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timestamp[s]date 2026-01-01 00:00:00
2026-01-01 00:00:00
| topic
stringclasses 14
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stringclasses 10
values | difficulty
stringclasses 3
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|---|---|---|---|---|---|---|---|---|---|---|
train_42800
| 2026-01-01T00:00:00
|
Mixture-of-Experts (MoE) for code
|
agent_loop
|
advanced
|
Task: agent_loop
Topic: Mixture-of-Experts (MoE) for code
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.
Loop: Plan → Edit → Test → Reflect → Human gate
|
[] |
{
"target_language": "Java",
"developer_needs": [
"cost_latency_tradeoffs",
"tooling",
"ci_integration",
"documentation"
],
"moe_experts": [
"agentic_systems_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
f9e23de698b1d2a4a3fc33ee3ffb84b634a7c83b
|
|
train_42801
| 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: 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": "TypeScript",
"developer_needs": [
"governance",
"auditability",
"evaluation_metrics",
"tests_are_truth"
],
"moe_experts": [
"evaluation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
4b44c09964d2e7c43c067f4754170e145f459dd5
|
|
train_42802
| 2026-01-01T00:00:00
|
Secure code generation and policy gates
|
design
|
expert
|
Task: design
Topic: Secure code generation and policy gates
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.
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": [
"auditability",
"tests_are_truth",
"ci_integration",
"documentation"
],
"moe_experts": [
"evaluation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
c9894db08ff55327f4957157eb45d85e80823bdd
|
|
train_42803
| 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: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
|
[] |
{
"target_language": "C#",
"developer_needs": [
"ci_integration",
"evaluation_metrics",
"auditability",
"tests_are_truth"
],
"moe_experts": [
"coding_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
bc2caf6ee9a23d0b37dab141d8d473614432756a
|
|
train_42804
| 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: Java
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[] |
{
"target_language": "Java",
"developer_needs": [
"ci_integration",
"repo_scale_reasoning",
"auditability",
"tests_are_truth"
],
"moe_experts": [
"governance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
3878f7d409632fde556389cc9dceab523d0ee833
|
|
train_42805
| 2026-01-01T00:00:00
|
Agentic coding systems (plan→edit→test→reflect)
|
compare
|
expert
|
Task: compare
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.
Compare: capability, cost, latency, reliability
|
[] |
{
"target_language": "C#",
"developer_needs": [
"tooling",
"governance",
"auditability",
"evaluation_metrics"
],
"moe_experts": [
"coding_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
b9729e283a8930aa99b0ac5133ca6b78d6b0d7dd
|
|
train_42806
| 2026-01-01T00:00:00
|
Model merging, distillation, and continued pretraining
|
explain
|
expert
|
Task: explain
Topic: Model merging, distillation, and continued pretraining
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": [
"security_gates",
"ci_integration",
"repo_scale_reasoning",
"governance"
],
"moe_experts": [
"agentic_systems_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
34626fa2bb670662f92380e852e909a0a264df78
|
|
train_42807
| 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: 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.
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": "SQL",
"developer_needs": [
"ci_integration",
"security_gates",
"reproducibility",
"evaluation_metrics"
],
"moe_experts": [
"performance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
726e1ccfb0a59e0722bebe2c03052150043fb12f
|
|
train_42808
| 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: 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": "Rust",
"developer_needs": [
"tests_are_truth",
"security_gates",
"evaluation_metrics",
"tooling"
],
"moe_experts": [
"data_curation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
4e8e0fa741bc59173a47f82c1af5dae7b8f1bf2c
|
|
train_42809
| 2026-01-01T00:00:00
|
Governance, provenance, and licensing for code data
|
agent_loop
|
expert
|
Task: agent_loop
Topic: Governance, provenance, and licensing for code data
Difficulty: expert
Target language: Go
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
|
[] |
{
"target_language": "Go",
"developer_needs": [
"repo_scale_reasoning",
"tests_are_truth",
"tooling",
"documentation"
],
"moe_experts": [
"security_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
b2e291e33a4babe4e8c9084c919f54d03b214228
|
|
train_42810
| 2026-01-01T00:00:00
|
Self-improving agents and feedback loops
|
patch_diff
|
expert
|
Task: patch_diff
Topic: Self-improving agents and feedback loops
Difficulty: expert
Target language: 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.
