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2026-01-01 00:00:00
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train_44100
| 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: 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": [
"repo_scale_reasoning",
"cost_latency_tradeoffs",
"auditability",
"security_gates"
],
"moe_experts": [
"evaluation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
79effe8d8f23e2e4b7662cdf2ae086dc899bcf05
|
|
train_44101
| 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: Python
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Patch (diff-style):
```diff
- if x == 0:
- return 1/x
+ if x == 0:
+ raise ValueError('division by zero')
```
Acceptance:
- Tests pass
- No new regressions
|
[
"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",
"tests_are_truth",
"tooling"
],
"moe_experts": [
"evaluation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
0a6be66bf5152b2a52f1b2f3c83067cb1e6ad9f7
|
|
train_44102
| 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: 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": [
"governance",
"security_gates",
"ci_integration",
"tooling"
],
"moe_experts": [
"performance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
3775a586e1096557ae8e709af7e5f197ead18d17
|
|
train_44103
| 2026-01-01T00:00:00
|
Multimodal dev workflows (docs, diagrams, traces)
|
compare
|
intermediate
|
Task: compare
Topic: Multimodal dev workflows (docs, diagrams, traces)
Difficulty: intermediate
Target language: Bash
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
|
[] |
{
"target_language": "Bash",
"developer_needs": [
"repo_scale_reasoning",
"security_gates",
"tooling",
"governance"
],
"moe_experts": [
"coding_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
589fa069e9fc150bca03ff820d3f29a05972090a
|
|
train_44104
| 2026-01-01T00:00:00
|
Self-improving agents and feedback loops
|
design
|
expert
|
Task: design
Topic: Self-improving agents and feedback loops
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.
Design with risks, metrics, acceptance criteria
|
[] |
{
"target_language": "SQL",
"developer_needs": [
"security_gates",
"tests_are_truth",
"repo_scale_reasoning",
"evaluation_metrics"
],
"moe_experts": [
"evaluation_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
09b705f8b75dd5d411c21394691d79e230692c86
|
|
train_44105
| 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: 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",
"governance",
"ci_integration"
],
"moe_experts": [
"agentic_systems_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
4607894d9b7a300f55d78df4c8aed7a6b39fb575
|
|
train_44106
| 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: TypeScript
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Patch (diff-style):
```diff
- if x == 0:
- return 1/x
+ if x == 0:
+ raise ValueError('division by zero')
```
Acceptance:
- Tests pass
- No new regressions
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "TypeScript",
"developer_needs": [
"auditability",
"security_gates",
"evaluation_metrics",
"documentation"
],
"moe_experts": [
"data_curation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
62bdb40fb861a019bee08c2564234fa5e3dfdd0a
|
|
train_44107
| 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: 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
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Go",
"developer_needs": [
"governance",
"auditability",
"evaluation_metrics",
"documentation"
],
"moe_experts": [
"coding_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
1d5942a4b616b0830c20cedc655bd8b5adad8d93
|
|
train_44108
| 2026-01-01T00:00:00
|
SWE-bench style real-repo evaluation
|
design
|
expert
|
Task: design
Topic: SWE-bench style real-repo evaluation
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.
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": [
"documentation",
"evaluation_metrics",
"tests_are_truth",
"ci_integration"
],
"moe_experts": [
"coding_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
62cb8b9a9bbd185da8f87869018dc95dea179223
|
|
train_44109
| 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: 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
|
[] |
{
"target_language": "SQL",
"developer_needs": [
"governance",
"ci_integration",
"tests_are_truth",
"reproducibility"
],
"moe_experts": [
"governance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
fc9932597b0cdfda9a74234231a93d842045b5cf
|
|
train_44110
| 2026-01-01T00:00:00
|
Agentic coding systems (plan→edit→test→reflect)
|
compare
|
intermediate
|
Task: compare
Topic: Agentic coding systems (plan→edit→test→reflect)
Difficulty: intermediate
Target language: Java
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
|
[
"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",
"governance",
"evaluation_metrics",
"tests_are_truth"
],
"moe_experts": [
"evaluation_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
0bb1cb3b4d3af417ab7d74585ce04dc1b0f38d19
|
|
train_44111
| 2026-01-01T00:00:00
|
Latency, cost, and reliability optimization
|
code
|
expert
|
Task: code
Topic: Latency, cost, and reliability optimization
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": [
"reproducibility",
"repo_scale_reasoning",
"security_gates",
"governance"
],
"moe_experts": [
"agentic_systems_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
8ebc897824efa75147612af6472b0b63e0bfefdb
|
|
train_44112
| 2026-01-01T00:00:00
|
Model merging, distillation, and continued pretraining
|
agent_loop
|
intermediate
|
Task: agent_loop
Topic: Model merging, distillation, and continued pretraining
Difficulty: intermediate
Target language: Java
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
|
[] |
{
"target_language": "Java",
"developer_needs": [
"tooling",
"security_gates",
"auditability",
"governance"
],
"moe_experts": [
"coding_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
bdeefee183582262f88206a4e347b27d69f2e5d8
|
|
train_44113
| 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: 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": "TypeScript",
"developer_needs": [
"tooling",
"auditability",
"governance",
"documentation"
],
"moe_experts": [
"performance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
6e75f278064879c5219744dbf586b3e1dd5e6bd3
|
|
train_44114
| 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: Java
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
|
[] |
{
"target_language": "Java",
"developer_needs": [
"tooling",
"ci_integration",
"security_gates",
"cost_latency_tradeoffs"
],
"moe_experts": [
"governance_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
758412a33208cc61340f085db01f21e30c9cef05
|
|
train_44115
| 2026-01-01T00:00:00
|
Model merging, distillation, and continued pretraining
|
explain
|
advanced
|
Task: explain
Topic: Model merging, distillation, and continued pretraining
Difficulty: advanced
Target language: C#
Context: 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": [
"documentation",
"tooling",
"tests_are_truth",
"governance"
],
"moe_experts": [
"evaluation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
d504d7474dfa4ca7343e2d1ced550caa9647c4b6
|
|
train_44116
| 2026-01-01T00:00:00
|
Agentic coding systems (plan→edit→test→reflect)
|
code
|
intermediate
|
Task: code
Topic: Agentic coding systems (plan→edit→test→reflect)
Difficulty: intermediate
Target language: Python
Context: 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.
