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_37900 | 2026-01-01T00:00:00 | Dataset curation pipelines (filter, dedupe, quality) | review | intermediate | Task: review
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: intermediate
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.
Review: correctness, security, performance, governance
| [] | {
"target_language": "C#",
"developer_needs": [
"security_gates",
"tooling",
"cost_latency_tradeoffs",
"governance"
],
"moe_experts": [
"agentic_systems_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | a5cd725038e9be7984fdfb22ddf5f14a6e82bff9 | |
train_37901 | 2026-01-01T00:00:00 | Self-improving agents and feedback loops | data_pipeline | expert | Task: data_pipeline
Topic: Self-improving agents and feedback loops
Difficulty: expert
Target language: 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": [
"governance",
"tooling",
"cost_latency_tradeoffs",
"ci_integration"
],
"moe_experts": [
"performance_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | ac87c3d72d6b7fff06f0f1c9b87534f94a662e15 | |
train_37902 | 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: 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": [
"documentation",
"auditability",
"reproducibility",
"tooling"
],
"moe_experts": [
"performance_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 600e211610d54202580137092ae3491676562ea9 | |
train_37903 | 2026-01-01T00:00:00 | SWE-bench style real-repo evaluation | eval | expert | Task: eval
Topic: SWE-bench style real-repo evaluation
Difficulty: expert
Target language: 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
| [] | {
"target_language": "Java",
"developer_needs": [
"evaluation_metrics",
"ci_integration",
"tooling",
"governance"
],
"moe_experts": [
"agentic_systems_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 06f115c6babc19b67ed78edef0d986bc3f8137a3 | |
train_37904 | 2026-01-01T00:00:00 | Dataset curation pipelines (filter, dedupe, quality) | eval | expert | Task: eval
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: expert
Target language: JavaScript
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
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",
"tests_are_truth",
"evaluation_metrics",
"repo_scale_reasoning"
],
"moe_experts": [
"evaluation_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 37fbabbba2fbfa5276b58e25021bc8a3da22b358 | |
train_37905 | 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: 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.
Review: correctness, security, performance, governance
| [] | {
"target_language": "SQL",
"developer_needs": [
"security_gates",
"cost_latency_tradeoffs",
"ci_integration",
"tooling"
],
"moe_experts": [
"agentic_systems_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 8bdd6a277ce236a8659e585f0364815b194e4d71 | |
train_37906 | 2026-01-01T00:00:00 | Multimodal dev workflows (docs, diagrams, traces) | data_pipeline | expert | Task: data_pipeline
Topic: Multimodal dev workflows (docs, diagrams, traces)
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.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
| [] | {
"target_language": "TypeScript",
"developer_needs": [
"tooling",
"governance",
"reproducibility",
"documentation"
],
"moe_experts": [
"security_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 574f2e26aac6453d27f4aa7364056551908b14d0 | |
train_37907 | 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: 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.
Compare: capability, cost, latency, reliability
| [] | {
"target_language": "SQL",
"developer_needs": [
"ci_integration",
"governance",
"evaluation_metrics",
"tests_are_truth"
],
"moe_experts": [
"security_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | a77817cbffcceec5bcd46f0213b00a1bf8813f8a | |
train_37908 | 2026-01-01T00:00:00 | Secure code generation and policy gates | patch_diff | intermediate | Task: patch_diff
Topic: Secure code generation and policy gates
Difficulty: intermediate
Target language: Rust
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
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": [
"tests_are_truth",
"auditability",
"security_gates",
"cost_latency_tradeoffs"
],
"moe_experts": [
"security_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 4e50eb6a619704b7ee6fe5037ea59a0fce37c3d9 | |
train_37909 | 2026-01-01T00:00:00 | Model merging, distillation, and continued pretraining | review | advanced | Task: review
Topic: Model merging, distillation, and continued pretraining
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.
Review: correctness, security, performance, governance
| [] | {
"target_language": "TypeScript",
"developer_needs": [
"governance",
"evaluation_metrics",
"auditability",
"cost_latency_tradeoffs"
],
"moe_experts": [
"evaluation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | dc6761b4f6b7bee820ee3141208955a6fb4d71ab | |
train_37910 | 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: 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": [
"cost_latency_tradeoffs",
"repo_scale_reasoning",
"governance",
"reproducibility"
],
"moe_experts": [
"performance_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 461e2d5858dfde19b736653b36abf8bb7d7d335b | |
train_37911 | 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: TypeScript
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "TypeScript",
"developer_needs": [
"repo_scale_reasoning",
"ci_integration",
"auditability",
"cost_latency_tradeoffs"
],
"moe_experts": [
"governance_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 2510273386d3de29d285b04256042203b4a4075e | |
train_37912 | 2026-01-01T00:00:00 | Code-specialized model families and sizing tradeoffs | failure_analysis | expert | Task: failure_analysis
Topic: Code-specialized model families and sizing tradeoffs
Difficulty: expert
Target language: Rust
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Rust",
"developer_needs": [
"repo_scale_reasoning",
"ci_integration",
"evaluation_metrics",
"auditability"
],
"moe_experts": [
"evaluation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 88656de645a0574c385ed80f8c05c6694b76b75a | |
train_37913 | 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: 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": [
"cost_latency_tradeoffs",
"governance",
"tooling",
"ci_integration"
],
"moe_experts": [
"evaluation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | f5a57f63bf767d6cc1c5be13b73f1e9556fd6791 | |
train_37914 | 2026-01-01T00:00:00 | Agentic coding systems (plan→edit→test→reflect) | explain | expert | Task: explain
Topic: Agentic coding systems (plan→edit→test→reflect)
Difficulty: expert
Target language: SQL
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "SQL",
"developer_needs": [
"repo_scale_reasoning",
"reproducibility",
"tests_are_truth",
"documentation"
],
"moe_experts": [
"coding_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 1ff00073f58c8a5c62b1ded253f0f73bf9c22900 | |
train_37915 | 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: 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.
