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_39700
| 2026-01-01T00:00:00
|
SWE-bench style real-repo evaluation
|
design
|
advanced
|
Task: design
Topic: SWE-bench style real-repo evaluation
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": [
"governance",
"evaluation_metrics",
"security_gates",
"repo_scale_reasoning"
],
"moe_experts": [
"performance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
95bff4e872c7d2905f702e71d22ff3ce90db22f4
|
|
train_39701
| 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: 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",
"documentation",
"repo_scale_reasoning",
"ci_integration"
],
"moe_experts": [
"performance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
e9e27d62058701841691e7184d792ac544bb2f50
|
|
train_39702
| 2026-01-01T00:00:00
|
Self-improving agents and feedback loops
|
failure_analysis
|
advanced
|
Task: failure_analysis
Topic: Self-improving agents and feedback loops
Difficulty: advanced
Target language: 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.
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": [
"tooling",
"auditability",
"reproducibility",
"security_gates"
],
"moe_experts": [
"data_curation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
c43991833904ac1ea13c66ec61447394ac85499f
|
|
train_39703
| 2026-01-01T00:00:00
|
Self-improving agents and feedback loops
|
design
|
intermediate
|
Task: design
Topic: Self-improving agents and feedback loops
Difficulty: intermediate
Target language: 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": [
"reproducibility",
"documentation",
"tests_are_truth",
"governance"
],
"moe_experts": [
"coding_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
a3feb1389744c37b074c32fc7d487f0a853081a7
|
|
train_39704
| 2026-01-01T00:00:00
|
Extended context and repo-scale understanding
|
explain
|
intermediate
|
Task: explain
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": [
"documentation",
"cost_latency_tradeoffs",
"auditability",
"governance"
],
"moe_experts": [
"security_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
700fd55535058ced437597a7d12c17ac86f31c6e
|
|
train_39705
| 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: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[] |
{
"target_language": "Bash",
"developer_needs": [
"cost_latency_tradeoffs",
"security_gates",
"tests_are_truth",
"governance"
],
"moe_experts": [
"performance_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
33ccf4e12d85884514a44e1856f2cb6638780c0a
|
|
train_39706
| 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: 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": [
"ci_integration",
"auditability",
"governance",
"security_gates"
],
"moe_experts": [
"governance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
6560d490bc672dfb2857eef30048ea9d650c1387
|
|
train_39707
| 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: Bash
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Bash",
"developer_needs": [
"tooling",
"documentation",
"security_gates",
"reproducibility"
],
"moe_experts": [
"evaluation_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
4db46c163bec03d649d607081f56c7aef5849f47
|
|
train_39708
| 2026-01-01T00:00:00
|
Secure code generation and policy gates
|
agent_loop
|
expert
|
Task: agent_loop
Topic: Secure code generation and policy gates
Difficulty: expert
Target language: SQL
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
|
[] |
{
"target_language": "SQL",
"developer_needs": [
"security_gates",
"governance",
"tests_are_truth",
"documentation"
],
"moe_experts": [
"data_curation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
69b9814858e16a42242fc163c2ae4e838ca81fb5
|
|
train_39709
| 2026-01-01T00:00:00
|
Model merging, distillation, and continued pretraining
|
data_pipeline
|
intermediate
|
Task: data_pipeline
Topic: Model merging, distillation, and continued pretraining
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": [
"documentation",
"security_gates",
"repo_scale_reasoning",
"governance"
],
"moe_experts": [
"security_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
775cd05784419f06a75ed9f2cb4df730d75c83e9
|
|
train_39710
| 2026-01-01T00:00:00
|
SWE-bench style real-repo evaluation
|
design
|
intermediate
|
Task: design
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.
Design with risks, metrics, acceptance criteria
|
[] |
{
"target_language": "Python",
"developer_needs": [
"cost_latency_tradeoffs",
"documentation",
"reproducibility",
"auditability"
],
"moe_experts": [
"security_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
c15d62484936b9da7a65aef5af872e7108926d57
|
|
train_39711
| 2026-01-01T00:00:00
|
Agentic coding systems (plan→edit→test→reflect)
|
code
|
advanced
|
Task: code
Topic: Agentic coding systems (plan→edit→test→reflect)
Difficulty: advanced
Target language: Go
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[] |
{
"target_language": "Go",
"developer_needs": [
"security_gates",
"repo_scale_reasoning",
"tests_are_truth",
"governance"
],
"moe_experts": [
"agentic_systems_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
b5e7c74d26d4ec9337a3c9cac26d79b280d9ce42
|
|
train_39712
| 2026-01-01T00:00:00
|
Latency, cost, and reliability optimization
|
eval
|
expert
|
Task: eval
Topic: Latency, cost, and reliability optimization
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.
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": "JavaScript",
"developer_needs": [
"ci_integration",
"tooling",
"reproducibility",
"security_gates"
],
"moe_experts": [
"performance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
a1b7288e871d2c69fb2ba1f3ff3fb45478bb2d5f
|
|
train_39713
| 2026-01-01T00:00:00
|
Agentic coding systems (plan→edit→test→reflect)
|
design
|
advanced
|
Task: design
Topic: Agentic coding systems (plan→edit→test→reflect)
Difficulty: advanced
Target language: TypeScript
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "TypeScript",
"developer_needs": [
"ci_integration",
"repo_scale_reasoning",
"documentation",
"governance"
],
"moe_experts": [
"security_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
4ce9b0b2e70262a0c702c4b304da793e5615760e
|
|
train_39714
| 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: 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.
