moe_experts": [
"performance_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 46acb660a144f8092a17ea0aa0f8d63bc75e40d8 |
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