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2026-01-01 00:00:00
| topic
stringclasses 14
values | task_type
stringclasses 10
values | difficulty
stringclasses 3
values | instruction
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|---|---|---|---|---|---|---|---|---|---|---|
train_39800
| 2026-01-01T00:00:00
|
Extended context and repo-scale understanding
|
data_pipeline
|
advanced
|
Task: data_pipeline
Topic: Extended context and repo-scale understanding
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
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Bash",
"developer_needs": [
"governance",
"cost_latency_tradeoffs",
"security_gates",
"documentation"
],
"moe_experts": [
"evaluation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
9c9a4b5d42892b8b9a07a2e2bca4dc565f8ad94f
|
|
train_39801
| 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: 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": "JavaScript",
"developer_needs": [
"security_gates",
"auditability",
"evaluation_metrics",
"ci_integration"
],
"moe_experts": [
"governance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
7ab962e53e8b610e2e1aea9b0ce82f98884a06c0
|
|
train_39802
| 2026-01-01T00:00:00
|
Tool calling, sandboxes, and CI integration
|
review
|
expert
|
Task: review
Topic: Tool calling, sandboxes, and CI integration
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.
Review: correctness, security, performance, governance
|
[] |
{
"target_language": "Python",
"developer_needs": [
"security_gates",
"documentation",
"evaluation_metrics",
"reproducibility"
],
"moe_experts": [
"coding_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
0ac755972c953c4fac27e9727fbcb039a7eab3a3
|
|
train_39803
| 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: 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": [
"tests_are_truth",
"reproducibility",
"tooling",
"governance"
],
"moe_experts": [
"agentic_systems_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
9fe251321aedf7ec1841f74c229c4f16606e2a96
|
|
train_39804
| 2026-01-01T00:00:00
|
Reasoning-first coding models and tunable deliberation
|
code
|
expert
|
Task: code
Topic: Reasoning-first coding models and tunable deliberation
Difficulty: expert
Target language: 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": [
"documentation",
"auditability",
"cost_latency_tradeoffs",
"tooling"
],
"moe_experts": [
"coding_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
863d0add4b2ae3a37a6000480da2d2bb3fdbb666
|
|
train_39805
| 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: C#
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "C#",
"developer_needs": [
"repo_scale_reasoning",
"cost_latency_tradeoffs",
"governance",
"reproducibility"
],
"moe_experts": [
"evaluation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
72b5f34e95b40e699e48babccbbdfa9ef8e9dc7e
|
|
train_39806
| 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: C#
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "C#",
"developer_needs": [
"governance",
"documentation",
"reproducibility",
"repo_scale_reasoning"
],
"moe_experts": [
"data_curation_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
0e93fc0e9b0b17daddcd12a63e4429db5bf7043e
|
|
train_39807
| 2026-01-01T00:00:00
|
Mixture-of-Experts (MoE) for code
|
failure_analysis
|
intermediate
|
Task: failure_analysis
Topic: Mixture-of-Experts (MoE) for code
Difficulty: intermediate
Target language: 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.
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": [
"auditability",
"documentation",
"evaluation_metrics",
"cost_latency_tradeoffs"
],
"moe_experts": [
"security_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
8bda9a0919de3a90887adccd9eef80fd02997eac
|
|
train_39808
| 2026-01-01T00:00:00
|
Model merging, distillation, and continued pretraining
|
agent_loop
|
advanced
|
Task: agent_loop
Topic: Model merging, distillation, and continued pretraining
Difficulty: advanced
Target language: 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.
Loop: Plan → Edit → Test → Reflect → Human gate
|
[] |
{
"target_language": "SQL",
"developer_needs": [
"cost_latency_tradeoffs",
"reproducibility",
"documentation",
"repo_scale_reasoning"
],
"moe_experts": [
"data_curation_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
0f159440d4cb7886c81408b24d9b208a660afbd7
|
|
train_39809
| 2026-01-01T00:00:00
|
Extended context and repo-scale understanding
|
data_pipeline
|
advanced
|
Task: data_pipeline
Topic: Extended context and repo-scale understanding
Difficulty: advanced
Target language: Java
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
|
[] |
{
"target_language": "Java",
"developer_needs": [
"cost_latency_tradeoffs",
"tests_are_truth",
"documentation",
"security_gates"
],
"moe_experts": [
"governance_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
537ced0ddbaf5eeee1cf69ad7de355202637b1ae
|
|
train_39810
| 2026-01-01T00:00:00
|
Tool calling, sandboxes, and CI integration
|
design
|
expert
|
Task: design
Topic: Tool calling, sandboxes, and CI integration
Difficulty: expert
Target language: 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",
"repo_scale_reasoning",
"documentation",
"cost_latency_tradeoffs"
],
"moe_experts": [
"governance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
4fdfd6f7b1f825182787c9cef7c31ba87a83a54a
|
|
train_39811
| 2026-01-01T00:00:00
|
Dataset curation pipelines (filter, dedupe, quality)
|
compare
|
expert
|
Task: compare
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: expert
Target language: Bash
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Bash",
"developer_needs": [
"documentation",
"cost_latency_tradeoffs",
"security_gates",
"reproducibility"
],
"moe_experts": [
"performance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
16f642c4804837577fc607d942cf0428fdf85643
|
|
train_39812
| 2026-01-01T00:00:00
|
Multimodal dev workflows (docs, diagrams, traces)
|
agent_loop
|
intermediate
|
Task: agent_loop
Topic: Multimodal dev workflows (docs, diagrams, traces)
Difficulty: intermediate
Target language: Java
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Java",
"developer_needs": [
"repo_scale_reasoning",
"tests_are_truth",
"reproducibility",
"evaluation_metrics"
],
"moe_experts": [
"governance_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
432c6f88a781e41faf92376254bb43bea0a31a5f
|
|
train_39813
| 2026-01-01T00:00:00
|
Secure code generation and policy gates
|
explain
|
intermediate
|
Task: explain
Topic: Secure code generation and policy gates
Difficulty: intermediate
Target language: JavaScript
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[] |
{
"target_language": "JavaScript",
"developer_needs": [
"repo_scale_reasoning",
"reproducibility",
"security_gates",
"cost_latency_tradeoffs"
],
"moe_experts": [
"agentic_systems_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
f82170060a362f760611ef8ebd380298e57d6483
|
|
train_39814
| 2026-01-01T00:00:00
|
SWE-bench style real-repo evaluation
|
patch_diff
