id
stringlengths 11
11
| created
timestamp[s]date 2026-01-01 00:00:00
2026-01-01 00:00:00
| topic
stringclasses 14
values | task_type
stringclasses 10
values | difficulty
stringclasses 3
values | instruction
stringlengths 189
248
| input
stringclasses 1
value | output
stringclasses 9
values | reasoning_steps
listlengths 0
5
| metadata
dict | hash
stringlengths 40
40
|
|---|---|---|---|---|---|---|---|---|---|---|
train_06000
| 2026-01-01T00:00:00
|
Model merging, distillation, and continued pretraining
|
explain
|
expert
|
Task: explain
Topic: Model merging, distillation, and continued pretraining
Difficulty: expert
Target language: 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": [
"governance",
"documentation",
"tooling",
"tests_are_truth"
],
"moe_experts": [
"security_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
9a394575e27f3a40c4ad08bc997560feb6d92ffd
|
|
train_06001
| 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: C#
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
|
[] |
{
"target_language": "C#",
"developer_needs": [
"repo_scale_reasoning",
"reproducibility",
"cost_latency_tradeoffs",
"security_gates"
],
"moe_experts": [
"evaluation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
9bdb3d5260b3e60dea0619ef08bca3352cb2d6ae
|
|
train_06002
| 2026-01-01T00:00:00
|
Extended context and repo-scale understanding
|
eval
|
expert
|
Task: eval
Topic: Extended context and repo-scale understanding
Difficulty: expert
Target language: 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.
Eval:
pass@k, time-to-green, regressions, diff size
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "TypeScript",
"developer_needs": [
"governance",
"tests_are_truth",
"repo_scale_reasoning",
"cost_latency_tradeoffs"
],
"moe_experts": [
"governance_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
83f90eea36104cf5d2a155d9875ebc13ac8c6a95
|
|
train_06003
| 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: 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.
Review: correctness, security, performance, governance
|
[] |
{
"target_language": "SQL",
"developer_needs": [
"ci_integration",
"reproducibility",
"repo_scale_reasoning",
"documentation"
],
"moe_experts": [
"coding_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
8ff94c75f34d6585bfc3fee6cd18bd881e7b894b
|
|
train_06004
| 2026-01-01T00:00:00
|
Tool calling, sandboxes, and CI integration
|
failure_analysis
|
expert
|
Task: failure_analysis
Topic: Tool calling, sandboxes, and CI integration
Difficulty: expert
Target language: TypeScript
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
|
[] |
{
"target_language": "TypeScript",
"developer_needs": [
"repo_scale_reasoning",
"governance",
"evaluation_metrics",
"reproducibility"
],
"moe_experts": [
"governance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
546e1744ad7444806b8225d5d4ed4e925fb0f080
|
|
train_06005
| 2026-01-01T00:00:00
|
Latency, cost, and reliability optimization
|
review
|
intermediate
|
Task: review
Topic: Latency, cost, and reliability optimization
Difficulty: intermediate
Target language: SQL
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Review: correctness, security, performance, governance
|
[] |
{
"target_language": "SQL",
"developer_needs": [
"security_gates",
"documentation",
"reproducibility",
"repo_scale_reasoning"
],
"moe_experts": [
"data_curation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
e50c942bc705d01435dbe78b20fa917f8971768c
|
|
train_06006
| 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: 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.
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": [
"repo_scale_reasoning",
"reproducibility",
"documentation",
"auditability"
],
"moe_experts": [
"coding_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
10b4c9c5daaafc5c1ea07dc01958ebf54a90429a
|
|
train_06007
| 2026-01-01T00:00:00
|
Governance, provenance, and licensing for code data
|
data_pipeline
|
intermediate
|
Task: data_pipeline
Topic: Governance, provenance, and licensing for code data
Difficulty: intermediate
Target language: 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": [
"auditability",
"tests_are_truth",
"ci_integration",
"reproducibility"
],
"moe_experts": [
"data_curation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
91b8f0d135ea3986fbd91ab44ffe1e26ef82a0b8
|
|
train_06008
| 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: 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.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
|
[] |
{
"target_language": "Java",
"developer_needs": [
"tests_are_truth",
"cost_latency_tradeoffs",
"security_gates",
"reproducibility"
],
"moe_experts": [
"governance_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
a9bc102617e5f8a03bf0787a6c7bccde04f36951
|
|
train_06009
| 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: SQL
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
|
[] |
{
"target_language": "SQL",
"developer_needs": [
"cost_latency_tradeoffs",
"auditability",
"tooling",
"ci_integration"
],
"moe_experts": [
"governance_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
52a634069a9799c4d7d2b247f6385543fa6c5e68
|
|
train_06010
| 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: 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
|
[] |
{
"target_language": "Go",
"developer_needs": [
"documentation",
"repo_scale_reasoning",
"reproducibility",
"cost_latency_tradeoffs"
],
"moe_experts": [
"governance_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
9a4a5048ca10e7709d6df5853b33ca894d2130cc
|
|
train_06011
| 2026-01-01T00:00:00
|
Multimodal dev workflows (docs, diagrams, traces)
|
explain
|
expert
|
Task: explain
Topic: Multimodal dev workflows (docs, diagrams, traces)
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",
"auditability",
"security_gates",
"ci_integration"
],
"moe_experts": [
"performance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
f61e2a2a02de9a92333c23196ad0ea7499150c7c
|
|
train_06012
| 2026-01-01T00:00:00
|
Code-specialized model families and sizing tradeoffs
|
explain
|
expert
|
Task: explain
Topic: Code-specialized model families and sizing tradeoffs
Difficulty: expert
Target language: C#
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[] |
{
"target_language": "C#",
"developer_needs": [
"governance",
"reproducibility",
"auditability",
"ci_integration"
],
"moe_experts": [
"security_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
8fb131c42fff326761891678cc632aa24a7aa5d7
|
|
train_06013
| 2026-01-01T00:00:00
|
Latency, cost, and reliability optimization
|
review
|
expert
|
Task: review
Topic: Latency, cost, and reliability optimization
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.
