id
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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
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|---|---|---|---|---|---|---|---|---|---|---|
train_11900
| 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": [
"reproducibility",
"tests_are_truth",
"evaluation_metrics",
"auditability"
],
"moe_experts": [
"data_curation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
0cafe257c6eda478ac5b034f17c4f7c06fbe36b4
|
|
train_11901
| 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: 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.
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": [
"cost_latency_tradeoffs",
"auditability",
"reproducibility",
"evaluation_metrics"
],
"moe_experts": [
"governance_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
33b41372fc2f5e8fbbdf6c0f08f778e89b02f595
|
|
train_11902
| 2026-01-01T00:00:00
|
Model merging, distillation, and continued pretraining
|
compare
|
expert
|
Task: compare
Topic: Model merging, distillation, and continued pretraining
Difficulty: expert
Target language: 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.
Compare: capability, cost, latency, reliability
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "TypeScript",
"developer_needs": [
"cost_latency_tradeoffs",
"tooling",
"documentation",
"evaluation_metrics"
],
"moe_experts": [
"data_curation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
94367700160f03c2022e5755dd63cb3c159f45af
|
|
train_11903
| 2026-01-01T00:00:00
|
Code-specialized model families and sizing tradeoffs
|
review
|
expert
|
Task: review
Topic: Code-specialized model families and sizing tradeoffs
Difficulty: expert
Target language: JavaScript
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Review: correctness, security, performance, governance
|
[] |
{
"target_language": "JavaScript",
"developer_needs": [
"tests_are_truth",
"ci_integration",
"auditability",
"repo_scale_reasoning"
],
"moe_experts": [
"coding_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
77ed8ff11481e12ae6128fce11433eb867917a64
|
|
train_11904
| 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: 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",
"cost_latency_tradeoffs",
"tooling",
"evaluation_metrics"
],
"moe_experts": [
"coding_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
084265739af59f6b24f5d90517aa5f222df2fbff
|
|
train_11905
| 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: 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.
Eval:
pass@k, time-to-green, regressions, diff size
|
[] |
{
"target_language": "SQL",
"developer_needs": [
"reproducibility",
"cost_latency_tradeoffs",
"repo_scale_reasoning",
"auditability"
],
"moe_experts": [
"security_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
b1ca289769414925a8e8e6c8141c97bca5c96bc1
|
|
train_11906
| 2026-01-01T00:00:00
|
Governance, provenance, and licensing for code data
|
compare
|
advanced
|
Task: compare
Topic: Governance, provenance, and licensing for code data
Difficulty: advanced
Target language: Java
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
|
[
"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": [
"coding_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
3f511949ed9d49cd0c666f1bab4a2d683a8df7ed
|
|
train_11907
| 2026-01-01T00:00:00
|
Dataset curation pipelines (filter, dedupe, quality)
|
code
|
advanced
|
Task: code
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: advanced
Target language: JavaScript
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "JavaScript",
"developer_needs": [
"security_gates",
"ci_integration",
"auditability",
"repo_scale_reasoning"
],
"moe_experts": [
"security_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
11bb0f95f2da3159a3a23b56b97c3de63d797872
|
|
train_11908
| 2026-01-01T00:00:00
|
SWE-bench style real-repo evaluation
|
eval
|
advanced
|
Task: eval
Topic: SWE-bench style real-repo evaluation
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.
Eval:
pass@k, time-to-green, regressions, diff size
|
[] |
{
"target_language": "TypeScript",
"developer_needs": [
"repo_scale_reasoning",
"ci_integration",
"evaluation_metrics",
"tests_are_truth"
],
"moe_experts": [
"security_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
625088aec6459253d0bc1fcc0ed27490ce2d3f96
|
|
train_11909
| 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: TypeScript
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
|
[] |
{
"target_language": "TypeScript",
"developer_needs": [
"evaluation_metrics",
"repo_scale_reasoning",
"governance",
"cost_latency_tradeoffs"
],
"moe_experts": [
"performance_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
3f734246ac54c6fbe45a2a4b711fb7c6174f4277
|
|
train_11910
| 2026-01-01T00:00:00
|
Reasoning-first coding models and tunable deliberation
|
code
|
advanced
|
Task: code
Topic: Reasoning-first coding models and tunable deliberation
Difficulty: advanced
Target language: 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": [
"repo_scale_reasoning",
"reproducibility",
"auditability",
"ci_integration"
],
"moe_experts": [
"security_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
aa80581c6a84ad2da7f2256cb7cd99990822d2c5
|
|
train_11911
| 2026-01-01T00:00:00
|
Latency, cost, and reliability optimization
|
patch_diff
|
expert
|
Task: patch_diff
Topic: Latency, cost, and reliability optimization
Difficulty: expert
Target language: 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": [
"cost_latency_tradeoffs",
"governance",
"evaluation_metrics",
"reproducibility"
],
"moe_experts": [
"agentic_systems_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
abe4f7067aef9813317234f1a04971b97a61b68d
|
|
train_11912
| 2026-01-01T00:00:00
|
Governance, provenance, and licensing for code data
|
agent_loop
|
advanced
|
Task: agent_loop
Topic: Governance, provenance, and licensing for code data
Difficulty: advanced
Target language: 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.