|
expert
|
Task: patch_diff
Topic: SWE-bench style real-repo evaluation
Difficulty: expert
Target language: Go
Context: 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": "Go",
"developer_needs": [
"cost_latency_tradeoffs",
"ci_integration",
"repo_scale_reasoning",
"auditability"
],
"moe_experts": [
"data_curation_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
886e4ed0594e7729598eb43c309deb90689088ea
|
|
train_39815
| 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: 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
```
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Python",
"developer_needs": [
"tooling",
"repo_scale_reasoning",
"auditability",
"evaluation_metrics"
],
"moe_experts": [
"performance_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
0b36cd8ebfed07812f24b1386431aeecdd0a2dc4
|
|
train_39816
| 2026-01-01T00:00:00
|
Latency, cost, and reliability optimization
|
patch_diff
|
intermediate
|
Task: patch_diff
Topic: Latency, cost, and reliability optimization
Difficulty: intermediate
Target language: 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.
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": [
"tests_are_truth",
"auditability",
"ci_integration",
"repo_scale_reasoning"
],
"moe_experts": [
"coding_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
979894975c4616152dc814cca69a4df02ebb4c28
|
|
train_39817
| 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: 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": [
"security_gates",
"ci_integration",
"evaluation_metrics",
"documentation"
],
"moe_experts": [
"performance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
df835003cb7a2eaa54c92e3a256dcfa1d0244959
|
|
train_39818
| 2026-01-01T00:00:00
|
Secure code generation and policy gates
|
failure_analysis
|
intermediate
|
Task: failure_analysis
Topic: Secure code generation and policy gates
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.
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": [
"documentation",
"governance",
"cost_latency_tradeoffs",
"evaluation_metrics"
],
"moe_experts": [
"performance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
70838dd6d7d8b6a246b8207cfb1cf98ecc352318
|
|
train_39819
| 2026-01-01T00:00:00
|
Tool calling, sandboxes, and CI integration
|
design
|
intermediate
|
Task: design
Topic: Tool calling, sandboxes, and CI integration
Difficulty: intermediate
Target language: Bash
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[] |
{
"target_language": "Bash",
"developer_needs": [
"documentation",
"governance",
"cost_latency_tradeoffs",
"evaluation_metrics"
],
"moe_experts": [
"governance_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
5fd95876479ac939780ad6367b6403d87105e3e6
|
|
train_39820
| 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: 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.
Eval:
pass@k, time-to-green, regressions, diff size
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Python",
"developer_needs": [
"ci_integration",
"repo_scale_reasoning",
"security_gates",
"reproducibility"
],
"moe_experts": [
"security_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
124f26ee2af8450dac7eaed5ba194fa7ca876790
|
|
train_39821
| 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: 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.
Review: correctness, security, performance, governance
|
[] |
{
"target_language": "Python",
"developer_needs": [
"documentation",
"reproducibility",
"cost_latency_tradeoffs",
"auditability"
],
"moe_experts": [
"coding_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
b3976a2d35c6949590a3714eae958de8ed20412d
|
|
train_39822
| 2026-01-01T00:00:00
|
Governance, provenance, and licensing for code data
|
agent_loop
|
advanced
|
Task: agent_loop
Topic: Governance, provenance, and licensing for code data
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
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "JavaScript",
"developer_needs": [
"ci_integration",
"evaluation_metrics",
"reproducibility",
"tooling"
],
"moe_experts": [
"agentic_systems_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
dbc782db23ef8469d7c803b5e75ec66279ac015e
|
|
train_39823
| 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: 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": [
"evaluation_metrics",
"governance",
"documentation",
"tests_are_truth"
],
"moe_experts": [
"security_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
cb16dad803b6ab38b512d6772bd465a5fd569151
|
|
train_39824
| 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: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[] |
{
"target_language": "SQL",
"developer_needs": [
"tooling",
"tests_are_truth",
"cost_latency_tradeoffs",
"reproducibility"
],
"moe_experts": [
"performance_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
56d11a4f5cf81951b7d663cef0fa640ff8e6106b
|
|
train_39825
| 2026-01-01T00:00:00
|
Latency, cost, and reliability optimization
|
code
|
intermediate
|
Task: code
Topic: Latency, cost, and reliability optimization
Difficulty: intermediate
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": [
"tests_are_truth",
"documentation",
"ci_integration",
"tooling"
],
"moe_experts": [
"data_curation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
390f0757f2741c01744b6598a7d4864ced55d445
|
|
train_39826
| 2026-01-01T00:00:00
|
Extended context and repo-scale understanding
|
failure_analysis
|
advanced
|
Task: failure_analysis
Topic: Extended context and repo-scale understanding
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
|
[] |
{
"target_language": "Go",
"developer_needs": [
"cost_latency_tradeoffs",
"documentation",
"ci_integration",
"reproducibility"
],
"moe_experts": [
"performance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
06d48d3dd6ce549d9db6b89bb838a273b299f16f
|
|
train_39827
| 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: 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": [
"cost_latency_tradeoffs",
"repo_scale_reasoning",
"ci_integration",
"tests_are_truth"
],
"moe_experts": [
"security_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
a38041335c201c52edd01f17d1e697edc7c48e10
|
|
train_39828
| 2026-01-01T00:00:00
|
Reasoning-first coding models and tunable deliberation
|
review
|
advanced
|
Task: review
Topic: Reasoning-first coding models and tunable deliberation
Difficulty: advanced
Target language: Go
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Review: correctness, security, performance, governance
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Go",
"developer_needs": [
"evaluation_metrics",
"governance",
"ci_integration",
"auditability"
],
"moe_experts": [
"agentic_systems_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
885f5b5dda86ce9f2435f5d4ea3c376f4976d873
|
|
train_39829
| 2026-01-01T00:00:00
|
Code-specialized model families and sizing tradeoffs
|
eval
|
expert
|
Task: eval
Topic: Code-specialized model families and sizing tradeoffs
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.
