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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_00000
| 2026-01-01T00:00:00
|
SWE-bench style real-repo evaluation
|
data_pipeline
|
advanced
|
Task: data_pipeline
Topic: SWE-bench style real-repo evaluation
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.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
|
[] |
{
"target_language": "Bash",
"developer_needs": [
"tooling",
"tests_are_truth",
"documentation",
"evaluation_metrics"
],
"moe_experts": [
"security_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
e64f74928db65a124cf00640ea9ee30b46f1df3b
|
|
train_00001
| 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: 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": [
"reproducibility",
"security_gates",
"ci_integration",
"auditability"
],
"moe_experts": [
"performance_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
d27475797664ba25ec2f2653af8689e83b3396f0
|
|
train_00002
| 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: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
|
[] |
{
"target_language": "Bash",
"developer_needs": [
"evaluation_metrics",
"documentation",
"repo_scale_reasoning",
"tooling"
],
"moe_experts": [
"agentic_systems_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
f46441a94792cb47d69fc6c44a760559da5a552d
|
|
train_00003
| 2026-01-01T00:00:00
|
Code-specialized model families and sizing tradeoffs
|
failure_analysis
|
intermediate
|
Task: failure_analysis
Topic: Code-specialized model families and sizing tradeoffs
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.
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": "Python",
"developer_needs": [
"ci_integration",
"auditability",
"reproducibility",
"tooling"
],
"moe_experts": [
"governance_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
12055db54c11db8da6b9ecdb03cb4193fc36825c
|
|
train_00004
| 2026-01-01T00:00:00
|
Model merging, distillation, and continued pretraining
|
eval
|
intermediate
|
Task: eval
Topic: Model merging, distillation, and continued pretraining
Difficulty: intermediate
Target language: C#
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
|
[] |
{
"target_language": "C#",
"developer_needs": [
"auditability",
"repo_scale_reasoning",
"security_gates",
"documentation"
],
"moe_experts": [
"evaluation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
206c7a4d3827aa092a861233a24e8e345958f736
|
|
train_00005
| 2026-01-01T00:00:00
|
Secure code generation and policy gates
|
data_pipeline
|
expert
|
Task: data_pipeline
Topic: Secure code generation and policy gates
Difficulty: expert
Target language: JavaScript
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "JavaScript",
"developer_needs": [
"evaluation_metrics",
"auditability",
"tests_are_truth",
"tooling"
],
"moe_experts": [
"governance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
4d6e189b622425bde24b147a07ececdb384b10dc
|
|
train_00006
| 2026-01-01T00:00:00
|
Secure code generation and policy gates
|
patch_diff
|
expert
|
Task: patch_diff
Topic: Secure code generation and policy gates
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.
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": [
"tooling",
"cost_latency_tradeoffs",
"reproducibility",
"evaluation_metrics"
],
"moe_experts": [
"agentic_systems_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
33445229691c5a9d6310f6d10caf883f50a5ba8b
|
|
train_00007
| 2026-01-01T00:00:00
|
Model merging, distillation, and continued pretraining
|
data_pipeline
|
expert
|
Task: data_pipeline
Topic: Model merging, distillation, and continued pretraining
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.
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": "TypeScript",
"developer_needs": [
"tooling",
"security_gates",
"auditability",
"cost_latency_tradeoffs"
],
"moe_experts": [
"governance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
bc4d75ef0267b893b9a67b60ffc642475e9de2eb
|
|
train_00008
| 2026-01-01T00:00:00
|
Code-specialized model families and sizing tradeoffs
|
failure_analysis
|
intermediate
|
Task: failure_analysis
Topic: Code-specialized model families and sizing tradeoffs
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.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
|
[] |
{
"target_language": "SQL",
"developer_needs": [
"reproducibility",
"cost_latency_tradeoffs",
"evaluation_metrics",
"tests_are_truth"
],
"moe_experts": [
"governance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
8433b93806187746fe182fc2cf2b29977e0ddd31
|
|
train_00009
| 2026-01-01T00:00:00
|
Secure code generation and policy gates
|
explain
|
intermediate
|
Task: explain
Topic: Secure code generation and policy gates
Difficulty: intermediate
Target language: 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": [
"tooling",
"ci_integration",
"cost_latency_tradeoffs",
"evaluation_metrics"
],
"moe_experts": [
"data_curation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
6668298056bb64c5197d13fdaa1af40d92419ea6
|
|
train_00010
| 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: 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
|
[
"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",
"security_gates",
"evaluation_metrics",
"reproducibility"
],
"moe_experts": [
"coding_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
794f6a7b95adba75e9e83ef2e68a7ef24c2ba66b
|
|
train_00011
| 2026-01-01T00:00:00
|
Secure code generation and policy gates
|
design
|
advanced
|
Task: design
Topic: Secure code generation and policy gates
Difficulty: advanced
Target language: Bash
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Bash",
"developer_needs": [
"evaluation_metrics",
"auditability",
"documentation",
"cost_latency_tradeoffs"
],
"moe_experts": [
"coding_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
c06725f21f399a3e42710990c8c3aba546392f09
|
|
train_00012
| 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: 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": [
"cost_latency_tradeoffs",
"evaluation_metrics",
"auditability",
"tooling"
],
"moe_experts": [
"governance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
7ef7c743d68b12def868b839b2d25d3c24c62c30
|
|
train_00013
| 2026-01-01T00:00:00
|
Tool calling, sandboxes, and CI integration
|
review
|
advanced
|
Task: review
Topic: Tool calling, sandboxes, and CI integration
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.