Review: correctness, security, performance, governance
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Bash",
"developer_needs": [
"reproducibility",
"governance",
"security_gates",
"tests_are_truth"
],
"moe_experts": [
"governance_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
a3d90aa766ba6a7e52bee82b6a72039f3f791844
|
|
train_06014
| 2026-01-01T00:00:00
|
Mixture-of-Experts (MoE) for code
|
explain
|
intermediate
|
Task: explain
Topic: Mixture-of-Experts (MoE) for code
Difficulty: intermediate
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": [
"evaluation_metrics",
"documentation",
"repo_scale_reasoning",
"auditability"
],
"moe_experts": [
"agentic_systems_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
728b4c1da6058cb2b2e77f7c350ac755293ff00e
|
|
train_06015
| 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: 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.
Review: correctness, security, performance, governance
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Java",
"developer_needs": [
"security_gates",
"reproducibility",
"repo_scale_reasoning",
"ci_integration"
],
"moe_experts": [
"agentic_systems_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
92a77c14d72843a238787ba51c64eb059684f951
|
|
train_06016
| 2026-01-01T00:00:00
|
Latency, cost, and reliability optimization
|
design
|
advanced
|
Task: design
Topic: Latency, cost, and reliability optimization
Difficulty: advanced
Target language: JavaScript
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[] |
{
"target_language": "JavaScript",
"developer_needs": [
"evaluation_metrics",
"ci_integration",
"auditability",
"repo_scale_reasoning"
],
"moe_experts": [
"coding_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
0cbab1122d6b4ce7af40050b796a5cd54380dbb3
|
|
train_06017
| 2026-01-01T00:00:00
|
Agentic coding systems (plan→edit→test→reflect)
|
design
|
intermediate
|
Task: design
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.
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": [
"reproducibility",
"tests_are_truth",
"ci_integration",
"cost_latency_tradeoffs"
],
"moe_experts": [
"agentic_systems_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
bc62b2e8b6593948ea77e4836298fac98176b4d1
|
|
train_06018
| 2026-01-01T00:00:00
|
Reasoning-first coding models and tunable deliberation
|
compare
|
intermediate
|
Task: compare
Topic: Reasoning-first coding models and tunable deliberation
Difficulty: intermediate
Target language: Rust
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
|
[] |
{
"target_language": "Rust",
"developer_needs": [
"ci_integration",
"tests_are_truth",
"auditability",
"reproducibility"
],
"moe_experts": [
"coding_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
4268d9700a9b136d5b85eec8d8f8d71f25673ccc
|
|
train_06019
| 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: 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": "Python",
"developer_needs": [
"reproducibility",
"governance",
"tooling",
"security_gates"
],
"moe_experts": [
"coding_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
d4ac61ddde2e1488d65decc675ff5505a2b05dbb
|
|
train_06020
| 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: 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.
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": "Java",
"developer_needs": [
"documentation",
"tooling",
"auditability",
"tests_are_truth"
],
"moe_experts": [
"coding_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
7942400ae274d16be096942845da94d5d9ad4503
|
|
train_06021
| 2026-01-01T00:00:00
|
Secure code generation and policy gates
|
patch_diff
|
intermediate
|
Task: patch_diff
Topic: Secure code generation and policy gates
Difficulty: intermediate
Target language: C#
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Patch (diff-style):
```diff
- if x == 0:
- return 1/x
+ if x == 0:
+ raise ValueError('division by zero')
```
Acceptance:
- Tests pass
- No new regressions
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "C#",
"developer_needs": [
"tooling",
"tests_are_truth",
"reproducibility",
"repo_scale_reasoning"
],
"moe_experts": [
"performance_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
c0da6a17b22abb23aa62976cfd09d734db4ca2b0
|
|
train_06022
| 2026-01-01T00:00:00
|
Secure code generation and policy gates
|
explain
|
advanced
|
Task: explain
Topic: Secure code generation and policy gates
Difficulty: advanced
Target language: 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.
Design with risks, metrics, acceptance criteria
|
[] |
{
"target_language": "JavaScript",
"developer_needs": [
"tooling",
"tests_are_truth",
"evaluation_metrics",
"documentation"
],
"moe_experts": [
"performance_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
998f941d3ac23a65f9786237fc5f03f926445542
|
|
train_06023
| 2026-01-01T00:00:00
|
Latency, cost, and reliability optimization
|
review
|
intermediate
|
Task: review
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.
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": [
"documentation",
"repo_scale_reasoning",
"evaluation_metrics",
"governance"
],
"moe_experts": [
"evaluation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
f8769e08fd84a6a38a8b68153e2849cfa26d5530
|
|
train_06024
| 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: 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": [
"security_gates",
"tooling",
"ci_integration",
"evaluation_metrics"
],
"moe_experts": [
"agentic_systems_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
edcd5fe162b95ff34b5d2154b9e53581491c6817
|
|
train_06025
| 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: C#
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[] |
{
"target_language": "C#",
"developer_needs": [
"documentation",
"security_gates",
"tooling",
"auditability"
],
"moe_experts": [
"evaluation_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
8c4a2580477b0deba99031eca3a243c8a2b3900e
|
|
train_06026
| 2026-01-01T00:00:00
|
Latency, cost, and reliability optimization
|
eval
|
expert
|
Task: eval
Topic: Latency, cost, and reliability optimization
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.