Eval:
pass@k, time-to-green, regressions, diff size
|
[] |
{
"target_language": "C#",
"developer_needs": [
"tests_are_truth",
"auditability",
"repo_scale_reasoning",
"documentation"
],
"moe_experts": [
"data_curation_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
f2226a5f62aeae03f32d569619a539033f30716c
|
|
train_39830
| 2026-01-01T00:00:00
|
Extended context and repo-scale understanding
|
data_pipeline
|
advanced
|
Task: data_pipeline
Topic: Extended context and repo-scale understanding
Difficulty: advanced
Target language: Rust
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
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": [
"governance",
"repo_scale_reasoning",
"auditability",
"evaluation_metrics"
],
"moe_experts": [
"performance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
619f21c0be1270e959f25314587a27d455a9aa52
|
|
train_39831
| 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: C#
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[] |
{
"target_language": "C#",
"developer_needs": [
"ci_integration",
"governance",
"cost_latency_tradeoffs",
"repo_scale_reasoning"
],
"moe_experts": [
"coding_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
4194cc17c76059096ad81d098cd4fe4902145717
|
|
train_39832
| 2026-01-01T00:00:00
|
Extended context and repo-scale understanding
|
failure_analysis
|
expert
|
Task: failure_analysis
Topic: Extended context and repo-scale understanding
Difficulty: expert
Target language: TypeScript
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
|
[
"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",
"reproducibility",
"repo_scale_reasoning"
],
"moe_experts": [
"data_curation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
6eae90485645bff855410b838a0239c26fc2b25f
|
|
train_39833
| 2026-01-01T00:00:00
|
Code-specialized model families and sizing tradeoffs
|
eval
|
expert
|
Task: eval
Topic: Code-specialized model families and sizing tradeoffs
Difficulty: expert
Target language: C#
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
|
[] |
{
"target_language": "C#",
"developer_needs": [
"documentation",
"auditability",
"repo_scale_reasoning",
"evaluation_metrics"
],
"moe_experts": [
"data_curation_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
d08016954e0f0cf6435469ea00d4d88bc523c878
|
|
train_39834
| 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: C#
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
|
[] |
{
"target_language": "C#",
"developer_needs": [
"security_gates",
"tooling",
"governance",
"reproducibility"
],
"moe_experts": [
"security_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
20be21bdde3dcd2e712879ac36ab4f4c8938db84
|
|
train_39835
| 2026-01-01T00:00:00
|
Reasoning-first coding models and tunable deliberation
|
data_pipeline
|
advanced
|
Task: data_pipeline
Topic: Reasoning-first coding models and tunable deliberation
Difficulty: advanced
Target language: Go
Context: 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": "Go",
"developer_needs": [
"reproducibility",
"repo_scale_reasoning",
"ci_integration",
"auditability"
],
"moe_experts": [
"evaluation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
0b694d87f03ec14b8d0691f3b23e92cc4644f0c6
|
|
train_39836
| 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: Go
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Go",
"developer_needs": [
"documentation",
"repo_scale_reasoning",
"governance",
"tooling"
],
"moe_experts": [
"evaluation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
b1ef62763da226ddd4549f9ae2556b583e7cd636
|
|
train_39837
| 2026-01-01T00:00:00
|
Reasoning-first coding models and tunable deliberation
|
review
|
intermediate
|
Task: review
Topic: Reasoning-first coding models and tunable deliberation
Difficulty: intermediate
Target language: 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
|
[] |
{
"target_language": "Java",
"developer_needs": [
"evaluation_metrics",
"ci_integration",
"governance",
"tests_are_truth"
],
"moe_experts": [
"performance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
5f1deba9d261f13564df3452fc380f100d6a23a9
|
|
train_39838
| 2026-01-01T00:00:00
|
Secure code generation and policy gates
|
agent_loop
|
advanced
|
Task: agent_loop
Topic: Secure code generation and policy gates
Difficulty: advanced
Target language: Bash
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
|
[] |
{
"target_language": "Bash",
"developer_needs": [
"security_gates",
"tooling",
"cost_latency_tradeoffs",
"governance"
],
"moe_experts": [
"agentic_systems_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
0d2e04bf1de57e9399ae83d20427971787f6378f
|
|
train_39839
| 2026-01-01T00:00:00
|
Code-specialized model families and sizing tradeoffs
|
agent_loop
|
advanced
|
Task: agent_loop
Topic: Code-specialized model families and sizing tradeoffs
Difficulty: advanced
Target language: JavaScript
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
|
[] |
{
"target_language": "JavaScript",
"developer_needs": [
"auditability",
"ci_integration",
"repo_scale_reasoning",
"tooling"
],
"moe_experts": [
"data_curation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
e40f11375e770c3da40981bcc8c03cf9c8f2089a
|
|
train_39840
| 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: 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.