Design with risks, metrics, acceptance criteria
|
[] |
{
"target_language": "Python",
"developer_needs": [
"reproducibility",
"tooling",
"governance",
"repo_scale_reasoning"
],
"moe_experts": [
"performance_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
1e91a83b54c68af94c9968530f0e4a08300fb1bf
|
|
train_39715
| 2026-01-01T00:00:00
|
Multimodal dev workflows (docs, diagrams, traces)
|
agent_loop
|
expert
|
Task: agent_loop
Topic: Multimodal dev workflows (docs, diagrams, traces)
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.
Loop: Plan → Edit → Test → Reflect → Human gate
|
[] |
{
"target_language": "Java",
"developer_needs": [
"ci_integration",
"security_gates",
"documentation",
"tooling"
],
"moe_experts": [
"governance_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
9d1df00035210c4253cf8722595886b6c878d3fc
|
|
train_39716
| 2026-01-01T00:00:00
|
Model merging, distillation, and continued pretraining
|
explain
|
advanced
|
Task: explain
Topic: Model merging, distillation, and continued pretraining
Difficulty: advanced
Target language: 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": [
"auditability",
"tests_are_truth",
"evaluation_metrics",
"governance"
],
"moe_experts": [
"coding_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
d36d3cac495c0399cef57c42c72a5a790b24f678
|
|
train_39717
| 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: 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.
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": "SQL",
"developer_needs": [
"ci_integration",
"auditability",
"repo_scale_reasoning",
"reproducibility"
],
"moe_experts": [
"data_curation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
09bd3afff29dd4fd083a13a211e23a0db71974b3
|
|
train_39718
| 2026-01-01T00:00:00
|
Agentic coding systems (plan→edit→test→reflect)
|
code
|
intermediate
|
Task: code
Topic: Agentic coding systems (plan→edit→test→reflect)
Difficulty: intermediate
Target language: C#
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[] |
{
"target_language": "C#",
"developer_needs": [
"tests_are_truth",
"auditability",
"evaluation_metrics",
"documentation"
],
"moe_experts": [
"governance_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
b07a601d688084d6d90bd688fbc689c6f655aea6
|
|
train_39719
| 2026-01-01T00:00:00
|
Mixture-of-Experts (MoE) for code
|
explain
|
expert
|
Task: explain
Topic: Mixture-of-Experts (MoE) for code
Difficulty: expert
Target language: TypeScript
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[] |
{
"target_language": "TypeScript",
"developer_needs": [
"tests_are_truth",
"reproducibility",
"repo_scale_reasoning",
"cost_latency_tradeoffs"
],
"moe_experts": [
"security_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
4b24c71d255c02fb4d860f2d632d9a237bc37c82
|
|
train_39720
| 2026-01-01T00:00:00
|
Extended context and repo-scale understanding
|
eval
|
advanced
|
Task: eval
Topic: Extended context and repo-scale understanding
Difficulty: advanced
Target language: 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": [
"governance",
"tooling",
"ci_integration",
"reproducibility"
],
"moe_experts": [
"coding_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
390aa64d28014a15dd32ebffab8c83d556238a96
|
|
train_39721
| 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: SQL
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "SQL",
"developer_needs": [
"governance",
"tooling",
"ci_integration",
"auditability"
],
"moe_experts": [
"performance_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
d047bd4f94591ceffb1aed4ed06936254f1f6dc2
|
|
train_39722
| 2026-01-01T00:00:00
|
Latency, cost, and reliability optimization
|
explain
|
intermediate
|
Task: explain
Topic: Latency, cost, and reliability optimization
Difficulty: intermediate
Target language: Python
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[] |
{
"target_language": "Python",
"developer_needs": [
"tooling",
"documentation",
"tests_are_truth",
"evaluation_metrics"
],
"moe_experts": [
"coding_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
a59506ee56e7fab36400f31ef5e0412be0ffafe0
|
|
train_39723
| 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: 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
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "JavaScript",
"developer_needs": [
"reproducibility",
"documentation",
"evaluation_metrics",
"auditability"
],
"moe_experts": [
"security_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
7cbdb8004db78d99fc3d359d45c546b3b0cc5cc1
|
|
train_39724
| 2026-01-01T00:00:00
|
Self-improving agents and feedback loops
|
eval
|
advanced
|
Task: eval
Topic: Self-improving agents and feedback loops
Difficulty: advanced
Target language: Bash
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
|
[] |
{
"target_language": "Bash",
"developer_needs": [
"auditability",
"security_gates",
"tests_are_truth",
"ci_integration"
],
"moe_experts": [
"data_curation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
796c073f6afcb8b17326181a8408b3d5c8006507
|
|
train_39725
| 2026-01-01T00:00:00
|
Reasoning-first coding models and tunable deliberation
|
code
|
intermediate
|
Task: code
Topic: Reasoning-first coding models and tunable deliberation
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": [
"auditability",
"tests_are_truth",
"evaluation_metrics",
"security_gates"
],
"moe_experts": [
"data_curation_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