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": [
"reproducibility",
"cost_latency_tradeoffs",
"tests_are_truth",
"evaluation_metrics"
],
"moe_experts": [
"coding_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
3e16608323d5ee051d043cf2e91a0f9a10963921
|
|
train_11913
| 2026-01-01T00:00:00
|
Latency, cost, and reliability optimization
|
patch_diff
|
expert
|
Task: patch_diff
Topic: Latency, cost, and reliability optimization
Difficulty: expert
Target language: TypeScript
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Patch (diff-style):
```diff
- if x == 0:
- return 1/x
+ if x == 0:
+ raise ValueError('division by zero')
```
Acceptance:
- Tests pass
- No new regressions
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "TypeScript",
"developer_needs": [
"ci_integration",
"tooling",
"governance",
"repo_scale_reasoning"
],
"moe_experts": [
"performance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
d09aff1741f7d5fee467f035ce0a808a1271388f
|
|
train_11914
| 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: Python
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
|
[] |
{
"target_language": "Python",
"developer_needs": [
"tooling",
"documentation",
"cost_latency_tradeoffs",
"tests_are_truth"
],
"moe_experts": [
"coding_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
9bf6f3cedbffd8681ab7105b2201fce0fc102d1a
|
|
train_11915
| 2026-01-01T00:00:00
|
Extended context and repo-scale understanding
|
design
|
expert
|
Task: design
Topic: Extended context and repo-scale understanding
Difficulty: expert
Target language: SQL
Context: 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": "SQL",
"developer_needs": [
"documentation",
"ci_integration",
"cost_latency_tradeoffs",
"evaluation_metrics"
],
"moe_experts": [
"data_curation_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
46dc563a87ae6761b986a82142c304fca2157be2
|
|
train_11916
| 2026-01-01T00:00:00
|
Code-specialized model families and sizing tradeoffs
|
compare
|
advanced
|
Task: compare
Topic: Code-specialized model families and sizing tradeoffs
Difficulty: advanced
Target language: Bash
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
|
[] |
{
"target_language": "Bash",
"developer_needs": [
"documentation",
"reproducibility",
"security_gates",
"evaluation_metrics"
],
"moe_experts": [
"governance_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
480aaea3325a2a5d379fb0ef2a58551f820febc2
|
|
train_11917
| 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: TypeScript
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
|
[] |
{
"target_language": "TypeScript",
"developer_needs": [
"tooling",
"documentation",
"ci_integration",
"evaluation_metrics"
],
"moe_experts": [
"data_curation_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
66d69fed7220905aeb7545ee1b05e6794588c9f8
|
|
train_11918
| 2026-01-01T00:00:00
|
Code-specialized model families and sizing tradeoffs
|
compare
|
intermediate
|
Task: compare
Topic: Code-specialized model families and sizing tradeoffs
Difficulty: intermediate
Target language: Python
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
|
[] |
{
"target_language": "Python",
"developer_needs": [
"reproducibility",
"tests_are_truth",
"cost_latency_tradeoffs",
"governance"
],
"moe_experts": [
"agentic_systems_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
4a86aa65b4dcf0ca85131eac93723b2738fedbb5
|
|
train_11919
| 2026-01-01T00:00:00
|
Dataset curation pipelines (filter, dedupe, quality)
|
eval
|
intermediate
|
Task: eval
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: intermediate
Target language: Python
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Python",
"developer_needs": [
"evaluation_metrics",
"governance",
"tooling",
"cost_latency_tradeoffs"
],
"moe_experts": [
"agentic_systems_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
ee43ccaac1fbc6f6ccd119aed628638306a37703
|
|
train_11920
| 2026-01-01T00:00:00
|
Self-improving agents and feedback loops
|
agent_loop
|
advanced
|
Task: agent_loop
Topic: Self-improving agents and feedback loops
Difficulty: advanced
Target language: Python
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
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",
"ci_integration",
"security_gates",
"evaluation_metrics"
],
"moe_experts": [
"data_curation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
54e22fe218a9e3f1112f67564a36a39279d68fe9
|
|
train_11921
| 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: 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": [
"tooling",
"cost_latency_tradeoffs",
"tests_are_truth",
"security_gates"
],
"moe_experts": [
"performance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
6775ea14959ea36586a8c1e411d740f3c995661f
|
|
train_11922
| 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: Bash
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Bash",
"developer_needs": [
"documentation",
"auditability",
"evaluation_metrics",
"repo_scale_reasoning"
],
"moe_experts": [
"coding_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
afef1afa86848f1ca433423fe791c43e92a513a7
|
|
train_11923
| 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: 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": [
"documentation",
"governance",
"cost_latency_tradeoffs",
"tests_are_truth"
],
"moe_experts": [
"agentic_systems_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
406404c9556cc3faf204c06a20646226c6048480
|
|
train_11924
| 2026-01-01T00:00:00
|
Agentic coding systems (plan→edit→test→reflect)
|
failure_analysis
|
expert
|
Task: failure_analysis
Topic: Agentic coding systems (plan→edit→test→reflect)
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.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
|
[] |
{
"target_language": "Bash",
"developer_needs": [
"tooling",
"security_gates",
"ci_integration",
"reproducibility"
],
"moe_experts": [
"agentic_systems_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
c4bc64313633d3557cd010779b62202210f3469c
|
|
train_11925
| 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: 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": [
"repo_scale_reasoning",