Eval:
pass@k, time-to-green, regressions, diff size
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "C#",
"developer_needs": [
"security_gates",
"tooling",
"ci_integration",
"governance"
],
"moe_experts": [
"coding_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
a7d181a13497438b3e92b645fe4e81c640e1ca23
|
|
train_39841
| 2026-01-01T00:00:00
|
Mixture-of-Experts (MoE) for code
|
code
|
expert
|
Task: code
Topic: Mixture-of-Experts (MoE) for code
Difficulty: expert
Target language: 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": [
"repo_scale_reasoning",
"tooling",
"cost_latency_tradeoffs",
"security_gates"
],
"moe_experts": [
"security_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
541f5ca670135562715542f0c04df84f8fc54f39
|
|
train_39842
| 2026-01-01T00:00:00
|
Model merging, distillation, and continued pretraining
|
eval
|
advanced
|
Task: eval
Topic: Model merging, distillation, and continued pretraining
Difficulty: advanced
Target language: 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
|
[] |
{
"target_language": "Java",
"developer_needs": [
"ci_integration",
"governance",
"evaluation_metrics",
"documentation"
],
"moe_experts": [
"coding_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
4797eba72ffdd1dc33939fdcb3172827708814db
|
|
train_39843
| 2026-01-01T00:00:00
|
Secure code generation and policy gates
|
review
|
expert
|
Task: review
Topic: Secure code generation and policy gates
Difficulty: expert
Target language: JavaScript
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Review: correctness, security, performance, governance
|
[] |
{
"target_language": "JavaScript",
"developer_needs": [
"evaluation_metrics",
"tests_are_truth",
"security_gates",
"auditability"
],
"moe_experts": [
"agentic_systems_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
10a3d38fb7565133abe45743257d87bfe08bc438
|
|
train_39844
| 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: Bash
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
|
[] |
{
"target_language": "Bash",
"developer_needs": [
"tests_are_truth",
"cost_latency_tradeoffs",
"ci_integration",
"evaluation_metrics"
],
"moe_experts": [
"data_curation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
73418797b686ce3c9d7516843f91bf945604c1a6
|
|
train_39845
| 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: Bash
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Bash",
"developer_needs": [
"repo_scale_reasoning",
"security_gates",
"documentation",
"tooling"
],
"moe_experts": [
"coding_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
ee3b7ab01bda7b5a3214b0c03e43fff90db9f9e1
|
|
train_39846
| 2026-01-01T00:00:00
|
Mixture-of-Experts (MoE) for code
|
code
|
advanced
|
Task: code
Topic: Mixture-of-Experts (MoE) for code
Difficulty: advanced
Target language: 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": [
"documentation",
"tooling",
"tests_are_truth",
"reproducibility"
],
"moe_experts": [
"performance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
7a09d3631c198f634697916c0eb43bbcf5038c5f
|
|
train_39847
| 2026-01-01T00:00:00
|
Latency, cost, and reliability optimization
|
data_pipeline
|
intermediate
|
Task: data_pipeline
Topic: Latency, cost, and reliability optimization
Difficulty: intermediate
Target language: TypeScript
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
|
[] |
{
"target_language": "TypeScript",
"developer_needs": [
"tests_are_truth",
"tooling",
"cost_latency_tradeoffs",
"documentation"
],
"moe_experts": [
"agentic_systems_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
b21873863e0e52a0cb3b3d0f7a2b9ec0fe10de90
|
|
train_39848
| 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: Go
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[] |
{
"target_language": "Go",
"developer_needs": [
"security_gates",
"tooling",
"ci_integration",
"governance"
],
"moe_experts": [
"security_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
7ebeee507d1099954739d0f31b7861c768cbf232
|
|
train_39849
| 2026-01-01T00:00:00
|
Multimodal dev workflows (docs, diagrams, traces)
|
review
|
advanced
|
Task: review
Topic: Multimodal dev workflows (docs, diagrams, traces)
Difficulty: advanced
Target language: 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.