97cd3224985c5c2ff2746f0e9c19ffa17b634536
|
|
train_39726
| 2026-01-01T00:00:00
|
Governance, provenance, and licensing for code data
|
eval
|
intermediate
|
Task: eval
Topic: Governance, provenance, and licensing for code data
Difficulty: intermediate
Target language: Bash
Context: 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": [
"documentation",
"reproducibility",
"cost_latency_tradeoffs",
"repo_scale_reasoning"
],
"moe_experts": [
"agentic_systems_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
eae855e82252b0268fedf0b80b0a4f3e70dae5f2
|
|
train_39727
| 2026-01-01T00:00:00
|
Reasoning-first coding models and tunable deliberation
|
data_pipeline
|
advanced
|
Task: data_pipeline
Topic: Reasoning-first coding models and tunable deliberation
Difficulty: advanced
Target language: 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": [
"auditability",
"evaluation_metrics",
"tooling",
"reproducibility"
],
"moe_experts": [
"coding_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
7caf3266c3fd97f0a504051d8f9aa70f56913130
|
|
train_39728
| 2026-01-01T00:00:00
|
Self-improving agents and feedback loops
|
eval
|
advanced
|
Task: eval
Topic: Self-improving agents and feedback loops
Difficulty: advanced
Target language: Python
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
|
[
"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",
"security_gates",
"governance",
"ci_integration"
],
"moe_experts": [
"security_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
d8f1cb99ae452e4c9e7a087b8b071abe8d1c11b4
|
|
train_39729
| 2026-01-01T00:00:00
|
Model merging, distillation, and continued pretraining
|
patch_diff
|
advanced
|
Task: patch_diff
Topic: Model merging, distillation, and continued pretraining
Difficulty: advanced
Target language: 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": [
"security_gates",
"documentation",
"repo_scale_reasoning",
"tests_are_truth"
],
"moe_experts": [
"security_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
970431286f0083848a424eb3dbb2d80c1cf870d6
|
|
train_39730
| 2026-01-01T00:00:00
|
Multimodal dev workflows (docs, diagrams, traces)
|
compare
|
advanced
|
Task: compare
Topic: Multimodal dev workflows (docs, diagrams, traces)
Difficulty: advanced
Target language: Bash
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
|
[] |
{
"target_language": "Bash",
"developer_needs": [
"repo_scale_reasoning",
"auditability",
"documentation",
"ci_integration"
],
"moe_experts": [
"governance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
538c8377828dc2f89c6f4e4f5cf57dc1781de9c2
|
|
train_39731
| 2026-01-01T00:00:00
|
Latency, cost, and reliability optimization
|
agent_loop
|
intermediate
|
Task: agent_loop
Topic: Latency, cost, and reliability optimization
Difficulty: intermediate
Target language: Python
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
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": [
"documentation",
"reproducibility",
"security_gates",
"tooling"
],
"moe_experts": [
"agentic_systems_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
b0ef4ab8948ea24f89da6d132a2d7d4bc0c8f6dd
|
|
train_39732
| 2026-01-01T00:00:00
|
Reasoning-first coding models and tunable deliberation
|
failure_analysis
|
expert
|
Task: failure_analysis
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.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "SQL",
"developer_needs": [
"evaluation_metrics",
"security_gates",
"documentation",
"tooling"
],
"moe_experts": [
"evaluation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
907453efedba7a789a7c3b711fdd39e09803883c
|
|
train_39733
| 2026-01-01T00:00:00
|
Agentic coding systems (plan→edit→test→reflect)
|
agent_loop
|
advanced
|
Task: agent_loop
Topic: Agentic coding systems (plan→edit→test→reflect)
Difficulty: advanced
Target language: 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.
Loop: Plan → Edit → Test → Reflect → Human gate
|
[] |
{
"target_language": "Rust",
"developer_needs": [
"auditability",
"ci_integration",
"security_gates",
"evaluation_metrics"
],
"moe_experts": [
"data_curation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
ccbe964c54f0b5722208fc05362631c265a248c6
|
|
train_39734
| 2026-01-01T00:00:00
|
Secure code generation and policy gates
|
data_pipeline
|
intermediate
|
Task: data_pipeline
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.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
|
[] |
{
"target_language": "Java",
"developer_needs": [
"auditability",
"security_gates",
"ci_integration",
"tooling"
],
"moe_experts": [
"agentic_systems_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
2dd22705658ca5ede0b0af7a006fdadfa1e02a4f
|
|
train_39735
| 2026-01-01T00:00:00
|
Dataset curation pipelines (filter, dedupe, quality)
|
design
|
advanced
|
Task: design
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: advanced
Target language: SQL
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "SQL",
"developer_needs": [
"tests_are_truth",
"documentation",
"ci_integration",
"cost_latency_tradeoffs"
],
"moe_experts": [
"data_curation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
bbb8b72d4d663925867be7c3100a307061f9b204
|
|
train_39736
| 2026-01-01T00:00:00
|
Mixture-of-Experts (MoE) for code
|
data_pipeline
|
expert
|
Task: data_pipeline
Topic: Mixture-of-Experts (MoE) for code
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.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
|
[] |
{
"target_language": "C#",