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": [
"tooling",
"governance",
"documentation",
"ci_integration"
],
"moe_experts": [
"security_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 75065abdef662044082065e36be9e1b3924cfe5b | |
train_37916 | 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: Python
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Python",
"developer_needs": [
"security_gates",
"ci_integration",
"documentation",
"cost_latency_tradeoffs"
],
"moe_experts": [
"agentic_systems_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 21b4a0adc2477dad2dd2d83dd7b5627e9cdee639 | |
train_37917 | 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: 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": [
"governance",
"reproducibility",
"auditability",
"documentation"
],
"moe_experts": [
"governance_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 484f6eaa79e765e4a1f5aa9223744d1f80aaf3e0 | |
train_37918 | 2026-01-01T00:00:00 | Agentic coding systems (plan→edit→test→reflect) | design | advanced | Task: design
Topic: Agentic coding systems (plan→edit→test→reflect)
Difficulty: advanced
Target language: 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.
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": [
"security_gates",
"cost_latency_tradeoffs",
"auditability",
"tooling"
],
"moe_experts": [
"evaluation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 82719cc96e389770ac27ea054a22ee5d9e73774d | |
train_37919 | 2026-01-01T00:00:00 | Secure code generation and policy gates | eval | advanced | Task: eval
Topic: Secure code generation and policy gates
Difficulty: advanced
Target language: Rust
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
| [] | {
"target_language": "Rust",
"developer_needs": [
"tests_are_truth",
"ci_integration",
"auditability",
"evaluation_metrics"
],
"moe_experts": [
"coding_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | a5b47fe764be3d653dedad3ced26910534e7cfd5 | |
train_37920 | 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: Java
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
| [] | {
"target_language": "Java",
"developer_needs": [
"governance",
"tests_are_truth",
"reproducibility",
"documentation"
],
"moe_experts": [
"evaluation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | fcfb392fc468a370d25d640413619433d01122b5 | |
train_37921 | 2026-01-01T00:00:00 | Extended context and repo-scale understanding | data_pipeline | intermediate | Task: data_pipeline
Topic: Extended context and repo-scale understanding
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.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
| [] | {
"target_language": "Rust",
"developer_needs": [
"reproducibility",
"security_gates",
"tooling",
"evaluation_metrics"
],
"moe_experts": [
"data_curation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 110892f60e28624c5cfd40a7832be3b585662a58 | |
train_37922 | 2026-01-01T00:00:00 | Agentic coding systems (plan→edit→test→reflect) | compare | intermediate | Task: compare
Topic: Agentic coding systems (plan→edit→test→reflect)
Difficulty: intermediate
Target language: Bash
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
| [] | {
"target_language": "Bash",
"developer_needs": [
"security_gates",
"cost_latency_tradeoffs",
"documentation",
"reproducibility"
],
"moe_experts": [
"coding_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 1424c4013100c480e981172a40cb52b6f7376f79 | |
train_37923 | 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: 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
| [] | {
"target_language": "TypeScript",
"developer_needs": [
"ci_integration",
"tests_are_truth",
"evaluation_metrics",
"auditability"
],
"moe_experts": [
"performance_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 4c5cc823c6893235f796cc8a06cbe9e477912310 | |
train_37924 | 2026-01-01T00:00:00 | Code-specialized model families and sizing tradeoffs | eval | advanced | Task: eval
Topic: Code-specialized model families and sizing tradeoffs
Difficulty: advanced
Target language: 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
| [] | {
"target_language": "Java",
"developer_needs": [
"tests_are_truth",
"security_gates",
"governance",
"reproducibility"
],
"moe_experts": [
"coding_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 821570273d4610f8c43eb371a5410b7672f360f5 | |
train_37925 | 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: 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.
