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train_17500
2026-01-01T00:00:00
Code-specialized model families and sizing tradeoffs
design
advanced
Task: design Topic: Code-specialized model families and sizing tradeoffs Difficulty: advanced Target language: TypeScript Context: High-traffic service with latency SLOs. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "TypeScript", "developer_needs": [ "repo_scale_reasoning", "governance", "auditability", "cost_latency_tradeoffs" ], "moe_experts": [ "performance_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
21f7e26eac0145e30a142e904c9817ad07b9e10b
train_17501
2026-01-01T00:00:00
Dataset curation pipelines (filter, dedupe, quality)
code
intermediate
Task: code Topic: Dataset curation pipelines (filter, dedupe, quality) Difficulty: intermediate Target language: 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
[ "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", "documentation", "tooling" ], "moe_experts": [ "coding_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
36629ec6d2c6a0d0ba9f779bebbea014c8b1061c
train_17502
2026-01-01T00:00:00
Code-specialized model families and sizing tradeoffs
explain
intermediate
Task: explain Topic: Code-specialized model families and sizing tradeoffs Difficulty: intermediate Target language: JavaScript Context: Research team validating claims against real repos. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. 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", "reproducibility", "repo_scale_reasoning", "tests_are_truth" ], "moe_experts": [ "coding_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
6f10730ac326434c64e73d2b75d65f51cfd8ff3f
train_17503
2026-01-01T00:00:00
Self-improving agents and feedback loops
explain
expert
Task: explain Topic: Self-improving agents and feedback loops 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
[]
{ "target_language": "Go", "developer_needs": [ "governance", "documentation", "security_gates", "tests_are_truth" ], "moe_experts": [ "data_curation_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
dfae99c409d0dfbe2dd6ee6801af690c13c60912
train_17504
2026-01-01T00:00:00
Secure code generation and policy gates
explain
advanced
Task: explain Topic: Secure code generation and policy gates Difficulty: advanced Target language: JavaScript Context: 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": [ "documentation", "auditability", "evaluation_metrics", "cost_latency_tradeoffs" ], "moe_experts": [ "agentic_systems_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
1f6500f013165e6d12fed3bc591887c9ba95c76a
train_17505
2026-01-01T00:00:00
Governance, provenance, and licensing for code data
data_pipeline
expert
Task: data_pipeline Topic: Governance, provenance, and licensing for code data Difficulty: expert Target language: Bash Context: Offline/local deployment with limited compute. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. 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": [ "tooling", "tests_are_truth", "repo_scale_reasoning", "documentation" ], "moe_experts": [ "performance_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
1a54dccf9e78c25ed66e58483e589767c5d9476c
train_17506
2026-01-01T00:00:00
Reasoning-first coding models and tunable deliberation
patch_diff
advanced
Task: patch_diff Topic: Reasoning-first coding models and tunable deliberation Difficulty: advanced Target language: 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. Patch (diff-style): ```diff - if x == 0: - return 1/x + if x == 0: + raise ValueError('division by zero') ``` Acceptance: - Tests pass - No new regressions
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "C#", "developer_needs": [ "documentation", "evaluation_metrics", "auditability", "ci_integration" ], "moe_experts": [ "evaluation_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
a33166b6a2f246fc6ed666bc689150df2e6a2d07
train_17507
2026-01-01T00:00:00
Secure code generation and policy gates
data_pipeline
intermediate
Task: data_pipeline Topic: Secure code generation and policy gates Difficulty: intermediate Target language: Go Context: Offline/local deployment with limited compute. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Pipeline: Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
[]
{ "target_language": "Go", "developer_needs": [ "evaluation_metrics", "ci_integration", "cost_latency_tradeoffs", "tooling" ], "moe_experts": [ "agentic_systems_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
7467f2b9083df814e317193d54aab2ea3f28949e
train_17508
2026-01-01T00:00:00
Tool calling, sandboxes, and CI integration
failure_analysis
expert
Task: failure_analysis Topic: Tool calling, sandboxes, and CI integration Difficulty: expert Target language: 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": [ "governance", "tests_are_truth", "repo_scale_reasoning", "reproducibility" ], "moe_experts": [ "security_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
5e397a8ca983d0e6b8d2e5a6b411e6f3d5c6240e
train_17509
2026-01-01T00:00:00
Agentic coding systems (plan→edit→test→reflect)
agent_loop
intermediate