Review: correctness, security, performance, governance
|
[
"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",
"tests_are_truth",
"reproducibility"
],
"moe_experts": [
"security_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
79723633f3177d9a6d70bcf9952a97a7ca0841f3
|
|
train_00014
| 2026-01-01T00:00:00
|
Reasoning-first coding models and tunable deliberation
|
design
|
advanced
|
Task: design
Topic: Reasoning-first coding models and tunable deliberation
Difficulty: advanced
Target language: Go
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[] |
{
"target_language": "Go",
"developer_needs": [
"auditability",
"repo_scale_reasoning",
"tooling",
"cost_latency_tradeoffs"
],
"moe_experts": [
"performance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
1edc9091d8145c345c43497436a1b02efb3ae64d
|
|
train_00015
| 2026-01-01T00:00:00
|
Multimodal dev workflows (docs, diagrams, traces)
|
explain
|
expert
|
Task: explain
Topic: Multimodal dev workflows (docs, diagrams, traces)
Difficulty: expert
Target language: 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
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Python",
"developer_needs": [
"auditability",
"cost_latency_tradeoffs",
"tooling",
"evaluation_metrics"
],
"moe_experts": [
"agentic_systems_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
1115301701af81904a8bc8322df46bd8e6d2e46d
|
|
train_00016
| 2026-01-01T00:00:00
|
Reasoning-first coding models and tunable deliberation
|
explain
|
expert
|
Task: explain
Topic: Reasoning-first coding models and tunable deliberation
Difficulty: expert
Target language: 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
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Python",
"developer_needs": [
"evaluation_metrics",
"tests_are_truth",
"cost_latency_tradeoffs",
"security_gates"
],
"moe_experts": [
"evaluation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
c3ae378568b568c5dc1e027d6bab60f99e3616a8
|
|
train_00017
| 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: 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": "TypeScript",
"developer_needs": [
"cost_latency_tradeoffs",
"ci_integration",
"reproducibility",
"tooling"
],
"moe_experts": [
"evaluation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
1f692831fb7b128b0d3ca205ae9c2be83fdd713b
|
|
train_00018
| 2026-01-01T00:00:00
|
Reasoning-first coding models and tunable deliberation
|
explain
|
expert
|
Task: explain
Topic: Reasoning-first coding models and tunable deliberation
Difficulty: expert
Target language: Go
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[] |
{
"target_language": "Go",
"developer_needs": [
"evaluation_metrics",
"tooling",
"security_gates",
"auditability"
],
"moe_experts": [
"governance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
ef691b92d5539fea41de971c8c49917ac58dfb88
|
|
train_00019
| 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: C#
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Review: correctness, security, performance, governance
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "C#",
"developer_needs": [
"auditability",
"documentation",
"cost_latency_tradeoffs",
"repo_scale_reasoning"
],
"moe_experts": [
"governance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
51e0d8e56bce643faeaa51670ad6377293168503
|
|
train_00020
| 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: 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": [
"auditability",
"governance",
"tooling",
"cost_latency_tradeoffs"
],
"moe_experts": [
"data_curation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
70438cee26a353aa8d8db3262c0e7012d8e81198
|
|
train_00021
| 2026-01-01T00:00:00
|
Multimodal dev workflows (docs, diagrams, traces)
|
patch_diff
|
expert
|
Task: patch_diff
Topic: Multimodal dev workflows (docs, diagrams, traces)
Difficulty: expert
Target language: 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": [
"security_gates",
"evaluation_metrics",
"repo_scale_reasoning",
"governance"
],
"moe_experts": [
"evaluation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
761c3821d4741e62b524a044821973fbb131bef6
|
|
train_00022
| 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: 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.
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": [
"tooling",
"evaluation_metrics",
"repo_scale_reasoning",
"cost_latency_tradeoffs"
],
"moe_experts": [
"governance_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
f8ee4bb00c3fceade8c5e19f63c1ccdcb8c4a51c
|
|
train_00023
| 2026-01-01T00:00:00
|
Governance, provenance, and licensing for code data
|
agent_loop
|
intermediate
|
Task: agent_loop
Topic: Governance, provenance, and licensing for code data
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.