"ci_integration",
"governance",
"tooling"
],
"moe_experts": [
"agentic_systems_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
4e57c4265c8c7844e06cd0577c05cde1e5518983
|
|
train_11926
| 2026-01-01T00:00:00
|
Secure code generation and policy gates
|
eval
|
intermediate
|
Task: eval
Topic: Secure code generation and policy gates
Difficulty: intermediate
Target language: JavaScript
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
|
[] |
{
"target_language": "JavaScript",
"developer_needs": [
"documentation",
"security_gates",
"repo_scale_reasoning",
"auditability"
],
"moe_experts": [
"data_curation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
d58a125cedfaee93464607b768803c96aeba1e2c
|
|
train_11927
| 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: Go
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Review: correctness, security, performance, governance
|
[] |
{
"target_language": "Go",
"developer_needs": [
"governance",
"documentation",
"tests_are_truth",
"evaluation_metrics"
],
"moe_experts": [
"governance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
030437eff15793829f638aad99011b3af30164bd
|
|
train_11928
| 2026-01-01T00:00:00
|
SWE-bench style real-repo evaluation
|
failure_analysis
|
intermediate
|
Task: failure_analysis
Topic: SWE-bench style real-repo evaluation
Difficulty: intermediate
Target language: 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
|
[
"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",
"governance",
"documentation",
"reproducibility"
],
"moe_experts": [
"data_curation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
bea4c214cf1a535cf8e3bfb63d9638eeb8a485dd
|
|
train_11929
| 2026-01-01T00:00:00
|
Latency, cost, and reliability optimization
|
data_pipeline
|
expert
|
Task: data_pipeline
Topic: Latency, cost, and reliability optimization
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.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Python",
"developer_needs": [
"tests_are_truth",
"evaluation_metrics",
"auditability",
"governance"
],
"moe_experts": [
"evaluation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
a54fb0d8c32a56b206fee1bd96552ad15a314ec3
|
|
train_11930
| 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: 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.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
|
[] |
{
"target_language": "SQL",
"developer_needs": [
"tooling",
"governance",
"documentation",
"security_gates"
],
"moe_experts": [
"security_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
418809d5f9f4dd72915460fa5e6a1b72e7a127a1
|
|
train_11931
| 2026-01-01T00:00:00
|
Self-improving agents and feedback loops
|
compare
|
expert
|
Task: compare
Topic: Self-improving agents and feedback loops
Difficulty: expert
Target language: Python
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Python",
"developer_needs": [
"governance",
"tests_are_truth",
"tooling",
"ci_integration"
],
"moe_experts": [
"data_curation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
e2456e30cb5bbea480d6de2f98b389222e01350f
|
|
train_11932
| 2026-01-01T00:00:00
|
Code-specialized model families and sizing tradeoffs
|
patch_diff
|
advanced
|
Task: patch_diff
Topic: Code-specialized model families and sizing tradeoffs
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.
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": [
"tests_are_truth",
"cost_latency_tradeoffs",
"reproducibility",
"security_gates"
],
"moe_experts": [
"security_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
ecd0137f69c9c0bc25f4b08cdf161d0f1ba7fd65
|
|
train_11933
| 2026-01-01T00:00:00
|
Tool calling, sandboxes, and CI integration
|
agent_loop
|
advanced
|
Task: agent_loop
Topic: Tool calling, sandboxes, and CI integration
Difficulty: advanced
Target language: JavaScript
Context: 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": [
"tests_are_truth",
"auditability",
"documentation",
"governance"
],
"moe_experts": [
"coding_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
1f60b6dc4250fb54429e3cc447ca96d58cd2cd9a
|
|
train_11934
| 2026-01-01T00:00:00
|
SWE-bench style real-repo evaluation
|
review
|
intermediate
|
Task: review
Topic: SWE-bench style real-repo evaluation
Difficulty: intermediate
Target language: 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": [
"tests_are_truth",
"repo_scale_reasoning",
"auditability",
"reproducibility"
],
"moe_experts": [
"security_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
44d6a748a84a15eb50fddb2b08e41b5fe3ee5a7c
|
|
train_11935
| 2026-01-01T00:00:00
|
Mixture-of-Experts (MoE) for code
|
compare
|
intermediate
|
Task: compare
Topic: Mixture-of-Experts (MoE) for code
Difficulty: intermediate
Target language: Python
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
|
[] |
{
"target_language": "Python",
"developer_needs": [
"repo_scale_reasoning",
"governance",
"cost_latency_tradeoffs",
"evaluation_metrics"
],
"moe_experts": [
"security_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
285cdec25b1d30123cd44fa206b52f3e391e8634
|
|
train_11936
| 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: 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
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "SQL",
"developer_needs": [
"repo_scale_reasoning",
"ci_integration",
"evaluation_metrics",
"security_gates"
],
"moe_experts": [
"security_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
54fa13c0d817d38ba5c58eb152a9459bcdbe4073
|
|
train_11937
| 2026-01-01T00:00:00
|
Code-specialized model families and sizing tradeoffs
|
compare
|
advanced
|
Task: compare
Topic: Code-specialized model families and sizing tradeoffs
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
|
[
"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",
"reproducibility",
"repo_scale_reasoning"
],
"moe_experts": [
"governance_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
e8085fe2b613a6702a8db8ac7f3ad0fb2fc3f493
|
|
train_11938
| 2026-01-01T00:00:00
|
Reasoning-first coding models and tunable deliberation
|
agent_loop
|
expert
|
Task: agent_loop
Topic: Reasoning-first coding models and tunable deliberation
Difficulty: expert