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": [
"evaluation_metrics",
"documentation",
"auditability",
"cost_latency_tradeoffs"
],
"moe_experts": [
"data_curation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
9c927cafaa15686c965761eeee2dc03879d6a213
|
|
train_44117
| 2026-01-01T00:00:00
|
Self-improving agents and feedback loops
|
data_pipeline
|
intermediate
|
Task: data_pipeline
Topic: Self-improving agents and feedback loops
Difficulty: intermediate
Target language: Go
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
|
[] |
{
"target_language": "Go",
"developer_needs": [
"tooling",
"security_gates",
"reproducibility",
"auditability"
],
"moe_experts": [
"coding_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
528175710d65be7374506190593b5ea4e41f6155
|
|
train_44118
| 2026-01-01T00:00:00
|
Mixture-of-Experts (MoE) for code
|
data_pipeline
|
intermediate
|
Task: data_pipeline
Topic: Mixture-of-Experts (MoE) for code
Difficulty: intermediate
Target language: Python
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
|
[] |
{
"target_language": "Python",
"developer_needs": [
"reproducibility",
"repo_scale_reasoning",
"auditability",
"cost_latency_tradeoffs"
],
"moe_experts": [
"agentic_systems_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
3007d829e626b963939e0fe33244555974421461
|
|
train_44119
| 2026-01-01T00:00:00
|
Dataset curation pipelines (filter, dedupe, quality)
|
agent_loop
|
advanced
|
Task: agent_loop
Topic: Dataset curation pipelines (filter, dedupe, quality)
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.
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": [
"tooling",
"governance",
"ci_integration",
"documentation"
],
"moe_experts": [
"evaluation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
fe7c7632d1341aecbd7e75354ff10a871eb85454
|
|
train_44120
| 2026-01-01T00:00:00
|
Governance, provenance, and licensing for code data
|
design
|
advanced
|
Task: design
Topic: Governance, provenance, and licensing for code data
Difficulty: advanced
Target language: TypeScript
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[] |
{
"target_language": "TypeScript",
"developer_needs": [
"reproducibility",
"evaluation_metrics",
"repo_scale_reasoning",
"governance"
],
"moe_experts": [
"governance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
8d382fdfcc3b084546be8ec49a912524b21edc6b
|
|
train_44121
| 2026-01-01T00:00:00
|
Extended context and repo-scale understanding
|
agent_loop
|
expert
|
Task: agent_loop
Topic: Extended context and repo-scale understanding
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.
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": [
"cost_latency_tradeoffs",
"security_gates",
"tests_are_truth",
"auditability"
],
"moe_experts": [
"performance_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
fcd5efd991cc902bc4f1cd5710762fe61b05d191
|
|
train_44122
| 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: 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
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Bash",
"developer_needs": [
"reproducibility",
"repo_scale_reasoning",
"security_gates",
"tests_are_truth"
],
"moe_experts": [
"agentic_systems_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
1b0152fc867cb73ce7f0a370c4069462bcf7cbc2
|
|
train_44123
| 2026-01-01T00:00:00
|
Self-improving agents and feedback loops
|
failure_analysis
|
advanced
|
Task: failure_analysis
Topic: Self-improving agents and feedback loops
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.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
|
[] |
{
"target_language": "Java",
"developer_needs": [
"reproducibility",
"repo_scale_reasoning",
"ci_integration",
"security_gates"
],
"moe_experts": [
"coding_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
57abcb1194ef9fc8014bc9b8c30a203b466de7fd
|
|
train_44124
| 2026-01-01T00:00:00
|
Dataset curation pipelines (filter, dedupe, quality)
|
code
|
expert
|
Task: code
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: expert
Target language: Java
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Java",
"developer_needs": [
"ci_integration",
"evaluation_metrics",
"cost_latency_tradeoffs",
"governance"
],
"moe_experts": [
"governance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
6762e79c9a68ea273180876043559ce258666ae3
|
|
train_44125
| 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: 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": [
"cost_latency_tradeoffs",
"evaluation_metrics",
"ci_integration",
"tooling"
],
"moe_experts": [
"performance_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
f5cd521284c498dce77f6b49f132e6489a1b1604
|
|
train_44126
| 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: 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.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
|
[] |
{
"target_language": "C#",
"developer_needs": [
"reproducibility",
"tests_are_truth",
"auditability",
"documentation"
],
"moe_experts": [
"evaluation_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
9e8340b7c056f9fb55a075b9ed42859c5e966591
|
|
train_44127
| 2026-01-01T00:00:00
|