Loop: Plan → Edit → Test → Reflect → Human gate
|
[] |
{
"target_language": "TypeScript",
"developer_needs": [
"documentation",
"tooling",
"cost_latency_tradeoffs",
"tests_are_truth"
],
"moe_experts": [
"evaluation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
ae64d3bd2ccc01633fc9ca4faa2483e9f94e0222
|
|
train_00024
| 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: 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": [
"evaluation_metrics",
"auditability",
"reproducibility",
"ci_integration"
],
"moe_experts": [
"governance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
86bce4532697d11d61bf219717e7e0e12a7ac8c1
|
|
train_00025
| 2026-01-01T00:00:00
|
Governance, provenance, and licensing for code data
|
data_pipeline
|
advanced
|
Task: data_pipeline
Topic: Governance, provenance, and licensing for code data
Difficulty: advanced
Target language: Java
Context: 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": [
"documentation",
"auditability",
"evaluation_metrics",
"ci_integration"
],
"moe_experts": [
"coding_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
88f2e7c76e0a878d8774c8cced9a8078902a3a63
|
|
train_00026
| 2026-01-01T00:00:00
|
Code-specialized model families and sizing tradeoffs
|
failure_analysis
|
intermediate
|
Task: failure_analysis
Topic: Code-specialized model families and sizing tradeoffs
Difficulty: intermediate
Target language: JavaScript
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "JavaScript",
"developer_needs": [
"reproducibility",
"documentation",
"auditability",
"ci_integration"
],
"moe_experts": [
"data_curation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
1ae78269b8c7551fb70cac8c547462cdd6d9efca
|
|
train_00027
| 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: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Patch (diff-style):
```diff
- if x == 0:
- return 1/x
+ if x == 0:
+ raise ValueError('division by zero')
```
Acceptance:
- Tests pass
- No new regressions
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Java",
"developer_needs": [
"ci_integration",
"documentation",
"tests_are_truth",
"cost_latency_tradeoffs"
],
"moe_experts": [
"coding_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
dcbeeaacc59b3c0d2d42d19ac9dda4a5b6e1c6fa
|
|
train_00028
| 2026-01-01T00:00:00
|
Secure code generation and policy gates
|
failure_analysis
|
advanced
|
Task: failure_analysis
Topic: Secure code generation and policy gates
Difficulty: advanced
Target language: Rust
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Rust",
"developer_needs": [
"auditability",
"documentation",
"cost_latency_tradeoffs",
"evaluation_metrics"
],
"moe_experts": [
"coding_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
526211db4c366083cd4b243809f19c5d7976c722
|
|
train_00029
| 2026-01-01T00:00:00
|
Mixture-of-Experts (MoE) for code
|
agent_loop
|
advanced
|
Task: agent_loop
Topic: Mixture-of-Experts (MoE) for code
Difficulty: advanced
Target language: 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": [
"governance",
"documentation",
"reproducibility",
"evaluation_metrics"
],
"moe_experts": [
"security_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
194a7ddd1150007057e4a1a7d5e0ffb89d7bf3f6
|
|
train_00030
| 2026-01-01T00:00:00
|
Dataset curation pipelines (filter, dedupe, quality)
|
review
|
intermediate
|
Task: review
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: intermediate
Target language: 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.
Review: correctness, security, performance, governance
|
[] |
{
"target_language": "Rust",
"developer_needs": [
"tooling",
"evaluation_metrics",
"cost_latency_tradeoffs",
"repo_scale_reasoning"
],
"moe_experts": [
"agentic_systems_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
2c3d6b8bac177688e46fa6c8447c673f2b190ede
|
|
train_00031
| 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: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Review: correctness, security, performance, governance
|
[] |
{
"target_language": "C#",
"developer_needs": [
"security_gates",
"documentation",
"cost_latency_tradeoffs",
"tooling"
],
"moe_experts": [
"data_curation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
d40d196039503cd25879510746e046bd431e22bf
|
|
train_00032
| 2026-01-01T00:00:00
|
Secure code generation and policy gates
|
data_pipeline
|
advanced
|
Task: data_pipeline
Topic: Secure code generation and policy gates
Difficulty: advanced
Target language: C#
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
|
[] |
{
"target_language": "C#",
"developer_needs": [
"documentation",
"cost_latency_tradeoffs",
"auditability",
"repo_scale_reasoning"
],
"moe_experts": [
"governance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
feb34a106dc4541afcf68f49e3778b4ec16d3af0
|
|
train_00033
| 2026-01-01T00:00:00
|
Latency, cost, and reliability optimization
|
failure_analysis
|
intermediate
|
Task: failure_analysis
Topic: Latency, cost, and reliability optimization
Difficulty: intermediate
Target language: C#
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
|
[] |
{
"target_language": "C#",
"developer_needs": [
"repo_scale_reasoning",
"ci_integration",
"reproducibility",
"tests_are_truth"
],
"moe_experts": [
"agentic_systems_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
eeee30a4107fdd59b87d30308198ca13eabbc339
|
|
train_00034
| 2026-01-01T00:00:00
|
Agentic coding systems (plan→edit→test→reflect)
|
eval
|
expert
|
Task: eval
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.
Eval:
pass@k, time-to-green, regressions, diff size
|
[] |
{
"target_language": "Rust",
"developer_needs": [
"evaluation_metrics",
"security_gates",
"repo_scale_reasoning",
"cost_latency_tradeoffs"
],
"moe_experts": [
"data_curation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
133c748f2a54b9f5f3fac22859b574ebc907b82a
|
|
train_00035
| 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": [
"tooling",
"reproducibility",
"cost_latency_tradeoffs",
"repo_scale_reasoning"
],
"moe_experts": [
"evaluation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
d4c9de750c3fcf61742509b5ec33edac4ecd4fd5
|
|
train_00036
| 2026-01-01T00:00:00
|
Code-specialized model families and sizing tradeoffs
|
agent_loop
|
expert
|
Task: agent_loop
Topic: Code-specialized model families and sizing tradeoffs
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.
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": [
"tooling",
"auditability",
"tests_are_truth",
"cost_latency_tradeoffs"
],
"moe_experts": [
"security_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
d04a14adb32b746aa16c12c416d393e9fec3515d
|
|
train_00037
| 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: 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",
"documentation",
"evaluation_metrics",
"auditability"
],
"moe_experts": [
"evaluation_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
4cdd138e061a6800f5eb3c648a627b1f39ed566c
|
|
train_00038
| 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: Rust
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
|
[] |
{
"target_language": "Rust",
"developer_needs": [
"auditability",
"governance",
"tests_are_truth",
"repo_scale_reasoning"
],
"moe_experts": [
"agentic_systems_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
9ec802de33f0406f151fd791b0b01308fa53e8e3
|
|
train_00039
| 2026-01-01T00:00:00
|
Model merging, distillation, and continued pretraining
|
compare
|
intermediate
|
Task: compare
Topic: Model merging, distillation, and continued pretraining
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.