Eval:
pass@k, time-to-green, regressions, diff size
|
[] |
{
"target_language": "Bash",
"developer_needs": [
"cost_latency_tradeoffs",
"tooling",
"governance",
"reproducibility"
],
"moe_experts": [
"evaluation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
54bcd8e3b42da83f28bf0bb492be083698f9320f
|
|
train_06027
| 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: JavaScript
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
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": [
"tooling",
"auditability",
"ci_integration",
"repo_scale_reasoning"
],
"moe_experts": [
"agentic_systems_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
1159d8b4d95ae6f24102acb993bc64363db00816
|
|
train_06028
| 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: 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.
Patch (diff-style):
```diff
- if x == 0:
- return 1/x
+ if x == 0:
+ raise ValueError('division by zero')
```
Acceptance:
- Tests pass
- No new regressions
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "C#",
"developer_needs": [
"tests_are_truth",
"documentation",
"evaluation_metrics",
"tooling"
],
"moe_experts": [
"evaluation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
b2d8b8da0fb779b98befc862bd0e1093438bedbf
|
|
train_06029
| 2026-01-01T00:00:00
|
Secure code generation and policy gates
|
failure_analysis
|
advanced
|
Task: failure_analysis
Topic: Secure code generation and policy gates
Difficulty: advanced
Target language: JavaScript
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "JavaScript",
"developer_needs": [
"reproducibility",
"security_gates",
"auditability",
"tests_are_truth"
],
"moe_experts": [
"evaluation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
fefdee8be42e79e8278d741c7fbdddbeca012af8
|
|
train_06030
| 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: SQL
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "SQL",
"developer_needs": [
"security_gates",
"reproducibility",
"tooling",
"repo_scale_reasoning"
],
"moe_experts": [
"performance_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
dc9467f04aeeb5e23f6e8d9e26d1083e9a1511d5
|
|
train_06031
| 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: JavaScript
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[] |
{
"target_language": "JavaScript",
"developer_needs": [
"security_gates",
"documentation",
"evaluation_metrics",
"repo_scale_reasoning"
],
"moe_experts": [
"security_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
f3ddec5dc810a880e21fa6b276a3a0af1b233cb8
|
|
train_06032
| 2026-01-01T00:00:00
|
Tool calling, sandboxes, and CI integration
|
failure_analysis
|
advanced
|
Task: failure_analysis
Topic: Tool calling, sandboxes, and CI integration
Difficulty: advanced
Target language: 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
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Rust",
"developer_needs": [
"cost_latency_tradeoffs",
"governance",
"ci_integration",
"documentation"
],
"moe_experts": [
"evaluation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
55b39708e3f7996a7f7a4b299f8d935dcd5129b4
|
|
train_06033
| 2026-01-01T00:00:00
|
Latency, cost, and reliability optimization
|
compare
|
expert
|
Task: compare
Topic: Latency, cost, and reliability optimization
Difficulty: expert
Target language: Go
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
|
[] |
{
"target_language": "Go",
"developer_needs": [
"tests_are_truth",
"auditability",
"evaluation_metrics",
"cost_latency_tradeoffs"
],
"moe_experts": [
"coding_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
29375ad93912c9f22bff34b837cddbaf79de6670
|
|
train_06034
| 2026-01-01T00:00:00
|
Governance, provenance, and licensing for code data
|
compare
|
intermediate
|
Task: compare
Topic: Governance, provenance, and licensing for code data
Difficulty: intermediate
Target language: 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.
Compare: capability, cost, latency, reliability
|
[] |
{
"target_language": "C#",
"developer_needs": [
"documentation",
"evaluation_metrics",
"auditability",
"security_gates"
],
"moe_experts": [
"evaluation_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
03a2be210c9b91f55a3e156fc1daf32c0cb47331
|
|
train_06035
| 2026-01-01T00:00:00
|
Self-improving agents and feedback loops
|
explain
|
intermediate
|
Task: explain
Topic: Self-improving agents and feedback loops
Difficulty: intermediate
Target language: Java
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[] |
{
"target_language": "Java",
"developer_needs": [
"governance",
"cost_latency_tradeoffs",
"security_gates",
"tooling"
],
"moe_experts": [
"evaluation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
b8bb467fe16f0393caf8096ce3c4346b105140ab
|
|
train_06036
| 2026-01-01T00:00:00
|
Latency, cost, and reliability optimization
|
eval
|
advanced
|
Task: eval
Topic: Latency, cost, and reliability optimization
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.