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": [
"cost_latency_tradeoffs",
"security_gates",
"repo_scale_reasoning",
"ci_integration"
],
"moe_experts": [
"evaluation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
0ec6275b1f5b3ddd4e119ddc2570469d4db1481a
|
|
train_42811
| 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: 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": [
"evaluation_metrics",
"tests_are_truth",
"cost_latency_tradeoffs",
"tooling"
],
"moe_experts": [
"data_curation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
7f690eb62963fa5cd508bffe325d7d5392bbcf7f
|
|
train_42812
| 2026-01-01T00:00:00
|
Dataset curation pipelines (filter, dedupe, quality)
|
code
|
advanced
|
Task: code
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: advanced
Target language: Go
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[] |
{
"target_language": "Go",
"developer_needs": [
"evaluation_metrics",
"auditability",
"governance",
"repo_scale_reasoning"
],
"moe_experts": [
"performance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
724939db5db965610acc40faa44ca68a894eadb2
|
|
train_42813
| 2026-01-01T00:00:00
|
SWE-bench style real-repo evaluation
|
code
|
advanced
|
Task: code
Topic: SWE-bench style real-repo evaluation
Difficulty: advanced
Target language: TypeScript
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[] |
{
"target_language": "TypeScript",
"developer_needs": [
"repo_scale_reasoning",
"reproducibility",
"documentation",
"tooling"
],
"moe_experts": [
"performance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
8da14a0007ee6aabeccf594ab69e800b338a2978
|
|
train_42814
| 2026-01-01T00:00:00
|
Self-improving agents and feedback loops
|
design
|
intermediate
|
Task: design
Topic: Self-improving agents and feedback loops
Difficulty: intermediate
Target language: Java
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[] |
{
"target_language": "Java",
"developer_needs": [
"ci_integration",
"security_gates",
"reproducibility",
"repo_scale_reasoning"
],
"moe_experts": [
"agentic_systems_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
c7a1287ba1165f848578642e1ecb7264b54e8874
|
|
train_42815
| 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: Java
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Java",
"developer_needs": [
"evaluation_metrics",
"tests_are_truth",
"ci_integration",
"security_gates"
],
"moe_experts": [
"performance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
7fc6480bffe5ed2bb8afb6043fdd82de1609151e
|
|
train_42816
| 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: 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": [
"security_gates",
"documentation",
"governance",
"tooling"
],
"moe_experts": [
"performance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
738e59870d9cec94390676c2fc93e1a423b97622
|
|
train_42817
| 2026-01-01T00:00:00
|
Dataset curation pipelines (filter, dedupe, quality)
|
patch_diff
|
advanced
|
Task: patch_diff
Topic: Dataset curation pipelines (filter, dedupe, quality)
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.
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": "Go",
"developer_needs": [
"auditability",
"repo_scale_reasoning",
"cost_latency_tradeoffs",
"tooling"
],
"moe_experts": [
"data_curation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
70b6510b7d1048a0a750c5e1c216f9a36d768a49
|
|
train_42818
| 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: 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.
Review: correctness, security, performance, governance
|
[] |
{
"target_language": "SQL",
"developer_needs": [
"reproducibility",
"security_gates",
"auditability",
"evaluation_metrics"
],
"moe_experts": [
"coding_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
c04485d9a2ec5b160cf3c586eff7d4e856d78a61
|
|
train_42819
| 2026-01-01T00:00:00
|
Mixture-of-Experts (MoE) for code
|
compare
|
expert
|
Task: compare
Topic: Mixture-of-Experts (MoE) for code
Difficulty: expert
Target language: 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.
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": [
"ci_integration",
"tooling",
"security_gates",
"repo_scale_reasoning"
],
"moe_experts": [
"agentic_systems_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
5ae10e58249135bde12c7784a1073cfe65090d9d
|
|
train_42820
| 2026-01-01T00:00:00
|
Governance, provenance, and licensing for code data
|
patch_diff
|
expert
|
Task: patch_diff
Topic: Governance, provenance, and licensing for code data
Difficulty: expert
Target language: 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.
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": [
"governance",
"repo_scale_reasoning",
"documentation",
"tooling"
],
"moe_experts": [
"agentic_systems_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
1ffa2ffc2094e64265a69133a307479acf46dcee
|
|
train_42821
| 2026-01-01T00:00:00
|
Self-improving agents and feedback loops
|
review
|
intermediate
|
Task: review
Topic: Self-improving agents and feedback loops
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.
Review: correctness, security, performance, governance
|
[] |
{
"target_language": "Rust",
"developer_needs": [
"cost_latency_tradeoffs",
"security_gates",
"tests_are_truth",
"reproducibility"
],
"moe_experts": [
"governance_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
dec44cc5b7f03d6c332ef86bda30481b83ed56e0
|
|
train_42822
| 2026-01-01T00:00:00
|
Self-improving agents and feedback loops
|
compare
|
advanced
|
Task: compare
Topic: Self-improving agents and feedback loops
Difficulty: advanced
Target language: 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.
Compare: capability, cost, latency, reliability
|
[] |
{
"target_language": "C#",
"developer_needs": [
"evaluation_metrics",
"repo_scale_reasoning",
"auditability",
"tests_are_truth"
],
"moe_experts": [
"agentic_systems_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
58e0b81ec58196536575947ef1fad5ff8efc47c0
|
|
train_42823
| 2026-01-01T00:00:00
|
Tool calling, sandboxes, and CI integration
|
explain
|
intermediate
|
Task: explain
Topic: Tool calling, sandboxes, and CI integration
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.
Design with risks, metrics, acceptance criteria
|
[] |
{
"target_language": "Bash",
"developer_needs": [
"security_gates",
"auditability",
"repo_scale_reasoning",
"governance"
],
"moe_experts": [
"agentic_systems_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
397d5aa576e418b231f03b25da002206203398df
|
|
train_42824
| 2026-01-01T00:00:00
|
Latency, cost, and reliability optimization
|
explain
|
expert
|
Task: explain
Topic: Latency, cost, and reliability optimization
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": [
"governance",
"reproducibility",
"repo_scale_reasoning",
"auditability"
],
"moe_experts": [
"data_curation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
f4bb26ca493bd48a313b02edc47c393fac6d0018
|
|
train_42825
| 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: 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": [
"tooling",
"ci_integration",
"documentation",
"security_gates"
],
"moe_experts": [
"evaluation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
56e6b5ee9851c35d53292c03fc8065e6f906a57d
|
|
train_42826
| 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: 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": [
"cost_latency_tradeoffs",
"tooling",
"ci_integration",
"reproducibility"
],
"moe_experts": [
"data_curation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
32a7a6588521854009aab85f007a17c3531d8368
|
|
train_42827
| 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: 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.