Compare: capability, cost, latency, reliability
|
[] |
{
"target_language": "JavaScript",
"developer_needs": [
"security_gates",
"tooling",
"reproducibility",
"documentation"
],
"moe_experts": [
"performance_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
d0275b71c53e24ad8425d520b4406cddec9a7ec9
|
|
train_00040
| 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: 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": [
"evaluation_metrics",
"ci_integration",
"cost_latency_tradeoffs",
"documentation"
],
"moe_experts": [
"agentic_systems_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
63cbc72a41bed999d8f83ad24d72c51f8313144a
|
|
train_00041
| 2026-01-01T00:00:00
|
Code-specialized model families and sizing tradeoffs
|
eval
|
expert
|
Task: eval
Topic: Code-specialized model families and sizing tradeoffs
Difficulty: expert
Target language: C#
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "C#",
"developer_needs": [
"governance",
"cost_latency_tradeoffs",
"ci_integration",
"repo_scale_reasoning"
],
"moe_experts": [
"governance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
d08016954e0f0cf6435469ea00d4d88bc523c878
|
|
train_00042
| 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: Rust
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Rust",
"developer_needs": [
"security_gates",
"evaluation_metrics",
"governance",
"cost_latency_tradeoffs"
],
"moe_experts": [
"coding_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
3c0584122880a0a08be0cadf6fa36c9f1561b59b
|
|
train_00043
| 2026-01-01T00:00:00
|
SWE-bench style real-repo evaluation
|
patch_diff
|
expert
|
Task: patch_diff
Topic: SWE-bench style real-repo evaluation
Difficulty: expert
Target language: 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.
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": "Bash",
"developer_needs": [
"security_gates",
"cost_latency_tradeoffs",
"tooling",
"documentation"
],
"moe_experts": [
"security_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
d796a54b0f4ccda72c637baad7b2b902c66e94f1
|
|
train_00044
| 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: SQL
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "SQL",
"developer_needs": [
"ci_integration",
"evaluation_metrics",
"auditability",
"tooling"
],
"moe_experts": [
"evaluation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
5b16b1206e2ff34af52d76cc1796f90968e74f42
|
|
train_00045
| 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: 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.
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": [
"reproducibility",
"governance",
"evaluation_metrics",
"security_gates"
],
"moe_experts": [
"evaluation_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
5781997bf00a71a09a40e51836495025f185a9d6
|
|
train_00046
| 2026-01-01T00:00:00
|
Reasoning-first coding models and tunable deliberation
|
explain
|
advanced
|
Task: explain
Topic: Reasoning-first coding models and tunable deliberation
Difficulty: advanced
Target language: C#
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "C#",
"developer_needs": [
"evaluation_metrics",
"reproducibility",
"ci_integration",
"repo_scale_reasoning"
],
"moe_experts": [
"data_curation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
c37c76294970d79af730826148476d6d982bf0a0
|
|
train_00047
| 2026-01-01T00:00:00
|
Governance, provenance, and licensing for code data
|
code
|
expert
|
Task: code
Topic: Governance, provenance, and licensing for code data
Difficulty: expert
Target language: Go
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[] |
{
"target_language": "Go",
"developer_needs": [
"auditability",
"repo_scale_reasoning",
"governance",
"reproducibility"
],
"moe_experts": [
"security_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
7c7af049c1b7251e1d24bafaf26ba03560cf4285
|
|
train_00048
| 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: Go
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Patch (diff-style):
```diff
- if x == 0:
- return 1/x
+ if x == 0:
+ raise ValueError('division by zero')
```
Acceptance:
- Tests pass
- No new regressions
|
[] |
{
"target_language": "Go",
"developer_needs": [
"reproducibility",
"auditability",
"tests_are_truth",
"tooling"
],
"moe_experts": [
"performance_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
b5641ad7a1377440c71c496178eeb849076e20d2
|
|
train_00049
| 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: Python
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
|
[] |
{
"target_language": "Python",
"developer_needs": [
"security_gates",
"tooling",
"governance",
"documentation"
],
"moe_experts": [
"performance_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
4ce7ef1adde19e69c768c4a3231d5d31359900c2
|
|
train_00050
| 2026-01-01T00:00:00
|
Self-improving agents and feedback loops
|
eval
|
intermediate
|
Task: eval
Topic: Self-improving agents and feedback loops
Difficulty: intermediate
Target language: 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.
