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train_48800
2026-01-01T00:00:00
Governance, provenance, and licensing for code data
patch_diff
intermediate
Task: patch_diff Topic: Governance, provenance, and licensing for code data Difficulty: intermediate Target language: 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": [ "governance", "tooling", "reproducibility", "auditability" ], "moe_experts": [ "coding_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
cbc09dc7674ab8737b66279b112ae1388c718493
train_48801
2026-01-01T00:00:00
Reasoning-first coding models and tunable deliberation
failure_analysis
expert
Task: failure_analysis Topic: Reasoning-first coding models and tunable deliberation Difficulty: expert Target language: JavaScript Context: Offline/local deployment with limited compute. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Failure: - Initial patch broke edge case Reflection: - Missing zero-input guard Correction: - Add explicit validation + test
[]
{ "target_language": "JavaScript", "developer_needs": [ "auditability", "documentation", "governance", "evaluation_metrics" ], "moe_experts": [ "security_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
e6bcf062f84e3c9890f27821c55a1e808a33690d
train_48802
2026-01-01T00:00:00
Model merging, distillation, and continued pretraining
code
intermediate
Task: code Topic: Model merging, distillation, and continued pretraining Difficulty: intermediate Target language: SQL Context: Large monorepo with flaky tests and strict CI. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "SQL", "developer_needs": [ "auditability", "governance", "tooling", "tests_are_truth" ], "moe_experts": [ "coding_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
504d7a943f184a5635cfcc78f1e2babc010b6541
train_48803
2026-01-01T00:00:00
Latency, cost, and reliability optimization
agent_loop
intermediate
Task: agent_loop Topic: Latency, cost, and reliability optimization Difficulty: intermediate Target language: Rust Context: Research team validating claims against real repos. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Loop: Plan → Edit → Test → Reflect → Human gate
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Rust", "developer_needs": [ "evaluation_metrics", "tooling", "documentation", "auditability" ], "moe_experts": [ "agentic_systems_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
48e14be1c2135d0145eee3ebacf2b713a337e4e9
train_48804
2026-01-01T00:00:00
Governance, provenance, and licensing for code data
design
expert
Task: design Topic: Governance, provenance, and licensing for code data 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. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "Bash", "developer_needs": [ "auditability", "security_gates", "ci_integration", "governance" ], "moe_experts": [ "data_curation_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
247edf034544159c33ea8cc271bc92ead15754f6
train_48805
2026-01-01T00:00:00
Tool calling, sandboxes, and CI integration
compare
intermediate
Task: compare Topic: Tool calling, sandboxes, and CI integration 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. Compare: capability, cost, latency, reliability
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "SQL", "developer_needs": [ "documentation", "auditability", "reproducibility", "ci_integration" ], "moe_experts": [ "evaluation_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
af7e551ad262c329ad55293807f6e51fd9314a8f
train_48806
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: 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. Loop: Plan → Edit → Test → Reflect → Human gate
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Python", "developer_needs": [ "tooling", "repo_scale_reasoning", "reproducibility", "tests_are_truth" ], "moe_experts": [ "evaluation_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
2fbc4765fa3c2153d74d53cdd5f4565410809356
train_48807
2026-01-01T00:00:00
Reasoning-first coding models and tunable deliberation
data_pipeline
expert
Task: data_pipeline Topic: Reasoning-first coding models and tunable deliberation Difficulty: expert Target language: Bash Context: Large monorepo with flaky tests and strict CI. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Pipeline: Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
[]
{ "target_language": "Bash", "developer_needs": [ "reproducibility", "cost_latency_tradeoffs", "tooling", "auditability" ], "moe_experts": [ "security_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
601a8db1bf5f29e7951c8efed104870bcfdc0286
train_48808
2026-01-01T00:00:00
Self-improving agents and feedback loops
code
expert
Task: code Topic: Self-improving agents and feedback loops Difficulty: expert Target language: 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": [ "reproducibility", "tests_are_truth", "ci_integration", "governance" ], "moe_experts": [ "evaluation_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
8c70897e144508fb77980fec13297ee795f6ae1d
train_48809
2026-01-01T00:00:00
SWE-bench style real-repo evaluation
failure_analysis
expert
Task: failure_analysis Topic: SWE-bench style real-repo evaluation Difficulty: expert Target language: Python Context: Research team validating claims against real repos. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Failure: - Initial patch broke edge case Reflection: - Missing zero-input guard Correction: - Add explicit validation + test
[]
{ "target_language": "Python", "developer_needs": [ "ci_integration", "governance", "reproducibility", "tooling" ], "moe_experts": [ "evaluation_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
d8f02c1f4d932a347301ba3bef48ff87e71da238
train_48810
2026-01-01T00:00:00
Extended context and repo-scale understanding
code
advanced
Task: code Topic: Extended context and repo-scale understanding Difficulty: advanced Target language: 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 ```
[]
{ "target_language": "Python", "developer_needs": [ "ci_integration", "auditability", "cost_latency_tradeoffs", "security_gates" ], "moe_experts": [ "data_curation_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
a1ff4289366ab49b380e5f80de71ef692911cb15
train_48811
2026-01-01T00:00:00
Reasoning-first coding models and tunable deliberation
agent_loop
advanced
Task: agent_loop Topic: Reasoning-first coding models and tunable deliberation Difficulty: advanced Target language: Python Context: Offline/local deployment with limited compute. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Loop: Plan → Edit → Test → Reflect → Human gate
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Python", "developer_needs": [ "security_gates", "tests_are_truth", "ci_integration", "governance" ], "moe_experts": [ "coding_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
2abaff69fc3f38cbb02470fb20a44710a748b2cf
train_48812
2026-01-01T00:00:00