Eval:
pass@k, time-to-green, regressions, diff size
|
[] |
{
"target_language": "C#",
"developer_needs": [
"ci_integration",
"documentation",
"evaluation_metrics",
"tooling"
],
"moe_experts": [
"evaluation_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
7f82b4a683ebbf15b09cf8d20104c4b7d55c9646
|
|
train_06037
| 2026-01-01T00:00:00
|
Model merging, distillation, and continued pretraining
|
code
|
intermediate
|
Task: code
Topic: Model merging, distillation, and continued pretraining
Difficulty: intermediate
Target language: Java
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
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": [
"cost_latency_tradeoffs",
"governance",
"tests_are_truth",
"security_gates"
],
"moe_experts": [
"evaluation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
15b5ae78aff40c76c3f3982906281409dd0d31f4
|
|
train_06038
| 2026-01-01T00:00:00
|
Secure code generation and policy gates
|
eval
|
advanced
|
Task: eval
Topic: Secure code generation and policy gates
Difficulty: advanced
Target language: Java
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Java",
"developer_needs": [
"evaluation_metrics",
"auditability",
"reproducibility",
"security_gates"
],
"moe_experts": [
"data_curation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
0a571e55e066eb53ba2f6ea3bdb2ece7b2771388
|
|
train_06039
| 2026-01-01T00:00:00
|
Code-specialized model families and sizing tradeoffs
|
explain
|
advanced
|
Task: explain
Topic: Code-specialized model families and sizing tradeoffs
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": [
"reproducibility",
"evaluation_metrics",
"documentation",
"cost_latency_tradeoffs"
],
"moe_experts": [
"performance_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
e519c5f9aa05b5dd8ac993d2505d86473b1624a9
|
|
train_06040
| 2026-01-01T00:00:00
|
Tool calling, sandboxes, and CI integration
|
review
|
intermediate
|
Task: review
Topic: Tool calling, sandboxes, and CI integration
Difficulty: intermediate
Target language: Python
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Review: correctness, security, performance, governance
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Python",
"developer_needs": [
"reproducibility",
"tests_are_truth",
"tooling",
"ci_integration"
],
"moe_experts": [
"governance_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
54de4d6d318669347357ff35cc9bb08e6b74df20
|
|
train_06041
| 2026-01-01T00:00:00
|
Dataset curation pipelines (filter, dedupe, quality)
|
review
|
intermediate
|
Task: review
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: intermediate
Target language: JavaScript
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Review: correctness, security, performance, governance
|
[] |
{
"target_language": "JavaScript",
"developer_needs": [
"security_gates",
"cost_latency_tradeoffs",
"documentation",
"ci_integration"
],
"moe_experts": [
"security_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
d65e0764e75db68fb44bdf6138e216466d320213
|
|
train_06042
| 2026-01-01T00:00:00
|
Secure code generation and policy gates
|
code
|
intermediate
|
Task: code
Topic: Secure code generation and policy gates
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": [
"auditability",
"tests_are_truth",
"tooling",
"documentation"
],
"moe_experts": [
"governance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
acd0d1647511dddc208479fc91eb3e61569d3c88
|
|
train_06043
| 2026-01-01T00:00:00
|
Reasoning-first coding models and tunable deliberation
|
patch_diff
|
intermediate
|
Task: patch_diff
Topic: Reasoning-first coding models and tunable deliberation
Difficulty: intermediate
Target language: 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.
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": [
"cost_latency_tradeoffs",
"evaluation_metrics",
"governance",
"auditability"
],
"moe_experts": [
"coding_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
77be0753357ff2dbff9081fb7fcce13f9363f7a3
|
|
train_06044
| 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: Java
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Patch (diff-style):
```diff
- if x == 0:
- return 1/x
+ if x == 0:
+ raise ValueError('division by zero')
```
Acceptance:
- Tests pass
- No new regressions
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Java",
"developer_needs": [
"cost_latency_tradeoffs",
"security_gates",
"auditability",
"documentation"
],
"moe_experts": [
"coding_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
dc2199d999992d608f9f083b4a999122b72ff481
|
|
train_06045
| 2026-01-01T00:00:00
|
Dataset curation pipelines (filter, dedupe, quality)
|
data_pipeline
|
intermediate
|
Task: data_pipeline
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: intermediate
Target language: 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": [
"tooling",
"tests_are_truth",
"auditability",
"evaluation_metrics"
],
"moe_experts": [
"performance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
af0a1ec68f5fb69c31aa0dd02f01824b6a810a07
|
|
train_06046
| 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: 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.
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",
"reproducibility",
"evaluation_metrics",
"governance"
],
"moe_experts": [
"data_curation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
59dcca3e66246ac8ac42c5b92b4aec5632ff9f2a
|
|
train_06047
| 2026-01-01T00:00:00
|
Multimodal dev workflows (docs, diagrams, traces)
|
failure_analysis
|
intermediate
|
Task: failure_analysis
Topic: Multimodal dev workflows (docs, diagrams, traces)
Difficulty: intermediate
Target language: JavaScript
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
|
[] |
{
"target_language": "JavaScript",
"developer_needs": [
"reproducibility",
"security_gates",
"tests_are_truth",
"tooling"
],
"moe_experts": [
"data_curation_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
ac1f9abdf028f35042561f4c553d8c657d480bd3
|
|
train_06048
| 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: 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": [
"cost_latency_tradeoffs",
"auditability",
"tooling",
"documentation"
],
"moe_experts": [
"agentic_systems_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
0aa2072913acb43b1f1888ee5eecefb54851414f
|
|
train_06049
| 2026-01-01T00:00:00
|
Latency, cost, and reliability optimization
|
data_pipeline
|
advanced
|
Task: data_pipeline
Topic: Latency, cost, and reliability optimization
Difficulty: advanced
Target language: 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.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
|
[] |
{
"target_language": "Java",
"developer_needs": [
"evaluation_metrics",
"tooling",
"governance",
"documentation"
],
"moe_experts": [
"data_curation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
6d4605192527c9da0b6725f0defdb9835afad935
|
|
train_06050
| 2026-01-01T00:00:00
|
Secure code generation and policy gates
|
compare
|
expert
|
Task: compare
Topic: Secure code generation and policy gates
Difficulty: expert
Target language: Bash
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
|
[] |
{
"target_language": "Bash",
"developer_needs": [
"ci_integration",
"cost_latency_tradeoffs",
"tests_are_truth",
"security_gates"
],
"moe_experts": [
"agentic_systems_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
2c76d744c240193bb05b19877e0c1cfbc2fc12b3
|
|
train_06051
| 2026-01-01T00:00:00
|
Extended context and repo-scale understanding
|
explain
|
expert
|
Task: explain
Topic: Extended context and repo-scale understanding
Difficulty: expert
Target language: Java
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Java",
"developer_needs": [
"cost_latency_tradeoffs",
"reproducibility",
"auditability",
"tooling"
],
"moe_experts": [
"performance_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
7e4adde41f0f0b0bf139345dd64f0f0d1db956c1
|
|
train_06052
| 2026-01-01T00:00:00
|
Secure code generation and policy gates
|
design
|
advanced
|
Task: design
Topic: Secure code generation and policy gates
Difficulty: advanced
Target language: JavaScript
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[] |
{
"target_language": "JavaScript",
"developer_needs": [
"tests_are_truth",
"repo_scale_reasoning",
"security_gates",
"auditability"
],
"moe_experts": [
"data_curation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
d49a371ceebd0303de13f82380e600c230ce84bd
|
|
train_06053
| 2026-01-01T00:00:00
|
Reasoning-first coding models and tunable deliberation
|
compare
|
advanced
|
Task: compare
Topic: Reasoning-first coding models and tunable deliberation
Difficulty: advanced
Target language: 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": [
"documentation",
"evaluation_metrics",
"ci_integration",
"auditability"
],
"moe_experts": [
"agentic_systems_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
6d037878618ccca634011752ef0e33d75219ed1a
|
|
train_06054
| 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: 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.