Review: correctness, security, performance, governance
|
[] |
{
"target_language": "Python",
"developer_needs": [
"documentation",
"governance",
"cost_latency_tradeoffs",
"auditability"
],
"moe_experts": [
"data_curation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
faab8848fade1809ab4d4bcbe8b7568d2e63eb29
|
|
train_39850
| 2026-01-01T00:00:00
|
Model merging, distillation, and continued pretraining
|
failure_analysis
|
intermediate
|
Task: failure_analysis
Topic: Model merging, distillation, and continued pretraining
Difficulty: intermediate
Target language: Rust
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Rust",
"developer_needs": [
"governance",
"tooling",
"cost_latency_tradeoffs",
"ci_integration"
],
"moe_experts": [
"data_curation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
f222e54c10d7c498cfc42817ed0bfd8f594989bb
|
|
train_39851
| 2026-01-01T00:00:00
|
Code-specialized model families and sizing tradeoffs
|
design
|
intermediate
|
Task: design
Topic: Code-specialized model families and sizing tradeoffs
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": [
"documentation",
"tests_are_truth",
"repo_scale_reasoning",
"ci_integration"
],
"moe_experts": [
"data_curation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
b47eb1cb9c8b21a7fd92b61f32f8275b9599836f
|
|
train_39852
| 2026-01-01T00:00:00
|
Multimodal dev workflows (docs, diagrams, traces)
|
compare
|
expert
|
Task: compare
Topic: Multimodal dev workflows (docs, diagrams, traces)
Difficulty: expert
Target language: TypeScript
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "TypeScript",
"developer_needs": [
"reproducibility",
"tests_are_truth",
"documentation",
"governance"
],
"moe_experts": [
"security_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
13c24bf7557a0d2b5ba2d48edd4249d135d424eb
|
|
train_39853
| 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: SQL
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[] |
{
"target_language": "SQL",
"developer_needs": [
"tests_are_truth",
"reproducibility",
"governance",
"documentation"
],
"moe_experts": [
"data_curation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
ce580ea147a4bbc5231d21b24e4b7495dc059b6c
|
|
train_39854
| 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: 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": "Go",
"developer_needs": [
"cost_latency_tradeoffs",
"documentation",
"reproducibility",
"tests_are_truth"
],
"moe_experts": [
"evaluation_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
d02ce4db000e2b49689176bbc97f34540d457587
|
|
train_39855
| 2026-01-01T00:00:00
|
SWE-bench style real-repo evaluation
|
patch_diff
|
intermediate
|
Task: patch_diff
Topic: SWE-bench style real-repo evaluation
Difficulty: intermediate
Target language: Go
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Patch (diff-style):
```diff
- if x == 0:
- return 1/x
+ if x == 0:
+ raise ValueError('division by zero')
```
Acceptance:
- Tests pass
- No new regressions
|
[] |
{
"target_language": "Go",
"developer_needs": [
"reproducibility",
"auditability",
"documentation",
"governance"
],
"moe_experts": [
"governance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
856cd150b84836264469c2704defe8ba172bc2f0
|
|
train_39856
| 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: SQL
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "SQL",
"developer_needs": [
"governance",
"security_gates",
"documentation",
"ci_integration"
],
"moe_experts": [
"coding_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
ded02dd70830ef1194988eb1bb375e8b1c04b4b8
|
|
train_39857
| 2026-01-01T00:00:00
|
Multimodal dev workflows (docs, diagrams, traces)
|
review
|
advanced
|
Task: review
Topic: Multimodal dev workflows (docs, diagrams, traces)
Difficulty: advanced
Target language: Go
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Review: correctness, security, performance, governance
|
[] |
{
"target_language": "Go",
"developer_needs": [
"reproducibility",
"evaluation_metrics",
"documentation",
"repo_scale_reasoning"
],
"moe_experts": [
"security_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
c8c7a96f9b4323c84ef3bf91231777f90accab1d
|
|
train_39858
| 2026-01-01T00:00:00
|
Tool calling, sandboxes, and CI integration
|
data_pipeline
|
intermediate
|
Task: data_pipeline
Topic: Tool calling, sandboxes, and CI integration
Difficulty: intermediate
Target language: Rust
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
|
[] |
{
"target_language": "Rust",
"developer_needs": [
"tooling",
"ci_integration",
"evaluation_metrics",
"governance"
],
"moe_experts": [
"coding_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
a0b4f921a6ea118f115b2e795e874a3a47921d0c
|
|
train_39859
| 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: SQL
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Patch (diff-style):
```diff
- if x == 0:
- return 1/x
+ if x == 0:
+ raise ValueError('division by zero')
```
Acceptance:
- Tests pass
- No new regressions
|
[] |
{
"target_language": "SQL",
"developer_needs": [
"repo_scale_reasoning",
"auditability",
"tooling",
"cost_latency_tradeoffs"
],
"moe_experts": [
"security_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
aa9b28837c311e5fd00e6b3ac3ed51adf6520405
|
|
train_39860
| 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: SQL
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
|
[
"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",
"security_gates",
"reproducibility",
"auditability"
],
"moe_experts": [
"security_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
fd095c7101a79631125be38d3d44a3ae251176d1
|
|
train_39861
| 2026-01-01T00:00:00
|
Self-improving agents and feedback loops
|
data_pipeline
|
advanced
|
Task: data_pipeline
Topic: Self-improving agents and feedback loops
Difficulty: advanced
Target language: Python
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Python",
"developer_needs": [
"documentation",
"ci_integration",
"reproducibility",
"repo_scale_reasoning"
],
"moe_experts": [
"coding_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
8ea3f19b66f60a5e6a6b9b29027a75aab0f1f22d
|
|
train_39862
| 2026-01-01T00:00:00
|
Self-improving agents and feedback loops
|
explain
|
expert
|
Task: explain
Topic: Self-improving agents and feedback loops
Difficulty: expert
Target language: 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": [
"security_gates",
"tests_are_truth",
"documentation",
"cost_latency_tradeoffs"
],
"moe_experts": [
"security_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
79cbb50b146db0dd4c76f675201087b01c45a38e
|
|
train_39863
| 2026-01-01T00:00:00
|
Extended context and repo-scale understanding
|
failure_analysis
|
intermediate
|
Task: failure_analysis
Topic: Extended context and repo-scale understanding
Difficulty: intermediate
Target language: C#
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
|
[] |
{
"target_language": "C#",
"developer_needs": [
"evaluation_metrics",
"tests_are_truth",
"ci_integration",
"cost_latency_tradeoffs"
],
"moe_experts": [
"security_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
ccbb92ac8b8056c09f743565d8eb7dceb74bd0df
|
|
train_39864
| 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: 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.