Governance, provenance, and licensing for code data
compare
advanced
Task: compare Topic: Governance, provenance, and licensing for code data Difficulty: advanced Target language: TypeScript Context: Regulated environment requiring audit trails. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Compare: capability, cost, latency, reliability
[]
{ "target_language": "TypeScript", "developer_needs": [ "cost_latency_tradeoffs", "governance", "tests_are_truth", "tooling" ], "moe_experts": [ "evaluation_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
4d963016ee80bab3c7cd82eb1b5cab04c06b380d
train_48813
2026-01-01T00:00:00
Mixture-of-Experts (MoE) for code
patch_diff
intermediate
Task: patch_diff Topic: Mixture-of-Experts (MoE) for code Difficulty: intermediate Target language: TypeScript Context: Large monorepo with flaky tests and strict CI. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. 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": [ "tests_are_truth", "evaluation_metrics", "auditability", "tooling" ], "moe_experts": [ "agentic_systems_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
1c97ed724e93ef6115d5b1d88c26cab73e5b1c09
train_48814
2026-01-01T00:00:00
Multimodal dev workflows (docs, diagrams, traces)
review
expert
Task: review Topic: Multimodal dev workflows (docs, diagrams, traces) Difficulty: expert Target language: TypeScript Context: Offline/local deployment with limited compute. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Review: correctness, security, performance, governance
[]
{ "target_language": "TypeScript", "developer_needs": [ "cost_latency_tradeoffs", "tooling", "ci_integration", "reproducibility" ], "moe_experts": [ "governance_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
b85e533e1c5326612e7b9127621a4956977c4592
train_48815
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: 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": "JavaScript", "developer_needs": [ "security_gates", "tests_are_truth", "auditability", "governance" ], "moe_experts": [ "governance_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
102c9f6e44d378faf9e5e9f515813f73defefd45
train_48816
2026-01-01T00:00:00
Model merging, distillation, and continued pretraining
eval
expert
Task: eval Topic: Model merging, distillation, and continued pretraining Difficulty: expert Target language: SQL Context: Regulated environment requiring audit trails. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Eval: pass@k, time-to-green, regressions, diff size
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "SQL", "developer_needs": [ "tooling", "repo_scale_reasoning", "auditability", "cost_latency_tradeoffs" ], "moe_experts": [ "evaluation_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
f4fe0986c87372f51cea0ad78d2014ac6ff5aff6
train_48817
2026-01-01T00:00:00
Self-improving agents and feedback loops
design
expert
Task: design Topic: Self-improving agents and feedback loops Difficulty: expert Target language: 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. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "JavaScript", "developer_needs": [ "tests_are_truth", "governance", "auditability", "cost_latency_tradeoffs" ], "moe_experts": [ "coding_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
6b8f85dae81fa224cd9e36fb26c9dbc3125c3040
train_48818
2026-01-01T00:00:00
Extended context and repo-scale understanding
eval
expert
Task: eval Topic: Extended context and repo-scale understanding Difficulty: expert Target language: 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. Eval: pass@k, time-to-green, regressions, diff size
[]
{ "target_language": "Java", "developer_needs": [ "documentation", "tests_are_truth", "ci_integration", "reproducibility" ], "moe_experts": [ "performance_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
088ae1f2a8e7c90dfe19b8a54f2f0c2f7da12245
train_48819
2026-01-01T00:00:00
Secure code generation and policy gates
compare
expert
Task: compare Topic: Secure code generation and policy gates Difficulty: expert Target language: C# Context: 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": "C#", "developer_needs": [ "auditability", "ci_integration", "reproducibility", "documentation" ], "moe_experts": [ "coding_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
1d2978aa5e18f15e6e368caf8a6aac010f77a16c
train_48820
2026-01-01T00:00:00
Multimodal dev workflows (docs, diagrams, traces)
failure_analysis
advanced
Task: failure_analysis Topic: Multimodal dev workflows (docs, diagrams, traces) Difficulty: advanced Target language: Bash Context: High-traffic service with latency SLOs. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Failure: - Initial patch broke edge case Reflection: - Missing zero-input guard Correction: - Add explicit validation + test
[]
{ "target_language": "Bash", "developer_needs": [ "governance", "cost_latency_tradeoffs", "documentation", "ci_integration" ], "moe_experts": [ "data_curation_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
0402ea2401676b6c4177a4c0170a096b191732de
train_48821
2026-01-01T00:00:00
Reasoning-first coding models and tunable deliberation
data_pipeline
expert
Task: data_pipeline Topic: Reasoning-first coding models and tunable deliberation 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. Pipeline: Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
[]
{ "target_language": "SQL", "developer_needs": [ "tooling", "auditability", "ci_integration", "tests_are_truth" ], "moe_experts": [ "evaluation_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
14c0bdd10cf435e4f789d1cd96068398a9b8c856
train_48822
2026-01-01T00:00:00
SWE-bench style real-repo evaluation
explain
intermediate
Task: explain Topic: SWE-bench style real-repo evaluation Difficulty: intermediate Target language: SQL Context: Offline/local deployment with limited compute. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "SQL", "developer_needs": [ "security_gates", "auditability", "ci_integration", "cost_latency_tradeoffs" ], "moe_experts": [ "coding_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
5f2d2a75c861e61af211b2f132f68cae1eb06441
train_48823
2026-01-01T00:00:00
Multimodal dev workflows (docs, diagrams, traces)
failure_analysis
advanced
Task: failure_analysis Topic: Multimodal dev workflows (docs, diagrams, traces) 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. 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": "Go", "developer_needs": [ "tooling", "security_gates", "ci_integration", "evaluation_metrics" ], "moe_experts": [ "agentic_systems_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
4d25a3c21c865391fe7f4ae1de28c11a4b8d4458
train_48824
2026-01-01T00:00:00
Model merging, distillation, and continued pretraining
eval
expert
Task: eval Topic: Model merging, distillation, and continued pretraining Difficulty: expert Target language: 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. Eval: pass@k, time-to-green, regressions, diff size