"developer_needs": [
"tooling",
"security_gates",
"cost_latency_tradeoffs",
"auditability"
],
"moe_experts": [
"security_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
7632bca8831d1b73b293b27090ab30705ff75683
|
|
train_39737
| 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: 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": [
"reproducibility",
"tooling",
"documentation",
"governance"
],
"moe_experts": [
"coding_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
5fc967746cb8b707acdb4978409ef6f2aedc5e1e
|
|
train_39738
| 2026-01-01T00:00:00
|
Dataset curation pipelines (filter, dedupe, quality)
|
agent_loop
|
advanced
|
Task: agent_loop
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: advanced
Target language: Rust
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
|
[] |
{
"target_language": "Rust",
"developer_needs": [
"cost_latency_tradeoffs",
"repo_scale_reasoning",
"evaluation_metrics",
"documentation"
],
"moe_experts": [
"governance_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
fe7c7632d1341aecbd7e75354ff10a871eb85454
|
|
train_39739
| 2026-01-01T00:00:00
|
Multimodal dev workflows (docs, diagrams, traces)
|
data_pipeline
|
advanced
|
Task: data_pipeline
Topic: Multimodal dev workflows (docs, diagrams, traces)
Difficulty: advanced
Target language: 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
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "SQL",
"developer_needs": [
"documentation",
"ci_integration",
"tooling",
"security_gates"
],
"moe_experts": [
"data_curation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
dafda0f5e7844ac27f64e732cf97308ea99e51d5
|
|
train_39740
| 2026-01-01T00:00:00
|
Mixture-of-Experts (MoE) for code
|
failure_analysis
|
advanced
|
Task: failure_analysis
Topic: Mixture-of-Experts (MoE) for code
Difficulty: advanced
Target language: Python
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
|
[] |
{
"target_language": "Python",
"developer_needs": [
"security_gates",
"ci_integration",
"repo_scale_reasoning",
"auditability"
],
"moe_experts": [
"coding_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
b31a9106bebd55c176cb6fcfa649244b861516b0
|
|
train_39741
| 2026-01-01T00:00:00
|
Mixture-of-Experts (MoE) for code
|
eval
|
advanced
|
Task: eval
Topic: Mixture-of-Experts (MoE) for code
Difficulty: advanced
Target language: 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",
"ci_integration",
"repo_scale_reasoning",
"tests_are_truth"
],
"moe_experts": [
"performance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
149e173e194bd55408d1444ce9690b9c96e1a483
|
|
train_39742
| 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: 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.
Eval:
pass@k, time-to-green, regressions, diff size
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Go",
"developer_needs": [
"cost_latency_tradeoffs",
"governance",
"reproducibility",
"evaluation_metrics"
],
"moe_experts": [
"data_curation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
69dba35c2384177e4ccf7abccb57c5c07b326dfe
|
|
train_39743
| 2026-01-01T00:00:00
|
SWE-bench style real-repo evaluation
|
compare
|
expert
|
Task: compare
Topic: SWE-bench style real-repo evaluation
Difficulty: expert
Target language: 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": [
"reproducibility",
"documentation",
"evaluation_metrics",
"security_gates"
],
"moe_experts": [
"performance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
b048c41ffad9c83cd25837592c4020b40728c48d
|
|
train_39744
| 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
|
[
"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",
"tooling",
"auditability",
"security_gates"
],
"moe_experts": [
"data_curation_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
12fe1d0a85373b8fc52d2aa1ac44736924633daa
|
|
train_39745
| 2026-01-01T00:00:00
|
SWE-bench style real-repo evaluation
|
explain
|
advanced
|
Task: explain
Topic: SWE-bench style real-repo evaluation
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": [
"auditability",
"repo_scale_reasoning",
"documentation",
"reproducibility"
],
"moe_experts": [
"coding_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
c6c56a6b3c1f24081c3008b2a0bd53a2ef66bd32
|
|
train_39746
| 2026-01-01T00:00:00
|
Dataset curation pipelines (filter, dedupe, quality)
|
code
|
intermediate
|
Task: code
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: intermediate
Target language: Bash
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[] |
{
"target_language": "Bash",
"developer_needs": [
"repo_scale_reasoning",
"evaluation_metrics",
"tests_are_truth",
"security_gates"
],
"moe_experts": [
"security_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
a4b3257b50cfcdf01d31797d0748262ca5a22913
|
|
train_39747
| 2026-01-01T00:00:00
|
Multimodal dev workflows (docs, diagrams, traces)
|
explain
|
intermediate
|
Task: explain
Topic: Multimodal dev workflows (docs, diagrams, traces)
Difficulty: intermediate
Target language: Rust
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[] |
{
"target_language": "Rust",
"developer_needs": [
"reproducibility",
"auditability",
"governance",
"evaluation_metrics"
],
"moe_experts": [
"security_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
e8890185846755cb2c25dc1263791a8194df5067
|
|
train_39748
| 2026-01-01T00:00:00
|
Self-improving agents and feedback loops
|
code
|
expert
|
Task: code
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.