Target language: Python
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
|
[] |
{
"target_language": "Python",
"developer_needs": [
"ci_integration",
"reproducibility",
"cost_latency_tradeoffs",
"auditability"
],
"moe_experts": [
"security_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
2d628ff621ec93f6dafa80ec6836e2792af97fc4
|
|
train_11939
| 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: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "C#",
"developer_needs": [
"repo_scale_reasoning",
"evaluation_metrics",
"cost_latency_tradeoffs",
"tooling"
],
"moe_experts": [
"governance_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
23a6549553e3d1fb8c483fc3ac801cb33797f4fa
|
|
train_11940
| 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: 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
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Java",
"developer_needs": [
"auditability",
"tooling",
"security_gates",
"evaluation_metrics"
],
"moe_experts": [
"coding_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
6824960fdd48b57a08e76ed6f001ea39f8e349b8
|
|
train_11941
| 2026-01-01T00:00:00
|
Dataset curation pipelines (filter, dedupe, quality)
|
code
|
advanced
|
Task: code
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: advanced
Target language: 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",
"cost_latency_tradeoffs",
"security_gates",
"tooling"
],
"moe_experts": [
"evaluation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
e69dd797687dd8726ae30bbea84094697b7bdfd4
|
|
train_11942
| 2026-01-01T00:00:00
|
Code-specialized model families and sizing tradeoffs
|
data_pipeline
|
advanced
|
Task: data_pipeline
Topic: Code-specialized model families and sizing tradeoffs
Difficulty: advanced
Target language: Go
Context: 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": [
"tests_are_truth",
"ci_integration",
"cost_latency_tradeoffs",
"governance"
],
"moe_experts": [
"evaluation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
12fe1d0a85373b8fc52d2aa1ac44736924633daa
|
|
train_11943
| 2026-01-01T00:00:00
|
Model merging, distillation, and continued pretraining
|
code
|
expert
|
Task: code
Topic: Model merging, distillation, and continued pretraining
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": [
"reproducibility",
"tests_are_truth",
"evaluation_metrics",
"documentation"
],
"moe_experts": [
"evaluation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
8534ae78ecf4e49327adec448f8952a924586265
|
|
train_11944
| 2026-01-01T00:00:00
|
Reasoning-first coding models and tunable deliberation
|
design
|
expert
|
Task: design
Topic: Reasoning-first coding models and tunable deliberation
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": [
"ci_integration",
"cost_latency_tradeoffs",
"reproducibility",
"evaluation_metrics"
],
"moe_experts": [
"evaluation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
b472e7ba8c596e5b4e5385b07cc47ed2a528ab7e
|
|
train_11945
| 2026-01-01T00:00:00
|
Secure code generation and policy gates
|
review
|
intermediate
|
Task: review
Topic: Secure code generation and policy gates
Difficulty: intermediate
Target language: Go
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Review: correctness, security, performance, governance
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Go",
"developer_needs": [
"governance",
"repo_scale_reasoning",
"tests_are_truth",
"ci_integration"
],
"moe_experts": [
"agentic_systems_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
c60a044fa4bbd720e897a0644dee29baf1e9b6c9
|
|
train_11946
| 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: 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": [
"governance",
"reproducibility",
"evaluation_metrics",
"ci_integration"
],
"moe_experts": [
"performance_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
8b9324d966f10c01f689a810bfae40711820c527
|
|
train_11947
| 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: 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": [
"auditability",
"tooling",
"cost_latency_tradeoffs",
"tests_are_truth"
],
"moe_experts": [
"performance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
5976639c522c4bcb35f7f7e15bf16b06ae114bdd
|
|
train_11948
| 2026-01-01T00:00:00
|
Secure code generation and policy gates
|
review
|
expert
|
Task: review
Topic: Secure code generation and policy gates
Difficulty: expert
Target language: TypeScript
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Review: correctness, security, performance, governance
|
[
"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",
"documentation",
"ci_integration",
"tooling"
],
"moe_experts": [
"data_curation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
64aef519872aa1b1aff39bce87373c39836bc4e1
|
|
train_11949
| 2026-01-01T00:00:00
|
Code-specialized model families and sizing tradeoffs
|
review
|
intermediate
|
Task: review
Topic: Code-specialized model families and sizing tradeoffs
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.
Review: correctness, security, performance, governance
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Java",
"developer_needs": [
"tooling",
"governance",
"ci_integration",
"documentation"
],
"moe_experts": [
"data_curation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
e171b6dd610e0b47499b83c1c85fb70a5126e26b
|
|
train_11950
| 2026-01-01T00:00:00
|
Reasoning-first coding models and tunable deliberation
|
data_pipeline
|
intermediate
|
Task: data_pipeline
Topic: Reasoning-first coding models and tunable deliberation
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.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
|
[] |
{
"target_language": "Rust",
"developer_needs": [
"evaluation_metrics",
"governance",
"tests_are_truth",
"ci_integration"
],
"moe_experts": [
"performance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
6778e3ea09eec491b73a657870c8845530bd54ee
|
|
train_11951
| 2026-01-01T00:00:00
|
Dataset curation pipelines (filter, dedupe, quality)
|
eval
|
intermediate
|
Task: eval
Topic: Dataset curation pipelines (filter, dedupe, quality)
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.