[]
{ "target_language": "SQL", "developer_needs": [ "tests_are_truth", "repo_scale_reasoning", "cost_latency_tradeoffs", "evaluation_metrics" ], "moe_experts": [ "security_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
ea5e74a9e8dfdb14be0b309bde7b5e639711fb2b
train_48825
2026-01-01T00:00:00
Extended context and repo-scale understanding
data_pipeline
intermediate
Task: data_pipeline Topic: Extended context and repo-scale understanding Difficulty: intermediate Target language: C# Context: Regulated environment requiring audit trails. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Pipeline: Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
[]
{ "target_language": "C#", "developer_needs": [ "reproducibility", "tooling", "tests_are_truth", "auditability" ], "moe_experts": [ "security_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
ffed4af49f0f3d6c21e6ae4ac0e3109853f578c6
train_48826
2026-01-01T00:00:00
SWE-bench style real-repo evaluation
compare
intermediate
Task: compare Topic: SWE-bench style real-repo evaluation Difficulty: intermediate Target language: SQL Context: High-traffic service with latency SLOs. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Compare: capability, cost, latency, reliability
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "SQL", "developer_needs": [ "tooling", "governance", "ci_integration", "tests_are_truth" ], "moe_experts": [ "agentic_systems_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
f058e1badcd4bbc176b9392029c6a4104ab9cc8f
train_48827
2026-01-01T00:00:00
Governance, provenance, and licensing for code data
design
intermediate
Task: design Topic: Governance, provenance, and licensing for code data 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. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "Go", "developer_needs": [ "repo_scale_reasoning", "cost_latency_tradeoffs", "security_gates", "tooling" ], "moe_experts": [ "coding_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
b501f3dc2fbba7b0fae50a7f638fc63ac81c3bdf
train_48828
2026-01-01T00:00:00
Reasoning-first coding models and tunable deliberation
patch_diff
expert
Task: patch_diff Topic: Reasoning-first coding models and tunable deliberation 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. Patch (diff-style): ```diff - if x == 0: - return 1/x + if x == 0: + raise ValueError('division by zero') ``` Acceptance: - Tests pass - No new regressions
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Rust", "developer_needs": [ "governance", "auditability", "evaluation_metrics", "security_gates" ], "moe_experts": [ "agentic_systems_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
f6b65663886f7204efe3c351ac8a3635bd0a9528
train_48829
2026-01-01T00:00:00
Latency, cost, and reliability optimization
agent_loop
advanced
Task: agent_loop Topic: Latency, cost, and reliability optimization Difficulty: advanced Target language: Bash Context: High-traffic service with latency SLOs. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Loop: Plan → Edit → Test → Reflect → Human gate
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Bash", "developer_needs": [ "cost_latency_tradeoffs", "documentation", "governance", "security_gates" ], "moe_experts": [ "governance_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
f5ca31cd3bc43de20aaff70be64426c970d7a8d1
train_48830
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: SQL Context: Large monorepo with flaky tests and strict CI. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "SQL", "developer_needs": [ "ci_integration", "repo_scale_reasoning", "documentation", "auditability" ], "moe_experts": [ "security_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
fb4eb35266139c98bfaf952074468d395df199e8
train_48831
2026-01-01T00:00:00
Self-improving agents and feedback loops
compare
advanced
Task: compare Topic: Self-improving agents and feedback loops Difficulty: advanced Target language: Java Context: Regulated environment requiring audit trails. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Compare: capability, cost, latency, reliability
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Java", "developer_needs": [ "evaluation_metrics", "tests_are_truth", "repo_scale_reasoning", "documentation" ], "moe_experts": [ "security_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
0bf037373edfaadeeb9bd53cb672cb1c10945f36
train_48832
2026-01-01T00:00:00
SWE-bench style real-repo evaluation
compare
intermediate
Task: compare Topic: SWE-bench style real-repo evaluation Difficulty: intermediate Target language: Rust Context: Large monorepo with flaky tests and strict CI. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Compare: capability, cost, latency, reliability
[]
{ "target_language": "Rust", "developer_needs": [ "cost_latency_tradeoffs", "tests_are_truth", "evaluation_metrics", "repo_scale_reasoning" ], "moe_experts": [ "governance_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
8e72d76c8188fd3135b23d89f658c80e54827520
train_48833
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: TypeScript Context: High-traffic service with latency SLOs. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "TypeScript", "developer_needs": [ "auditability", "tooling", "repo_scale_reasoning", "ci_integration" ], "moe_experts": [ "coding_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
50aa309132bfbc50b31b812480a11c3a45b6e4f1
train_48834
2026-01-01T00:00:00
Extended context and repo-scale understanding
patch_diff
advanced
Task: patch_diff Topic: Extended context and repo-scale understanding 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. Patch (diff-style): ```diff - if x == 0: - return 1/x + if x == 0: + raise ValueError('division by zero') ``` Acceptance: - Tests pass - No new regressions
[]
{ "target_language": "JavaScript", "developer_needs": [ "cost_latency_tradeoffs", "evaluation_metrics", "auditability", "security_gates" ], "moe_experts": [ "coding_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
ed25fee20c73ecd2047815d9349e8c61ef114205
train_48835
2026-01-01T00:00:00
Self-improving agents and feedback loops
patch_diff
expert
Task: patch_diff 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. 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": [ "ci_integration", "auditability", "tests_are_truth", "governance" ], "moe_experts": [ "governance_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
55a869b6853401241f18c95dc0fe0703306da9d5
train_48836
2026-01-01T00:00:00
Code-specialized model families and sizing tradeoffs
explain
advanced
Task: explain Topic: Code-specialized model families and sizing tradeoffs Difficulty: advanced Target language: Java Context: Offline/local deployment with limited compute. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "Java", "developer_needs": [ "repo_scale_reasoning", "tests_are_truth", "security_gates", "governance" ], "moe_experts": [ "data_curation_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