Design with risks, metrics, acceptance criteria
|
[] |
{
"target_language": "Go",
"developer_needs": [
"evaluation_metrics",
"tooling",
"tests_are_truth",
"reproducibility"
],
"moe_experts": [
"security_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
666c3f35a5766c1ee96ed0ca98e5f00f87a505ac
|
|
train_39749
| 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: TypeScript
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Review: correctness, security, performance, governance
|
[] |
{
"target_language": "TypeScript",
"developer_needs": [
"evaluation_metrics",
"reproducibility",
"auditability",
"documentation"
],
"moe_experts": [
"data_curation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
e3e0d36bc2d25026177bbfc402521a082a702656
|
|
train_39750
| 2026-01-01T00:00:00
|
Mixture-of-Experts (MoE) for code
|
review
|
advanced
|
Task: review
Topic: Mixture-of-Experts (MoE) for code
Difficulty: advanced
Target language: C#
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
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": [
"governance",
"security_gates",
"tooling",
"repo_scale_reasoning"
],
"moe_experts": [
"agentic_systems_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
141975cd86c423e4dbbd6b716acd335b2847cc9d
|
|
train_39751
| 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: Go
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Review: correctness, security, performance, governance
|
[] |
{
"target_language": "Go",
"developer_needs": [
"governance",
"repo_scale_reasoning",
"tooling",
"ci_integration"
],
"moe_experts": [
"performance_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
fb3132cb4b038d2cd542eaf3e1709fa07c7c9eff
|
|
train_39752
| 2026-01-01T00:00:00
|
Tool calling, sandboxes, and CI integration
|
patch_diff
|
intermediate
|
Task: patch_diff
Topic: Tool calling, sandboxes, and CI integration
Difficulty: intermediate
Target language: TypeScript
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Patch (diff-style):
```diff
- if x == 0:
- return 1/x
+ if x == 0:
+ raise ValueError('division by zero')
```
Acceptance:
- Tests pass
- No new regressions
|
[] |
{
"target_language": "TypeScript",
"developer_needs": [
"security_gates",
"cost_latency_tradeoffs",
"documentation",
"repo_scale_reasoning"
],
"moe_experts": [
"coding_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
d4c9de750c3fcf61742509b5ec33edac4ecd4fd5
|
|
train_39753
| 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: 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": [
"auditability",
"tooling",
"reproducibility",
"documentation"
],
"moe_experts": [
"agentic_systems_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
2e973f64cf9bd19ffda173b452f4cb62c07dae07
|
|
train_39754
| 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: 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.
Review: correctness, security, performance, governance
|
[] |
{
"target_language": "Rust",
"developer_needs": [
"tooling",
"reproducibility",
"security_gates",
"auditability"
],
"moe_experts": [
"agentic_systems_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
3c8fefdfc529e1e33b80ccecffb1e47740d07497
|
|
train_39755
| 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: 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.
Scaffold:
```python
def agent_loop(plan, edit, test, issue, max_iters=4):
history = []
p = plan(issue)
for _ in range(max_iters):
patch = edit(issue, p)
ok, report = test(patch)
history.append({"plan": p, "ok": ok})
if ok:
return patch, history
p = p + " | refine"
return patch, history
```
|
[] |
{
"target_language": "Python",
"developer_needs": [
"security_gates",
"auditability",
"governance",
"documentation"
],
"moe_experts": [
"performance_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
bada5367d321c4e6de66a66dac06afddd7441ac5
|
|
train_39756
| 2026-01-01T00:00:00
|
Self-improving agents and feedback loops
|
eval
|
advanced
|
Task: eval
Topic: Self-improving agents and feedback loops
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
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "TypeScript",
"developer_needs": [
"evaluation_metrics",
"tooling",
"cost_latency_tradeoffs",
"governance"
],
"moe_experts": [
"evaluation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
5e4427377a7ea66d4bbef120c114805091b1d5fc
|
|
train_39757
| 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: 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": [
"evaluation_metrics",
"ci_integration",
"tooling",
"auditability"
],
"moe_experts": [
"coding_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
40e05c60338aca11ced32fe1452d25fa71b1b69f
|
|
train_39758
| 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: Java
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[] |
{
"target_language": "Java",
"developer_needs": [
"governance",
"evaluation_metrics",
"cost_latency_tradeoffs",
"repo_scale_reasoning"
],
"moe_experts": [
"coding_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
6379c691d63a438feebd21dcae5f237570633286
|
|
train_39759
| 2026-01-01T00:00:00
|
SWE-bench style real-repo evaluation
|
explain
|
advanced
|
Task: explain
Topic: SWE-bench style real-repo evaluation
Difficulty: advanced
Target language: Rust
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Rust",
"developer_needs": [
"auditability",
"documentation",
"evaluation_metrics",
"reproducibility"
],
"moe_experts": [
"governance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
53afac17f669932faded1300f904682bec59647d
|
|
train_39760
| 2026-01-01T00:00:00
|
Governance, provenance, and licensing for code data
|
review
|
advanced
|
Task: review
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.