Eval:
pass@k, time-to-green, regressions, diff size
|
[] |
{
"target_language": "Python",
"developer_needs": [
"repo_scale_reasoning",
"tooling",
"tests_are_truth",
"security_gates"
],
"moe_experts": [
"data_curation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
0cce39be9ca28d6597dc5be78f397037a44cbf15
|
|
train_00051
| 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: 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
|
[] |
{
"target_language": "JavaScript",
"developer_needs": [
"repo_scale_reasoning",
"reproducibility",
"governance",
"tests_are_truth"
],
"moe_experts": [
"performance_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
0fe53fc398818e88c72a86ca11180f438aef4e22
|
|
train_00052
| 2026-01-01T00:00:00
|
Model merging, distillation, and continued pretraining
|
agent_loop
|
advanced
|
Task: agent_loop
Topic: Model merging, distillation, and continued pretraining
Difficulty: advanced
Target language: Go
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
|
[] |
{
"target_language": "Go",
"developer_needs": [
"security_gates",
"ci_integration",
"tooling",
"reproducibility"
],
"moe_experts": [
"agentic_systems_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
17d4f6ac8a1f45b39b0ee6bc10cd76084ed4f1b4
|
|
train_00053
| 2026-01-01T00:00:00
|
Secure code generation and policy gates
|
code
|
expert
|
Task: code
Topic: Secure code generation and policy gates
Difficulty: expert
Target language: Go
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
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": [
"tests_are_truth",
"documentation",
"auditability",
"governance"
],
"moe_experts": [
"performance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
3e230847e1356ed26fc97c6607de4fcf648703e9
|
|
train_00054
| 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: 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.
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": [
"governance",
"repo_scale_reasoning",
"tooling",
"tests_are_truth"
],
"moe_experts": [
"agentic_systems_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
10a2ab3c1037d5018482ee7bb013503b165bd487
|
|
train_00055
| 2026-01-01T00:00:00
|
Extended context and repo-scale understanding
|
data_pipeline
|
advanced
|
Task: data_pipeline
Topic: Extended context and repo-scale understanding
Difficulty: advanced
Target language: C#
Context: 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": "C#",
"developer_needs": [
"repo_scale_reasoning",
"documentation",
"reproducibility",
"cost_latency_tradeoffs"
],
"moe_experts": [
"coding_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
f7d60c1562a3ea10ead990825479271f6a71412b
|
|
train_00056
| 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: Python
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Patch (diff-style):
```diff
- if x == 0:
- return 1/x
+ if x == 0:
+ raise ValueError('division by zero')
```
Acceptance:
- Tests pass
- No new regressions
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Python",
"developer_needs": [
"auditability",
"evaluation_metrics",
"ci_integration",
"cost_latency_tradeoffs"
],
"moe_experts": [
"coding_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
bf49a7e9048be1e0b3bbda8dba74d960f4084d73
|
|
train_00057
| 2026-01-01T00:00:00
|
Code-specialized model families and sizing tradeoffs
|
eval
|
expert
|
Task: eval
Topic: Code-specialized model families and sizing tradeoffs
Difficulty: expert
Target language: 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.
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": [
"auditability",
"documentation",
"evaluation_metrics",
"repo_scale_reasoning"
],
"moe_experts": [
"governance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
e84100486f020f94ac48f7de64e4933af1a8d498
|
|
train_00058
| 2026-01-01T00:00:00
|
Governance, provenance, and licensing for code data
|
failure_analysis
|
advanced
|
Task: failure_analysis
Topic: Governance, provenance, and licensing for code data
Difficulty: advanced
Target language: 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.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
|
[] |
{
"target_language": "SQL",
"developer_needs": [
"documentation",
"governance",
"auditability",
"security_gates"
],
"moe_experts": [
"coding_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
cd7aae7df7eea98aacad8c4ff1bab500d7643024
|
|
train_00059
| 2026-01-01T00:00:00
|
Tool calling, sandboxes, and CI integration
|
failure_analysis
|
intermediate
|
Task: failure_analysis
Topic: Tool calling, sandboxes, and CI integration
Difficulty: intermediate
Target language: JavaScript
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
|
[] |
{
"target_language": "JavaScript",
"developer_needs": [
"documentation",
"reproducibility",
"evaluation_metrics",
"ci_integration"
],
"moe_experts": [
"agentic_systems_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
290f44af830f8f6c86ff1d0d38f53c034514bab4
|
|
train_00060
| 2026-01-01T00:00:00
|
Code-specialized model families and sizing tradeoffs
|
eval
|
advanced
|
Task: eval
Topic: Code-specialized model families and sizing tradeoffs
Difficulty: advanced
Target language: Go
Context: 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": "Go",
"developer_needs": [
"evaluation_metrics",
"tooling",
"ci_integration",
"reproducibility"
],
"moe_experts": [
"security_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
cb48bd866fa4d9ff39099d06e546351725b63631
|
|
train_00061
| 2026-01-01T00:00:00
|
Secure code generation and policy gates
|
failure_analysis
|
expert
|
Task: failure_analysis
Topic: Secure code generation and policy gates
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.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
|
[] |
{
"target_language": "JavaScript",
"developer_needs": [
"tooling",
"documentation",
"governance",
"reproducibility"
],
"moe_experts": [
"performance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
fc385268edbd307cd3ccc0c87408e19620334d59
|
|
train_00062
| 2026-01-01T00:00:00
|
Multimodal dev workflows (docs, diagrams, traces)
|
agent_loop
|
advanced
|
Task: agent_loop
Topic: Multimodal dev workflows (docs, diagrams, traces)
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.