463d76314ed7bfd0bca06f3535ecd5dba2e2bd2b
train_48837
2026-01-01T00:00:00
Latency, cost, and reliability optimization
review
intermediate
Task: review Topic: Latency, cost, and reliability optimization Difficulty: intermediate Target language: SQL Context: Large monorepo with flaky tests and strict CI. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Review: correctness, security, performance, governance
[]
{ "target_language": "SQL", "developer_needs": [ "tooling", "governance", "auditability", "ci_integration" ], "moe_experts": [ "security_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
e50c942bc705d01435dbe78b20fa917f8971768c
train_48838
2026-01-01T00:00:00
Tool calling, sandboxes, and CI integration
compare
intermediate
Task: compare Topic: Tool calling, sandboxes, and CI integration Difficulty: intermediate Target language: Go Context: Regulated environment requiring audit trails. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Compare: capability, cost, latency, reliability
[]
{ "target_language": "Go", "developer_needs": [ "repo_scale_reasoning", "governance", "evaluation_metrics", "ci_integration" ], "moe_experts": [ "evaluation_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
b85c2acdd7f3d0130add9b64af2931695bb0d9b7
train_48839
2026-01-01T00:00:00
Reasoning-first coding models and tunable deliberation
agent_loop
intermediate
Task: agent_loop Topic: Reasoning-first coding models and tunable deliberation Difficulty: intermediate Target language: JavaScript Context: Regulated environment requiring audit trails. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Loop: Plan → Edit → Test → Reflect → Human gate
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "JavaScript", "developer_needs": [ "repo_scale_reasoning", "governance", "reproducibility", "auditability" ], "moe_experts": [ "data_curation_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
a06b9eea8584902a63ff9151d9a695570b60ed35
train_48840
2026-01-01T00:00:00
Dataset curation pipelines (filter, dedupe, quality)
design
expert
Task: design Topic: Dataset curation pipelines (filter, dedupe, quality) Difficulty: expert Target language: 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": [ "tests_are_truth", "tooling", "ci_integration", "evaluation_metrics" ], "moe_experts": [ "coding_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
f91a09497b621d12dbf2e24ba35ba39305a5e8bc
train_48841
2026-01-01T00:00:00
SWE-bench style real-repo evaluation
explain
advanced
Task: explain Topic: SWE-bench style real-repo evaluation Difficulty: advanced Target language: TypeScript Context: Regulated environment requiring audit trails. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "TypeScript", "developer_needs": [ "tests_are_truth", "security_gates", "evaluation_metrics", "governance" ], "moe_experts": [ "data_curation_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
8702533e65c9e003e67116834e63bbde136fe94d
train_48842
2026-01-01T00:00:00
Latency, cost, and reliability optimization
failure_analysis
advanced
Task: failure_analysis Topic: Latency, cost, and reliability optimization Difficulty: advanced Target language: Java Context: Research team validating claims against real repos. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Failure: - Initial patch broke edge case Reflection: - Missing zero-input guard Correction: - Add explicit validation + test
[]
{ "target_language": "Java", "developer_needs": [ "auditability", "evaluation_metrics", "documentation", "tooling" ], "moe_experts": [ "coding_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
64e4571618e0986c4dbbbc799e1e676739bbadaa
train_48843
2026-01-01T00:00:00
Self-improving agents and feedback loops
data_pipeline
advanced
Task: data_pipeline Topic: Self-improving agents and feedback loops Difficulty: advanced Target language: 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
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "TypeScript", "developer_needs": [ "evaluation_metrics", "governance", "tooling", "auditability" ], "moe_experts": [ "evaluation_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
f413e73d7821a0d3e2557a3e4d8b029e21a7224e
train_48844
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: Java Context: Regulated environment requiring audit trails. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Eval: pass@k, time-to-green, regressions, diff size
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Java", "developer_needs": [ "auditability", "tests_are_truth", "tooling", "repo_scale_reasoning" ], "moe_experts": [ "governance_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
bd5eb9a3752e6814e823eb37c602ddfc36180bb7
train_48845
2026-01-01T00:00:00
Agentic coding systems (plan→edit→test→reflect)
code
expert
Task: code Topic: Agentic coding systems (plan→edit→test→reflect) Difficulty: expert Target language: SQL Context: Regulated environment requiring audit trails. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "SQL", "developer_needs": [ "repo_scale_reasoning", "cost_latency_tradeoffs", "auditability", "governance" ], "moe_experts": [ "data_curation_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
dd0a8be38449b3cd4c655c7979f9735ae0aabdeb
train_48846
2026-01-01T00:00:00
Agentic coding systems (plan→edit→test→reflect)
patch_diff
expert
Task: patch_diff Topic: Agentic coding systems (plan→edit→test→reflect) 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. Patch (diff-style): ```diff - if x == 0: - return 1/x + if x == 0: + raise ValueError('division by zero') ``` Acceptance: - Tests pass - No new regressions
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "JavaScript", "developer_needs": [ "tooling", "reproducibility", "evaluation_metrics", "tests_are_truth" ], "moe_experts": [ "coding_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
0bb9efa042c3bb4b5af881944f4535ae340cde24
train_48847
2026-01-01T00:00:00
Tool calling, sandboxes, and CI integration
code
intermediate
Task: code Topic: Tool calling, sandboxes, and CI integration Difficulty: intermediate Target language: 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": [ "security_gates", "tests_are_truth", "governance", "reproducibility" ], "moe_experts": [ "agentic_systems_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
33c8d3af2e98e543c3a8bc600705963730549e40
train_48848
2026-01-01T00:00:00
Dataset curation pipelines (filter, dedupe, quality)
code
advanced
Task: code Topic: Dataset curation pipelines (filter, dedupe, quality) Difficulty: advanced Target language: 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": [ "auditability", "repo_scale_reasoning", "evaluation_metrics", "cost_latency_tradeoffs" ], "moe_experts": [ "performance_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