Task: agent_loop Topic: Agentic coding systems (plan→edit→test→reflect) Difficulty: intermediate Target language: Python Context: Regulated environment requiring audit trails. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Loop: Plan → Edit → Test → Reflect → Human gate
[]
{ "target_language": "Python", "developer_needs": [ "cost_latency_tradeoffs", "evaluation_metrics", "reproducibility", "documentation" ], "moe_experts": [ "governance_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
e91befb3b7410fe92d2bf43645457d946782991a
train_17510
2026-01-01T00:00:00
Agentic coding systems (plan→edit→test→reflect)
compare
intermediate
Task: compare Topic: Agentic coding systems (plan→edit→test→reflect) Difficulty: intermediate Target language: TypeScript Context: Regulated environment requiring audit trails. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Compare: capability, cost, latency, reliability
[]
{ "target_language": "TypeScript", "developer_needs": [ "ci_integration", "governance", "reproducibility", "tooling" ], "moe_experts": [ "evaluation_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
b3993a734a39be74ba0f600c7601aed0dcc3e432
train_17511
2026-01-01T00:00:00
Reasoning-first coding models and tunable deliberation
code
advanced
Task: code Topic: Reasoning-first coding models and tunable deliberation Difficulty: advanced Target language: Go Context: Research team validating claims against real repos. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "Go", "developer_needs": [ "reproducibility", "repo_scale_reasoning", "tooling", "cost_latency_tradeoffs" ], "moe_experts": [ "coding_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
aa80581c6a84ad2da7f2256cb7cd99990822d2c5
train_17512
2026-01-01T00:00:00
Mixture-of-Experts (MoE) for code
review
intermediate
Task: review Topic: Mixture-of-Experts (MoE) for code Difficulty: intermediate Target language: C# Context: Regulated environment requiring audit trails. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Review: correctness, security, performance, governance
[]
{ "target_language": "C#", "developer_needs": [ "ci_integration", "cost_latency_tradeoffs", "evaluation_metrics", "reproducibility" ], "moe_experts": [ "data_curation_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
85763caac51b7d2b044b0668d8158dcd86384e07
train_17513
2026-01-01T00:00:00
Dataset curation pipelines (filter, dedupe, quality)
patch_diff
intermediate
Task: patch_diff Topic: Dataset curation pipelines (filter, dedupe, quality) 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. 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": [ "ci_integration", "tests_are_truth", "cost_latency_tradeoffs", "tooling" ], "moe_experts": [ "governance_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
ac9626d85d968ec6e0dc51a210b4d0d582269076
train_17514
2026-01-01T00:00:00
Dataset curation pipelines (filter, dedupe, quality)
review
advanced
Task: review Topic: Dataset curation pipelines (filter, dedupe, quality) Difficulty: advanced Target language: 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
[]
{ "target_language": "C#", "developer_needs": [ "auditability", "documentation", "evaluation_metrics", "reproducibility" ], "moe_experts": [ "performance_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
379eb6b2ba9932c9c10a6da5097bdbb239dbb9d7
train_17515
2026-01-01T00:00:00
Mixture-of-Experts (MoE) for code
eval
intermediate
Task: eval Topic: Mixture-of-Experts (MoE) for code Difficulty: intermediate Target language: C# Context: Large monorepo with flaky tests and strict CI. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Eval: pass@k, time-to-green, regressions, diff size
[]
{ "target_language": "C#", "developer_needs": [ "documentation", "governance", "evaluation_metrics", "auditability" ], "moe_experts": [ "performance_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
5dc0c984af7fd48b802945741d56baf05b7d942c
train_17516
2026-01-01T00:00:00
Dataset curation pipelines (filter, dedupe, quality)
patch_diff
intermediate
Task: patch_diff Topic: Dataset curation pipelines (filter, dedupe, quality) Difficulty: intermediate Target language: SQL Context: High-traffic service with latency SLOs. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. 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": "SQL", "developer_needs": [ "tests_are_truth", "tooling", "ci_integration", "repo_scale_reasoning" ], "moe_experts": [ "governance_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
f84e0ddb44224321361cf802fc7f25980d1e3363
train_17517
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: 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": [ "governance", "ci_integration", "tooling", "cost_latency_tradeoffs" ], "moe_experts": [ "evaluation_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
eb3362a7bcfc9d866b44b804460e3762f5311820
train_17518
2026-01-01T00:00:00
Model merging, distillation, and continued pretraining
code
expert
Task: code Topic: Model merging, distillation, and continued pretraining Difficulty: expert Target language: C# Context: Offline/local deployment with limited compute. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "C#", "developer_needs": [ "security_gates", "governance", "auditability", "repo_scale_reasoning" ], "moe_experts": [ "data_curation_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