Eval:
pass@k, time-to-green, regressions, diff size
|
[] |
{
"target_language": "Java",
"developer_needs": [
"auditability",
"security_gates",
"tests_are_truth",
"governance"
],
"moe_experts": [
"data_curation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
ad3edd5ec62ebe89bfc19f5f0ec6c583794a767b
|
|
train_11952
| 2026-01-01T00:00:00
|
Secure code generation and policy gates
|
explain
|
expert
|
Task: explain
Topic: Secure code generation and policy gates
Difficulty: expert
Target language: Java
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[] |
{
"target_language": "Java",
"developer_needs": [
"reproducibility",
"evaluation_metrics",
"security_gates",
"documentation"
],
"moe_experts": [
"evaluation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
97e54083aaee83d4935453c36b99f61bb612e244
|
|
train_11953
| 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: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
|
[] |
{
"target_language": "Go",
"developer_needs": [
"tooling",
"governance",
"repo_scale_reasoning",
"documentation"
],
"moe_experts": [
"performance_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
b608634be04a17337913f4f80f5aa505b9d0432a
|
|
train_11954
| 2026-01-01T00:00:00
|
Latency, cost, and reliability optimization
|
eval
|
intermediate
|
Task: eval
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.
Eval:
pass@k, time-to-green, regressions, diff size
|
[] |
{
"target_language": "JavaScript",
"developer_needs": [
"security_gates",
"ci_integration",
"auditability",
"cost_latency_tradeoffs"
],
"moe_experts": [
"security_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
d62515a2d04d731be24552fdea9ecb041f0b1a87
|
|
train_11955
| 2026-01-01T00:00:00
|
SWE-bench style real-repo evaluation
|
eval
|
intermediate
|
Task: eval
Topic: SWE-bench style real-repo evaluation
Difficulty: intermediate
Target language: 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": [
"cost_latency_tradeoffs",
"ci_integration",
"documentation",
"tooling"
],
"moe_experts": [
"agentic_systems_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
f7c920d4b9076f3cdc69283a456cde4b4daf51eb
|
|
train_11956
| 2026-01-01T00:00:00
|
Reasoning-first coding models and tunable deliberation
|
agent_loop
|
intermediate
|
Task: agent_loop
Topic: Reasoning-first coding models and tunable deliberation
Difficulty: intermediate
Target language: Rust
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Rust",
"developer_needs": [
"security_gates",
"documentation",
"tests_are_truth",
"cost_latency_tradeoffs"
],
"moe_experts": [
"coding_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
a66999cb7b3285fb30a1b9da232e2f8cb3ebaf75
|
|
train_11957
| 2026-01-01T00:00:00
|
Model merging, distillation, and continued pretraining
|
failure_analysis
|
advanced
|
Task: failure_analysis
Topic: Model merging, distillation, and continued pretraining
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
|
[] |
{
"target_language": "Rust",
"developer_needs": [
"documentation",
"tooling",
"auditability",
"ci_integration"
],
"moe_experts": [
"performance_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
26a7a31543249f832efa2d875a1b57431a2b1e8a
|
|
train_11958
| 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: 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.
Loop: Plan → Edit → Test → Reflect → Human gate
|
[] |
{
"target_language": "Python",
"developer_needs": [
"repo_scale_reasoning",
"documentation",
"governance",
"auditability"
],
"moe_experts": [
"coding_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
56847a90fe8b0ff8b828121106d97092690082d7
|
|
train_11959
| 2026-01-01T00:00:00
|
Reasoning-first coding models and tunable deliberation
|
eval
|
advanced
|
Task: eval
Topic: Reasoning-first coding models and tunable deliberation
Difficulty: advanced
Target language: SQL
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
|
[] |
{
"target_language": "SQL",
"developer_needs": [
"governance",
"evaluation_metrics",
"repo_scale_reasoning",
"tooling"
],
"moe_experts": [
"data_curation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
631ff12d132748acff54f08e1a1baff70b3f001d
|
|
train_11960
| 2026-01-01T00:00:00
|
Latency, cost, and reliability optimization
|
eval
|
advanced
|
Task: eval
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.
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": [
"tooling",
"governance",
"reproducibility",
"ci_integration"
],
"moe_experts": [
"evaluation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
4de4b65480836023245f92f5a13d76238d3c5b96
|
|
train_11961
| 2026-01-01T00:00:00
|
Agentic coding systems (plan→edit→test→reflect)
|
design
|
expert
|
Task: design
Topic: Agentic coding systems (plan→edit→test→reflect)
Difficulty: expert
Target language: 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
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Go",
"developer_needs": [
"security_gates",
"tests_are_truth",
"documentation",
"repo_scale_reasoning"
],
"moe_experts": [
"evaluation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
24983bfc251a6ec44496cf06055852819998e4e2
|
|
train_11962
| 2026-01-01T00:00:00
|
Secure code generation and policy gates
|
review
|
advanced
|
Task: review
Topic: Secure code generation and policy gates
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.
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": [
"ci_integration",
"evaluation_metrics",
"tests_are_truth",
"documentation"
],
"moe_experts": [
"evaluation_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
3d33449e73cf010ddcc74254787568f4613354b7
|
|
train_11963
| 2026-01-01T00:00:00
|
Multimodal dev workflows (docs, diagrams, traces)
|
compare
|
expert
|
Task: compare
Topic: Multimodal dev workflows (docs, diagrams, traces)
Difficulty: expert
Target language: C#
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
|
[] |
{
"target_language": "C#",
"developer_needs": [
"ci_integration",
"governance",
"auditability",
"documentation"
],
"moe_experts": [
"data_curation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
df630987ac2a0881482bc88a618b37190daeaae0
|
|
train_11964
| 2026-01-01T00:00:00
|
Self-improving agents and feedback loops
|
patch_diff
|
advanced
|
Task: patch_diff
Topic: Self-improving agents and feedback loops
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.