Loop: Plan → Edit → Test → Reflect → Human gate
|
[] |
{
"target_language": "SQL",
"developer_needs": [
"reproducibility",
"cost_latency_tradeoffs",
"evaluation_metrics",
"security_gates"
],
"moe_experts": [
"data_curation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
13e65a20431a67b1a5cc630804928fef1b87f87a
|
|
train_39865
| 2026-01-01T00:00:00
|
Code-specialized model families and sizing tradeoffs
|
code
|
expert
|
Task: code
Topic: Code-specialized model families and sizing tradeoffs
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.
Design with risks, metrics, acceptance criteria
|
[] |
{
"target_language": "TypeScript",
"developer_needs": [
"auditability",
"security_gates",
"reproducibility",
"evaluation_metrics"
],
"moe_experts": [
"agentic_systems_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
af3315f73e52318ae09784a957c85a36ffd0c4c2
|
|
train_39866
| 2026-01-01T00:00:00
|
Tool calling, sandboxes, and CI integration
|
design
|
advanced
|
Task: design
Topic: Tool calling, sandboxes, and CI integration
Difficulty: advanced
Target language: Python
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[] |
{
"target_language": "Python",
"developer_needs": [
"tests_are_truth",
"security_gates",
"repo_scale_reasoning",
"documentation"
],
"moe_experts": [
"governance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
dd3ae17605b0c17608667cf356c3f7c97d44cc08
|
|
train_39867
| 2026-01-01T00:00:00
|
Reasoning-first coding models and tunable deliberation
|
agent_loop
|
intermediate
|
Task: agent_loop
Topic: Reasoning-first coding models and tunable deliberation
Difficulty: intermediate
Target language: SQL
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "SQL",
"developer_needs": [
"security_gates",
"repo_scale_reasoning",
"cost_latency_tradeoffs",
"tests_are_truth"
],
"moe_experts": [
"evaluation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
eb3362a7bcfc9d866b44b804460e3762f5311820
|
|
train_39868
| 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: Go
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Review: correctness, security, performance, governance
|
[] |
{
"target_language": "Go",
"developer_needs": [
"governance",
"auditability",
"repo_scale_reasoning",
"cost_latency_tradeoffs"
],
"moe_experts": [
"agentic_systems_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
c60a044fa4bbd720e897a0644dee29baf1e9b6c9
|
|
train_39869
| 2026-01-01T00:00:00
|
Model merging, distillation, and continued pretraining
|
explain
|
advanced
|
Task: explain
Topic: Model merging, distillation, and continued pretraining
Difficulty: advanced
Target language: Rust
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Rust",
"developer_needs": [
"auditability",
"tooling",
"documentation",
"governance"
],
"moe_experts": [
"security_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
1e17ee16e39a02049524db9a6fafda50b1c43d02
|
|
train_39870
| 2026-01-01T00:00:00
|
Reasoning-first coding models and tunable deliberation
|
agent_loop
|
advanced
|
Task: agent_loop
Topic: Reasoning-first coding models and tunable deliberation
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.
Loop: Plan → Edit → Test → Reflect → Human gate
|
[] |
{
"target_language": "Go",
"developer_needs": [
"evaluation_metrics",
"reproducibility",
"tooling",
"repo_scale_reasoning"
],
"moe_experts": [
"evaluation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
9116679843bb169333a3adf9e5a906034628940b
|
|
train_39871
| 2026-01-01T00:00:00
|
Code-specialized model families and sizing tradeoffs
|
agent_loop
|
intermediate
|
Task: agent_loop
Topic: Code-specialized model families and sizing tradeoffs
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.
Loop: Plan → Edit → Test → Reflect → Human gate
|
[] |
{
"target_language": "C#",
"developer_needs": [
"tests_are_truth",
"tooling",
"cost_latency_tradeoffs",
"reproducibility"
],
"moe_experts": [
"coding_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
0339b4a5b9127e65ee9d60224c523e09d1472464
|
|
train_39872
| 2026-01-01T00:00:00
|
Model merging, distillation, and continued pretraining
|
compare
|
expert
|
Task: compare
Topic: Model merging, distillation, and continued pretraining
Difficulty: expert
Target language: Bash
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Bash",
"developer_needs": [
"ci_integration",
"documentation",
"auditability",
"repo_scale_reasoning"
],
"moe_experts": [
"coding_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
ad4140d457f05aeb113a4e89b0807ef0b4dc70dc
|
|
train_39873
| 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: Python
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[] |
{
"target_language": "Python",
"developer_needs": [
"repo_scale_reasoning",
"ci_integration",
"cost_latency_tradeoffs",
"evaluation_metrics"
],
"moe_experts": [
"evaluation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
3462c392b3f9cf70cab0b603d8a9d499a3c1e1be
|
|
train_39874
| 2026-01-01T00:00:00
|
Multimodal dev workflows (docs, diagrams, traces)
|
design
|
advanced
|
Task: design
Topic: Multimodal dev workflows (docs, diagrams, traces)
Difficulty: advanced
Target language: 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": [
"tooling",
"reproducibility",
"repo_scale_reasoning",
"cost_latency_tradeoffs"
],
"moe_experts": [
"governance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
864952cd658d46adccdbe43246317f95f7ccc6f6
|
|
train_39875
| 2026-01-01T00:00:00
|
Dataset curation pipelines (filter, dedupe, quality)
|
review
|
expert
|
Task: review
Topic: Dataset curation pipelines (filter, dedupe, quality)
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.