8fab15aa765e6e0cdf23418f595c88ddf715bb75
train_17519
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: 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": "C#", "developer_needs": [ "reproducibility", "security_gates", "governance", "documentation" ], "moe_experts": [ "evaluation_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
740738bc65380e40f1feb46ef7b3c11576e17f3f
train_17520
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: 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": "Bash", "developer_needs": [ "repo_scale_reasoning", "documentation", "security_gates", "evaluation_metrics" ], "moe_experts": [ "agentic_systems_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
7bad252102ac01af46f06ac76c7f6ec83f475bb1
train_17521
2026-01-01T00:00:00
Self-improving agents and feedback loops
explain
expert
Task: explain Topic: Self-improving agents and feedback loops 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": [ "ci_integration", "evaluation_metrics", "tests_are_truth", "governance" ], "moe_experts": [ "evaluation_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
718e103d48919e91941db321175dce71d4c1ae64
train_17522
2026-01-01T00:00:00
Reasoning-first coding models and tunable deliberation
eval
advanced
Task: eval Topic: Reasoning-first coding models and tunable deliberation Difficulty: advanced Target language: 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. Eval: pass@k, time-to-green, regressions, diff size
[]
{ "target_language": "C#", "developer_needs": [ "governance", "evaluation_metrics", "cost_latency_tradeoffs", "auditability" ], "moe_experts": [ "performance_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
7037aa64f69b49bf12c9e1d3ff53de350606cde2
train_17523
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: SQL Context: Offline/local deployment with limited compute. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "SQL", "developer_needs": [ "security_gates", "tooling", "reproducibility", "ci_integration" ], "moe_experts": [ "data_curation_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
de5b11ad64834eda1cffed307b1e0bcde60acb86
train_17524
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: 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. Review: correctness, security, performance, governance
[]
{ "target_language": "SQL", "developer_needs": [ "auditability", "reproducibility", "evaluation_metrics", "tooling" ], "moe_experts": [ "coding_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
28c922ebef96931a75a2caa48e0daa5074fb2ee3
train_17525
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: 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. Review: correctness, security, performance, governance
[]
{ "target_language": "Bash", "developer_needs": [ "cost_latency_tradeoffs", "reproducibility", "evaluation_metrics", "governance" ], "moe_experts": [ "data_curation_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
361b2340384e2b6c9ef267a885322af08846a2d7
train_17526
2026-01-01T00:00:00
Model merging, distillation, and continued pretraining
code
expert
Task: code Topic: Model merging, distillation, and continued pretraining Difficulty: expert Target language: TypeScript Context: Research team validating claims against real repos. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "TypeScript", "developer_needs": [ "documentation", "security_gates", "auditability", "ci_integration" ], "moe_experts": [ "governance_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
18954c6d2a1dd82d6298c761f94ef6c0bef06935
train_17527
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: C# Context: Large monorepo with flaky tests and strict CI. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "C#", "developer_needs": [ "tests_are_truth", "reproducibility", "ci_integration", "cost_latency_tradeoffs" ], "moe_experts": [ "coding_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
f1b9b22ce5ead9fba3bbe763ba260621526d0797
train_17528
2026-01-01T00:00:00
Multimodal dev workflows (docs, diagrams, traces)
agent_loop
intermediate
Task: agent_loop Topic: Multimodal dev workflows (docs, diagrams, traces) Difficulty: intermediate Target language: SQL Context: Research team validating claims against real repos. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. 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": "SQL", "developer_needs": [ "tooling", "evaluation_metrics", "auditability", "reproducibility" ], "moe_experts": [ "evaluation_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
a8ed8cf037d33d9d36ab8d540c63bda0200297e1
train_17529
2026-01-01T00:00:00
Agentic coding systems (plan→edit→test→reflect)
data_pipeline
intermediate
Task: data_pipeline Topic: Agentic coding systems (plan→edit→test→reflect) Difficulty: intermediate Target language: Java Context: High-traffic service with latency SLOs. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Pipeline: Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Java", "developer_needs": [ "ci_integration", "cost_latency_tradeoffs", "security_gates", "tooling" ], "moe_experts": [ "performance_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