Latency, cost, and reliability optimization
|
failure_analysis
|
advanced
|
Task: failure_analysis
Topic: Latency, cost, and reliability optimization
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.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Java",
"developer_needs": [
"governance",
"tests_are_truth",
"security_gates",
"ci_integration"
],
"moe_experts": [
"coding_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
27ade62b1a4083f062ce61f9254371c3cb96794c
|
|
train_44128
| 2026-01-01T00:00:00
|
Agentic coding systems (plan→edit→test→reflect)
|
explain
|
advanced
|
Task: explain
Topic: Agentic coding systems (plan→edit→test→reflect)
Difficulty: advanced
Target language: TypeScript
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "TypeScript",
"developer_needs": [
"repo_scale_reasoning",
"tooling",
"governance",
"cost_latency_tradeoffs"
],
"moe_experts": [
"agentic_systems_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
73d53c9590ee4deeac43dc281a4d088c8effcf82
|
|
train_44129
| 2026-01-01T00:00:00
|
Dataset curation pipelines (filter, dedupe, quality)
|
code
|
intermediate
|
Task: code
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: intermediate
Target language: Rust
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[] |
{
"target_language": "Rust",
"developer_needs": [
"security_gates",
"auditability",
"evaluation_metrics",
"tooling"
],
"moe_experts": [
"evaluation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
21498f064008547e0b14227aa55344e8f72f8e62
|
|
train_44130
| 2026-01-01T00:00:00
|
Secure code generation and policy gates
|
eval
|
expert
|
Task: eval
Topic: Secure code generation and policy gates
Difficulty: expert
Target language: Bash
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
|
[] |
{
"target_language": "Bash",
"developer_needs": [
"repo_scale_reasoning",
"governance",
"documentation",
"auditability"
],
"moe_experts": [
"coding_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
77db71fddf5bde859f7b4bc4a14e3ead264b07e0
|
|
train_44131
| 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: 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.
Eval:
pass@k, time-to-green, regressions, diff size
|
[] |
{
"target_language": "SQL",
"developer_needs": [
"security_gates",
"cost_latency_tradeoffs",
"evaluation_metrics",
"tests_are_truth"
],
"moe_experts": [
"performance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
4ce247574c925702f8ddf7b324b0742d4ada6b0d
|
|
train_44132
| 2026-01-01T00:00:00
|
Latency, cost, and reliability optimization
|
review
|
advanced
|
Task: review
Topic: Latency, cost, and reliability optimization
Difficulty: advanced
Target language: Go
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
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": [
"tooling",
"ci_integration",
"evaluation_metrics",
"reproducibility"
],
"moe_experts": [
"agentic_systems_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
0d582a85c87f3e200c55fcc2a61ad4ab710dd0b5
|
|
train_44133
| 2026-01-01T00:00:00
|
Secure code generation and policy gates
|
agent_loop
|
intermediate
|
Task: agent_loop
Topic: Secure code generation and policy gates
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.
Loop: Plan → Edit → Test → Reflect → Human gate
|
[] |
{
"target_language": "Go",
"developer_needs": [
"documentation",
"security_gates",
"reproducibility",
"cost_latency_tradeoffs"
],
"moe_experts": [
"data_curation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
3b28e8a8367da16895aa81705470b5fd21ba33f0
|
|
train_44134
| 2026-01-01T00:00:00
|
Code-specialized model families and sizing tradeoffs
|
patch_diff
|
expert
|
Task: patch_diff
Topic: Code-specialized model families and sizing tradeoffs
Difficulty: expert
Target language: 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": [
"tooling",
"cost_latency_tradeoffs",
"evaluation_metrics",
"reproducibility"
],
"moe_experts": [
"evaluation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
631eebc58e8484db95cba88b3b4ab2a14a0171f4
|
|
train_44135
| 2026-01-01T00:00:00
|
SWE-bench style real-repo evaluation
|
explain
|
expert
|
Task: explain
Topic: SWE-bench style real-repo evaluation
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
|
[] |
{
"target_language": "TypeScript",
"developer_needs": [
"repo_scale_reasoning",
"tests_are_truth",
"reproducibility",
"documentation"
],
"moe_experts": [
"security_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
2e2ed6cb2f0554868c148743af3783c619729d20
|
|
train_44136
| 2026-01-01T00:00:00
|
Model merging, distillation, and continued pretraining
|
failure_analysis
|
expert
|
Task: failure_analysis
Topic: Model merging, distillation, and continued pretraining
Difficulty: expert
Target language: Python
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
|
[] |
{
"target_language": "Python",
"developer_needs": [
"cost_latency_tradeoffs",
"auditability",
"ci_integration",
"reproducibility"
],
"moe_experts": [
"coding_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
c5ff58f871f6f73dbf6750234a5fce9c6cb0fc85
|
|
train_44137
| 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: 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.