Review: correctness, security, performance, governance
|
[] |
{
"target_language": "TypeScript",
"developer_needs": [
"evaluation_metrics",
"tests_are_truth",
"repo_scale_reasoning",
"documentation"
],
"moe_experts": [
"coding_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
44eca9414ba16b00f342b649141a149223afbadc
|
|
train_39876
| 2026-01-01T00:00:00
|
Code-specialized model families and sizing tradeoffs
|
review
|
advanced
|
Task: review
Topic: Code-specialized model families and sizing tradeoffs
Difficulty: advanced
Target language: JavaScript
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Review: correctness, security, performance, governance
|
[] |
{
"target_language": "JavaScript",
"developer_needs": [
"evaluation_metrics",
"security_gates",
"tooling",
"reproducibility"
],
"moe_experts": [
"agentic_systems_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
9083fda08ad7d144521ce9123119dfe0afd72879
|
|
train_39877
| 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: Rust
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
|
[] |
{
"target_language": "Rust",
"developer_needs": [
"governance",
"ci_integration",
"tests_are_truth",
"reproducibility"
],
"moe_experts": [
"security_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
bb09ab70ad1b2e40a622c4626630b7cff58f5714
|
|
train_39878
| 2026-01-01T00:00:00
|
Dataset curation pipelines (filter, dedupe, quality)
|
compare
|
expert
|
Task: compare
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: expert
Target language: SQL
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
|
[] |
{
"target_language": "SQL",
"developer_needs": [
"governance",
"tests_are_truth",
"security_gates",
"documentation"
],
"moe_experts": [
"data_curation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
8b59d1bc448e936582d93e2a782a68cdbc4e3068
|
|
train_39879
| 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: 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": "JavaScript",
"developer_needs": [
"tests_are_truth",
"governance",
"evaluation_metrics",
"ci_integration"
],
"moe_experts": [
"agentic_systems_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
14a046ce8d8ecf010decbb66e61ac235e1aeffcd
|
|
train_39880
| 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: 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": "TypeScript",
"developer_needs": [
"auditability",
"repo_scale_reasoning",
"evaluation_metrics",
"governance"
],
"moe_experts": [
"agentic_systems_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
8a87daa32bd1f37fad71cf767e4a5e9d2c079400
|
|
train_39881
| 2026-01-01T00:00:00
|
Model merging, distillation, and continued pretraining
|
eval
|
intermediate
|
Task: eval
Topic: Model merging, distillation, and continued pretraining
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": [
"cost_latency_tradeoffs",
"ci_integration",
"documentation",
"reproducibility"
],
"moe_experts": [
"security_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
015a5ae8e239b7fd9b69c6bf5cef8df703795ec7
|
|
train_39882
| 2026-01-01T00:00:00
|
SWE-bench style real-repo evaluation
|
review
|
expert
|
Task: review
Topic: SWE-bench style real-repo evaluation
Difficulty: expert
Target language: 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": [
"tests_are_truth",
"ci_integration",
"security_gates",
"evaluation_metrics"
],
"moe_experts": [
"governance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
7272158fc3f0ff15be517fbc1136ec8287de8ccf
|
|
train_39883
| 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": [
"reproducibility",
"tooling",
"cost_latency_tradeoffs",
"ci_integration"
],
"moe_experts": [
"evaluation_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
738e59870d9cec94390676c2fc93e1a423b97622
|
|
train_39884
| 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: 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
|
[] |
{
"target_language": "Java",
"developer_needs": [
"tests_are_truth",
"security_gates",
"evaluation_metrics",
"reproducibility"
],
"moe_experts": [
"evaluation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
d2e5924673b2628d1cd839dc14300b1db8582d96
|
|
train_39885
| 2026-01-01T00:00:00
|
Dataset curation pipelines (filter, dedupe, quality)
|
agent_loop
|
intermediate
|
Task: agent_loop
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: intermediate
Target language: Bash
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
|
[] |
{
"target_language": "Bash",
"developer_needs": [
"security_gates",
"documentation",
"repo_scale_reasoning",
"auditability"
],
"moe_experts": [
"governance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
18e03ecd3a304fb80195b22b67b8b62270bfb9e4
|
|
train_39886
| 2026-01-01T00:00:00
|
Code-specialized model families and sizing tradeoffs
|
design
|
intermediate
|
Task: design
Topic: Code-specialized model families and sizing tradeoffs
Difficulty: intermediate
Target language: SQL
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[] |
{
"target_language": "SQL",
"developer_needs": [
"reproducibility",
"evaluation_metrics",
"tooling",
"governance"
],
"moe_experts": [
"security_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
1df2c76ada07607c8ec9e17d909c6623bab565f2
|
|
train_39887
| 2026-01-01T00:00:00
|
Mixture-of-Experts (MoE) for code
|
code
|
intermediate
|
Task: code
Topic: Mixture-of-Experts (MoE) for code
Difficulty: intermediate
Target language: Python
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Scaffold:
```python
def agent_loop(plan, edit, test, issue, max_iters=4):
history = []
p = plan(issue)
for _ in range(max_iters):
patch = edit(issue, p)
ok, report = test(patch)
history.append({"plan": p, "ok": ok})
if ok:
return patch, history
p = p + " | refine"
return patch, history
```
|
[] |
{
"target_language": "Python",
"developer_needs": [