Compare: capability, cost, latency, reliability
| [] | {
"target_language": "Bash",
"developer_needs": [
"tests_are_truth",
"repo_scale_reasoning",
"tooling",
"reproducibility"
],
"moe_experts": [
"security_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 0cc4edffaed7ea9781d0163b23e483d04f5f817b | |
train_37926 | 2026-01-01T00:00:00 | Governance, provenance, and licensing for code data | patch_diff | advanced | Task: patch_diff
Topic: Governance, provenance, and licensing for code data
Difficulty: advanced
Target language: 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": [
"tests_are_truth",
"evaluation_metrics",
"security_gates",
"documentation"
],
"moe_experts": [
"evaluation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 285a13de4c43eed440be276bb4ee26e0b88ac06f | |
train_37927 | 2026-01-01T00:00:00 | Dataset curation pipelines (filter, dedupe, quality) | failure_analysis | advanced | Task: failure_analysis
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: advanced
Target language: TypeScript
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
| [] | {
"target_language": "TypeScript",
"developer_needs": [
"security_gates",
"tests_are_truth",
"documentation",
"governance"
],
"moe_experts": [
"agentic_systems_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 4a3f1256d331a9c4f3ecdce51ee94708eb14d053 | |
train_37928 | 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: 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",
"evaluation_metrics",
"governance",
"security_gates"
],
"moe_experts": [
"agentic_systems_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 718caadc4b772839ad5d0ff1a888c9c8bd655054 | |
train_37929 | 2026-01-01T00:00:00 | Dataset curation pipelines (filter, dedupe, quality) | data_pipeline | advanced | Task: data_pipeline
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: advanced
Target language: 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.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
| [] | {
"target_language": "TypeScript",
"developer_needs": [
"reproducibility",
"repo_scale_reasoning",
"auditability",
"tooling"
],
"moe_experts": [
"security_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 4d6e4473516dc4d3afc2d247a12bdf4763e188d9 | |
train_37930 | 2026-01-01T00:00:00 | Secure code generation and policy gates | explain | expert | Task: explain
Topic: Secure code generation and policy gates
Difficulty: expert
Target language: Go
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "Go",
"developer_needs": [
"evaluation_metrics",
"auditability",
"security_gates",
"cost_latency_tradeoffs"
],
"moe_experts": [
"security_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 95ca16b5de90a5aab45e5071587d22d5bb37171a | |
train_37931 | 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: 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.
Review: correctness, security, performance, governance
| [] | {
"target_language": "Go",
"developer_needs": [
"tooling",
"tests_are_truth",
"cost_latency_tradeoffs",
"governance"
],
"moe_experts": [
"data_curation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 033b870c398c28e0a80d71c3812984cdbe2e1e57 | |
train_37932 | 2026-01-01T00:00:00 | Code-specialized model families and sizing tradeoffs | data_pipeline | advanced | Task: data_pipeline
Topic: Code-specialized model families and sizing tradeoffs
Difficulty: advanced
Target language: Go
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
| [] | {
"target_language": "Go",
"developer_needs": [
"reproducibility",
"tests_are_truth",
"documentation",
"evaluation_metrics"
],
"moe_experts": [
"governance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | c978bcfb73f196447e70c38dcfc819ac17683a98 | |
train_37933 | 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: 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
| [] | {
"target_language": "JavaScript",
"developer_needs": [
"reproducibility",
"repo_scale_reasoning",
"tooling",
"evaluation_metrics"
],
"moe_experts": [
"agentic_systems_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 48d6b6242fc9391f9f43d4edfb4c68b42cb7aabd | |
train_37934 | 2026-01-01T00:00:00 | Dataset curation pipelines (filter, dedupe, quality) | design | expert | Task: design
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.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "Bash",
"developer_needs": [
"documentation",
"evaluation_metrics",
"tests_are_truth",
"ci_integration"
],
"moe_experts": [
"performance_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 92bf72b7564244e2b65ad3b44664d4f1506f08b4 | |
train_37935 | 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: 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": [
"auditability",
"cost_latency_tradeoffs",
"security_gates",
"reproducibility"
],
"moe_experts": [
"coding_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | fae7d1923a92aad0368fedad0c6154251bdd5a89 | |
train_37936 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | code | expert | Task: code
Topic: Latency, cost, and reliability optimization
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.