724939db5db965610acc40faa44ca68a894eadb2
train_48849
2026-01-01T00:00:00
Model merging, distillation, and continued pretraining
eval
advanced
Task: eval Topic: Model merging, distillation, and continued pretraining Difficulty: advanced Target language: Bash Context: High-traffic service with latency SLOs. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Eval: pass@k, time-to-green, regressions, diff size
[]
{ "target_language": "Bash", "developer_needs": [ "repo_scale_reasoning", "governance", "tests_are_truth", "reproducibility" ], "moe_experts": [ "security_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
3e1fa0a19adead1adfe9198f6743240fa9f74614
train_48850
2026-01-01T00:00:00
Extended context and repo-scale understanding
compare
advanced
Task: compare Topic: Extended context and repo-scale understanding Difficulty: advanced Target language: Go Context: Regulated environment requiring audit trails. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Compare: capability, cost, latency, reliability
[]
{ "target_language": "Go", "developer_needs": [ "tests_are_truth", "cost_latency_tradeoffs", "governance", "tooling" ], "moe_experts": [ "security_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
6945b99adaeefaff7a0ee96224c7f38853bae2ba
train_48851
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: TypeScript Context: Large monorepo with flaky tests and strict CI. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Review: correctness, security, performance, governance
[]
{ "target_language": "TypeScript", "developer_needs": [ "tooling", "tests_are_truth", "repo_scale_reasoning", "evaluation_metrics" ], "moe_experts": [ "coding_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
fadc3664022d793f1eadeeb576780fdc1c420948
train_48852
2026-01-01T00:00:00
Extended context and repo-scale understanding
agent_loop
advanced
Task: agent_loop Topic: Extended context and repo-scale understanding Difficulty: advanced Target language: Rust Context: Research team validating claims against real repos. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Loop: Plan → Edit → Test → Reflect → Human gate
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Rust", "developer_needs": [ "governance", "documentation", "ci_integration", "repo_scale_reasoning" ], "moe_experts": [ "data_curation_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
8a442d2000f833f6e415b225ef5c2a5ec8af7cf9
train_48853
2026-01-01T00:00:00
Extended context and repo-scale understanding
failure_analysis
intermediate
Task: failure_analysis Topic: Extended context and repo-scale understanding Difficulty: intermediate Target language: Python Context: Regulated environment requiring audit trails. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Failure: - Initial patch broke edge case Reflection: - Missing zero-input guard Correction: - Add explicit validation + test
[]
{ "target_language": "Python", "developer_needs": [ "evaluation_metrics", "tests_are_truth", "documentation", "cost_latency_tradeoffs" ], "moe_experts": [ "coding_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
f5a8c55e868e6387f8468a56ddb60172fc97d8bd
train_48854
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: Offline/local deployment with limited compute. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Failure: - Initial patch broke edge case Reflection: - Missing zero-input guard Correction: - Add explicit validation + test
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Rust", "developer_needs": [ "tests_are_truth", "tooling", "auditability", "cost_latency_tradeoffs" ], "moe_experts": [ "agentic_systems_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
682cbb0da9499292695dac98e68c836808a3bc41
train_48855
2026-01-01T00:00:00
Reasoning-first coding models and tunable deliberation
code
advanced
Task: code Topic: Reasoning-first coding models and tunable deliberation Difficulty: advanced Target language: 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
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Rust", "developer_needs": [ "documentation", "tests_are_truth", "evaluation_metrics", "cost_latency_tradeoffs" ], "moe_experts": [ "performance_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
8b56f0c4f71c4c86a35a408e3080161e22dda34c
train_48856
2026-01-01T00:00:00
Mixture-of-Experts (MoE) for code
data_pipeline
expert
Task: data_pipeline Topic: Mixture-of-Experts (MoE) for code Difficulty: expert Target language: C# Context: High-traffic service with latency SLOs. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Pipeline: Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
[]
{ "target_language": "C#", "developer_needs": [ "ci_integration", "evaluation_metrics", "security_gates", "auditability" ], "moe_experts": [ "security_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
7632bca8831d1b73b293b27090ab30705ff75683
train_48857
2026-01-01T00:00:00
Multimodal dev workflows (docs, diagrams, traces)
patch_diff
intermediate
Task: patch_diff Topic: Multimodal dev workflows (docs, diagrams, traces) Difficulty: intermediate Target language: TypeScript Context: Research team validating claims against real repos. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. 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": [ "evaluation_metrics", "auditability", "reproducibility", "documentation" ], "moe_experts": [ "governance_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
2910c0cd8e9ce0a987b7426743a9bee0048e5308
train_48858
2026-01-01T00:00:00
Secure code generation and policy gates
eval
advanced
Task: eval Topic: Secure code generation and policy gates Difficulty: advanced Target language: 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
[]
{ "target_language": "C#", "developer_needs": [ "cost_latency_tradeoffs", "tests_are_truth", "ci_integration", "tooling" ], "moe_experts": [ "security_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
cf580dd9d2084bd2be9c0b5d413267e3b954a097
train_48859
2026-01-01T00:00:00
Agentic coding systems (plan→edit→test→reflect)
explain
advanced
Task: explain Topic: Agentic coding systems (plan→edit→test→reflect) Difficulty: advanced Target language: Java Context: Research team validating claims against real repos. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "Java", "developer_needs": [ "tests_are_truth", "evaluation_metrics", "documentation", "tooling" ], "moe_experts": [ "data_curation_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
7e0f35071e988f91cfb5201d9c15e87ae4832c25
train_48860
2026-01-01T00:00:00
Multimodal dev workflows (docs, diagrams, traces)
patch_diff
intermediate
Task: patch_diff Topic: Multimodal dev workflows (docs, diagrams, traces) Difficulty: intermediate Target language: Bash Context: Large monorepo with flaky tests and strict CI. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. 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", "tests_are_truth", "documentation", "tooling" ], "moe_experts": [ "evaluation_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