Loop: Plan → Edit → Test → Reflect → Human gate
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "TypeScript",
"developer_needs": [
"evaluation_metrics",
"tests_are_truth",
"auditability",
"cost_latency_tradeoffs"
],
"moe_experts": [
"data_curation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
58f8ed6e7d81c5f650094361063209b15d3e122a
|
|
train_00063
| 2026-01-01T00:00:00
|
Multimodal dev workflows (docs, diagrams, traces)
|
explain
|
expert
|
Task: explain
Topic: Multimodal dev workflows (docs, diagrams, traces)
Difficulty: expert
Target language: 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",
"tooling",
"repo_scale_reasoning",
"security_gates"
],
"moe_experts": [
"performance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
44e35fd43e70fe485de38ea906295df3a69ecce8
|
|
train_00064
| 2026-01-01T00:00:00
|
Agentic coding systems (plan→edit→test→reflect)
|
compare
|
expert
|
Task: compare
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.
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": [
"cost_latency_tradeoffs",
"tooling",
"reproducibility",
"documentation"
],
"moe_experts": [
"coding_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
88835deeb7b9cae958759be8f14d4083a7235d0d
|
|
train_00065
| 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: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
|
[] |
{
"target_language": "Python",
"developer_needs": [
"tests_are_truth",
"tooling",
"evaluation_metrics",
"cost_latency_tradeoffs"
],
"moe_experts": [
"data_curation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
1f4c2ce6f327a8aae1e111a83fca47c5f1cad05f
|
|
train_00066
| 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: 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": [
"evaluation_metrics",
"tests_are_truth",
"security_gates",
"reproducibility"
],
"moe_experts": [
"data_curation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
44fae51071b6aab33ae4e9b61ce23c6bc6763b40
|
|
train_00067
| 2026-01-01T00:00:00
|
Code-specialized model families and sizing tradeoffs
|
code
|
advanced
|
Task: code
Topic: Code-specialized model families and sizing tradeoffs
Difficulty: advanced
Target language: Go
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[] |
{
"target_language": "Go",
"developer_needs": [
"security_gates",
"documentation",
"repo_scale_reasoning",
"tests_are_truth"
],
"moe_experts": [
"evaluation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
a2488f99fb7cd358a9b92c6c223d96350d954ccb
|
|
train_00068
| 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: 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.
Loop: Plan → Edit → Test → Reflect → Human gate
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Go",
"developer_needs": [
"reproducibility",
"security_gates",
"evaluation_metrics",
"governance"
],
"moe_experts": [
"performance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
e282435a1d89180a062ae21a1e149e8956946c67
|
|
train_00069
| 2026-01-01T00:00:00
|
Dataset curation pipelines (filter, dedupe, quality)
|
design
|
intermediate
|
Task: design
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: intermediate
Target language: C#
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[] |
{
"target_language": "C#",
"developer_needs": [
"repo_scale_reasoning",
"security_gates",
"documentation",
"tooling"
],
"moe_experts": [
"performance_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
8c4a2580477b0deba99031eca3a243c8a2b3900e
|
|
train_00070
| 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: Bash
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[] |
{
"target_language": "Bash",
"developer_needs": [
"cost_latency_tradeoffs",
"documentation",
"tooling",
"governance"
],
"moe_experts": [
"evaluation_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
3686409d01a8eb5efb8dfdd0818f089a2c6410f5
|
|
train_00071
| 2026-01-01T00:00:00
|
Secure code generation and policy gates
|
compare
|
intermediate
|
Task: compare
Topic: Secure code generation and policy gates
Difficulty: intermediate
Target language: 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": [
"tooling",
"reproducibility",
"documentation",
"tests_are_truth"
],
"moe_experts": [
"evaluation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
c9e0bcb9e45869ebebdee7bae09effa322315bf2
|
|
train_00072
| 2026-01-01T00:00:00
|
Latency, cost, and reliability optimization
|
code
|
intermediate
|
Task: code
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.
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": [
"ci_integration",
"repo_scale_reasoning",
"reproducibility",
"governance"
],
"moe_experts": [
"security_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
24dbc1edb129136045a290f6ccd480e97f03eb18
|
|
train_00073
| 2026-01-01T00:00:00
|
Latency, cost, and reliability optimization
|
explain
|
intermediate
|
Task: explain
Topic: Latency, cost, and reliability optimization
Difficulty: intermediate
Target language: C#
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "C#",
"developer_needs": [
"documentation",
"ci_integration",
"cost_latency_tradeoffs",
"tooling"
],
"moe_experts": [
"coding_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
0e31566574dd7a6e7c753959c2959274e9c70319
|
|
train_00074
| 2026-01-01T00:00:00
|
Model merging, distillation, and continued pretraining
|
data_pipeline
|
advanced
|
Task: data_pipeline
Topic: Model merging, distillation, and continued pretraining
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.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
|
[] |
{
"target_language": "SQL",
"developer_needs": [
"auditability",
"tooling",
"cost_latency_tradeoffs",
"reproducibility"
],
"moe_experts": [
"performance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
ee1aa9be0073469989f748c8fa4a589cd01025d1
|
|
train_00075
| 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: 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": [
"governance",
"tests_are_truth",
"evaluation_metrics",
"auditability"
],
"moe_experts": [
"agentic_systems_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
1430a62d71fc4fb7a744e16ede6f4318e0e21aab
|
|
train_00076
| 2026-01-01T00:00:00
|
Model merging, distillation, and continued pretraining
|
review
|
intermediate
|
Task: review
Topic: Model merging, distillation, and continued pretraining
Difficulty: intermediate
Target language: JavaScript
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Review: correctness, security, performance, governance
|
[] |
{
"target_language": "JavaScript",
"developer_needs": [
"repo_scale_reasoning",
"reproducibility",
"documentation",
"auditability"
],
"moe_experts": [
"performance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
324c7cd9afeabab238afe5c71e9fda5172958c18
|
|
train_00077
| 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: Bash
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Bash",
"developer_needs": [
"ci_integration",
"tests_are_truth",
"cost_latency_tradeoffs",
"security_gates"
],
"moe_experts": [
"evaluation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
d615f811619b45e741bf28f39c77d1812fd49541
|
|
train_00078
| 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: Python
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Review: correctness, security, performance, governance
|
[
"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",
"auditability",
"governance",
"ci_integration"
],
"moe_experts": [
"agentic_systems_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
c629b9b3541f2cd9a571f854a5707b9fd5d34b8f
|
|
train_00079
| 2026-01-01T00:00:00
|
Reasoning-first coding models and tunable deliberation
|
compare
|
advanced
|
Task: compare
Topic: Reasoning-first coding models and tunable deliberation
Difficulty: advanced
Target language: C#
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
|
[] |
{
"target_language": "C#",
"developer_needs": [
"repo_scale_reasoning",
"evaluation_metrics",
"security_gates",
"auditability"
],
"moe_experts": [
"performance_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
bd324f8b002b73ea46aae71063924c4f674827c7
|
|
train_00080
| 2026-01-01T00:00:00
|
Tool calling, sandboxes, and CI integration
|
eval
|
intermediate
|
Task: eval
Topic: Tool calling, sandboxes, and CI integration
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.