"documentation",
"security_gates",
"tooling",
"evaluation_metrics"
],
"moe_experts": [
"agentic_systems_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
3f1cc1f6b1de1048d3a0476b1fbbdbbb0ad75aff
|
|
train_39888
| 2026-01-01T00:00:00
|
Model merging, distillation, and continued pretraining
|
patch_diff
|
expert
|
Task: patch_diff
Topic: Model merging, distillation, and continued pretraining
Difficulty: expert
Target language: TypeScript
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Patch (diff-style):
```diff
- if x == 0:
- return 1/x
+ if x == 0:
+ raise ValueError('division by zero')
```
Acceptance:
- Tests pass
- No new regressions
|
[] |
{
"target_language": "TypeScript",
"developer_needs": [
"tests_are_truth",
"tooling",
"cost_latency_tradeoffs",
"security_gates"
],
"moe_experts": [
"security_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
1fce3fd40fb2271c83baab7a401775ad62ac43e3
|
|
train_39889
| 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: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "C#",
"developer_needs": [
"tooling",
"tests_are_truth",
"documentation",
"security_gates"
],
"moe_experts": [
"agentic_systems_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
ee9c2efa0cad28cc1c8d8036bcfc956254ce75ce
|
|
train_39890
| 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: SQL
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "SQL",
"developer_needs": [
"tooling",
"ci_integration",
"reproducibility",
"auditability"
],
"moe_experts": [
"governance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
3114aace7c00041594bf28407d9f3b107a44f87c
|
|
train_39891
| 2026-01-01T00:00:00
|
Governance, provenance, and licensing for code data
|
code
|
expert
|
Task: code
Topic: Governance, provenance, and licensing for code data
Difficulty: expert
Target language: 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": [
"governance",
"tests_are_truth",
"repo_scale_reasoning",
"evaluation_metrics"
],
"moe_experts": [
"coding_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
86182081707b47e70fcac470ea12d3264f450c82
|
|
train_39892
| 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: 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",
"reproducibility",
"evaluation_metrics",
"ci_integration"
],
"moe_experts": [
"data_curation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
c73668d83f0d10ae032e52bfd486fd78a6372627
|
|
train_39893
| 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: Rust
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
|
[] |
{
"target_language": "Rust",
"developer_needs": [
"tooling",
"reproducibility",
"governance",
"evaluation_metrics"
],
"moe_experts": [
"security_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
fadfcbf18bc8b69a90944f43d6551da69cdec018
|
|
train_39894
| 2026-01-01T00:00:00
|
Self-improving agents and feedback loops
|
failure_analysis
|
intermediate
|
Task: failure_analysis
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.
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": [
"cost_latency_tradeoffs",
"security_gates",
"repo_scale_reasoning",
"ci_integration"
],
"moe_experts": [
"evaluation_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
24e44acb884ea7669af23150b5064e3218b08d5b
|
|
train_39895
| 2026-01-01T00:00:00
|
Agentic coding systems (plan→edit→test→reflect)
|
eval
|
advanced
|
Task: eval
Topic: Agentic coding systems (plan→edit→test→reflect)
Difficulty: advanced
Target language: Go
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
|
[] |
{
"target_language": "Go",
"developer_needs": [
"reproducibility",
"cost_latency_tradeoffs",
"repo_scale_reasoning",
"tooling"
],
"moe_experts": [
"evaluation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
ff05e91a734e30e2d1d79c2ab3b5c73886cc2bd3
|
|
train_39896
| 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: 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": [
"tests_are_truth",
"repo_scale_reasoning",
"governance",
"reproducibility"
],
"moe_experts": [
"coding_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
ff2c967f8def0c9f196dbc1073a1ccf7f249ca0c
|
|
train_39897
| 2026-01-01T00:00:00
|
Agentic coding systems (plan→edit→test→reflect)
|
review
|
expert
|
Task: review
Topic: Agentic coding systems (plan→edit→test→reflect)
Difficulty: expert
Target language: JavaScript
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Review: correctness, security, performance, governance
|
[] |
{
"target_language": "JavaScript",
"developer_needs": [
"evaluation_metrics",
"governance",
"repo_scale_reasoning",
"security_gates"
],
"moe_experts": [
"evaluation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
db2fc90de050ec00f8eed00a0ac0dd7781a501c4
|
|
train_39898
| 2026-01-01T00:00:00
|
Secure code generation and policy gates
|
compare
|
intermediate
|
Task: compare
Topic: Secure code generation and policy gates
Difficulty: intermediate
Target language: 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
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Bash",
"developer_needs": [
"auditability",
"evaluation_metrics",
"reproducibility",
"cost_latency_tradeoffs"
],
"moe_experts": [
"evaluation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
c52ba51cf9742672c691660acb9a14afb3d8267e
|
|
train_39899
| 2026-01-01T00:00:00
|
Secure code generation and policy gates
|
patch_diff
|
advanced
|
Task: patch_diff
Topic: Secure code generation and policy gates
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.
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": "JavaScript",
"developer_needs": [
"documentation",
"ci_integration",
"tests_are_truth",
"evaluation_metrics"
],
"moe_experts": [
"security_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
785ac4b5bf35571ef04d6d28d4eff824a75410fb
|
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