c5a7085bbd8e0063738302792f2b0d6b83e9a50c
train_48861
2026-01-01T00:00:00
SWE-bench style real-repo evaluation
compare
intermediate
Task: compare Topic: SWE-bench style real-repo evaluation Difficulty: intermediate Target language: 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. Compare: capability, cost, latency, reliability
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "SQL", "developer_needs": [ "repo_scale_reasoning", "ci_integration", "reproducibility", "governance" ], "moe_experts": [ "agentic_systems_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
dc118fcf2bc4ce0522c174b4aa0060e9ff95331d
train_48862
2026-01-01T00:00:00
Extended context and repo-scale understanding
code
intermediate
Task: code Topic: Extended context and repo-scale understanding Difficulty: intermediate Target language: TypeScript Context: Large monorepo with flaky tests and strict CI. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "TypeScript", "developer_needs": [ "ci_integration", "auditability", "reproducibility", "security_gates" ], "moe_experts": [ "security_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
d24ddbd475cb7bf8b3e680269dc96028463de666
train_48863
2026-01-01T00:00:00
Dataset curation pipelines (filter, dedupe, quality)
compare
intermediate
Task: compare Topic: Dataset curation pipelines (filter, dedupe, quality) Difficulty: intermediate Target language: Python Context: Research team validating claims against real repos. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Compare: capability, cost, latency, reliability
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Python", "developer_needs": [ "security_gates", "repo_scale_reasoning", "tests_are_truth", "cost_latency_tradeoffs" ], "moe_experts": [ "data_curation_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
3f1950202571672404226cb4b67328328074e271
train_48864
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: 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": "SQL", "developer_needs": [ "tooling", "ci_integration", "reproducibility", "governance" ], "moe_experts": [ "security_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
c622bc869fdeb177437f2491353e633cf9343858
train_48865
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: 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
[]
{ "target_language": "Java", "developer_needs": [ "security_gates", "governance", "ci_integration", "repo_scale_reasoning" ], "moe_experts": [ "governance_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
df2b3f46616fa0c47cd46cc1109a4eab1d07e264
train_48866
2026-01-01T00:00:00
Extended context and repo-scale understanding
review
intermediate
Task: review Topic: Extended context and repo-scale understanding Difficulty: intermediate Target language: Python Context: High-traffic service with latency SLOs. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Review: correctness, security, performance, governance
[ "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", "tests_are_truth", "tooling", "documentation" ], "moe_experts": [ "governance_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
4b3b39d29d50323687f31cdd02ba47dc558580b9
train_48867
2026-01-01T00:00:00
Model merging, distillation, and continued pretraining
patch_diff
intermediate
Task: patch_diff Topic: Model merging, distillation, and continued pretraining Difficulty: intermediate Target language: SQL Context: 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": "SQL", "developer_needs": [ "repo_scale_reasoning", "evaluation_metrics", "tests_are_truth", "security_gates" ], "moe_experts": [ "evaluation_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
b2740e998ae6d8483d6deb036de9a7be35df20d0
train_48868
2026-01-01T00:00:00
Extended context and repo-scale understanding
design
expert
Task: design Topic: Extended context and repo-scale understanding Difficulty: expert Target language: 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": [ "repo_scale_reasoning", "governance", "evaluation_metrics", "cost_latency_tradeoffs" ], "moe_experts": [ "governance_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
449e8aa7daffdcd92c4a729c9dc89643eab1cd0c
train_48869
2026-01-01T00:00:00
Agentic coding systems (plan→edit→test→reflect)
review
advanced
Task: review Topic: Agentic coding systems (plan→edit→test→reflect) Difficulty: advanced Target language: TypeScript Context: Large monorepo with flaky tests and strict CI. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Review: correctness, security, performance, governance
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "TypeScript", "developer_needs": [ "documentation", "reproducibility", "evaluation_metrics", "repo_scale_reasoning" ], "moe_experts": [ "evaluation_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
9880a9941d0661b112f7ae785d9c5d545eac6b7d
train_48870
2026-01-01T00:00:00
Latency, cost, and reliability optimization
data_pipeline
intermediate
Task: data_pipeline Topic: Latency, cost, and reliability optimization Difficulty: intermediate Target language: Go Context: Research team validating claims against real repos. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Pipeline: Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
[]
{ "target_language": "Go", "developer_needs": [ "cost_latency_tradeoffs", "governance", "reproducibility", "tests_are_truth" ], "moe_experts": [ "coding_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
0101aea55700892f232170a96b53e48868b1741c
train_48871
2026-01-01T00:00:00
Secure code generation and policy gates
eval
intermediate
Task: eval Topic: Secure code generation and policy gates Difficulty: intermediate Target language: SQL Context: Regulated environment requiring audit trails. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Eval: pass@k, time-to-green, regressions, diff size
[]
{ "target_language": "SQL", "developer_needs": [ "auditability", "evaluation_metrics", "reproducibility", "governance" ], "moe_experts": [ "data_curation_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
c08487bac94438075fc5cb279e718cdfc84449f5
train_48872
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: 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": [ "governance", "evaluation_metrics", "tooling", "cost_latency_tradeoffs" ], "moe_experts": [ "security_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
23847aec4837cdae28d64bab74fe4ae4ec526569
train_48873
2026-01-01T00:00:00
Code-specialized model families and sizing tradeoffs
review
expert
Task: review Topic: Code-specialized model families and sizing tradeoffs Difficulty: expert Target language: JavaScript Context: High-traffic service with latency SLOs. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Review: correctness, security, performance, governance