Eval:
pass@k, time-to-green, regressions, diff size
|
[] |
{
"target_language": "Rust",
"developer_needs": [
"auditability",
"repo_scale_reasoning",
"tooling",
"documentation"
],
"moe_experts": [
"agentic_systems_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
4235c0a47708143c2dcc01d24e29796e1772caa6
|
|
train_00081
| 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: 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.
Compare: capability, cost, latency, reliability
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Go",
"developer_needs": [
"ci_integration",
"evaluation_metrics",
"tooling",
"governance"
],
"moe_experts": [
"coding_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
16c0969649c06a7f6fcfef215e4dfb0737a8da64
|
|
train_00082
| 2026-01-01T00:00:00
|
Model merging, distillation, and continued pretraining
|
code
|
advanced
|
Task: code
Topic: Model merging, distillation, and continued pretraining
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.
Scaffold:
```python
def agent_loop(plan, edit, test, issue, max_iters=4):
history = []
p = plan(issue)
for _ in range(max_iters):
patch = edit(issue, p)
ok, report = test(patch)
history.append({"plan": p, "ok": ok})
if ok:
return patch, history
p = p + " | refine"
return patch, history
```
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Python",
"developer_needs": [
"repo_scale_reasoning",
"ci_integration",
"governance",
"security_gates"
],
"moe_experts": [
"security_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
1554ddd6a87917fbdac944f808850442c06d39aa
|
|
train_00083
| 2026-01-01T00:00:00
|
Extended context and repo-scale understanding
|
data_pipeline
|
expert
|
Task: data_pipeline
Topic: Extended context and repo-scale understanding
Difficulty: expert
Target language: Rust
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
|
[] |
{
"target_language": "Rust",
"developer_needs": [
"governance",
"documentation",
"security_gates",
"cost_latency_tradeoffs"
],
"moe_experts": [
"governance_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
2518002a55ca5242c8952cdc167f2a9492a728d8
|
|
train_00084
| 2026-01-01T00:00:00
|
Extended context and repo-scale understanding
|
data_pipeline
|
advanced
|
Task: data_pipeline
Topic: Extended context and repo-scale understanding
Difficulty: advanced
Target language: Java
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
|
[] |
{
"target_language": "Java",
"developer_needs": [
"ci_integration",
"documentation",
"auditability",
"tooling"
],
"moe_experts": [
"security_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
537ced0ddbaf5eeee1cf69ad7de355202637b1ae
|
|
train_00085
| 2026-01-01T00:00:00
|
Governance, provenance, and licensing for code data
|
data_pipeline
|
intermediate
|
Task: data_pipeline
Topic: Governance, provenance, and licensing for code data
Difficulty: intermediate
Target language: 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": [
"documentation",
"security_gates",
"cost_latency_tradeoffs",
"governance"
],
"moe_experts": [
"evaluation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
45d4036b3fb333f12c407b9aabc3c2fb40b45084
|
|
train_00086
| 2026-01-01T00:00:00
|
Self-improving agents and feedback loops
|
eval
|
expert
|
Task: eval
Topic: Self-improving agents and feedback loops
Difficulty: expert
Target language: Rust
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Rust",
"developer_needs": [
"repo_scale_reasoning",
"tests_are_truth",
"documentation",
"cost_latency_tradeoffs"
],
"moe_experts": [
"evaluation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
e44e8e5280e067d801d7126035271cad15d0afbf
|
|
train_00087
| 2026-01-01T00:00:00
|
Multimodal dev workflows (docs, diagrams, traces)
|
compare
|
intermediate
|
Task: compare
Topic: Multimodal dev workflows (docs, diagrams, traces)
Difficulty: intermediate
Target language: 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": [
"ci_integration",
"tooling",
"security_gates",
"cost_latency_tradeoffs"
],
"moe_experts": [
"governance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
53cffc2f29065bfd0992927ad22579fd2e63f0cd
|
|
train_00088
| 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: 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
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "Bash",
"developer_needs": [
"auditability",
"reproducibility",
"documentation",
"tests_are_truth"
],
"moe_experts": [
"security_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
f8ac4447ff5f26177f3413935fc4962974bd6bb7
|
|
train_00089
| 2026-01-01T00:00:00
|
Multimodal dev workflows (docs, diagrams, traces)
|
patch_diff
|
advanced
|
Task: patch_diff
Topic: Multimodal dev workflows (docs, diagrams, traces)
Difficulty: advanced
Target language: 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.