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",
"reproducibility",
"evaluation_metrics",
"tests_are_truth"
],
"moe_experts": [
"coding_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | bc30d6c375eb1a84459f338714e110b18bc8aaa3 | |
train_37937 | 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: TypeScript
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
| [] | {
"target_language": "TypeScript",
"developer_needs": [
"reproducibility",
"security_gates",
"tests_are_truth",
"cost_latency_tradeoffs"
],
"moe_experts": [
"evaluation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 1a6d6feaaac77b0d6fdeac78831c6e3749df438f | |
train_37938 | 2026-01-01T00:00:00 | Model merging, distillation, and continued pretraining | agent_loop | expert | Task: agent_loop
Topic: Model merging, distillation, and continued pretraining
Difficulty: expert
Target language: Bash
Context: 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": [
"tests_are_truth",
"evaluation_metrics",
"tooling",
"cost_latency_tradeoffs"
],
"moe_experts": [
"performance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | b161cf7d9915cb773b5f0e40b5f2e38a0607c12d | |
train_37939 | 2026-01-01T00:00:00 | Agentic coding systems (plan→edit→test→reflect) | data_pipeline | intermediate | Task: data_pipeline
Topic: Agentic coding systems (plan→edit→test→reflect)
Difficulty: intermediate
Target language: 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": [
"cost_latency_tradeoffs",
"governance",
"reproducibility",
"tooling"
],
"moe_experts": [
"agentic_systems_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 608a86ec1a1af253b742e828e1a36b4b200eedef | |
train_37940 | 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: TypeScript
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Patch (diff-style):
```diff
- if x == 0:
- return 1/x
+ if x == 0:
+ raise ValueError('division by zero')
```
Acceptance:
- Tests pass
- No new regressions
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "TypeScript",
"developer_needs": [
"ci_integration",
"security_gates",
"documentation",
"cost_latency_tradeoffs"
],
"moe_experts": [
"evaluation_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 50db3145f7bed8175a3004d859cae6a9e74a9902 | |
train_37941 | 2026-01-01T00:00:00 | Extended context and repo-scale understanding | design | advanced | Task: design
Topic: Extended context and repo-scale understanding
Difficulty: advanced
Target language: C#
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "C#",
"developer_needs": [
"tooling",
"auditability",
"ci_integration",
"security_gates"
],
"moe_experts": [
"coding_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 8b6916462c84f7aa582c8669eb4782350f8b0443 | |
train_37942 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | data_pipeline | advanced | Task: data_pipeline
Topic: Latency, cost, and reliability optimization
Difficulty: advanced
Target language: SQL
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "SQL",
"developer_needs": [
"ci_integration",
"evaluation_metrics",
"reproducibility",
"auditability"
],
"moe_experts": [
"governance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | bfd1e1eec0398781100fe5d24208078cc519264d | |
train_37943 | 2026-01-01T00:00:00 | Code-specialized model families and sizing tradeoffs | code | intermediate | Task: code
Topic: Code-specialized model families and sizing tradeoffs
Difficulty: intermediate
Target language: 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
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Go",
"developer_needs": [
"evaluation_metrics",
"ci_integration",
"documentation",
"tooling"
],
"moe_experts": [
"security_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 573dceb0a72f501090321fc5a328d0f114ede93c | |
train_37944 | 2026-01-01T00:00:00 | Governance, provenance, and licensing for code data | compare | expert | Task: compare
Topic: Governance, provenance, and licensing for code data
Difficulty: expert
Target language: 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
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Java",
"developer_needs": [
"governance",
"tests_are_truth",
"ci_integration",
"tooling"
],
"moe_experts": [
"coding_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 09ee32c8858101348849d4514982b8e919dc2ec1 | |
train_37945 | 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: Rust
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Patch (diff-style):
```diff
- if x == 0:
- return 1/x
+ if x == 0:
+ raise ValueError('division by zero')
```
Acceptance:
- Tests pass
- No new regressions
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Rust",
"developer_needs": [
"auditability",
"repo_scale_reasoning",
"security_gates",
"documentation"
],
"moe_experts": [
"data_curation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | c18659a2035ab244e984ba68735996bbaae776be | |
train_37946 | 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: 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": [
"security_gates",
"auditability",
"evaluation_metrics",
"documentation"
],
"moe_experts": [
"security_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 469a14d3a59d0f5d5202893c7a299b87aad54df7 | |
train_37947 | 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
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Go",
"developer_needs": [
"ci_integration",
"repo_scale_reasoning",
"evaluation_metrics",
"reproducibility"
],
"moe_experts": [
"security_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 52817542c23032420f74675680881574bf5eed9d | |
train_37948 | 2026-01-01T00:00:00 | Secure code generation and policy gates | failure_analysis | advanced | Task: failure_analysis
Topic: Secure code generation and policy gates
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.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
| [] | {
"target_language": "Python",
"developer_needs": [
"governance",
"tests_are_truth",
"cost_latency_tradeoffs",
"ci_integration"
],
"moe_experts": [
"evaluation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 31bb34a20aae8a557c9cb451f4d20abe55c3ec6d | |
train_37949 | 2026-01-01T00:00:00 | Agentic coding systems (plan→edit→test→reflect) | eval | intermediate | Task: eval
Topic: Agentic coding systems (plan→edit→test→reflect)
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.