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",
"governance",
"reproducibility"
],
"moe_experts": [
"security_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
7763094b3273de143e3d2abb0b9f891cd89ddfa9
|
|
train_42828
| 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: 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",
"repo_scale_reasoning",
"auditability",
"security_gates"
],
"moe_experts": [
"governance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
d530dff81a1195ab85a876b5d29939372cc686d1
|
|
train_42829
| 2026-01-01T00:00:00
|
Self-improving agents and feedback loops
|
compare
|
expert
|
Task: compare
Topic: Self-improving agents and feedback loops
Difficulty: expert
Target language: 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": [
"security_gates",
"cost_latency_tradeoffs",
"governance",
"reproducibility"
],
"moe_experts": [
"security_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
992fb59989bfb5401162e45b5ff327c521a590ea
|
|
train_42830
| 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: 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": "Python",
"developer_needs": [
"ci_integration",
"security_gates",
"evaluation_metrics",
"tests_are_truth"
],
"moe_experts": [
"performance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
ec093006cc408c3a9e378778de2c8fe8cb213fb5
|
|
train_42831
| 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: 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": [
"tests_are_truth",
"security_gates",
"evaluation_metrics",
"reproducibility"
],
"moe_experts": [
"coding_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
59f8d762fdbbe3a75629193c74438f5d5e784a70
|
|
train_42832
| 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: JavaScript
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "JavaScript",
"developer_needs": [
"repo_scale_reasoning",
"documentation",
"reproducibility",
"ci_integration"
],
"moe_experts": [
"governance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
124535f824ad81f48e045b67f918d703e6a1921f
|
|
train_42833
| 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: 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.
Review: correctness, security, performance, governance
|
[] |
{
"target_language": "Rust",
"developer_needs": [
"ci_integration",
"cost_latency_tradeoffs",
"auditability",
"tooling"
],
"moe_experts": [
"performance_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
21849a7c820160f4ba460b6689e707683e6553f0
|
|
train_42834
| 2026-01-01T00:00:00
|
Governance, provenance, and licensing for code data
|
data_pipeline
|
advanced
|
Task: data_pipeline
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.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
|
[] |
{
"target_language": "SQL",
"developer_needs": [
"tooling",
"evaluation_metrics",
"documentation",
"repo_scale_reasoning"
],
"moe_experts": [
"data_curation_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
d3652099940251296d5f518991c8c963b2b61015
|
|
train_42835
| 2026-01-01T00:00:00
|
SWE-bench style real-repo evaluation
|
review
|
advanced
|
Task: review
Topic: SWE-bench style real-repo evaluation
Difficulty: advanced
Target language: Go
Context: 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
|
[] |
{
"target_language": "Go",
"developer_needs": [
"security_gates",
"tests_are_truth",
"ci_integration",
"auditability"
],
"moe_experts": [
"security_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
c5f9f4c76a9d8af65b4075e58b78a9c979b4aa61
|
|
train_42836
| 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: 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": "Rust",
"developer_needs": [
"cost_latency_tradeoffs",
"security_gates",
"ci_integration",
"reproducibility"
],
"moe_experts": [
"governance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
cf4e71d4f16493e21266dd9f46d67d46cb02e6ba
|
|
train_42837
| 2026-01-01T00:00:00
|
Governance, provenance, and licensing for code data
|
compare
|
intermediate
|
Task: compare
Topic: Governance, provenance, and licensing for code data
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.
Compare: capability, cost, latency, reliability
|
[] |
{
"target_language": "JavaScript",
"developer_needs": [
"cost_latency_tradeoffs",
"auditability",
"evaluation_metrics",
"ci_integration"
],
"moe_experts": [
"performance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
9b0dd3d0c11f4bbe2da50ed323870408a6fe68a6
|
|
train_42838
| 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: Python
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Python",
"developer_needs": [
"ci_integration",
"evaluation_metrics",
"cost_latency_tradeoffs",
"security_gates"
],
"moe_experts": [
"evaluation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
4a4290c70fd8b825cbd390870e0dec1095c4eb99
|
|
train_42839
| 2026-01-01T00:00:00
|
SWE-bench style real-repo evaluation
|
review
|
intermediate
|
Task: review
Topic: SWE-bench style real-repo evaluation
Difficulty: intermediate
Target language: C#
Context: 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
|
[] |
{
"target_language": "C#",
"developer_needs": [
"auditability",
"tooling",
"repo_scale_reasoning",
"security_gates"
],
"moe_experts": [
"agentic_systems_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
b317000f88d205ee1ede4718d94b1138e95a468b
|
|
train_42840
| 2026-01-01T00:00:00
|
Tool calling, sandboxes, and CI integration
|
eval
|
advanced
|
Task: eval
Topic: Tool calling, sandboxes, and CI integration
Difficulty: advanced
Target language: 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.