Review: correctness, security, performance, governance
|
[] |
{
"target_language": "Rust",
"developer_needs": [
"tooling",
"cost_latency_tradeoffs",
"evaluation_metrics",
"governance"
],
"moe_experts": [
"governance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
42294db117eb5ba876939dd3e8994b3275ee80d9
|
|
train_39761
| 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: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Patch (diff-style):
```diff
- if x == 0:
- return 1/x
+ if x == 0:
+ raise ValueError('division by zero')
```
Acceptance:
- Tests pass
- No new regressions
|
[] |
{
"target_language": "Go",
"developer_needs": [
"ci_integration",
"documentation",
"governance",
"tests_are_truth"
],
"moe_experts": [
"data_curation_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
36c62040276ee1613d9c89ecafd4d76f271e084d
|
|
train_39762
| 2026-01-01T00:00:00
|
Code-specialized model families and sizing tradeoffs
|
review
|
advanced
|
Task: review
Topic: Code-specialized model families and sizing tradeoffs
Difficulty: advanced
Target language: TypeScript
Context: 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": "TypeScript",
"developer_needs": [
"documentation",
"governance",
"auditability",
"reproducibility"
],
"moe_experts": [
"agentic_systems_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
960863b6c5927ae18d9eaa7f9ff8f4a7f6b66dbc
|
|
train_39763
| 2026-01-01T00:00:00
|
Agentic coding systems (plan→edit→test→reflect)
|
data_pipeline
|
expert
|
Task: data_pipeline
Topic: Agentic coding systems (plan→edit→test→reflect)
Difficulty: expert
Target language: 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.
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": [
"evaluation_metrics",
"tests_are_truth",
"documentation",
"reproducibility"
],
"moe_experts": [
"agentic_systems_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
f46003ac356a092d66fd1d51718d1660974fca2d
|
|
train_39764
| 2026-01-01T00:00:00
|
Extended context and repo-scale understanding
|
review
|
intermediate
|
Task: review
Topic: Extended context and repo-scale understanding
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.
Review: correctness, security, performance, governance
|
[] |
{
"target_language": "SQL",
"developer_needs": [
"tooling",
"evaluation_metrics",
"ci_integration",
"auditability"
],
"moe_experts": [
"coding_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
d1d86aa3edf3535dc070d1ba34f9ac1bb00f8b69
|
|
train_39765
| 2026-01-01T00:00:00
|
Multimodal dev workflows (docs, diagrams, traces)
|
code
|
intermediate
|
Task: code
Topic: Multimodal dev workflows (docs, diagrams, traces)
Difficulty: intermediate
Target language: Rust
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[] |
{
"target_language": "Rust",
"developer_needs": [
"evaluation_metrics",
"cost_latency_tradeoffs",
"reproducibility",
"repo_scale_reasoning"
],
"moe_experts": [
"security_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
08ddaee0f4ae2db5a7058ca2f3ae0f246e45404e
|
|
train_39766
| 2026-01-01T00:00:00
|
Extended context and repo-scale understanding
|
code
|
intermediate
|
Task: code
Topic: Extended context and repo-scale understanding
Difficulty: intermediate
Target language: Rust
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Rust",
"developer_needs": [
"evaluation_metrics",
"tooling",
"tests_are_truth",
"auditability"
],
"moe_experts": [
"performance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
e5381d8fa9a364e3a3c097617c5e109dcfc73156
|
|
train_39767
| 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: SQL
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
|
[
"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",
"repo_scale_reasoning",
"documentation",
"governance"
],
"moe_experts": [
"security_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
279227a82e65bdd4549abc601f6a029b126ab61b
|
|
train_39768
| 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: 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
|
[] |
{
"target_language": "Rust",
"developer_needs": [
"documentation",
"security_gates",
"ci_integration",
"cost_latency_tradeoffs"
],
"moe_experts": [
"evaluation_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
a8433c7f2691fa2160a81715320afbd7a7771ec4
|
|
train_39769
| 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: 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": [
"tooling",
"tests_are_truth",
"reproducibility",
"ci_integration"
],
"moe_experts": [
"data_curation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
e14e1ba7e96e93366c7fdc439f32215b8c0819d9
|
|
train_39770
| 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: Java
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[] |
{
"target_language": "Java",
"developer_needs": [
"evaluation_metrics",
"tooling",
"reproducibility",
"ci_integration"
],
"moe_experts": [
"performance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
a8298c3e85ec586dd2b712db3468d51e2c85844d
|
|
train_39771
| 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": [
"cost_latency_tradeoffs",
"repo_scale_reasoning",
"auditability",
"ci_integration"
],
"moe_experts": [
"evaluation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
bc11e6fc8110586b0f0100862af05b6ce8971adb
|
|
train_39772
| 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: 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.