Compare: capability, cost, latency, reliability
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "JavaScript",
"developer_needs": [
"cost_latency_tradeoffs",
"auditability",
"tests_are_truth",
"evaluation_metrics"
],
"moe_experts": [
"governance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
24ec06c71883dc99b78ee58f8e72880d3908963e
|
|
train_06055
| 2026-01-01T00:00:00
|
Agentic coding systems (plan→edit→test→reflect)
|
agent_loop
|
intermediate
|
Task: agent_loop
Topic: Agentic coding systems (plan→edit→test→reflect)
Difficulty: intermediate
Target language: JavaScript
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
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": [
"auditability",
"governance",
"repo_scale_reasoning",
"tests_are_truth"
],
"moe_experts": [
"coding_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
ecf43aab777ca4347221fae797bd13d58fac9dac
|
|
train_06056
| 2026-01-01T00:00:00
|
Latency, cost, and reliability optimization
|
explain
|
advanced
|
Task: explain
Topic: Latency, cost, and reliability optimization
Difficulty: advanced
Target language: SQL
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[] |
{
"target_language": "SQL",
"developer_needs": [
"security_gates",
"tooling",
"reproducibility",
"auditability"
],
"moe_experts": [
"performance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
739a5277096c1b19c463a2bf31e4c2ab40ad037a
|
|
train_06057
| 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: 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": "Java",
"developer_needs": [
"security_gates",
"governance",
"ci_integration",
"tests_are_truth"
],
"moe_experts": [
"data_curation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
90b12c967788efce0835ef7acafe077564c1811e
|
|
train_06058
| 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: 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": [
"security_gates",
"governance",
"tests_are_truth",
"documentation"
],
"moe_experts": [
"agentic_systems_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
ec00dfd4fc667ead8bd61bfed10ef77f5dc0e37a
|
|
train_06059
| 2026-01-01T00:00:00
|
Model merging, distillation, and continued pretraining
|
review
|
expert
|
Task: review
Topic: Model merging, distillation, and continued pretraining
Difficulty: expert
Target language: Rust
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Review: correctness, security, performance, governance
|
[] |
{
"target_language": "Rust",
"developer_needs": [
"documentation",
"security_gates",
"reproducibility",
"ci_integration"
],
"moe_experts": [
"agentic_systems_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
15006074fb4a3803a33c450c7deec2626e4e7cea
|
|
train_06060
| 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: 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": "Java",
"developer_needs": [
"evaluation_metrics",
"tests_are_truth",
"tooling",
"auditability"
],
"moe_experts": [
"coding_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
7a752d388e5df568f996be024d941bce436f9bbf
|
|
train_06061
| 2026-01-01T00:00:00
|
Governance, provenance, and licensing for code data
|
failure_analysis
|
intermediate
|
Task: failure_analysis
Topic: Governance, provenance, and licensing for code data
Difficulty: intermediate
Target language: 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": [
"reproducibility",
"security_gates",
"documentation",
"cost_latency_tradeoffs"
],
"moe_experts": [
"evaluation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
2b9329351117c01f446d547a33f47b34d52faea4
|
|
train_06062
| 2026-01-01T00:00:00
|
Model merging, distillation, and continued pretraining
|
review
|
expert
|
Task: review
Topic: Model merging, distillation, and continued pretraining
Difficulty: expert
Target language: JavaScript
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Review: correctness, security, performance, governance
|
[] |
{
"target_language": "JavaScript",
"developer_needs": [
"tests_are_truth",
"tooling",
"repo_scale_reasoning",
"documentation"
],
"moe_experts": [
"governance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
53b60aa39a6dd4efa24a8cfd945bf015e2f364e7
|
|
train_06063
| 2026-01-01T00:00:00
|
Dataset curation pipelines (filter, dedupe, quality)
|
design
|
expert
|
Task: design
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: expert
Target language: Python
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[] |
{
"target_language": "Python",
"developer_needs": [
"cost_latency_tradeoffs",
"evaluation_metrics",
"security_gates",
"documentation"
],
"moe_experts": [
"governance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
c4516c939e4c77ff5e438d83fc78e4b9ca02b93e
|
|
train_06064
| 2026-01-01T00:00:00
|
Model merging, distillation, and continued pretraining
|
design
|
advanced
|
Task: design
Topic: Model merging, distillation, and continued pretraining
Difficulty: advanced
Target language: JavaScript
Context: 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": [
"cost_latency_tradeoffs",
"governance",
"reproducibility",
"security_gates"
],
"moe_experts": [
"data_curation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
49e2507e561ec6b9408a27bc260876c048ba8e15
|
|
train_06065
| 2026-01-01T00:00:00
|
Extended context and repo-scale understanding
|
review
|
advanced
|
Task: review
Topic: Extended context and repo-scale understanding
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.