Eval:
pass@k, time-to-green, regressions, diff size
|
[] |
{
"target_language": "C#",
"developer_needs": [
"cost_latency_tradeoffs",
"auditability",
"tests_are_truth",
"repo_scale_reasoning"
],
"moe_experts": [
"data_curation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
8d53b582b3acb1ea6837e47afca2fb595ba58e52
|
|
train_42841
| 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: 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": [
"reproducibility",
"cost_latency_tradeoffs",
"security_gates",
"ci_integration"
],
"moe_experts": [
"coding_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
4fb9a380da262bdd0d8fce65f4e5629233ac6780
|
|
train_42842
| 2026-01-01T00:00:00
|
Tool calling, sandboxes, and CI integration
|
review
|
intermediate
|
Task: review
Topic: Tool calling, sandboxes, and CI integration
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.
Review: correctness, security, performance, governance
|
[] |
{
"target_language": "Rust",
"developer_needs": [
"tooling",
"cost_latency_tradeoffs",
"reproducibility",
"auditability"
],
"moe_experts": [
"security_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
28ffd172ccab05a12512e2a3bbf89b1c1eec71d2
|
|
train_42843
| 2026-01-01T00:00:00
|
Model merging, distillation, and continued pretraining
|
design
|
intermediate
|
Task: design
Topic: Model merging, distillation, and continued pretraining
Difficulty: intermediate
Target language: 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
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Bash",
"developer_needs": [
"reproducibility",
"ci_integration",
"auditability",
"repo_scale_reasoning"
],
"moe_experts": [
"performance_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
aa79b3025505ea402db5623c1cd07a1cbd3e3977
|
|
train_42844
| 2026-01-01T00:00:00
|
Model merging, distillation, and continued pretraining
|
data_pipeline
|
expert
|
Task: data_pipeline
Topic: Model merging, distillation, and continued pretraining
Difficulty: expert
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
|
[] |
{
"target_language": "SQL",
"developer_needs": [
"security_gates",
"tests_are_truth",
"ci_integration",
"auditability"
],
"moe_experts": [
"governance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
24f4dd561ccaf911cbea7e5f6a5b684c8fb1ee94
|
|
train_42845
| 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: C#
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Patch (diff-style):
```diff
- if x == 0:
- return 1/x
+ if x == 0:
+ raise ValueError('division by zero')
```
Acceptance:
- Tests pass
- No new regressions
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "C#",
"developer_needs": [
"security_gates",
"evaluation_metrics",
"repo_scale_reasoning",
"ci_integration"
],
"moe_experts": [
"performance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
4e88fe0416d75cb98847aaf20916e9abbdbf515f
|
|
train_42846
| 2026-01-01T00:00:00
|
Reasoning-first coding models and tunable deliberation
|
explain
|
intermediate
|
Task: explain
Topic: Reasoning-first coding models and tunable deliberation
Difficulty: intermediate
Target language: 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",
"ci_integration",
"repo_scale_reasoning",
"tooling"
],
"moe_experts": [
"evaluation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
db4c388c50e1e91f700f5829c4021dbfbe7c2b79
|
|
train_42847
| 2026-01-01T00:00:00
|
Model merging, distillation, and continued pretraining
|
patch_diff
|
advanced
|
Task: patch_diff
Topic: Model merging, distillation, and continued pretraining
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.
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": "Go",
"developer_needs": [
"tooling",
"cost_latency_tradeoffs",
"evaluation_metrics",
"repo_scale_reasoning"
],
"moe_experts": [
"governance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
982e166ca53a5adaf2d9cd63a667a1f1cc954cff
|
|
train_42848
| 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: 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": [
"repo_scale_reasoning",
"tests_are_truth",
"security_gates",
"reproducibility"
],
"moe_experts": [
"security_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
f048f79c5f7cc1236f937c415b281c80a3668554
|
|
train_42849
| 2026-01-01T00:00:00
|
Extended context and repo-scale understanding
|
compare
|
expert
|
Task: compare
Topic: Extended context and repo-scale understanding
Difficulty: expert
Target language: SQL
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "SQL",
"developer_needs": [
"documentation",
"auditability",
"governance",
"tests_are_truth"
],
"moe_experts": [
"evaluation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
fe4b5c84cd9f7a45009d2df35bb47651cdec50f7
|
|
train_42850
| 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: Bash
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Bash",
"developer_needs": [
"documentation",
"evaluation_metrics",
"repo_scale_reasoning",
"ci_integration"
],
"moe_experts": [
"data_curation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
e87b0d26735b7d2b32f8fdbce774fa91b376b0e2
|
|
train_42851
| 2026-01-01T00:00:00
|
Reasoning-first coding models and tunable deliberation
|
agent_loop
|
expert
|
Task: agent_loop
Topic: Reasoning-first coding models and tunable deliberation
Difficulty: expert
Target language: Java
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Java",
"developer_needs": [
"documentation",
"repo_scale_reasoning",
"evaluation_metrics",
"ci_integration"
],
"moe_experts": [
"coding_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
6a9a1a03cd4dad653ae3639d07609abe87ffac3b
|
|
train_42852
| 2026-01-01T00:00:00
|
SWE-bench style real-repo evaluation
|
review
|
advanced
|
Task: review
Topic: SWE-bench style real-repo evaluation
Difficulty: advanced
Target language: Go
Context: 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
|
[] |
{
"target_language": "Go",
"developer_needs": [
"reproducibility",
"tooling",
"cost_latency_tradeoffs",
"security_gates"
],
"moe_experts": [
"governance_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
c5f9f4c76a9d8af65b4075e58b78a9c979b4aa61
|
|
train_42853
| 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: Java
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[] |
{
"target_language": "Java",
"developer_needs": [
"auditability",
"security_gates",
"cost_latency_tradeoffs",
"reproducibility"
],
"moe_experts": [
"data_curation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
166ccf50976c1f2c649a92ea71900bb9f32c259e
|
|
train_42854
| 2026-01-01T00:00:00
|
Secure code generation and policy gates
|
design
|
intermediate
|
Task: design
Topic: Secure code generation and policy gates
Difficulty: intermediate
Target language: Go
Context: 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": [
"auditability",
"tooling",
"security_gates",
"reproducibility"
],
"moe_experts": [
"governance_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
933ecae5220c9d9b1cbd992be6cb32b99ea509a4
|
|
train_42855
| 2026-01-01T00:00:00
|
Secure code generation and policy gates
|
agent_loop
|
expert
|
Task: agent_loop
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.