Eval:
pass@k, time-to-green, regressions, diff size
| [] | {
"target_language": "Java",
"developer_needs": [
"evaluation_metrics",
"tooling",
"cost_latency_tradeoffs",
"reproducibility"
],
"moe_experts": [
"performance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 093e41f8669848ed3529281fcd396943cc2bc70a | |
train_37950 | 2026-01-01T00:00:00 | SWE-bench style real-repo evaluation | compare | advanced | Task: compare
Topic: SWE-bench style real-repo evaluation
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": [
"ci_integration",
"documentation",
"auditability",
"security_gates"
],
"moe_experts": [
"coding_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | e29c0680fd3b264bb98c43598d37fdb76fd1c221 | |
train_37951 | 2026-01-01T00:00:00 | Tool calling, sandboxes, and CI integration | failure_analysis | intermediate | Task: failure_analysis
Topic: Tool calling, sandboxes, and CI integration
Difficulty: intermediate
Target language: TypeScript
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "TypeScript",
"developer_needs": [
"tests_are_truth",
"documentation",
"reproducibility",
"auditability"
],
"moe_experts": [
"security_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 79fa242a3f536f4f3186b4994f438d765eefbc5b | |
train_37952 | 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: C#
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
| [] | {
"target_language": "C#",
"developer_needs": [
"documentation",
"tooling",
"cost_latency_tradeoffs",
"ci_integration"
],
"moe_experts": [
"agentic_systems_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 5b81edeeece53dbaa70c82537574207c17bd6b6f | |
train_37953 | 2026-01-01T00:00:00 | Model merging, distillation, and continued pretraining | data_pipeline | advanced | Task: data_pipeline
Topic: Model merging, distillation, and continued pretraining
Difficulty: advanced
Target language: SQL
Context: 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": "SQL",
"developer_needs": [
"documentation",
"repo_scale_reasoning",
"evaluation_metrics",
"reproducibility"
],
"moe_experts": [
"performance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 4d9c6370c52a9dc1ecdccf393da7dfd7abe9d5f6 | |
train_37954 | 2026-01-01T00:00:00 | Model merging, distillation, and continued pretraining | design | advanced | Task: design
Topic: Model merging, distillation, and continued pretraining
Difficulty: advanced
Target language: JavaScript
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "JavaScript",
"developer_needs": [
"tests_are_truth",
"ci_integration",
"repo_scale_reasoning",
"reproducibility"
],
"moe_experts": [
"data_curation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 413a9e43e3f3f5e1e61a40d53178c3160e36cc2e | |
train_37955 | 2026-01-01T00:00:00 | Dataset curation pipelines (filter, dedupe, quality) | data_pipeline | advanced | Task: data_pipeline
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: advanced
Target language: JavaScript
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "JavaScript",
"developer_needs": [
"repo_scale_reasoning",
"ci_integration",
"governance",
"auditability"
],
"moe_experts": [
"evaluation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 3efcfcf28f2aae0287d63e5ea1227ee1ea0049fb | |
train_37956 | 2026-01-01T00:00:00 | Multimodal dev workflows (docs, diagrams, traces) | agent_loop | advanced | Task: agent_loop
Topic: Multimodal dev workflows (docs, diagrams, traces)
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.
Loop: Plan → Edit → Test → Reflect → Human gate
| [] | {
"target_language": "C#",
"developer_needs": [
"ci_integration",
"reproducibility",
"cost_latency_tradeoffs",
"auditability"
],
"moe_experts": [
"coding_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 56f5330b09d33f479605f27ea0c3a9b0112686b3 | |
train_37957 | 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: Java
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
| [] | {
"target_language": "Java",
"developer_needs": [
"security_gates",
"evaluation_metrics",
"repo_scale_reasoning",
"ci_integration"
],
"moe_experts": [
"coding_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 3f511949ed9d49cd0c666f1bab4a2d683a8df7ed | |
train_37958 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | patch_diff | expert | Task: patch_diff
Topic: Latency, cost, and reliability optimization
Difficulty: expert
Target language: TypeScript
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Patch (diff-style):
```diff
- if x == 0:
- return 1/x
+ if x == 0:
+ raise ValueError('division by zero')
```
Acceptance:
- Tests pass
- No new regressions
| [] | {
"target_language": "TypeScript",
"developer_needs": [
"tooling",
"governance",
"cost_latency_tradeoffs",
"documentation"
],
"moe_experts": [
"data_curation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | d09aff1741f7d5fee467f035ce0a808a1271388f | |
train_37959 | 2026-01-01T00:00:00 | Code-specialized model families and sizing tradeoffs | data_pipeline | advanced | Task: data_pipeline
Topic: Code-specialized model families and sizing tradeoffs
Difficulty: advanced
Target language: Python
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
| [] | {
"target_language": "Python",
"developer_needs": [
"tests_are_truth",
"tooling",
"auditability",
"repo_scale_reasoning"
],
"moe_experts": [
"performance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 5942f3f8d6badf8ccf9b897f3cb7e93506259519 | |
train_37960 | 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: Python
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
| [] | {
"target_language": "Python",
"developer_needs": [
"documentation",
"tests_are_truth",
"evaluation_metrics",
"cost_latency_tradeoffs"
],
"moe_experts": [
"evaluation_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 37a6b8c9c705b871aaa5e084f14b7df1f42ae48e | |
train_37961 | 2026-01-01T00:00:00 | Self-improving agents and feedback loops | code | advanced | Task: code
Topic: Self-improving agents and feedback loops
Difficulty: advanced
Target language: TypeScript
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "TypeScript",
"developer_needs": [
"evaluation_metrics",
"cost_latency_tradeoffs",
"auditability",
"tooling"
],
"moe_experts": [
"performance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | da40e6d646845b3b9bd36e1b3dc23e567dbbfbe9 | |
train_37962 | 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: 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": [
"tests_are_truth",
"evaluation_metrics",
"ci_integration",
"auditability"
],
"moe_experts": [
"performance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | efa548106269a0252b424851bfd1baf21c57080f | |