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",
"ci_integration",
"repo_scale_reasoning",
"tests_are_truth"
],
"moe_experts": [
"coding_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
7929b63fbc0c4a3a84fb8f315890b57cf2c17d83
|
|
train_39773
| 2026-01-01T00:00:00
|
Dataset curation pipelines (filter, dedupe, quality)
|
review
|
expert
|
Task: review
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: expert
Target language: TypeScript
Context: 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": "TypeScript",
"developer_needs": [
"governance",
"tooling",
"tests_are_truth",
"security_gates"
],
"moe_experts": [
"agentic_systems_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
e3076447d6116dbae7efa569ee71e262631f2ebc
|
|
train_39774
| 2026-01-01T00:00:00
|
Extended context and repo-scale understanding
|
design
|
advanced
|
Task: design
Topic: Extended context and repo-scale understanding
Difficulty: advanced
Target language: Python
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[] |
{
"target_language": "Python",
"developer_needs": [
"ci_integration",
"security_gates",
"reproducibility",
"tests_are_truth"
],
"moe_experts": [
"agentic_systems_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
491a79f1a6d3a03216b49b0abc1e66ed45719f2a
|
|
train_39775
| 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: 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
|
[
"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",
"auditability",
"reproducibility",
"tooling"
],
"moe_experts": [
"data_curation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
830e2c0a50add12ecba37b589ead9746c71603fb
|
|
train_39776
| 2026-01-01T00:00:00
|
Self-improving agents and feedback loops
|
failure_analysis
|
advanced
|
Task: failure_analysis
Topic: Self-improving agents and feedback loops
Difficulty: advanced
Target language: 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.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
|
[] |
{
"target_language": "Python",
"developer_needs": [
"auditability",
"ci_integration",
"repo_scale_reasoning",
"tooling"
],
"moe_experts": [
"performance_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
cc6d942c92a6161af86135cd652ada6110733aff
|
|
train_39777
| 2026-01-01T00:00:00
|
Self-improving agents and feedback loops
|
data_pipeline
|
advanced
|
Task: data_pipeline
Topic: Self-improving agents and feedback loops
Difficulty: advanced
Target language: SQL
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
|
[] |
{
"target_language": "SQL",
"developer_needs": [
"documentation",
"tooling",
"ci_integration",
"security_gates"
],
"moe_experts": [
"security_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
bce3b7a84c111edcf2f032ca060f614855b5d4e0
|
|
train_39778
| 2026-01-01T00:00:00
|
Multimodal dev workflows (docs, diagrams, traces)
|
data_pipeline
|
expert
|
Task: data_pipeline
Topic: Multimodal dev workflows (docs, diagrams, traces)
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.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
|
[] |
{
"target_language": "TypeScript",
"developer_needs": [
"cost_latency_tradeoffs",
"evaluation_metrics",
"ci_integration",
"documentation"
],
"moe_experts": [
"security_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
018f1fa145a75af5831f7622c6146a06f7fd8575
|
|
train_39779
| 2026-01-01T00:00:00
|
Self-improving agents and feedback loops
|
data_pipeline
|
intermediate
|
Task: data_pipeline
Topic: Self-improving agents and feedback loops
Difficulty: intermediate
Target language: SQL
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "SQL",
"developer_needs": [
"reproducibility",
"tooling",
"ci_integration",
"tests_are_truth"
],
"moe_experts": [
"performance_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
539e7df81984e833ac62d7c25e3c5032873ef730
|
|
train_39780
| 2026-01-01T00:00:00
|
Governance, provenance, and licensing for code data
|
design
|
advanced
|
Task: design
Topic: Governance, provenance, and licensing for code data
Difficulty: advanced
Target language: 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.
Design with risks, metrics, acceptance criteria
|
[] |
{
"target_language": "Bash",
"developer_needs": [
"tooling",
"tests_are_truth",
"cost_latency_tradeoffs",
"security_gates"
],
"moe_experts": [
"data_curation_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
e73f1618ed7561e8d53af404bf4785dfdb4db797
|
|
train_39781
| 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: TypeScript
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[] |
{
"target_language": "TypeScript",
"developer_needs": [
"cost_latency_tradeoffs",
"repo_scale_reasoning",
"reproducibility",
"auditability"
],
"moe_experts": [
"evaluation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
aab50aa8c1634ddcfc47aa69591c970b142b137c
|
|
train_39782
| 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: TypeScript
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "TypeScript",
"developer_needs": [
"governance",
"repo_scale_reasoning",
"tooling",
"security_gates"
],
"moe_experts": [
"agentic_systems_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
3646a8d8f837be0738e428e7a72c4eaac62dedfb
|
|
train_39783
| 2026-01-01T00:00:00
|
Latency, cost, and reliability optimization
|
patch_diff
|
advanced
|
Task: patch_diff
Topic: Latency, cost, and reliability optimization
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.
Patch (diff-style):
```diff
- if x == 0:
- return 1/x
+ if x == 0:
+ raise ValueError('division by zero')
```
Acceptance:
- Tests pass
- No new regressions
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Rust",
"developer_needs": [
"tests_are_truth",
"repo_scale_reasoning",
"reproducibility",
"cost_latency_tradeoffs"
],
"moe_experts": [
"evaluation_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
622eb129d0b2ca1c67f1247696ae5345a876bfec
|
|
train_39784
| 2026-01-01T00:00:00
|
Multimodal dev workflows (docs, diagrams, traces)
|
design
|
expert
|
Task: design
Topic: Multimodal dev workflows (docs, diagrams, traces)
Difficulty: expert
Target language: Java
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[
"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",
"tests_are_truth",
"evaluation_metrics"
],
"moe_experts": [
"evaluation_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
306afdd6977e3724e79e72d13f7527cd8ca19f8c
|
|
train_39785
| 2026-01-01T00:00:00
|
Reasoning-first coding models and tunable deliberation
|
eval
|
intermediate
|
Task: eval
Topic: Reasoning-first coding models and tunable deliberation
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.
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": [
"repo_scale_reasoning",
"documentation",
"security_gates",
"cost_latency_tradeoffs"
],
"moe_experts": [
"agentic_systems_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
b0a9592f90f3d58b830f6dcc357b867eb9381b66
|
|
train_39786
| 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: JavaScript
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "JavaScript",
"developer_needs": [
"ci_integration",
"reproducibility",
"security_gates",
"governance"
],
"moe_experts": [
"performance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
c494727b3ed7c1510041317ca779aeb800f4c5d2
|
|
train_39787
| 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: 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.