Loop: Plan → Edit → Test → Reflect → Human gate
|
[] |
{
"target_language": "Python",
"developer_needs": [
"cost_latency_tradeoffs",
"repo_scale_reasoning",
"security_gates",
"auditability"
],
"moe_experts": [
"security_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
d5d898966be5477e6be0b9b37edccadfc4dbdd94
|
|
train_42856
| 2026-01-01T00:00:00
|
Governance, provenance, and licensing for code data
|
eval
|
advanced
|
Task: eval
Topic: Governance, provenance, and licensing for code data
Difficulty: advanced
Target language: Bash
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Bash",
"developer_needs": [
"reproducibility",
"security_gates",
"governance",
"repo_scale_reasoning"
],
"moe_experts": [
"security_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
0cd6d187054be336bb5de3374e30e78e9dfc80f7
|
|
train_42857
| 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: 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": "Python",
"developer_needs": [
"security_gates",
"reproducibility",
"auditability",
"governance"
],
"moe_experts": [
"performance_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
299f02e5ec0fbbdc94e82f9ac010748f9433c0f7
|
|
train_42858
| 2026-01-01T00:00:00
|
Latency, cost, and reliability optimization
|
agent_loop
|
advanced
|
Task: agent_loop
Topic: Latency, cost, and reliability optimization
Difficulty: advanced
Target language: SQL
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
|
[] |
{
"target_language": "SQL",
"developer_needs": [
"repo_scale_reasoning",
"tooling",
"cost_latency_tradeoffs",
"tests_are_truth"
],
"moe_experts": [
"governance_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
4f6bf9a5bf4c2a34f8fb2bf3e00cd3c168f08b9b
|
|
train_42859
| 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: SQL
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "SQL",
"developer_needs": [
"repo_scale_reasoning",
"reproducibility",
"governance",
"cost_latency_tradeoffs"
],
"moe_experts": [
"governance_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
ca8145fd6cb788e00b9de2ba7961db651aacb310
|
|
train_42860
| 2026-01-01T00:00:00
|
Dataset curation pipelines (filter, dedupe, quality)
|
patch_diff
|
expert
|
Task: patch_diff
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: expert
Target language: 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.
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": "Python",
"developer_needs": [
"tests_are_truth",
"ci_integration",
"documentation",
"evaluation_metrics"
],
"moe_experts": [
"coding_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
4697a90e56b448553bb6cfadd5f136370decdae5
|
|
train_42861
| 2026-01-01T00:00:00
|
Mixture-of-Experts (MoE) for code
|
failure_analysis
|
expert
|
Task: failure_analysis
Topic: Mixture-of-Experts (MoE) for code
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.
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": [
"evaluation_metrics",
"tooling",
"security_gates",
"ci_integration"
],
"moe_experts": [
"coding_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
96d4fdff6527549f2d823c7998186a1a3fbe11d0
|
|
train_42862
| 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: 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.
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": "C#",
"developer_needs": [
"governance",
"auditability",
"security_gates",
"ci_integration"
],
"moe_experts": [
"data_curation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
6eb1078d20d0f2e552228288e6c1366a9169a523
|
|
train_42863
| 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: 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": [
"reproducibility",
"tooling",
"governance",
"ci_integration"
],
"moe_experts": [
"evaluation_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
c4474e925f89f10b086c7e0f4fe4382f709a33da
|
|
train_42864
| 2026-01-01T00:00:00
|
Tool calling, sandboxes, and CI integration
|
code
|
intermediate
|
Task: code
Topic: Tool calling, sandboxes, and CI integration
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": [
"cost_latency_tradeoffs",
"ci_integration",
"governance",
"repo_scale_reasoning"
],
"moe_experts": [
"coding_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
da7dbb2e4a1e69c7c1f1db3e2056fdc2603aeb4e
|
|
train_42865
| 2026-01-01T00:00:00
|
Governance, provenance, and licensing for code data
|
eval
|
intermediate
|
Task: eval
Topic: Governance, provenance, and licensing for code data
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.