train_37963 | 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: 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": [
"tooling",
"evaluation_metrics",
"ci_integration",
"reproducibility"
],
"moe_experts": [
"data_curation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 109dad8ff05f4ce47fa6f34a34d100a8eab09ef8 | |
train_37964 | 2026-01-01T00:00:00 | Agentic coding systems (plan→edit→test→reflect) | compare | intermediate | Task: compare
Topic: Agentic coding systems (plan→edit→test→reflect)
Difficulty: intermediate
Target language: Go
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
| [] | {
"target_language": "Go",
"developer_needs": [
"governance",
"auditability",
"reproducibility",
"cost_latency_tradeoffs"
],
"moe_experts": [
"coding_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 2ea57d408ec313fb13e63e730db7e943bbbf1656 | |
train_37965 | 2026-01-01T00:00:00 | Multimodal dev workflows (docs, diagrams, traces) | code | intermediate | Task: code
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
| [] | {
"target_language": "C#",
"developer_needs": [
"auditability",
"reproducibility",
"security_gates",
"tooling"
],
"moe_experts": [
"governance_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | ae05f8f92feebb497c9e07dd36d6085502be6d64 | |
train_37966 | 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: 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",
"ci_integration",
"reproducibility",
"repo_scale_reasoning"
],
"moe_experts": [
"agentic_systems_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | f11136efff252704374d1467638a3530f52fffb1 | |
train_37967 | 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: Rust
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Rust",
"developer_needs": [
"evaluation_metrics",
"repo_scale_reasoning",
"security_gates",
"auditability"
],
"moe_experts": [
"performance_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 8e3943698dbdea7ba0e90509fddd142bd917885c | |
train_37968 | 2026-01-01T00:00:00 | Self-improving agents and feedback loops | code | advanced | Task: code
Topic: Self-improving agents and feedback loops
Difficulty: advanced
Target language: SQL
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "SQL",
"developer_needs": [
"documentation",
"reproducibility",
"tests_are_truth",
"ci_integration"
],
"moe_experts": [
"agentic_systems_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 665099c93d14093c7e31f869b11f8ed6583430d3 | |
train_37969 | 2026-01-01T00:00:00 | Agentic coding systems (plan→edit→test→reflect) | data_pipeline | intermediate | Task: data_pipeline
Topic: Agentic coding systems (plan→edit→test→reflect)
Difficulty: intermediate
Target language: Go
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Go",
"developer_needs": [
"auditability",
"tests_are_truth",
"tooling",
"repo_scale_reasoning"
],
"moe_experts": [
"coding_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 4e57d2f2b459c32d7f2994a3c12021c7421490a2 | |
train_37970 | 2026-01-01T00:00:00 | Reasoning-first coding models and tunable deliberation | compare | advanced | Task: compare
Topic: Reasoning-first coding models and tunable deliberation
Difficulty: advanced
Target language: 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.
Compare: capability, cost, latency, reliability
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "SQL",
"developer_needs": [
"documentation",
"tests_are_truth",
"evaluation_metrics",
"tooling"
],
"moe_experts": [
"evaluation_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 7c368f1cbf38cb216504c136de12407c647f233b | |
train_37971 | 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: 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": [
"cost_latency_tradeoffs",
"auditability",
"reproducibility",
"security_gates"
],
"moe_experts": [
"security_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 0b17bda48928c47d31260d752497aa59ec26008d | |
train_37972 | 2026-01-01T00:00:00 | SWE-bench style real-repo evaluation | patch_diff | advanced | Task: patch_diff
Topic: SWE-bench style real-repo evaluation
Difficulty: advanced
Target language: Rust
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
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": [
"ci_integration",
"security_gates",
"tests_are_truth",
"evaluation_metrics"
],
"moe_experts": [
"evaluation_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 5e0ac3c847ef0bd833b359c7354f5b00df5797ec | |
train_37973 | 2026-01-01T00:00:00 | Tool calling, sandboxes, and CI integration | compare | intermediate | Task: compare
Topic: Tool calling, sandboxes, and CI integration
Difficulty: intermediate
Target language: Java
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
| [] | {
"target_language": "Java",
"developer_needs": [
"evaluation_metrics",
"security_gates",
"cost_latency_tradeoffs",
"governance"
],
"moe_experts": [
"coding_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | b4fc366b93440570e2b2df1d601a2d7d330413a9 | |
train_37974 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | compare | advanced | Task: compare
Topic: Latency, cost, and reliability optimization
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.
Compare: capability, cost, latency, reliability
| [] | {
"target_language": "C#",
"developer_needs": [
"cost_latency_tradeoffs",
"tests_are_truth",
"ci_integration",
"documentation"
],
"moe_experts": [
"coding_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | a5c39deaecc079508783c49808fd91fd28624975 | |
train_37975 | 2026-01-01T00:00:00 | Agentic coding systems (plan→edit→test→reflect) | data_pipeline | intermediate | Task: data_pipeline
Topic: Agentic coding systems (plan→edit→test→reflect)
Difficulty: intermediate
Target language: 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.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "SQL",
"developer_needs": [
"evaluation_metrics",
"cost_latency_tradeoffs",
"governance",
"reproducibility"
],
"moe_experts": [
"coding_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 2a6bd18cc96b52cf1f81db4d7ee4576dc6298834 | |
train_37976 | 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: Java
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
| [] | {
"target_language": "Java",
"developer_needs": [
"evaluation_metrics",
"tests_are_truth",
"repo_scale_reasoning",
"governance"
],
"moe_experts": [
"agentic_systems_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 0c36dd21ecbaf1b215330ad1fcbd49295a9af7d6 | |
train_37977 | 2026-01-01T00:00:00 | Dataset curation pipelines (filter, dedupe, quality) | review | intermediate | Task: review
Topic: Dataset curation pipelines (filter, dedupe, quality)
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.