Review: correctness, security, performance, governance
|
[] |
{
"target_language": "JavaScript",
"developer_needs": [
"repo_scale_reasoning",
"reproducibility",
"tests_are_truth",
"tooling"
],
"moe_experts": [
"performance_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
cc703e5dc2a9783839261deec376dafa3ca569c0
|
|
train_06066
| 2026-01-01T00:00:00
|
Extended context and repo-scale understanding
|
design
|
intermediate
|
Task: design
Topic: Extended context and repo-scale understanding
Difficulty: intermediate
Target language: Bash
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[] |
{
"target_language": "Bash",
"developer_needs": [
"tests_are_truth",
"governance",
"ci_integration",
"evaluation_metrics"
],
"moe_experts": [
"performance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
001df8d625420b32aaba69ce9b2248774ebe543d
|
|
train_06067
| 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: JavaScript
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
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": [
"tests_are_truth",
"repo_scale_reasoning",
"reproducibility",
"documentation"
],
"moe_experts": [
"data_curation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
102b5b7a247c6185580f3764257368202ab17ad4
|
|
train_06068
| 2026-01-01T00:00:00
|
Self-improving agents and feedback loops
|
agent_loop
|
expert
|
Task: agent_loop
Topic: Self-improving agents and feedback loops
Difficulty: expert
Target language: Python
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Python",
"developer_needs": [
"auditability",
"repo_scale_reasoning",
"tooling",
"security_gates"
],
"moe_experts": [
"coding_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
a553d83a955a8a69c4b918acf2815e3085275d10
|
|
train_06069
| 2026-01-01T00:00:00
|
Mixture-of-Experts (MoE) for code
|
explain
|
advanced
|
Task: explain
Topic: Mixture-of-Experts (MoE) for code
Difficulty: advanced
Target language: Rust
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Rust",
"developer_needs": [
"tooling",
"cost_latency_tradeoffs",
"governance",
"documentation"
],
"moe_experts": [
"performance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
f169b906d4293d1aa4fe36a931abf71780eb965d
|
|
train_06070
| 2026-01-01T00:00:00
|
Code-specialized model families and sizing tradeoffs
|
explain
|
advanced
|
Task: explain
Topic: Code-specialized model families and sizing tradeoffs
Difficulty: advanced
Target language: Java
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Java",
"developer_needs": [
"documentation",
"governance",
"security_gates",
"tooling"
],
"moe_experts": [
"agentic_systems_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
fa2927fb317c67ffa7f0ae93ba17d654751202c0
|
|
train_06071
| 2026-01-01T00:00:00
|
Reasoning-first coding models and tunable deliberation
|
patch_diff
|
advanced
|
Task: patch_diff
Topic: Reasoning-first coding models and tunable deliberation
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.
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": "Java",
"developer_needs": [
"governance",
"ci_integration",
"evaluation_metrics",
"cost_latency_tradeoffs"
],
"moe_experts": [
"evaluation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
995bcbae683d43387bdadaa99a2bfe234792d021
|
|
train_06072
| 2026-01-01T00:00:00
|
Model merging, distillation, and continued pretraining
|
review
|
intermediate
|
Task: review
Topic: Model merging, distillation, and continued pretraining
Difficulty: intermediate
Target language: Bash
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Review: correctness, security, performance, governance
|
[] |
{
"target_language": "Bash",
"developer_needs": [
"evaluation_metrics",
"security_gates",
"tests_are_truth",
"repo_scale_reasoning"
],
"moe_experts": [
"security_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
b98c4e644f1de83a2c1c8104fae19003cb0a94c2
|
|
train_06073
| 2026-01-01T00:00:00
|
Reasoning-first coding models and tunable deliberation
|
compare
|
expert
|
Task: compare
Topic: Reasoning-first coding models and tunable deliberation
Difficulty: expert
Target language: Bash
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
|
[] |
{
"target_language": "Bash",
"developer_needs": [
"documentation",
"ci_integration",
"repo_scale_reasoning",
"cost_latency_tradeoffs"
],
"moe_experts": [
"agentic_systems_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
fa3469ae3d9aa43e59acc406a04d49f529f18df1
|
|
train_06074
| 2026-01-01T00:00:00
|
Dataset curation pipelines (filter, dedupe, quality)
|
data_pipeline
|
expert
|
Task: data_pipeline
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.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
|
[] |
{
"target_language": "SQL",
"developer_needs": [
"auditability",
"security_gates",
"ci_integration",
"cost_latency_tradeoffs"
],
"moe_experts": [
"performance_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
a48b88a0b02911058e605dc453945aa3885395de
|
|
train_06075
| 2026-01-01T00:00:00
|
SWE-bench style real-repo evaluation
|
failure_analysis
|
expert
|
Task: failure_analysis
Topic: SWE-bench style real-repo evaluation
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.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
|
[] |
{
"target_language": "C#",
"developer_needs": [
"ci_integration",
"reproducibility",
"tests_are_truth",
"cost_latency_tradeoffs"
],
"moe_experts": [
"governance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
3ba27224adda7f3dcf70b6be91be72ca950a1b41
|
|
train_06076
| 2026-01-01T00:00:00
|
Multimodal dev workflows (docs, diagrams, traces)
|
explain
|
expert
|
Task: explain
Topic: Multimodal dev workflows (docs, diagrams, traces)
Difficulty: expert
Target language: Rust
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Rust",
"developer_needs": [
"repo_scale_reasoning",
"reproducibility",
"documentation",
"tests_are_truth"
],
"moe_experts": [
"evaluation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
cfbdfb8f4c934b34dc7d705e240759a2c64c49a7
|
|
train_06077
| 2026-01-01T00:00:00
|
Mixture-of-Experts (MoE) for code
|
agent_loop
|
advanced
|
Task: agent_loop
Topic: Mixture-of-Experts (MoE) for code
Difficulty: advanced
Target language: 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.