Eval:
pass@k, time-to-green, regressions, diff size
|
[] |
{
"target_language": "Bash",
"developer_needs": [
"tests_are_truth",
"governance",
"cost_latency_tradeoffs",
"security_gates"
],
"moe_experts": [
"evaluation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
309130896e7d8691fef8a924634be5c4cec5d146
|
|
train_42866
| 2026-01-01T00:00:00
|
SWE-bench style real-repo evaluation
|
agent_loop
|
intermediate
|
Task: agent_loop
Topic: SWE-bench style real-repo evaluation
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.
Loop: Plan → Edit → Test → Reflect → Human gate
|
[] |
{
"target_language": "Java",
"developer_needs": [
"reproducibility",
"tooling",
"governance",
"auditability"
],
"moe_experts": [
"performance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
d376ef0fb8b50840debf0af6167c1c5b06b8954e
|
|
train_42867
| 2026-01-01T00:00:00
|
Agentic coding systems (plan→edit→test→reflect)
|
compare
|
expert
|
Task: compare
Topic: Agentic coding systems (plan→edit→test→reflect)
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.
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": [
"cost_latency_tradeoffs",
"governance",
"repo_scale_reasoning",
"tests_are_truth"
],
"moe_experts": [
"data_curation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
124aba0eb5dad3810473b6fa37882142a9667f5d
|
|
train_42868
| 2026-01-01T00:00:00
|
Tool calling, sandboxes, and CI integration
|
agent_loop
|
advanced
|
Task: agent_loop
Topic: Tool calling, sandboxes, and CI integration
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.
Loop: Plan → Edit → Test → Reflect → Human gate
|
[] |
{
"target_language": "JavaScript",
"developer_needs": [
"ci_integration",
"cost_latency_tradeoffs",
"tooling",
"reproducibility"
],
"moe_experts": [
"performance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
5b4c91c7c7d726f9b807a4b5bc125d8ad394344d
|
|
train_42869
| 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: 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": [
"security_gates",
"documentation",
"ci_integration",
"cost_latency_tradeoffs"
],
"moe_experts": [
"agentic_systems_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
d91e7971dc03d84142e1e6abdbca7e8a9a1ebbbf
|
|
train_42870
| 2026-01-01T00:00:00
|
Governance, provenance, and licensing for code data
|
failure_analysis
|
advanced
|
Task: failure_analysis
Topic: Governance, provenance, and licensing for code data
Difficulty: advanced
Target language: 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.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
|
[] |
{
"target_language": "Python",
"developer_needs": [
"repo_scale_reasoning",
"evaluation_metrics",
"tooling",
"ci_integration"
],
"moe_experts": [
"governance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
d965c663512115dd22caeb4936f8e9096421611e
|
|
train_42871
| 2026-01-01T00:00:00
|
Latency, cost, and reliability optimization
|
code
|
advanced
|
Task: code
Topic: Latency, cost, and reliability optimization
Difficulty: advanced
Target language: Java
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
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",
"ci_integration",
"cost_latency_tradeoffs",
"governance"
],
"moe_experts": [
"data_curation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
452a0561b856ff4c2b4f207fc8c8bd451f4092ed
|
|
train_42872
| 2026-01-01T00:00:00
|
Code-specialized model families and sizing tradeoffs
|
design
|
advanced
|
Task: design
Topic: Code-specialized model families and sizing tradeoffs
Difficulty: advanced
Target language: 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": [
"documentation",
"evaluation_metrics",
"ci_integration",
"reproducibility"
],
"moe_experts": [
"data_curation_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
405838758f38f1b8b4e6a81932a5514b316baa77
|
|
train_42873
| 2026-01-01T00:00:00
|
Latency, cost, and reliability optimization
|
agent_loop
|
advanced
|
Task: agent_loop
Topic: Latency, cost, and reliability optimization
Difficulty: advanced
Target language: 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.
Loop: Plan → Edit → Test → Reflect → Human gate
|
[] |
{
"target_language": "Bash",
"developer_needs": [
"tooling",
"security_gates",
"reproducibility",
"governance"
],
"moe_experts": [
"governance_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
f711b09e61504412f9c32ce18950264ab67b8cd3
|
|
train_42874
| 2026-01-01T00:00:00
|
Agentic coding systems (plan→edit→test→reflect)
|
review
|
intermediate
|
Task: review
Topic: Agentic coding systems (plan→edit→test→reflect)
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.
Review: correctness, security, performance, governance
|
[] |
{
"target_language": "Go",
"developer_needs": [
"governance",
"security_gates",
"reproducibility",
"auditability"
],
"moe_experts": [
"security_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
8f9c095c419df31593a30943e677218b49119823
|
|
train_42875
| 2026-01-01T00:00:00
|
Multimodal dev workflows (docs, diagrams, traces)
|
patch_diff
|
advanced
|
Task: patch_diff
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.