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": [
"tooling",
"security_gates",
"tests_are_truth",
"documentation"
],
"moe_experts": [
"evaluation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | d0218fffaf9087eec371a399a2fd89dc95da6640 | |
train_37978 | 2026-01-01T00:00:00 | Tool calling, sandboxes, and CI integration | compare | intermediate | Task: compare
Topic: Tool calling, sandboxes, and CI integration
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.
Compare: capability, cost, latency, reliability
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Python",
"developer_needs": [
"ci_integration",
"documentation",
"evaluation_metrics",
"repo_scale_reasoning"
],
"moe_experts": [
"evaluation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 871e8837fdb738648e4f21a82692e4198333803d | |
train_37979 | 2026-01-01T00:00:00 | SWE-bench style real-repo evaluation | compare | expert | Task: compare
Topic: SWE-bench style real-repo evaluation
Difficulty: expert
Target language: 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.
Compare: capability, cost, latency, reliability
| [] | {
"target_language": "Go",
"developer_needs": [
"repo_scale_reasoning",
"tooling",
"auditability",
"evaluation_metrics"
],
"moe_experts": [
"performance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | f5fd5183267f149c5c8adb252d0c20ddf1aeb285 | |
train_37980 | 2026-01-01T00:00:00 | Secure code generation and policy gates | patch_diff | expert | Task: patch_diff
Topic: Secure code generation and policy gates
Difficulty: expert
Target language: 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.
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": [
"reproducibility",
"tooling",
"governance",
"repo_scale_reasoning"
],
"moe_experts": [
"agentic_systems_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | b0215e77a5cd5015376203717084857944507021 | |
train_37981 | 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: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
| [] | {
"target_language": "Python",
"developer_needs": [
"tests_are_truth",
"repo_scale_reasoning",
"documentation",
"security_gates"
],
"moe_experts": [
"evaluation_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 17d9a8df3a4638283a55a9c20c39095a1a557277 | |
train_37982 | 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: 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": [
"evaluation_metrics",
"tooling",
"reproducibility",
"security_gates"
],
"moe_experts": [
"coding_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | ddbbac2beb16cc82df371e1322668b374c4a804a | |
train_37983 | 2026-01-01T00:00:00 | Self-improving agents and feedback loops | agent_loop | intermediate | Task: agent_loop
Topic: Self-improving agents and feedback loops
Difficulty: intermediate
Target language: 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.
Loop: Plan → Edit → Test → Reflect → Human gate
| [] | {
"target_language": "Bash",
"developer_needs": [
"auditability",
"repo_scale_reasoning",
"security_gates",
"tooling"
],
"moe_experts": [
"performance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | e4b98d32a3a8e8ce589d56167cb247a9e846afe6 | |
train_37984 | 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: Bash
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Bash",
"developer_needs": [
"governance",
"security_gates",
"ci_integration",
"reproducibility"
],
"moe_experts": [
"security_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 2564c8fd01ea189ce128c912036ced60cc1e492e | |
train_37985 | 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: 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.