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "JavaScript", "developer_needs": [ "security_gates", "tooling", "ci_integration", "governance" ], "moe_experts": [ "security_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
77ed8ff11481e12ae6128fce11433eb867917a64
train_48874
2026-01-01T00:00:00
Tool calling, sandboxes, and CI integration
patch_diff
expert
Task: patch_diff Topic: Tool calling, sandboxes, and CI integration 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": [ "cost_latency_tradeoffs", "repo_scale_reasoning", "documentation", "auditability" ], "moe_experts": [ "performance_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
eb54ef4a3198491078d12b257eadae67f68ae3a6
train_48875
2026-01-01T00:00:00
Extended context and repo-scale understanding
agent_loop
intermediate
Task: agent_loop Topic: Extended context and repo-scale understanding Difficulty: intermediate Target language: 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": [ "evaluation_metrics", "cost_latency_tradeoffs", "auditability", "repo_scale_reasoning" ], "moe_experts": [ "evaluation_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
a1ad92aae4ef4d7585829795917a4f2ad9b5be9c
train_48876
2026-01-01T00:00:00
Multimodal dev workflows (docs, diagrams, traces)
eval
expert
Task: eval Topic: Multimodal dev workflows (docs, diagrams, traces) Difficulty: expert Target language: Rust Context: Research team validating claims against real repos. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Eval: pass@k, time-to-green, regressions, diff size
[]
{ "target_language": "Rust", "developer_needs": [ "security_gates", "governance", "repo_scale_reasoning", "tooling" ], "moe_experts": [ "evaluation_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
1fbbedef2e55f3fa5b8d85b7b8eb97af0289c53f
train_48877
2026-01-01T00:00:00
Agentic coding systems (plan→edit→test→reflect)
agent_loop
advanced
Task: agent_loop Topic: Agentic coding systems (plan→edit→test→reflect) Difficulty: advanced Target language: 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. Loop: Plan → Edit → Test → Reflect → Human gate
[]
{ "target_language": "C#", "developer_needs": [ "security_gates", "tests_are_truth", "auditability", "cost_latency_tradeoffs" ], "moe_experts": [ "agentic_systems_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
ee9c2efa0cad28cc1c8d8036bcfc956254ce75ce
train_48878
2026-01-01T00:00:00
Multimodal dev workflows (docs, diagrams, traces)
compare
expert
Task: compare Topic: Multimodal dev workflows (docs, diagrams, traces) Difficulty: expert Target language: C# Context: Research team validating claims against real repos. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Compare: capability, cost, latency, reliability
[]
{ "target_language": "C#", "developer_needs": [ "evaluation_metrics", "auditability", "cost_latency_tradeoffs", "reproducibility" ], "moe_experts": [ "data_curation_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
5979ef1aa601412977b61c3eb94b8f0cefadb858
train_48879
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: Rust Context: Offline/local deployment with limited compute. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Pipeline: Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Rust", "developer_needs": [ "tooling", "ci_integration", "evaluation_metrics", "auditability" ], "moe_experts": [ "governance_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
a2add859e2ee21c2566fe10559defe678f40c8f0
train_48880
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
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Go", "developer_needs": [ "reproducibility", "repo_scale_reasoning", "auditability", "tests_are_truth" ], "moe_experts": [ "performance_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
cd04c65643dbb0b8ccdbc0200279f05d6e77943d
train_48881
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: SQL Context: High-traffic service with latency SLOs. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "SQL", "developer_needs": [ "documentation", "evaluation_metrics", "repo_scale_reasoning", "ci_integration" ], "moe_experts": [ "data_curation_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
3a6fc290633ee6e79c00f06e43776c2c4ad5b936
train_48882
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: 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. Compare: capability, cost, latency, reliability
[]
{ "target_language": "Go", "developer_needs": [ "cost_latency_tradeoffs", "reproducibility", "repo_scale_reasoning", "governance" ], "moe_experts": [ "security_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
948daeb0f7d9474a690854bb0224695261033fd6
train_48883
2026-01-01T00:00:00
Latency, cost, and reliability optimization
explain
expert
Task: explain Topic: Latency, cost, and reliability optimization Difficulty: expert Target language: JavaScript Context: Research team validating claims against real repos. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "JavaScript", "developer_needs": [ "auditability", "reproducibility", "repo_scale_reasoning", "ci_integration" ], "moe_experts": [ "agentic_systems_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
09d2d0194f6c36d1b5604d4a35ff45f00cf19228
train_48884
2026-01-01T00:00:00
Latency, cost, and reliability optimization
compare
advanced
Task: compare Topic: Latency, cost, and reliability optimization 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
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Rust", "developer_needs": [ "documentation", "evaluation_metrics", "auditability", "security_gates" ], "moe_experts": [ "coding_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
4f9dc402862a959424abd596ffb1178da44c38fc
train_48885
2026-01-01T00:00:00
Governance, provenance, and licensing for code data
explain
expert
Task: explain Topic: Governance, provenance, and licensing for code data Difficulty: expert Target language: Java Context: Offline/local deployment with limited compute. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "Java", "developer_needs": [ "cost_latency_tradeoffs", "auditability", "security_gates", "ci_integration" ], "moe_experts": [ "agentic_systems_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
0ad3c82b61f50932ddc34e36f96a055c053ad734
train_48886
2026-01-01T00:00:00
Governance, provenance, and licensing for code data
eval
expert
Task: eval Topic: Governance, provenance, and licensing for code data Difficulty: expert Target language: 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. Eval: pass@k, time-to-green, regressions, diff size
[]
{ "target_language": "Bash", "developer_needs": [ "reproducibility", "documentation", "governance", "repo_scale_reasoning" ], "moe_experts": [ "agentic_systems_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
4312f8c9026018b9aca6e3f16a5dbdb5b5d9f351
train_48887