0a6fde3b6849411e4ce1365233d2aa4cc6006421
train_17530
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: 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
[]
{ "target_language": "Python", "developer_needs": [ "auditability", "evaluation_metrics", "ci_integration", "cost_latency_tradeoffs" ], "moe_experts": [ "security_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
843bcc86f6752dd1a8aa48cca36ebbeedab5c1c6
train_17531
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: 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": [ "security_gates", "documentation", "governance", "auditability" ], "moe_experts": [ "security_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
9f61fe498703f4c7ddc2d9550a09beef690188c6
train_17532
2026-01-01T00:00:00
Extended context and repo-scale understanding
patch_diff
expert
Task: patch_diff Topic: Extended context and repo-scale understanding Difficulty: expert Target language: Bash Context: Offline/local deployment with limited compute. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. 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": "Bash", "developer_needs": [ "documentation", "repo_scale_reasoning", "evaluation_metrics", "ci_integration" ], "moe_experts": [ "agentic_systems_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
8982cb0f7eede2dece86533ab4b0848c1edcbbaf
train_17533
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: 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
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "TypeScript", "developer_needs": [ "tests_are_truth", "documentation", "governance", "reproducibility" ], "moe_experts": [ "agentic_systems_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
7508eae05c649e6ef8f0c3b9a6154996edfb40ad
train_17534
2026-01-01T00:00:00
Latency, cost, and reliability optimization
code
intermediate
Task: code Topic: Latency, cost, and reliability optimization 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": [ "governance", "auditability", "reproducibility", "tooling" ], "moe_experts": [ "governance_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
22316fc3992ab116a1a493805105da7c0fcd08aa
train_17535
2026-01-01T00:00:00
Latency, cost, and reliability optimization
explain
expert
Task: explain Topic: Latency, cost, and reliability optimization 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": [ "ci_integration", "tooling", "evaluation_metrics", "security_gates" ], "moe_experts": [ "security_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
f5aaa110699d3f132423a3104ec6a3cd87ac3860
train_17536
2026-01-01T00:00:00
Model merging, distillation, and continued pretraining
compare
advanced
Task: compare Topic: Model merging, distillation, and continued pretraining Difficulty: advanced Target language: 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
[]
{ "target_language": "SQL", "developer_needs": [ "tests_are_truth", "repo_scale_reasoning", "tooling", "evaluation_metrics" ], "moe_experts": [ "coding_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
33bfac3a5ab8eeb63118db2ff11b1f1d41b5627d
train_17537
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
[]
{ "target_language": "Rust", "developer_needs": [ "evaluation_metrics", "repo_scale_reasoning", "ci_integration", "cost_latency_tradeoffs" ], "moe_experts": [ "performance_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
8b56f0c4f71c4c86a35a408e3080161e22dda34c
train_17538
2026-01-01T00:00:00
Agentic coding systems (plan→edit→test→reflect)
data_pipeline
advanced
Task: data_pipeline Topic: Agentic coding systems (plan→edit→test→reflect) 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. 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": [ "tooling", "tests_are_truth", "governance", "security_gates" ], "moe_experts": [ "security_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
c8bc6011b662d52628e7661025dab7c7d3062bba
train_17539
2026-01-01T00:00:00
Mixture-of-Experts (MoE) for code
agent_loop
intermediate
Task: agent_loop Topic: Mixture-of-Experts (MoE) for code 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. 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": [ "tests_are_truth", "reproducibility", "documentation", "governance" ], "moe_experts": [ "security_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
00cfe8408d9784ec1ed1a022dc512faaa8a952e9
train_17540
2026-01-01T00:00:00
Dataset curation pipelines (filter, dedupe, quality)
code
advanced
Task: code Topic: Dataset curation pipelines (filter, dedupe, quality) Difficulty: advanced Target language: JavaScript Context: High-traffic service with latency SLOs. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "JavaScript", "developer_needs": [ "cost_latency_tradeoffs", "evaluation_metrics", "reproducibility", "auditability" ], "moe_experts": [ "performance_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
11bb0f95f2da3159a3a23b56b97c3de63d797872
train_17541
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: 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": [ "reproducibility", "governance", "documentation", "tooling" ], "moe_experts": [ "coding_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