Patch (diff-style):
```diff
- if x == 0:
- return 1/x
+ if x == 0:
+ raise ValueError('division by zero')
```
Acceptance:
- Tests pass
- No new regressions
|
[] |
{
"target_language": "Rust",
"developer_needs": [
"security_gates",
"repo_scale_reasoning",
"documentation",
"cost_latency_tradeoffs"
],
"moe_experts": [
"data_curation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
6929ddbd1f6d448c385c8b69eb2359082b8cf1cc
|
|
train_11965
| 2026-01-01T00:00:00
|
Agentic coding systems (plan→edit→test→reflect)
|
review
|
expert
|
Task: review
Topic: Agentic coding systems (plan→edit→test→reflect)
Difficulty: expert
Target language: Bash
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Review: correctness, security, performance, governance
|
[] |
{
"target_language": "Bash",
"developer_needs": [
"cost_latency_tradeoffs",
"documentation",
"tests_are_truth",
"reproducibility"
],
"moe_experts": [
"evaluation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
8c404ab3b93d9d4fb08b2f87816e3b6c9e2fcd0f
|
|
train_11966
| 2026-01-01T00:00:00
|
SWE-bench style real-repo evaluation
|
review
|
expert
|
Task: review
Topic: SWE-bench style real-repo evaluation
Difficulty: expert
Target language: 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.
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": [
"repo_scale_reasoning",
"tooling",
"tests_are_truth",
"ci_integration"
],
"moe_experts": [
"governance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
5a1a084ef74bfcb82781072c49105b13500f8ae6
|
|
train_11967
| 2026-01-01T00:00:00
|
Reasoning-first coding models and tunable deliberation
|
failure_analysis
|
intermediate
|
Task: failure_analysis
Topic: Reasoning-first coding models and tunable deliberation
Difficulty: intermediate
Target language: 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.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
|
[] |
{
"target_language": "Go",
"developer_needs": [
"cost_latency_tradeoffs",
"repo_scale_reasoning",
"security_gates",
"tooling"
],
"moe_experts": [
"governance_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
e257724b8711c50f7db02599a85a82b0c023f1f4
|
|
train_11968
| 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: Go
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Patch (diff-style):
```diff
- if x == 0:
- return 1/x
+ if x == 0:
+ raise ValueError('division by zero')
```
Acceptance:
- Tests pass
- No new regressions
|
[] |
{
"target_language": "Go",
"developer_needs": [
"governance",
"tests_are_truth",
"tooling",
"documentation"
],
"moe_experts": [
"performance_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
f5470e944ce54437a10d01c5ba69eb7b34bde6d7
|
|
train_11969
| 2026-01-01T00:00:00
|
Reasoning-first coding models and tunable deliberation
|
eval
|
expert
|
Task: eval
Topic: Reasoning-first coding models and tunable deliberation
Difficulty: expert
Target language: Java
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
|
[] |
{
"target_language": "Java",
"developer_needs": [
"security_gates",
"tooling",
"tests_are_truth",
"reproducibility"
],
"moe_experts": [
"coding_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
775554de9a4e6d4a3589555a81b6ea3c9f056dc5
|
|
train_11970
| 2026-01-01T00:00:00
|
Dataset curation pipelines (filter, dedupe, quality)
|
review
|
advanced
|
Task: review
Topic: Dataset curation pipelines (filter, dedupe, quality)
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.
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": [
"governance",
"evaluation_metrics",
"security_gates",
"cost_latency_tradeoffs"
],
"moe_experts": [
"performance_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
d15b6df9968abdc112b55a39361628ecd795d507
|
|
train_11971
| 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: 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.
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",
"tests_are_truth",
"repo_scale_reasoning",
"documentation"
],
"moe_experts": [
"data_curation_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
e459bc3e15dd0a0039c251349a6cf52cef5b9a01
|
|
train_11972
| 2026-01-01T00:00:00
|
Self-improving agents and feedback loops
|
code
|
intermediate
|
Task: code
Topic: Self-improving agents and feedback loops
Difficulty: intermediate
Target language: TypeScript
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[] |
{
"target_language": "TypeScript",
"developer_needs": [
"tooling",
"tests_are_truth",
"security_gates",
"ci_integration"
],
"moe_experts": [
"coding_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
6cf2355ef8a20943b546e92e21b493f66a2063b0
|
|
train_11973
| 2026-01-01T00:00:00
|
Mixture-of-Experts (MoE) for code
|
code
|
advanced
|
Task: code
Topic: Mixture-of-Experts (MoE) for code
Difficulty: advanced
Target language: 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": [
"repo_scale_reasoning",
"security_gates",
"tooling",
"ci_integration"
],
"moe_experts": [
"data_curation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
629dc048a2b99cb15142a4941b71bf8d0fc3c279
|
|
train_11974
| 2026-01-01T00:00:00
|
Code-specialized model families and sizing tradeoffs
|
compare
|
expert
|
Task: compare
Topic: Code-specialized model families and sizing tradeoffs
Difficulty: expert
Target language: 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.