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",
"ci_integration",
"documentation",
"auditability"
],
"moe_experts": [
"performance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
a8ed8cf037d33d9d36ab8d540c63bda0200297e1
|
|
train_44138
| 2026-01-01T00:00:00
|
Dataset curation pipelines (filter, dedupe, quality)
|
explain
|
expert
|
Task: explain
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: expert
Target language: 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",
"tests_are_truth",
"security_gates",
"auditability"
],
"moe_experts": [
"evaluation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
bab7cd3b1aacb4de1e9a5e47155856b54291671f
|
|
train_44139
| 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: 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",
"cost_latency_tradeoffs",
"security_gates",
"reproducibility"
],
"moe_experts": [
"security_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
e3441b76da53ef844eefe3cf630a34d3bbd8ca84
|
|
train_44140
| 2026-01-01T00:00:00
|
Latency, cost, and reliability optimization
|
compare
|
intermediate
|
Task: compare
Topic: Latency, cost, and reliability optimization
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.
Compare: capability, cost, latency, reliability
|
[] |
{
"target_language": "SQL",
"developer_needs": [
"cost_latency_tradeoffs",
"documentation",
"security_gates",
"tests_are_truth"
],
"moe_experts": [
"agentic_systems_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
475c4f7094e1c071bf03f48ab3a16bea4e597414
|
|
train_44141
| 2026-01-01T00:00:00
|
SWE-bench style real-repo evaluation
|
compare
|
advanced
|
Task: compare
Topic: SWE-bench style real-repo evaluation
Difficulty: advanced
Target language: 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": [
"documentation",
"tooling",
"security_gates",
"evaluation_metrics"
],
"moe_experts": [
"evaluation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
2d7fa9ab94ad6516fe2af36957b8dcb9bc95f171
|
|
train_44142
| 2026-01-01T00:00:00
|
Extended context and repo-scale understanding
|
eval
|
advanced
|
Task: eval
Topic: Extended context and repo-scale understanding
Difficulty: advanced
Target language: C#
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
|
[] |
{
"target_language": "C#",
"developer_needs": [
"governance",
"repo_scale_reasoning",
"cost_latency_tradeoffs",
"tests_are_truth"
],
"moe_experts": [
"data_curation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
591fb956552f22f601423eadf4872803cd4299f5
|
|
train_44143
| 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: 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": [
"reproducibility",
"governance",
"evaluation_metrics",
"tests_are_truth"
],
"moe_experts": [
"data_curation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
72cde4bb62c0ecfe135382a7ebf4486b79174688
|
|
train_44144
| 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: 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.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
|
[] |
{
"target_language": "C#",
"developer_needs": [
"ci_integration",
"reproducibility",
"evaluation_metrics",
"tests_are_truth"
],
"moe_experts": [
"performance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
c17f1bb9bdeb666191f0fd26c269e04da2038b11
|
|
train_44145
| 2026-01-01T00:00:00
|
Model merging, distillation, and continued pretraining
|
patch_diff
|
intermediate
|
Task: patch_diff
Topic: Model merging, distillation, and continued pretraining
Difficulty: intermediate
Target language: SQL
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Patch (diff-style):
```diff
- if x == 0:
- return 1/x
+ if x == 0:
+ raise ValueError('division by zero')
```
Acceptance:
- Tests pass
- No new regressions
|
[] |
{
"target_language": "SQL",
"developer_needs": [
"evaluation_metrics",
"ci_integration",
"security_gates",
"tests_are_truth"
],
"moe_experts": [
"agentic_systems_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
a7a3031d97220ffdfdd40e4c7032768a14ac83d1
|
|
train_44146
| 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: 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": [
"tooling",
"reproducibility",
"cost_latency_tradeoffs",
"security_gates"
],
"moe_experts": [
"performance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
ff7dab6c092628eaa16c4fc472a3554c171ee420
|
|
train_44147
| 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: 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": [
"documentation",
"tests_are_truth",
"ci_integration",
"reproducibility"
],
"moe_experts": [
"evaluation_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
2000560a3532c59d9e88e3fd110df792183f5237
|
|
train_44148
| 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: 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": [
"reproducibility",
"tests_are_truth",
"ci_integration",
"tooling"
],
"moe_experts": [
"data_curation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
c2a76788effe340e2217b7e443fc236d88857fc4
|
|
train_44149
| 2026-01-01T00:00:00
|
Mixture-of-Experts (MoE) for code
|
eval
|
advanced
|
Task: eval
Topic: Mixture-of-Experts (MoE) for code
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.