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": [
"repo_scale_reasoning",
"reproducibility",
"tests_are_truth",
"evaluation_metrics"
],
"moe_experts": [
"coding_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
8706c3596140063441bc438782a867bbcc66048a
|
|
train_06078
| 2026-01-01T00:00:00
|
Dataset curation pipelines (filter, dedupe, quality)
|
failure_analysis
|
advanced
|
Task: failure_analysis
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: advanced
Target language: Bash
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Bash",
"developer_needs": [
"evaluation_metrics",
"security_gates",
"ci_integration",
"repo_scale_reasoning"
],
"moe_experts": [
"evaluation_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
873c174b40a5cfe5bfc0c930c8dde9a1c6dbb405
|
|
train_06079
| 2026-01-01T00:00:00
|
Mixture-of-Experts (MoE) for code
|
eval
|
intermediate
|
Task: eval
Topic: Mixture-of-Experts (MoE) for code
Difficulty: intermediate
Target language: Rust
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
|
[] |
{
"target_language": "Rust",
"developer_needs": [
"documentation",
"tooling",
"evaluation_metrics",
"cost_latency_tradeoffs"
],
"moe_experts": [
"agentic_systems_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
a5c8b637cb8b3ac5633542199eb0043edc6e9d6c
|
|
train_06080
| 2026-01-01T00:00:00
|
Latency, cost, and reliability optimization
|
compare
|
expert
|
Task: compare
Topic: Latency, cost, and reliability optimization
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.
Compare: capability, cost, latency, reliability
|
[] |
{
"target_language": "C#",
"developer_needs": [
"repo_scale_reasoning",
"cost_latency_tradeoffs",
"documentation",
"evaluation_metrics"
],
"moe_experts": [
"evaluation_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
c028a36719ffd2745154a9739303df4fba9854b8
|
|
train_06081
| 2026-01-01T00:00:00
|
Governance, provenance, and licensing for code data
|
compare
|
expert
|
Task: compare
Topic: Governance, provenance, and licensing for code data
Difficulty: expert
Target language: 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.
Compare: capability, cost, latency, reliability
|
[] |
{
"target_language": "Rust",
"developer_needs": [
"auditability",
"cost_latency_tradeoffs",
"evaluation_metrics",
"ci_integration"
],
"moe_experts": [
"performance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
cdcf1d35ac33c41dbeb28f6b0ba0ee350f665bc0
|
|
train_06082
| 2026-01-01T00:00:00
|
Dataset curation pipelines (filter, dedupe, quality)
|
explain
|
advanced
|
Task: explain
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: advanced
Target language: C#
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[] |
{
"target_language": "C#",
"developer_needs": [
"tests_are_truth",
"security_gates",
"repo_scale_reasoning",
"auditability"
],
"moe_experts": [
"performance_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
ad1b837a0063e946f214fe51aeed78fd81b02967
|
|
train_06083
| 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: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[] |
{
"target_language": "Bash",
"developer_needs": [
"tests_are_truth",
"tooling",
"auditability",
"documentation"
],
"moe_experts": [
"data_curation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
1df23029ac49697b135e85d73e9ba31defd8af0b
|
|
train_06084
| 2026-01-01T00:00:00
|
Code-specialized model families and sizing tradeoffs
|
data_pipeline
|
expert
|
Task: data_pipeline
Topic: Code-specialized model families and sizing tradeoffs
Difficulty: expert
Target language: SQL
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "SQL",
"developer_needs": [
"tooling",
"auditability",
"tests_are_truth",
"repo_scale_reasoning"
],
"moe_experts": [
"performance_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
76f643fa289ca25a2a4fefe029af368ba1f598ab
|
|
train_06085
| 2026-01-01T00:00:00
|
SWE-bench style real-repo evaluation
|
compare
|
intermediate
|
Task: compare
Topic: SWE-bench style real-repo evaluation
Difficulty: intermediate
Target language: Rust
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Rust",
"developer_needs": [
"tests_are_truth",
"repo_scale_reasoning",
"reproducibility",
"governance"
],
"moe_experts": [
"data_curation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
6dbb4c3e6e23a7fb9b7d5f3217baf35f38a59449
|
|
train_06086
| 2026-01-01T00:00:00
|
Agentic coding systems (plan→edit→test→reflect)
|
code
|
expert
|
Task: code
Topic: Agentic coding systems (plan→edit→test→reflect)
Difficulty: expert
Target language: 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",
"ci_integration",
"documentation",
"auditability"
],
"moe_experts": [
"governance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
f0e86444332bf0d5858d609ab5b5ad0f3cf355f9
|
|
train_06087
| 2026-01-01T00:00:00
|
Mixture-of-Experts (MoE) for code
|
explain
|
intermediate
|
Task: explain
Topic: Mixture-of-Experts (MoE) for code
Difficulty: intermediate
Target language: Java
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[] |
{
"target_language": "Java",
"developer_needs": [
"reproducibility",
"auditability",
"tests_are_truth",
"tooling"
],
"moe_experts": [
"governance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
a3df3afa142d49d861a56572212e6fed3098d16f
|
|
train_06088
| 2026-01-01T00:00:00
|
Dataset curation pipelines (filter, dedupe, quality)
|
failure_analysis
|
intermediate
|
Task: failure_analysis
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: intermediate
Target language: Java
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
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": [
"repo_scale_reasoning",
"auditability",
"reproducibility",
"cost_latency_tradeoffs"
],
"moe_experts": [
"agentic_systems_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
0a5c405c8085942d71249383840899beec1aa417
|
|
train_06089
| 2026-01-01T00:00:00
|
Agentic coding systems (plan→edit→test→reflect)
|
explain
|
intermediate
|
Task: explain
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.