Compare: capability, cost, latency, reliability
|
[] |
{
"target_language": "JavaScript",
"developer_needs": [
"evaluation_metrics",
"ci_integration",
"tooling",
"cost_latency_tradeoffs"
],
"moe_experts": [
"performance_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
cb4dc2f49d2723095d657a4ba4854e1f84cc033d
|
|
train_11975
| 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: Python
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Python",
"developer_needs": [
"evaluation_metrics",
"cost_latency_tradeoffs",
"documentation",
"governance"
],
"moe_experts": [
"data_curation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
7ac96022d3f2c105cc1f9911547b40b8f2c0a326
|
|
train_11976
| 2026-01-01T00:00:00
|
Governance, provenance, and licensing for code data
|
eval
|
expert
|
Task: eval
Topic: Governance, provenance, and licensing for code data
Difficulty: expert
Target language: Python
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
|
[] |
{
"target_language": "Python",
"developer_needs": [
"repo_scale_reasoning",
"tooling",
"reproducibility",
"governance"
],
"moe_experts": [
"evaluation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
124f26ee2af8450dac7eaed5ba194fa7ca876790
|
|
train_11977
| 2026-01-01T00:00:00
|
Extended context and repo-scale understanding
|
agent_loop
|
advanced
|
Task: agent_loop
Topic: Extended context and repo-scale understanding
Difficulty: advanced
Target language: 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.
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": [
"governance",
"reproducibility",
"auditability",
"repo_scale_reasoning"
],
"moe_experts": [
"data_curation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
0f15c3fa8fd41019eed24e62136fbb0c4249703a
|
|
train_11978
| 2026-01-01T00:00:00
|
Reasoning-first coding models and tunable deliberation
|
failure_analysis
|
advanced
|
Task: failure_analysis
Topic: Reasoning-first coding models and tunable deliberation
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.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
|
[] |
{
"target_language": "C#",
"developer_needs": [
"cost_latency_tradeoffs",
"documentation",
"tests_are_truth",
"reproducibility"
],
"moe_experts": [
"security_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
1f343dc38bb86575c70c1dceb7410ff77650e520
|
|
train_11979
| 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: 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
|
[] |
{
"target_language": "JavaScript",
"developer_needs": [
"repo_scale_reasoning",
"reproducibility",
"security_gates",
"cost_latency_tradeoffs"
],
"moe_experts": [
"governance_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
498453613423d9a197c377119b88731ef1f32b91
|
|
train_11980
| 2026-01-01T00:00:00
|
SWE-bench style real-repo evaluation
|
failure_analysis
|
advanced
|
Task: failure_analysis
Topic: SWE-bench style real-repo evaluation
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
|
[] |
{
"target_language": "Java",
"developer_needs": [
"tests_are_truth",
"documentation",
"cost_latency_tradeoffs",
"governance"
],
"moe_experts": [
"coding_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
b87edfce13e7cbc1351a38b585a630a9a674c958
|
|
train_11981
| 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: Python
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Python",
"developer_needs": [
"auditability",
"tooling",
"reproducibility",
"cost_latency_tradeoffs"
],
"moe_experts": [
"coding_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
02c1ffebfff5c97b1efb71334dad4cb2d5b4d865
|
|
train_11982
| 2026-01-01T00:00:00
|
Extended context and repo-scale understanding
|
review
|
expert
|
Task: review
Topic: Extended context and repo-scale understanding
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.
Review: correctness, security, performance, governance
|
[] |
{
"target_language": "Python",
"developer_needs": [
"reproducibility",
"repo_scale_reasoning",
"documentation",
"governance"
],
"moe_experts": [
"coding_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
20a9a9d47d85b9e811990e2d3a79b336b410a980
|
|
train_11983
| 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: 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": [
"tests_are_truth",
"repo_scale_reasoning",
"documentation",
"cost_latency_tradeoffs"
],
"moe_experts": [
"security_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
cc5720b0c8b5b20937c80cf4569beb54430e96b6
|
|
train_11984
| 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: 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": [
"security_gates",
"evaluation_metrics",
"ci_integration",
"governance"
],
"moe_experts": [
"agentic_systems_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
baa166d8ac42e06fe68db04154b9e49ee144860b
|
|
train_11985
| 2026-01-01T00:00:00
|
Mixture-of-Experts (MoE) for code
|
compare
|
intermediate
|
Task: compare
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.