Eval:
pass@k, time-to-green, regressions, diff size
|
[] |
{
"target_language": "Python",
"developer_needs": [
"documentation",
"auditability",
"tooling",
"repo_scale_reasoning"
],
"moe_experts": [
"governance_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
d559bf3f91286992d55d6679105f32afcdbd13b4
|
|
train_44150
| 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: SQL
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[
"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",
"governance",
"ci_integration",
"repo_scale_reasoning"
],
"moe_experts": [
"security_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
2ade0c0dcbdc1ee19b9af0e484890f1c3a2399cf
|
|
train_44151
| 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: 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": [
"reproducibility",
"ci_integration",
"repo_scale_reasoning",
"evaluation_metrics"
],
"moe_experts": [
"governance_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
49dc16a4f4f9c1d78ea09524b3fb7c312cb78ddc
|
|
train_44152
| 2026-01-01T00:00:00
|
Dataset curation pipelines (filter, dedupe, quality)
|
data_pipeline
|
advanced
|
Task: data_pipeline
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: advanced
Target language: TypeScript
Context: 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": [
"ci_integration",
"security_gates",
"documentation",
"reproducibility"
],
"moe_experts": [
"security_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
d7accb4d6051e4ec1a92f8b97956351786ddb174
|
|
train_44153
| 2026-01-01T00:00:00
|
Code-specialized model families and sizing tradeoffs
|
failure_analysis
|
advanced
|
Task: failure_analysis
Topic: Code-specialized model families and sizing tradeoffs
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.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
|
[] |
{
"target_language": "TypeScript",
"developer_needs": [
"repo_scale_reasoning",
"ci_integration",
"security_gates",
"tooling"
],
"moe_experts": [
"coding_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
511bb8241930aeb214d399bd67edceb5e2330d15
|
|
train_44154
| 2026-01-01T00:00:00
|
Secure code generation and policy gates
|
data_pipeline
|
expert
|
Task: data_pipeline
Topic: Secure code generation and policy gates
Difficulty: expert
Target language: Python
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
|
[] |
{
"target_language": "Python",
"developer_needs": [
"auditability",
"tooling",
"repo_scale_reasoning",
"governance"
],
"moe_experts": [
"coding_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
635aeffc6f52fdb48fdb948b5ed9af400f572e17
|
|
train_44155
| 2026-01-01T00:00:00
|
Extended context and repo-scale understanding
|
code
|
intermediate
|
Task: code
Topic: Extended context and repo-scale understanding
Difficulty: intermediate
Target language: Go
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[] |
{
"target_language": "Go",
"developer_needs": [
"security_gates",
"reproducibility",
"tests_are_truth",
"governance"
],
"moe_experts": [
"evaluation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
a6b618306205e6534d285fbd95b71942c39acf80
|
|
train_44156
| 2026-01-01T00:00:00
|
Latency, cost, and reliability optimization
|
eval
|
expert
|
Task: eval
Topic: Latency, cost, and reliability optimization
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.
Eval:
pass@k, time-to-green, regressions, diff size
|
[] |
{
"target_language": "Rust",
"developer_needs": [
"tooling",
"tests_are_truth",
"evaluation_metrics",
"repo_scale_reasoning"
],
"moe_experts": [
"coding_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
d5e97295d7aba31b4032027a152d55c8e5bd6f91
|
|
train_44157
| 2026-01-01T00:00:00
|
Tool calling, sandboxes, and CI integration
|
data_pipeline
|
advanced
|
Task: data_pipeline
Topic: Tool calling, sandboxes, and CI integration
Difficulty: advanced
Target language: Go
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Go",
"developer_needs": [
"tests_are_truth",
"documentation",
"security_gates",
"reproducibility"
],
"moe_experts": [
"security_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
aa1db1df4d64f97f3ae6709757f75d686de161b4
|
|
train_44158
| 2026-01-01T00:00:00
|
Self-improving agents and feedback loops
|
compare
|
intermediate
|
Task: compare
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.
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",
"documentation",
"tooling",
"cost_latency_tradeoffs"
],
"moe_experts": [
"governance_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
240a65b05452b964c4566014741d5297f8b2b750
|
|
train_44159
| 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: SQL
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
|
[] |
{
"target_language": "SQL",
"developer_needs": [
"ci_integration",
"security_gates",
"evaluation_metrics",
"cost_latency_tradeoffs"
],
"moe_experts": [
"coding_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
13a20457ca0a09986a23d9be330a9612f2575b86
|
|
train_44160
| 2026-01-01T00:00:00
|
Mixture-of-Experts (MoE) for code
|
design
|
advanced
|
Task: design
Topic: Mixture-of-Experts (MoE) for code
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.
Design with risks, metrics, acceptance criteria
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Go",
"developer_needs": [
"cost_latency_tradeoffs",
"reproducibility",
"ci_integration",
"evaluation_metrics"
],
"moe_experts": [
"performance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
5f4bc176a47124910070f9d3450be12f0f20d966
|
|
train_44161
| 2026-01-01T00:00:00
|
Self-improving agents and feedback loops
|
review
|
advanced
|
Task: review
Topic: Self-improving agents and feedback loops
Difficulty: advanced
Target language: Go
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Review: correctness, security, performance, governance
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Go",
"developer_needs": [
"auditability",
"cost_latency_tradeoffs",
"repo_scale_reasoning",
"ci_integration"
],
"moe_experts": [
"performance_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
f54dad4831a2058bf6a15183187fc24987b7fab4
|
|
train_44162
| 2026-01-01T00:00:00
|
Reasoning-first coding models and tunable deliberation
|
explain
|
expert
|
Task: explain
Topic: Reasoning-first coding models and tunable deliberation
Difficulty: expert
Target language: Java
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[] |
{
"target_language": "Java",
"developer_needs": [
"security_gates",
"tests_are_truth",
"evaluation_metrics",
"documentation"
],
"moe_experts": [
"data_curation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
4db337c377d8ca6ee278b18fec98ea1bae97c79d
|
|
train_44163
| 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: 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
|
[] |
{
"target_language": "SQL",
"developer_needs": [
"auditability",
"repo_scale_reasoning",
"ci_integration",
"tooling"
],
"moe_experts": [
"evaluation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
d9d1841d0c7e2e1b61e956bd5b12844c0d6d5d0c
|
|
train_44164
| 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: 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": [
"cost_latency_tradeoffs",
"documentation",
"repo_scale_reasoning",
"evaluation_metrics"
],
"moe_experts": [
"coding_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
8f3b82c3b46ce5151983fdf71c7c46aa7b245ed4
|
|
train_44165
| 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: 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.