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: 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": [ "security_gates", "tooling", "governance", "auditability" ], "moe_experts": [ "coding_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
052ef3ec5936d5b5a2e97cd43d7c2ae4cc363905
train_48888
2026-01-01T00:00:00
Dataset curation pipelines (filter, dedupe, quality)
data_pipeline
intermediate
Task: data_pipeline Topic: Dataset curation pipelines (filter, dedupe, quality) Difficulty: intermediate Target language: 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
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "C#", "developer_needs": [ "auditability", "cost_latency_tradeoffs", "tooling", "evaluation_metrics" ], "moe_experts": [ "evaluation_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
5367ad6b3eb2718bc5e4c293238f97e00c4f79bc
train_48889
2026-01-01T00:00:00
Latency, cost, and reliability optimization
eval
expert
Task: eval Topic: Latency, cost, and reliability optimization Difficulty: expert Target language: C# Context: High-traffic service with latency SLOs. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Eval: pass@k, time-to-green, regressions, diff size
[]
{ "target_language": "C#", "developer_needs": [ "repo_scale_reasoning", "tests_are_truth", "documentation", "tooling" ], "moe_experts": [ "performance_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
c11127ea99ba814de6cc48d62197c0eb15e06e94
train_48890
2026-01-01T00:00:00
Extended context and repo-scale understanding
agent_loop
intermediate
Task: agent_loop Topic: Extended context and repo-scale understanding Difficulty: intermediate Target language: 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. Loop: Plan → Edit → Test → Reflect → Human gate
[]
{ "target_language": "Bash", "developer_needs": [ "ci_integration", "auditability", "cost_latency_tradeoffs", "security_gates" ], "moe_experts": [ "evaluation_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
a4dd36662148c54c4e3d0f4b8ee3789e60187b72
train_48891
2026-01-01T00:00:00
Latency, cost, and reliability optimization
design
advanced
Task: design Topic: Latency, cost, and reliability optimization 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. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "C#", "developer_needs": [ "security_gates", "tooling", "evaluation_metrics", "governance" ], "moe_experts": [ "security_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
fcc623e3139458c127b99c2dd4158252e6585d6b
train_48892
2026-01-01T00:00:00
Code-specialized model families and sizing tradeoffs
code
intermediate
Task: code Topic: Code-specialized model families and sizing tradeoffs Difficulty: intermediate Target language: C# Context: Large monorepo with flaky tests and strict CI. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "C#", "developer_needs": [ "security_gates", "evaluation_metrics", "repo_scale_reasoning", "tests_are_truth" ], "moe_experts": [ "evaluation_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
258bce57b732aeb3ca53ebee74c8168a8cdf699d
train_48893
2026-01-01T00:00:00
Governance, provenance, and licensing for code data
agent_loop
expert
Task: agent_loop Topic: Governance, provenance, and licensing for code data Difficulty: expert Target language: SQL Context: Offline/local deployment with limited compute. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Loop: Plan → Edit → Test → Reflect → Human gate
[]
{ "target_language": "SQL", "developer_needs": [ "security_gates", "repo_scale_reasoning", "tests_are_truth", "governance" ], "moe_experts": [ "performance_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
42cd0531e9e8eff3e3d6210d1c7b1d1e6c50c304
train_48894
2026-01-01T00:00:00
SWE-bench style real-repo evaluation
explain
intermediate
Task: explain Topic: SWE-bench style real-repo evaluation Difficulty: intermediate Target language: Go Context: Research team validating claims against real repos. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. 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": [ "reproducibility", "documentation", "repo_scale_reasoning", "cost_latency_tradeoffs" ], "moe_experts": [ "data_curation_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
53c78dd427b90de500938e9d5d064889ccbfafce
train_48895
2026-01-01T00:00:00
Extended context and repo-scale understanding
compare
intermediate
Task: compare Topic: Extended context and repo-scale understanding Difficulty: intermediate Target language: TypeScript Context: High-traffic service with latency SLOs. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Compare: capability, cost, latency, reliability
[]
{ "target_language": "TypeScript", "developer_needs": [ "governance", "repo_scale_reasoning", "cost_latency_tradeoffs", "tooling" ], "moe_experts": [ "data_curation_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
9357ab97ec96cee1e0801bf50cf85d26d2f9a210
train_48896
2026-01-01T00:00:00
Dataset curation pipelines (filter, dedupe, quality)
data_pipeline
advanced
Task: data_pipeline Topic: Dataset curation pipelines (filter, dedupe, quality) Difficulty: advanced Target language: Go Context: Offline/local deployment with limited compute. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Pipeline: Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Go", "developer_needs": [ "reproducibility", "cost_latency_tradeoffs", "documentation", "security_gates" ], "moe_experts": [ "agentic_systems_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
609fb123da95bb02881c87d4f3fa32fc7373a3db
train_48897
2026-01-01T00:00:00
SWE-bench style real-repo evaluation
review
intermediate
Task: review Topic: SWE-bench style real-repo evaluation Difficulty: intermediate Target language: Java Context: Regulated environment requiring audit trails. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Review: correctness, security, performance, governance
[]
{ "target_language": "Java", "developer_needs": [ "auditability", "evaluation_metrics", "cost_latency_tradeoffs", "governance" ], "moe_experts": [ "agentic_systems_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
7b23f6a8665c5486f9e72053065d8b82af75894e
train_48898
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": [ "repo_scale_reasoning", "auditability", "governance", "security_gates" ], "moe_experts": [ "evaluation_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
a4e6cd030c360ecf99d9da01cbd11033e5c4c3ec
train_48899
2026-01-01T00:00:00
Extended context and repo-scale understanding
design
intermediate
Task: design Topic: Extended context and repo-scale understanding Difficulty: intermediate Target language: JavaScript Context: High-traffic service with latency SLOs. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "JavaScript", "developer_needs": [ "tests_are_truth", "evaluation_metrics", "tooling", "repo_scale_reasoning" ], "moe_experts": [ "security_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
2a0ddea746733ad0a9cdd371821f257b19c813b8