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": [
"cost_latency_tradeoffs",
"tests_are_truth",
"ci_integration",
"security_gates"
],
"moe_experts": [
"data_curation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
7046562a89f3ccf949aae9d74035aef0f435870b
|
|
train_06090
| 2026-01-01T00:00:00
|
Model merging, distillation, and continued pretraining
|
eval
|
expert
|
Task: eval
Topic: Model merging, distillation, and continued pretraining
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.
Eval:
pass@k, time-to-green, regressions, diff size
|
[] |
{
"target_language": "C#",
"developer_needs": [
"repo_scale_reasoning",
"cost_latency_tradeoffs",
"ci_integration",
"tests_are_truth"
],
"moe_experts": [
"agentic_systems_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
49ac79c34a8cd0ca0abfe54a1146fe411d296de6
|
|
train_06091
| 2026-01-01T00:00:00
|
Extended context and repo-scale understanding
|
code
|
expert
|
Task: code
Topic: Extended context and repo-scale understanding
Difficulty: expert
Target language: Java
Context: 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": [
"cost_latency_tradeoffs",
"ci_integration",
"security_gates",
"reproducibility"
],
"moe_experts": [
"security_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
e0dac6ca89a26bb716bdef4bfaf2efdee80498ce
|
|
train_06092
| 2026-01-01T00:00:00
|
Self-improving agents and feedback loops
|
agent_loop
|
expert
|
Task: agent_loop
Topic: Self-improving agents and feedback loops
Difficulty: expert
Target language: Go
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
|
[] |
{
"target_language": "Go",
"developer_needs": [
"security_gates",
"ci_integration",
"tooling",
"governance"
],
"moe_experts": [
"data_curation_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
e4615d90119f5fc94507145e43cdbf3f3a1cde40
|
|
train_06093
| 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: 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",
"evaluation_metrics",
"security_gates",
"documentation"
],
"moe_experts": [
"evaluation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
77d4ff7be59b38e1d883411227fc1f19cd574ed1
|
|
train_06094
| 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: 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": [
"evaluation_metrics",
"auditability",
"tests_are_truth",
"governance"
],
"moe_experts": [
"security_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
cf2c78e0ba690df7ca6fb58c1eed7d72599fad79
|
|
train_06095
| 2026-01-01T00:00:00
|
Tool calling, sandboxes, and CI integration
|
code
|
expert
|
Task: code
Topic: Tool calling, sandboxes, and CI integration
Difficulty: expert
Target language: Bash
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[] |
{
"target_language": "Bash",
"developer_needs": [
"auditability",
"ci_integration",
"repo_scale_reasoning",
"tooling"
],
"moe_experts": [
"governance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
62d2617056c2b717d1866d6fbfd5a769210fda89
|
|
train_06096
| 2026-01-01T00:00:00
|
Dataset curation pipelines (filter, dedupe, quality)
|
compare
|
advanced
|
Task: compare
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: advanced
Target language: SQL
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
|
[] |
{
"target_language": "SQL",
"developer_needs": [
"tooling",
"evaluation_metrics",
"tests_are_truth",
"governance"
],
"moe_experts": [
"governance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
5d2af4ee04bc6b9b417c4c580b103643b40ea49e
|
|
train_06097
| 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: 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
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Python",
"developer_needs": [
"auditability",
"security_gates",
"documentation",
"repo_scale_reasoning"
],
"moe_experts": [
"security_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
bc11e6fc8110586b0f0100862af05b6ce8971adb
|
|
train_06098
| 2026-01-01T00:00:00
|
Self-improving agents and feedback loops
|
agent_loop
|
expert
|
Task: agent_loop
Topic: Self-improving agents and feedback loops
Difficulty: expert
Target language: TypeScript
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
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": "TypeScript",
"developer_needs": [
"evaluation_metrics",
"security_gates",
"reproducibility",
"tooling"
],
"moe_experts": [
"evaluation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
dfdc02ca850dad0c269e6c96386fef74c3c02404
|
|
train_06099
| 2026-01-01T00:00:00
|
Dataset curation pipelines (filter, dedupe, quality)
|
explain
|
intermediate
|
Task: explain
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: intermediate
Target language: 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": [
"evaluation_metrics",
"tests_are_truth",
"cost_latency_tradeoffs",
"auditability"
],
"moe_experts": [
"coding_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
8fb5bd816e1dc4f331d2afc070093541e6274ec7
|
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.