Loop: Plan → Edit → Test → Reflect → Human gate
|
[] |
{
"target_language": "TypeScript",
"developer_needs": [
"auditability",
"cost_latency_tradeoffs",
"governance",
"reproducibility"
],
"moe_experts": [
"governance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
da42d9e0d6df0d76a42a2c768649e99f14acde70
|
|
train_44166
| 2026-01-01T00:00:00
|
Tool calling, sandboxes, and CI integration
|
compare
|
advanced
|
Task: compare
Topic: Tool calling, sandboxes, and CI integration
Difficulty: advanced
Target language: 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": [
"documentation",
"governance",
"tests_are_truth",
"cost_latency_tradeoffs"
],
"moe_experts": [
"evaluation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
3ed9f3598c4379cbefcf71c698e79591e2ea5b44
|
|
train_44167
| 2026-01-01T00:00:00
|
Code-specialized model families and sizing tradeoffs
|
design
|
advanced
|
Task: design
Topic: Code-specialized model families and sizing tradeoffs
Difficulty: advanced
Target language: C#
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "C#",
"developer_needs": [
"documentation",
"cost_latency_tradeoffs",
"tests_are_truth",
"governance"
],
"moe_experts": [
"coding_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
5891b30153211125ea811bb0460c83c6b62935ee
|
|
train_44168
| 2026-01-01T00:00:00
|
SWE-bench style real-repo evaluation
|
data_pipeline
|
intermediate
|
Task: data_pipeline
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.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
|
[] |
{
"target_language": "C#",
"developer_needs": [
"security_gates",
"documentation",
"ci_integration",
"reproducibility"
],
"moe_experts": [
"performance_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
d5dc29d3ed1172d9d19eb767f53857f71d749b84
|
|
train_44169
| 2026-01-01T00:00:00
|
Agentic coding systems (plan→edit→test→reflect)
|
failure_analysis
|
intermediate
|
Task: failure_analysis
Topic: Agentic coding systems (plan→edit→test→reflect)
Difficulty: intermediate
Target language: TypeScript
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "TypeScript",
"developer_needs": [
"tests_are_truth",
"security_gates",
"auditability",
"documentation"
],
"moe_experts": [
"data_curation_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
d9f19113b3d0cc319b9a4226c9b20f35a8b6e700
|
|
train_44170
| 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: C#
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Review: correctness, security, performance, governance
|
[] |
{
"target_language": "C#",
"developer_needs": [
"tests_are_truth",
"cost_latency_tradeoffs",
"reproducibility",
"security_gates"
],
"moe_experts": [
"governance_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
6c445b07747f4052d15bc3fa4fc7ed14ba62aef4
|
|
train_44171
| 2026-01-01T00:00:00
|
Agentic coding systems (plan→edit→test→reflect)
|
failure_analysis
|
intermediate
|
Task: failure_analysis
Topic: Agentic coding systems (plan→edit→test→reflect)
Difficulty: intermediate
Target language: 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": [
"repo_scale_reasoning",
"cost_latency_tradeoffs",
"governance",
"reproducibility"
],
"moe_experts": [
"performance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
fb91e9cc17b75d690bdc40473808ef118719e355
|
|
train_44172
| 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: 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.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
|
[] |
{
"target_language": "Java",
"developer_needs": [
"repo_scale_reasoning",
"tests_are_truth",
"security_gates",
"cost_latency_tradeoffs"
],
"moe_experts": [
"coding_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
38a6fee21d5cc91b251982d8332720eaaf2bc9c5
|
|
train_44173
| 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: Bash
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
|
[] |
{
"target_language": "Bash",
"developer_needs": [
"security_gates",
"evaluation_metrics",
"governance",
"ci_integration"
],
"moe_experts": [
"performance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
b9ca11d22128e41dd9292191a499d3b22561ab71
|
|
train_44174
| 2026-01-01T00:00:00
|
Agentic coding systems (plan→edit→test→reflect)
|
explain
|
expert
|
Task: explain
Topic: Agentic coding systems (plan→edit→test→reflect)
Difficulty: expert
Target language: 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
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Bash",
"developer_needs": [
"documentation",
"governance",
"ci_integration",
"repo_scale_reasoning"
],
"moe_experts": [
"evaluation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
9b0c6c05e4c44a30ec17ff5a165782f7d2587a29
|
|
train_44175
| 2026-01-01T00:00:00
|
SWE-bench style real-repo evaluation
|
agent_loop
|
expert
|
Task: agent_loop
Topic: SWE-bench style real-repo evaluation
Difficulty: expert
Target language: Bash
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Bash",
"developer_needs": [
"tests_are_truth",
"documentation",
"security_gates",
"cost_latency_tradeoffs"
],
"moe_experts": [
"data_curation_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
0cbda5b5948afb982797e8143043b1f34d086d61
|
|
train_44176
| 2026-01-01T00:00:00
|
Latency, cost, and reliability optimization
|
code
|
advanced
|
Task: code
Topic: Latency, cost, and reliability optimization
Difficulty: advanced
Target language: Go
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[] |
{
"target_language": "Go",
"developer_needs": [
"documentation",
"tooling",
"tests_are_truth",
"repo_scale_reasoning"
],
"moe_experts": [
"governance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
c1ed93264bf4fdfe138d0c4f879f0f1a363e246b
|
|
train_44177
| 2026-01-01T00:00:00
|