Patch (diff-style):
```diff
- if x == 0:
- return 1/x
+ if x == 0:
+ raise ValueError('division by zero')
```
Acceptance:
- Tests pass
- No new regressions
|
[] |
{
"target_language": "Go",
"developer_needs": [
"tooling",
"tests_are_truth",
"security_gates",
"documentation"
],
"moe_experts": [
"agentic_systems_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
f5e7cf0667b14475c356ef48dba69a91ad6ef061
|
|
train_42876
| 2026-01-01T00:00:00
|
Reasoning-first coding models and tunable deliberation
|
code
|
advanced
|
Task: code
Topic: Reasoning-first coding models and tunable deliberation
Difficulty: advanced
Target language: 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": [
"documentation",
"governance",
"reproducibility",
"tests_are_truth"
],
"moe_experts": [
"evaluation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
fb4e32c2f88f73ed91a6835b2148f55c2126eb7b
|
|
train_42877
| 2026-01-01T00:00:00
|
Reasoning-first coding models and tunable deliberation
|
data_pipeline
|
advanced
|
Task: data_pipeline
Topic: Reasoning-first coding models and tunable deliberation
Difficulty: advanced
Target language: JavaScript
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
|
[] |
{
"target_language": "JavaScript",
"developer_needs": [
"tooling",
"governance",
"ci_integration",
"repo_scale_reasoning"
],
"moe_experts": [
"governance_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
bff923dd4f65887cf72856ba328e9b2df3e3af99
|
|
train_42878
| 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: TypeScript
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "TypeScript",
"developer_needs": [
"evaluation_metrics",
"tests_are_truth",
"governance",
"security_gates"
],
"moe_experts": [
"data_curation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
22d0e1c78c2e6cacaa2ff8fd1e6a7bb4b8973d70
|
|
train_42879
| 2026-01-01T00:00:00
|
SWE-bench style real-repo evaluation
|
agent_loop
|
advanced
|
Task: agent_loop
Topic: SWE-bench style real-repo evaluation
Difficulty: advanced
Target language: 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": [
"repo_scale_reasoning",
"evaluation_metrics",
"tests_are_truth",
"security_gates"
],
"moe_experts": [
"governance_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
1be04c48c8332cda3d12713721cdbb2ca3bb05bc
|
|
train_42880
| 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: Go
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
|
[] |
{
"target_language": "Go",
"developer_needs": [
"tooling",
"ci_integration",
"tests_are_truth",
"governance"
],
"moe_experts": [
"coding_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
956f1da0160faf53f6dd70395caf201a9d72f137
|
|
train_42881
| 2026-01-01T00:00:00
|
Dataset curation pipelines (filter, dedupe, quality)
|
data_pipeline
|
intermediate
|
Task: data_pipeline
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: intermediate
Target language: 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.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
|
[] |
{
"target_language": "SQL",
"developer_needs": [
"tests_are_truth",
"auditability",
"evaluation_metrics",
"cost_latency_tradeoffs"
],
"moe_experts": [
"governance_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
721731e2b9160beb4f329626808cd4fc88afccd5
|
|
train_42882
| 2026-01-01T00:00:00
|
Code-specialized model families and sizing tradeoffs
|
eval
|
advanced
|
Task: eval
Topic: Code-specialized model families and sizing tradeoffs
Difficulty: advanced
Target language: Bash
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Bash",
"developer_needs": [
"ci_integration",
"governance",
"documentation",
"evaluation_metrics"
],
"moe_experts": [
"data_curation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
c6f90a393e4caa8b28cef784bf28b3a2c71e54c6
|
|
train_42883
| 2026-01-01T00:00:00
|
SWE-bench style real-repo evaluation
|
failure_analysis
|
intermediate
|
Task: failure_analysis
Topic: SWE-bench style real-repo evaluation
Difficulty: intermediate
Target language: 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.
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": [
"ci_integration",
"security_gates",
"tests_are_truth",
"tooling"
],
"moe_experts": [
"coding_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
8ab131190ef3ab4e8336ef8beb37ea4e4df6db58
|
|
train_42884
| 2026-01-01T00:00:00
|
SWE-bench style real-repo evaluation
|
review
|
intermediate
|
Task: review
Topic: SWE-bench style real-repo evaluation
Difficulty: intermediate
Target language: 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
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Go",
"developer_needs": [
"auditability",
"governance",
"documentation",
"repo_scale_reasoning"
],
"moe_experts": [
"data_curation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
7c2bac95d56e3569ff5535738d1022bff4a700b2
|
|
train_42885
| 2026-01-01T00:00:00
|
Agentic coding systems (plan→edit→test→reflect)
|
data_pipeline
|
expert
|
Task: data_pipeline
Topic: Agentic coding systems (plan→edit→test→reflect)
Difficulty: expert
Target language: 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": [
"auditability",
"tests_are_truth",
"documentation",
"governance"
],
"moe_experts": [
"data_curation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
25143162f230c6780081c708795f96ccd0da37b6
|
|
train_42886
| 2026-01-01T00:00:00
|
Self-improving agents and feedback loops
|
design
|
advanced
|
Task: design
Topic: Self-improving agents and feedback loops
Difficulty: advanced
Target language: 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": [
"ci_integration",
"auditability",
"tests_are_truth",
"cost_latency_tradeoffs"
],
"moe_experts": [
"data_curation_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
7d3ea98e925864bb10520d499f6d4f9c4f406bf5
|
|
train_42887
| 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: Bash
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
|
[] |
{
"target_language": "Bash",
"developer_needs": [
"reproducibility",
"tests_are_truth",
"security_gates",
"evaluation_metrics"