Compare: capability, cost, latency, reliability
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "TypeScript",
"developer_needs": [
"tooling",
"ci_integration",
"tests_are_truth",
"repo_scale_reasoning"
],
"moe_experts": [
"governance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
4e537f7e6d39a5ca0cdc7b0dd014b01bcea4ba33
|
|
train_11986
| 2026-01-01T00:00:00
|
Latency, cost, and reliability optimization
|
patch_diff
|
intermediate
|
Task: patch_diff
Topic: Latency, cost, and reliability optimization
Difficulty: intermediate
Target language: Rust
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Patch (diff-style):
```diff
- if x == 0:
- return 1/x
+ if x == 0:
+ raise ValueError('division by zero')
```
Acceptance:
- Tests pass
- No new regressions
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Rust",
"developer_needs": [
"cost_latency_tradeoffs",
"security_gates",
"repo_scale_reasoning",
"governance"
],
"moe_experts": [
"evaluation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
500eaac51a4bda61540061e512dc7b675439df6c
|
|
train_11987
| 2026-01-01T00:00:00
|
Code-specialized model families and sizing tradeoffs
|
compare
|
intermediate
|
Task: compare
Topic: Code-specialized model families and sizing tradeoffs
Difficulty: intermediate
Target language: Bash
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
|
[] |
{
"target_language": "Bash",
"developer_needs": [
"documentation",
"security_gates",
"tests_are_truth",
"governance"
],
"moe_experts": [
"agentic_systems_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
30d2d742d9f4e72723400c48ee3fda26581ae30f
|
|
train_11988
| 2026-01-01T00:00:00
|
Self-improving agents and feedback loops
|
failure_analysis
|
intermediate
|
Task: failure_analysis
Topic: Self-improving agents and feedback loops
Difficulty: intermediate
Target language: Python
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
|
[] |
{
"target_language": "Python",
"developer_needs": [
"security_gates",
"cost_latency_tradeoffs",
"documentation",
"repo_scale_reasoning"
],
"moe_experts": [
"evaluation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
f2bd519b60c0afa8e1de002ba5fd748a622e1765
|
|
train_11989
| 2026-01-01T00:00:00
|
Extended context and repo-scale understanding
|
explain
|
advanced
|
Task: explain
Topic: Extended context and repo-scale understanding
Difficulty: advanced
Target language: 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": [
"security_gates",
"tooling",
"evaluation_metrics",
"auditability"
],
"moe_experts": [
"data_curation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
6d8ead2c234b5cdcde3512e42cdf0e93b9c32cb5
|
|
train_11990
| 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: 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": "TypeScript",
"developer_needs": [
"tooling",
"auditability",
"reproducibility",
"evaluation_metrics"
],
"moe_experts": [
"coding_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
76f058a0eb8512f6c6a10a5b2392814cbd4a4402
|
|
train_11991
| 2026-01-01T00:00:00
|
Reasoning-first coding models and tunable deliberation
|
review
|
intermediate
|
Task: review
Topic: Reasoning-first coding models and tunable deliberation
Difficulty: intermediate
Target language: C#
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Review: correctness, security, performance, governance
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "C#",
"developer_needs": [
"repo_scale_reasoning",
"cost_latency_tradeoffs",
"documentation",
"ci_integration"
],
"moe_experts": [
"coding_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
f9e6dd372d6f303439310902eb2a9855a31c3644
|
|
train_11992
| 2026-01-01T00:00:00
|
Tool calling, sandboxes, and CI integration
|
explain
|
intermediate
|
Task: explain
Topic: Tool calling, sandboxes, and CI integration
Difficulty: intermediate
Target language: 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": [
"ci_integration",
"reproducibility",
"repo_scale_reasoning",
"auditability"
],
"moe_experts": [
"performance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
e4e1b684927fff47867def3e7ee0d97fcd0b87b2
|
|
train_11993
| 2026-01-01T00:00:00
|
Latency, cost, and reliability optimization
|
review
|
advanced
|
Task: review
Topic: Latency, cost, and reliability optimization
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.
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": [
"ci_integration",
"governance",
"cost_latency_tradeoffs",
"auditability"
],
"moe_experts": [
"data_curation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
323149655b55cdf021d874a89584a0e1af28c28b
|
|
train_11994
| 2026-01-01T00:00:00
|
Mixture-of-Experts (MoE) for code
|
agent_loop
|
expert
|
Task: agent_loop
Topic: Mixture-of-Experts (MoE) for code
Difficulty: expert
Target language: C#
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
|
[] |
{
"target_language": "C#",
"developer_needs": [
"auditability",
"evaluation_metrics",
"tests_are_truth",
"cost_latency_tradeoffs"
],
"moe_experts": [
"evaluation_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
bd6951e2d6da2fd4a1bd2862df075ccc5f768d67
|
|
train_11995
| 2026-01-01T00:00:00
|
Reasoning-first coding models and tunable deliberation
|
code
|
advanced
|
Task: code
Topic: Reasoning-first coding models and tunable deliberation
Difficulty: advanced
Target language: 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": [
"security_gates",
"tests_are_truth",
"cost_latency_tradeoffs",
"ci_integration"
],
"moe_experts": [
"agentic_systems_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
4b1fb289bf80467a51ea3fb20ebd8819e6412093
|
|
train_11996
| 2026-01-01T00:00:00
|
Secure code generation and policy gates
|
design
|
expert
|
Task: design
Topic: Secure code generation and policy gates
Difficulty: expert
Target language: Go
Context: 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": "Go",
"developer_needs": [
"tooling",
"reproducibility",
"security_gates",
"ci_integration"
],
"moe_experts": [
"governance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
b1cded6fc6e6ada01bfcd13be93d8d1f066ed8bc
|
|
train_11997
| 2026-01-01T00:00:00
|
Latency, cost, and reliability optimization
|
data_pipeline
|
intermediate
|
Task: data_pipeline
Topic: Latency, cost, and reliability optimization
Difficulty: intermediate
Target language: 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": [
"security_gates",
"auditability",
"tests_are_truth",
"repo_scale_reasoning"
],
"moe_experts": [
"data_curation_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
eb4745e77cf673d0ad6c1fba06c225f32a3f779f
|
|
train_11998
| 2026-01-01T00:00:00
|
Code-specialized model families and sizing tradeoffs
|
patch_diff
|
advanced
|
Task: patch_diff
Topic: Code-specialized model families and sizing tradeoffs
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.
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": [
"ci_integration",
"governance",
"evaluation_metrics",
"tests_are_truth"
],
"moe_experts": [
"evaluation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
58a217617d67e72739d127da95dad95666cc88bb
|
|
train_11999
| 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: Go
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Review: correctness, security, performance, governance
|
[] |
{
"target_language": "Go",
"developer_needs": [
"reproducibility",
"evaluation_metrics",
"governance",
"repo_scale_reasoning"
],
"moe_experts": [
"evaluation_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
1d3c16a0317a816b955c14b267532a3487681c58
|
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