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": [
"auditability",
"governance",
"reproducibility",
"tooling"
],
"moe_experts": [
"performance_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
75adbc8e78274a5f19ff95fad2d764dd7834cc1d
|
|
train_39788
| 2026-01-01T00:00:00
|
Code-specialized model families and sizing tradeoffs
|
review
|
advanced
|
Task: review
Topic: Code-specialized model families and sizing tradeoffs
Difficulty: advanced
Target language: TypeScript
Context: 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": [
"reproducibility",
"tooling",
"auditability",
"tests_are_truth"
],
"moe_experts": [
"security_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
56229da2f426577bdbab396ebdf05207b484b76b
|
|
train_39789
| 2026-01-01T00:00:00
|
Extended context and repo-scale understanding
|
agent_loop
|
intermediate
|
Task: agent_loop
Topic: Extended context and repo-scale understanding
Difficulty: intermediate
Target language: 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.
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": [
"cost_latency_tradeoffs",
"tests_are_truth",
"governance",
"security_gates"
],
"moe_experts": [
"agentic_systems_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
bd7ae56f34f768cab0bd281862788dc8ef328801
|
|
train_39790
| 2026-01-01T00:00:00
|
Latency, cost, and reliability optimization
|
compare
|
expert
|
Task: compare
Topic: Latency, cost, and reliability optimization
Difficulty: expert
Target language: Rust
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
|
[] |
{
"target_language": "Rust",
"developer_needs": [
"repo_scale_reasoning",
"governance",
"auditability",
"documentation"
],
"moe_experts": [
"evaluation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
e134e28fce2ea7451b977d69852140a292ca6342
|
|
train_39791
| 2026-01-01T00:00:00
|
Self-improving agents and feedback loops
|
data_pipeline
|
intermediate
|
Task: data_pipeline
Topic: Self-improving agents and feedback loops
Difficulty: intermediate
Target language: 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.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Rust",
"developer_needs": [
"documentation",
"cost_latency_tradeoffs",
"reproducibility",
"security_gates"
],
"moe_experts": [
"coding_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
daa46feb0024e4e8e04c20a5b5ff2d7727c3212e
|
|
train_39792
| 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: Go
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
|
[] |
{
"target_language": "Go",
"developer_needs": [
"reproducibility",
"tests_are_truth",
"tooling",
"evaluation_metrics"
],
"moe_experts": [
"security_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
e523bd2a9474230c0e30815f4210eb0d9709c656
|
|
train_39793
| 2026-01-01T00:00:00
|
Governance, provenance, and licensing for code data
|
explain
|
advanced
|
Task: explain
Topic: Governance, provenance, and licensing for code data
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.
Design with risks, metrics, acceptance criteria
|
[] |
{
"target_language": "C#",
"developer_needs": [
"reproducibility",
"security_gates",
"tests_are_truth",
"auditability"
],
"moe_experts": [
"security_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
b8fb2a305d8da78462e63b7e48708d0260bc4a72
|
|
train_39794
| 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: TypeScript
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
|
[] |
{
"target_language": "TypeScript",
"developer_needs": [
"security_gates",
"governance",
"repo_scale_reasoning",
"reproducibility"
],
"moe_experts": [
"evaluation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
823e35fa0431c38a2c8d4b867b528edca25490f7
|
|
train_39795
| 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: 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": [
"security_gates",
"ci_integration",
"tests_are_truth",
"reproducibility"
],
"moe_experts": [
"coding_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
4d86566ca3ea1f2fa85f030f849e4fa06912d587
|
|
train_39796
| 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: 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",
"cost_latency_tradeoffs",
"governance",
"tests_are_truth"
],
"moe_experts": [
"security_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
dc09cf6010e9ac2d554c44710d77b0b4d4a59691
|
|
train_39797
| 2026-01-01T00:00:00
|
SWE-bench style real-repo evaluation
|
data_pipeline
|
expert
|
Task: data_pipeline
Topic: SWE-bench style real-repo evaluation
Difficulty: expert
Target language: C#
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
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": "C#",
"developer_needs": [
"auditability",
"evaluation_metrics",
"documentation",
"cost_latency_tradeoffs"
],
"moe_experts": [
"performance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
f34f67a40f09d0df036839cfdb62bb0efdca8407
|
|
train_39798
| 2026-01-01T00:00:00
|
Dataset curation pipelines (filter, dedupe, quality)
|
data_pipeline
|
advanced
|
Task: data_pipeline
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: advanced
Target language: Rust
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Rust",
"developer_needs": [
"tests_are_truth",
"documentation",
"governance",
"reproducibility"
],
"moe_experts": [
"evaluation_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
ad49338b7f8ef8f42b778c64f44f3cf9ae62296d
|
|
train_39799
| 2026-01-01T00:00:00
|
Model merging, distillation, and continued pretraining
|
explain
|
advanced
|
Task: explain
Topic: Model merging, distillation, and continued pretraining
Difficulty: advanced
Target language: 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": [
"ci_integration",
"governance",
"documentation",
"tooling"
],
"moe_experts": [
"evaluation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
b360361ef83ab5ddefdbefa10b8e83892d0f42a5
|
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.