],
"moe_experts": [
"security_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
c29c84e0ef5abd3cb95dfb4a5512579d5e60b9c2
|
|
train_42888
| 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: 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",
"governance",
"ci_integration",
"tests_are_truth"
],
"moe_experts": [
"performance_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
449e8aa7daffdcd92c4a729c9dc89643eab1cd0c
|
|
train_42889
| 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: 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": [
"governance",
"documentation",
"cost_latency_tradeoffs",
"tests_are_truth"
],
"moe_experts": [
"coding_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
53ff00aa2ad098c4adf4cf1107399b6b70e7e7fc
|
|
train_42890
| 2026-01-01T00:00:00
|
Multimodal dev workflows (docs, diagrams, traces)
|
data_pipeline
|
advanced
|
Task: data_pipeline
Topic: Multimodal dev workflows (docs, diagrams, traces)
Difficulty: advanced
Target language: 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.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
|
[] |
{
"target_language": "Bash",
"developer_needs": [
"documentation",
"auditability",
"security_gates",
"reproducibility"
],
"moe_experts": [
"agentic_systems_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
1c18090f636de1b0dc9a011c9af4b407b50822ab
|
|
train_42891
| 2026-01-01T00:00:00
|
Model merging, distillation, and continued pretraining
|
agent_loop
|
expert
|
Task: agent_loop
Topic: Model merging, distillation, and continued pretraining
Difficulty: expert
Target language: Go
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
|
[] |
{
"target_language": "Go",
"developer_needs": [
"repo_scale_reasoning",
"documentation",
"ci_integration",
"reproducibility"
],
"moe_experts": [
"performance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
6f4075effe229aa27c83bbd0f74d6f0e0d904a28
|
|
train_42892
| 2026-01-01T00:00:00
|
Reasoning-first coding models and tunable deliberation
|
patch_diff
|
intermediate
|
Task: patch_diff
Topic: Reasoning-first coding models and tunable deliberation
Difficulty: intermediate
Target language: 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.
Patch (diff-style):
```diff
- if x == 0:
- return 1/x
+ if x == 0:
+ raise ValueError('division by zero')
```
Acceptance:
- Tests pass
- No new regressions
|
[] |
{
"target_language": "Python",
"developer_needs": [
"documentation",
"governance",
"cost_latency_tradeoffs",
"repo_scale_reasoning"
],
"moe_experts": [
"agentic_systems_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
2d8b4f463fe2d4a51d2ea0097b31d58ef37f004b
|
|
train_42893
| 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: SQL
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[] |
{
"target_language": "SQL",
"developer_needs": [
"documentation",
"tooling",
"tests_are_truth",
"cost_latency_tradeoffs"
],
"moe_experts": [
"coding_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
da65526316801e470bba5adff4bc6767a04dff90
|
|
train_42894
| 2026-01-01T00:00:00
|
SWE-bench style real-repo evaluation
|
review
|
advanced
|
Task: review
Topic: SWE-bench style real-repo evaluation
Difficulty: advanced
Target language: Bash
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Review: correctness, security, performance, governance
|
[] |
{
"target_language": "Bash",
"developer_needs": [
"ci_integration",
"auditability",
"tooling",
"evaluation_metrics"
],
"moe_experts": [
"evaluation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
7e59645475f3ed9608d6fe900b90dc0bfbfefd90
|
|
train_42895
| 2026-01-01T00:00:00
|
Multimodal dev workflows (docs, diagrams, traces)
|
compare
|
advanced
|
Task: compare
Topic: Multimodal dev workflows (docs, diagrams, traces)
Difficulty: advanced
Target language: 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": [
"governance",
"documentation",
"repo_scale_reasoning",
"tests_are_truth"
],
"moe_experts": [
"performance_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
dc89cfd636dfc20943ac5e2dea2c2d6c04919f59
|
|
train_42896
| 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: Python
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
|
[] |
{
"target_language": "Python",
"developer_needs": [
"repo_scale_reasoning",
"evaluation_metrics",
"tooling",
"governance"
],
"moe_experts": [
"data_curation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
92788372a172f6ed02628a5cdf589cf477046908
|
|
train_42897
| 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: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
|
[] |
{
"target_language": "Python",
"developer_needs": [
"repo_scale_reasoning",
"tests_are_truth",
"ci_integration",
"security_gates"
],
"moe_experts": [
"evaluation_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
c6137da2e68581f48125c01cd8fbfbfda88752f2
|
|
train_42898
| 2026-01-01T00:00:00
|
Governance, provenance, and licensing for code data
|
review
|
intermediate
|
Task: review
Topic: Governance, provenance, and licensing for code data
Difficulty: intermediate
Target language: Java
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
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": [
"repo_scale_reasoning",
"security_gates",
"auditability",
"evaluation_metrics"
],
"moe_experts": [
"security_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
c7d2f594a0e5d21a5d34f9d1d363921bc228f72e
|
|
train_42899
| 2026-01-01T00:00:00
|
Governance, provenance, and licensing for code data
|
review
|
intermediate
|
Task: review
Topic: Governance, provenance, and licensing for code data
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.
Review: correctness, security, performance, governance
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "SQL",
"developer_needs": [
"security_gates",
"ci_integration",
"tests_are_truth",
"auditability"
],
"moe_experts": [
"data_curation_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
51502071c280db9df313f35300c23d58f358c102
|
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