Review: correctness, security, performance, governance
| [] | {
"target_language": "JavaScript",
"developer_needs": [
"auditability",
"documentation",
"tooling",
"evaluation_metrics"
],
"moe_experts": [
"data_curation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 1fa6b2d9c779736fb9b9ee37b18b2fb0df55c436 | |
train_37986 | 2026-01-01T00:00:00 | Mixture-of-Experts (MoE) for code | data_pipeline | advanced | Task: data_pipeline
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.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
| [] | {
"target_language": "Go",
"developer_needs": [
"tooling",
"cost_latency_tradeoffs",
"security_gates",
"reproducibility"
],
"moe_experts": [
"performance_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 838b96baf1b99f5daa3b67f4e6ac9f8246a9454a | |
train_37987 | 2026-01-01T00:00:00 | Multimodal dev workflows (docs, diagrams, traces) | failure_analysis | advanced | Task: failure_analysis
Topic: Multimodal dev workflows (docs, diagrams, traces)
Difficulty: advanced
Target language: Go
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Go",
"developer_needs": [
"reproducibility",
"ci_integration",
"cost_latency_tradeoffs",
"repo_scale_reasoning"
],
"moe_experts": [
"agentic_systems_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 18f4efff1d9f7b38f8e34cb5b442accb3e4d43f8 | |
train_37988 | 2026-01-01T00:00:00 | Tool calling, sandboxes, and CI integration | explain | advanced | Task: explain
Topic: Tool calling, sandboxes, and CI integration
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.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "Rust",
"developer_needs": [
"tooling",
"cost_latency_tradeoffs",
"security_gates",
"governance"
],
"moe_experts": [
"performance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 2edf0d259227290dac65b1c1145a62173bc36fea | |
train_37989 | 2026-01-01T00:00:00 | SWE-bench style real-repo evaluation | eval | intermediate | Task: eval
Topic: SWE-bench style real-repo evaluation
Difficulty: intermediate
Target language: Python
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
| [] | {
"target_language": "Python",
"developer_needs": [
"reproducibility",
"governance",
"auditability",
"tooling"
],
"moe_experts": [
"agentic_systems_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | cfa1176d12372a9da1a496f934d2c0d327545410 | |
train_37990 | 2026-01-01T00:00:00 | Code-specialized model families and sizing tradeoffs | patch_diff | intermediate | Task: patch_diff
Topic: Code-specialized model families and sizing tradeoffs
Difficulty: intermediate
Target language: Rust
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Patch (diff-style):
```diff
- if x == 0:
- return 1/x
+ if x == 0:
+ raise ValueError('division by zero')
```
Acceptance:
- Tests pass
- No new regressions
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Rust",
"developer_needs": [
"governance",
"repo_scale_reasoning",
"ci_integration",
"cost_latency_tradeoffs"
],
"moe_experts": [
"security_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 8eab44793ef8cb2e6ce1936353a3b2b8131ea993 | |
train_37991 | 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: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "C#",
"developer_needs": [
"tests_are_truth",
"security_gates",
"documentation",
"repo_scale_reasoning"
],
"moe_experts": [
"data_curation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 58c35bc22bbec02faaa6edfed7282be7a161baac | |
train_37992 | 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: Rust
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Rust",
"developer_needs": [
"ci_integration",
"auditability",
"cost_latency_tradeoffs",
"repo_scale_reasoning"
],
"moe_experts": [
"evaluation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | ac73df952c088e4ee7b542f6b70bc619dcca3076 | |
train_37993 | 2026-01-01T00:00:00 | Agentic coding systems (plan→edit→test→reflect) | agent_loop | advanced | Task: agent_loop
Topic: Agentic coding systems (plan→edit→test→reflect)
Difficulty: advanced
Target language: C#
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
| [] | {
"target_language": "C#",
"developer_needs": [
"evaluation_metrics",
"ci_integration",
"reproducibility",
"documentation"
],
"moe_experts": [
"security_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 545a35cc2ff0ca9ead19caf8e1f94ee293360826 | |
train_37994 | 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: 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
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Python",
"developer_needs": [
"security_gates",
"governance",
"documentation",
"tests_are_truth"
],
"moe_experts": [
"coding_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 6f0de66bfd4dca2d83d6552089b202932dfb65bf | |
train_37995 | 2026-01-01T00:00:00 | Extended context and repo-scale understanding | data_pipeline | intermediate | Task: data_pipeline
Topic: Extended context and repo-scale understanding
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
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "JavaScript",
"developer_needs": [
"security_gates",
"tests_are_truth",
"evaluation_metrics",
"governance"
],
"moe_experts": [
"governance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 4617ac7f1948260168dbb7fcf38a5e971e163220 | |
train_37996 | 2026-01-01T00:00:00 | Mixture-of-Experts (MoE) for code | compare | advanced | Task: compare
Topic: Mixture-of-Experts (MoE) for code
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.
Compare: capability, cost, latency, reliability
| [] | {
"target_language": "JavaScript",
"developer_needs": [
"reproducibility",
"ci_integration",
"auditability",
"documentation"
],
"moe_experts": [
"data_curation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | b95a29768738c549a16f0d6e83db1b77a3a013e9 | |
train_37997 | 2026-01-01T00:00:00 | Mixture-of-Experts (MoE) for code | review | intermediate | Task: review
Topic: Mixture-of-Experts (MoE) for code
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.
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": [
"ci_integration",
"security_gates",
"tests_are_truth",
"governance"
],
"moe_experts": [
"performance_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | b8764705f751db6c529c210f10fca2da487e4c93 | |
train_37998 | 2026-01-01T00:00:00 | Tool calling, sandboxes, and CI integration | patch_diff | expert | Task: patch_diff
Topic: Tool calling, sandboxes, and CI integration
Difficulty: expert
Target language: Java
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Patch (diff-style):
```diff
- if x == 0:
- return 1/x
+ if x == 0:
+ raise ValueError('division by zero')
```
Acceptance:
- Tests pass
- No new regressions
| [] | {
"target_language": "Java",
"developer_needs": [
"evaluation_metrics",
"auditability",
"security_gates",
"tooling"
],
"moe_experts": [
"security_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 5e914d4b521bdf24906e54e1834a2e5c80357afd | |
train_37999 | 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: 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": [
"governance",
"ci_integration",
"documentation",
"tests_are_truth"
],
"moe_experts": [
"governance_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | f1b56561d0f7ecb371f9d1ebc77babb0b31f0b35 |
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