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": "Bash",
"developer_needs": [
"repo_scale_reasoning",
"auditability",
"security_gates",
"tooling"
],
"moe_experts": [
"evaluation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
e2bcf02d2c096b6337567adc48b26059269c4ceb
|
|
train_00090
| 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: 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": [
"tests_are_truth",
"security_gates",
"cost_latency_tradeoffs",
"ci_integration"
],
"moe_experts": [
"performance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
fc29b09b1d31d8c2a9d9572984245a648d8348f8
|
|
train_00091
| 2026-01-01T00:00:00
|
Model merging, distillation, and continued pretraining
|
eval
|
intermediate
|
Task: eval
Topic: Model merging, distillation, and continued pretraining
Difficulty: intermediate
Target language: Go
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
|
[] |
{
"target_language": "Go",
"developer_needs": [
"cost_latency_tradeoffs",
"tooling",
"governance",
"auditability"
],
"moe_experts": [
"coding_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
cd04c65643dbb0b8ccdbc0200279f05d6e77943d
|
|
train_00092
| 2026-01-01T00:00:00
|
Governance, provenance, and licensing for code data
|
explain
|
intermediate
|
Task: explain
Topic: Governance, provenance, and licensing for code data
Difficulty: intermediate
Target language: C#
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
|
[
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] |
{
"target_language": "C#",
"developer_needs": [
"documentation",
"cost_latency_tradeoffs",
"repo_scale_reasoning",
"tests_are_truth"
],
"moe_experts": [
"performance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
2eb41c5bcc084abf88c072bf18a095c7309390be
|
|
train_00093
| 2026-01-01T00:00:00
|
SWE-bench style real-repo evaluation
|
agent_loop
|
advanced
|
Task: agent_loop
Topic: SWE-bench style real-repo evaluation
Difficulty: advanced
Target language: C#
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
|
[] |
{
"target_language": "C#",
"developer_needs": [
"security_gates",
"auditability",
"evaluation_metrics",
"documentation"
],
"moe_experts": [
"agentic_systems_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
163cb1c8fe24f4549288ee8174d67f4235a7fe7c
|
|
train_00094
| 2026-01-01T00:00:00
|
Model merging, distillation, and continued pretraining
|
agent_loop
|
expert
|
Task: agent_loop
Topic: Model merging, distillation, and continued pretraining
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.
Loop: Plan → Edit → Test → Reflect → Human gate
|
[] |
{
"target_language": "SQL",
"developer_needs": [
"cost_latency_tradeoffs",
"auditability",
"governance",
"repo_scale_reasoning"
],
"moe_experts": [
"coding_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
f5ad31a60526fd6005d6e10423ecc52340ca175b
|
|
train_00095
| 2026-01-01T00:00:00
|
Mixture-of-Experts (MoE) for code
|
review
|
expert
|
Task: review
Topic: Mixture-of-Experts (MoE) for code
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.
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": [
"ci_integration",
"tooling",
"tests_are_truth",
"reproducibility"
],
"moe_experts": [
"security_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
9422a0bd579a981d876f568aae15a6e5700ed1ce
|
|
train_00096
| 2026-01-01T00:00:00
|
Dataset curation pipelines (filter, dedupe, quality)
|
explain
|
advanced
|
Task: explain
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: advanced
Target language: 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": [
"governance",
"auditability",
"evaluation_metrics",
"cost_latency_tradeoffs"
],
"moe_experts": [
"performance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
957d3329ab5cd2aaea7709bcfd9e8da991329fd2
|
|
train_00097
| 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: 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": [
"tooling",
"reproducibility",
"repo_scale_reasoning",
"auditability"
],
"moe_experts": [
"governance_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
0f0356266fe236a1a6f25e7387683eeaf62007da
|
|
train_00098
| 2026-01-01T00:00:00
|
SWE-bench style real-repo evaluation
|
code
|
advanced
|
Task: code
Topic: SWE-bench style real-repo evaluation
Difficulty: advanced
Target language: Python
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts.
|
Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Scaffold:
```python
def agent_loop(plan, edit, test, issue, max_iters=4):
history = []
p = plan(issue)
for _ in range(max_iters):
patch = edit(issue, p)
ok, report = test(patch)
history.append({"plan": p, "ok": ok})
if ok:
return patch, history
p = p + " | refine"
return patch, history
```
|
[] |
{
"target_language": "Python",
"developer_needs": [
"tests_are_truth",
"tooling",
"reproducibility",
"auditability"
],
"moe_experts": [
"performance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
a4e6cd030c360ecf99d9da01cbd11033e5c4c3ec
|
|
train_00099
| 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: 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.
Eval:
pass@k, time-to-green, regressions, diff size
|
[] |
{
"target_language": "Python",
"developer_needs": [
"governance",
"reproducibility",
"repo_scale_reasoning",
"ci_integration"
],
"moe_experts": [
"performance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
}
|
4b3d8ec035ac590bdcd83876a36b251701cf340f
|
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