Model merging, distillation, and continued pretraining
|
compare
|
advanced
|
Task: compare
Topic: Model merging, distillation, and continued pretraining
Difficulty: advanced
Target language: TypeScript
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
|
[] |
{
"target_language": "TypeScript",
"developer_needs": [
"tooling",
"repo_scale_reasoning",
"security_gates",
"reproducibility"
],
"moe_experts": [
"data_curation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
08f24d1126f06b866a35a3c041765c46b1a648dc
|
|
train_44178
| 2026-01-01T00:00:00
|
SWE-bench style real-repo evaluation
|
compare
|
expert
|
Task: compare
Topic: SWE-bench style real-repo evaluation
Difficulty: expert
Target language: TypeScript
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
|
[] |
{
"target_language": "TypeScript",
"developer_needs": [
"auditability",
"reproducibility",
"evaluation_metrics",
"security_gates"
],
"moe_experts": [
"coding_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
afc494647434a93eae23e35f324087de431457d8
|
|
train_44179
| 2026-01-01T00:00:00
|
Self-improving agents and feedback loops
|
eval
|
intermediate
|
Task: eval
Topic: Self-improving agents and feedback loops
Difficulty: intermediate
Target language: Rust
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Rust",
"developer_needs": [
"tests_are_truth",
"documentation",
"repo_scale_reasoning",
"security_gates"
],
"moe_experts": [
"evaluation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
ad9ca42d6a7fdeb41c8156d243ec6d9a4bcf010d
|
|
train_44180
| 2026-01-01T00:00:00
|
Latency, cost, and reliability optimization
|
failure_analysis
|
expert
|
Task: failure_analysis
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.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
|
[] |
{
"target_language": "TypeScript",
"developer_needs": [
"repo_scale_reasoning",
"reproducibility",
"cost_latency_tradeoffs",
"ci_integration"
],
"moe_experts": [
"governance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
4befb2c4376feaaad5418298be9fde7d3eba1ca0
|
|
train_44181
| 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: 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": "Bash",
"developer_needs": [
"auditability",
"evaluation_metrics",
"reproducibility",
"cost_latency_tradeoffs"
],
"moe_experts": [
"evaluation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
38e75bec6fceace823d7d0acf78cf8272d0384de
|
|
train_44182
| 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: 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.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
|
[] |
{
"target_language": "Java",
"developer_needs": [
"governance",
"documentation",
"ci_integration",
"tests_are_truth"
],
"moe_experts": [
"performance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
3e2281e720cb845a86b2f4f87ffeaea3304595b3
|
|
train_44183
| 2026-01-01T00:00:00
|
Extended context and repo-scale understanding
|
agent_loop
|
intermediate
|
Task: agent_loop
Topic: Extended context and repo-scale understanding
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.
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": [
"tests_are_truth",
"tooling",
"documentation",
"auditability"
],
"moe_experts": [
"evaluation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
577230705a404d0a3d095e6941524c463c377f1d
|
|
train_44184
| 2026-01-01T00:00:00
|
Governance, provenance, and licensing for code data
|
patch_diff
|
intermediate
|
Task: patch_diff
Topic: Governance, provenance, and licensing for code data
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.
Patch (diff-style):
```diff
- if x == 0:
- return 1/x
+ if x == 0:
+ raise ValueError('division by zero')
```
Acceptance:
- Tests pass
- No new regressions
|
[] |
{
"target_language": "Java",
"developer_needs": [
"repo_scale_reasoning",
"governance",
"reproducibility",
"security_gates"
],
"moe_experts": [
"security_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
0cafe257c6eda478ac5b034f17c4f7c06fbe36b4
|
|
train_44185
| 2026-01-01T00:00:00
|
Code-specialized model families and sizing tradeoffs
|
design
|
expert
|
Task: design
Topic: Code-specialized model families and sizing tradeoffs
Difficulty: expert
Target language: 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": [
"reproducibility",
"security_gates",
"ci_integration",
"evaluation_metrics"
],
"moe_experts": [
"security_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
ec793e74b7a77238d196132885fd66098eb84bc1
|
|
train_44186
| 2026-01-01T00:00:00
|
Latency, cost, and reliability optimization
|
failure_analysis
|
intermediate
|
Task: failure_analysis
Topic: Latency, cost, and reliability optimization
Difficulty: intermediate
Target language: JavaScript
Context: 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": [
"auditability",
"governance",
"documentation",
"reproducibility"
],
"moe_experts": [
"agentic_systems_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
9c3770e7a94151089c6377d1dd1956a798f6b87f
|
|
train_44187
| 2026-01-01T00:00:00
|
Code-specialized model families and sizing tradeoffs
|
data_pipeline
|
intermediate
|
Task: data_pipeline
Topic: Code-specialized model families and sizing tradeoffs
Difficulty: intermediate
Target language: Go
Context: 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": "Go",
"developer_needs": [
"tooling",
"security_gates",
"governance",
"reproducibility"
],
"moe_experts": [
"coding_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
ac73655abc1c42d20079237b0de78b45154c1011
|
|
train_44188
| 2026-01-01T00:00:00
|
Mixture-of-Experts (MoE) for code
|
eval
|
intermediate
|
Task: eval
Topic: Mixture-of-Experts (MoE) for code
Difficulty: intermediate
Target language: Go
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
|
[] |
{
"target_language": "Go",
"developer_needs": [
"ci_integration",
"documentation",
"tests_are_truth",
"evaluation_metrics"
],
"moe_experts": [
"agentic_systems_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
298ada66a996e821fe13f0b85b2a2067b4652753
|
|
train_44189
| 2026-01-01T00:00:00
|
Code-specialized model families and sizing tradeoffs
|
failure_analysis
|
expert
|
Task: failure_analysis
Topic: Code-specialized model families and sizing tradeoffs
Difficulty: expert
Target language: Rust
Context: 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": "Rust",
"developer_needs": [
"cost_latency_tradeoffs",
"repo_scale_reasoning",
"security_gates",
"ci_integration"
],
"moe_experts": [
"security_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
c2f00e56169d6a9c40c564f6f4672c831ae62aee
|
|
train_44190
| 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: 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",
"security_gates",
"ci_integration",
"documentation"
],
"moe_experts": [
"evaluation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
d9d2631b90a5775b4111b9dc73ec72c0727ce640
|
|
train_44191
| 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: TypeScript
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Review: correctness, security, performance, governance
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "TypeScript",
"developer_needs": [
"tooling",
"security_gates",
"tests_are_truth",
"evaluation_metrics"
],
"moe_experts": [
"agentic_systems_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
2684f44cf4ea522415d5342aadeabbec17f5db6f
|
|
train_44192
| 2026-01-01T00:00:00
|
Multimodal dev workflows (docs, diagrams, traces)
|
patch_diff
|
expert
|
Task: patch_diff
Topic: Multimodal dev workflows (docs, diagrams, traces)
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.
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": [
"reproducibility",
"auditability",
"evaluation_metrics",
"ci_integration"
],
"moe_experts": [
"coding_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
87ad400fb436cce7274384967d6e1714d4b9c339
|
|
train_44193
| 2026-01-01T00:00:00
|
Tool calling, sandboxes, and CI integration
|
code
|
advanced
|
Task: code
Topic: Tool calling, sandboxes, and CI integration
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": [
"tooling",
"auditability",
"tests_are_truth",
"evaluation_metrics"
],
"moe_experts": [
"evaluation_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
077e8062b2b86c4574aa29f3e1412ad415e0cfaa
|
|
train_44194
| 2026-01-01T00:00:00
|
Extended context and repo-scale understanding
|
code
|
advanced
|
Task: code
Topic: Extended context and repo-scale understanding
Difficulty: advanced
Target language: Rust
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[] |
{
"target_language": "Rust",
"developer_needs": [
"ci_integration",
"security_gates",
"tests_are_truth",
"evaluation_metrics"
],
"moe_experts": [
"data_curation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
c91c66799b2a2aec58dd716bbbe798ae74b8ea9c
|
|
train_44195
| 2026-01-01T00:00:00
|
Multimodal dev workflows (docs, diagrams, traces)
|
eval
|
intermediate
|
Task: eval
Topic: Multimodal dev workflows (docs, diagrams, traces)
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.
Eval:
pass@k, time-to-green, regressions, diff size
|
[] |
{
"target_language": "Rust",
"developer_needs": [
"tests_are_truth",
"repo_scale_reasoning",
"governance",
"auditability"
],
"moe_experts": [
"agentic_systems_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
2a8eb02b74cc419003d73c5e172e67be10de9c38
|
|
train_44196
| 2026-01-01T00:00:00
|
Agentic coding systems (plan→edit→test→reflect)
|
data_pipeline
|
advanced
|
Task: data_pipeline
Topic: Agentic coding systems (plan→edit→test→reflect)
Difficulty: advanced
Target language: Go
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
|
[] |
{
"target_language": "Go",
"developer_needs": [
"reproducibility",
"governance",
"cost_latency_tradeoffs",
"tooling"
],
"moe_experts": [
"security_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
401210cb69046b5c8791915354e889b20ca9eeb4
|
|
train_44197
| 2026-01-01T00:00:00
|
Mixture-of-Experts (MoE) for code
|
review
|
intermediate
|
Task: review
Topic: Mixture-of-Experts (MoE) for code
Difficulty: intermediate
Target language: Python
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Review: correctness, security, performance, governance
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Python",
"developer_needs": [
"repo_scale_reasoning",
"security_gates",
"documentation",
"evaluation_metrics"
],
"moe_experts": [
"security_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
b8764705f751db6c529c210f10fca2da487e4c93
|
|
train_44198
| 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: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
|
[] |
{
"target_language": "Rust",
"developer_needs": [
"tests_are_truth",
"auditability",
"governance",
"documentation"
],
"moe_experts": [
"security_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
4386d42a8ff0f9e567f300ece0a437f6f1fa482c
|
|
train_44199
| 2026-01-01T00:00:00
|
Latency, cost, and reliability optimization
|
explain
|
intermediate
|
Task: explain
Topic: Latency, cost, and reliability optimization
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
|
[] |
{
"target_language": "Python",
"developer_needs": [
"ci_integration",
"auditability",
"evaluation_metrics",
"cost_latency_tradeoffs"
],
"moe_experts": [
"agentic_systems_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
bebcd6b8f6f87714dc3a1cab8bcc62bef8fec950
|
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