d5ebd2d6465066623a32f7e1074b5d6171120fc7
train_17542
2026-01-01T00:00:00
Agentic coding systems (plan→edit→test→reflect)
design
intermediate
Task: design Topic: Agentic coding systems (plan→edit→test→reflect) Difficulty: intermediate Target language: 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
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Java", "developer_needs": [ "cost_latency_tradeoffs", "tests_are_truth", "evaluation_metrics", "documentation" ], "moe_experts": [ "performance_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
5abaa141de42746539be727019d41ec493bf591f
train_17543
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: Bash Context: Offline/local deployment with limited compute. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Eval: pass@k, time-to-green, regressions, diff size
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Bash", "developer_needs": [ "reproducibility", "repo_scale_reasoning", "tooling", "ci_integration" ], "moe_experts": [ "governance_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
94c5f3c11e966398cef2928d5ec2ca23adc51924
train_17544
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: Large monorepo with flaky tests and strict CI. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Eval: pass@k, time-to-green, regressions, diff size
[]
{ "target_language": "C#", "developer_needs": [ "reproducibility", "ci_integration", "evaluation_metrics", "tests_are_truth" ], "moe_experts": [ "performance_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
f2226a5f62aeae03f32d569619a539033f30716c
train_17545
2026-01-01T00:00:00
Agentic coding systems (plan→edit→test→reflect)
data_pipeline
intermediate
Task: data_pipeline Topic: Agentic coding systems (plan→edit→test→reflect) Difficulty: intermediate Target language: Bash Context: Offline/local deployment with limited compute. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Pipeline: Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
[]
{ "target_language": "Bash", "developer_needs": [ "auditability", "ci_integration", "cost_latency_tradeoffs", "security_gates" ], "moe_experts": [ "performance_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
74301d46d7d4a54648e245649f715e90545695f5
train_17546
2026-01-01T00:00:00
Dataset curation pipelines (filter, dedupe, quality)
eval
expert
Task: eval Topic: Dataset curation pipelines (filter, dedupe, quality) 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. Eval: pass@k, time-to-green, regressions, diff size
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "JavaScript", "developer_needs": [ "reproducibility", "tests_are_truth", "tooling", "auditability" ], "moe_experts": [ "security_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
ccc727e7523625114a2b47edb7cfaa4e8006b64b
train_17547
2026-01-01T00:00:00
Code-specialized model families and sizing tradeoffs
patch_diff
intermediate
Task: patch_diff Topic: Code-specialized model families and sizing tradeoffs Difficulty: intermediate Target language: 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": [ "governance", "auditability", "tests_are_truth", "documentation" ], "moe_experts": [ "evaluation_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
d631d50528642def994f4ebd5819a6a6dbf6c692
train_17548
2026-01-01T00:00:00
Secure code generation and policy gates
agent_loop
advanced
Task: agent_loop Topic: Secure code generation and policy gates 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": [ "evaluation_metrics", "security_gates", "tooling", "ci_integration" ], "moe_experts": [ "security_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
e9e2708241998f6a15bd96dd5f5c874e2d0ee22e
train_17549
2026-01-01T00:00:00
Extended context and repo-scale understanding
code
expert
Task: code Topic: Extended context and repo-scale understanding Difficulty: expert Target language: 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": [ "reproducibility", "tooling", "auditability", "evaluation_metrics" ], "moe_experts": [ "governance_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
1d35d3d3c8c872e92b48ee5b15faf3cef858ea17
train_17550
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: 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": [ "reproducibility", "evaluation_metrics", "tooling", "documentation" ], "moe_experts": [ "security_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
49a3901adac757c843f33cdd391119bab8d21afb
train_17551
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": [ "tests_are_truth", "governance", "cost_latency_tradeoffs", "security_gates" ], "moe_experts": [ "evaluation_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
1430a62d71fc4fb7a744e16ede6f4318e0e21aab
train_17552
2026-01-01T00:00:00
Agentic coding systems (plan→edit→test→reflect)
design
advanced
Task: design Topic: Agentic coding systems (plan→edit→test→reflect) Difficulty: advanced Target language: 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": [ "tooling", "tests_are_truth", "ci_integration", "evaluation_metrics" ], "moe_experts": [ "coding_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
089a19431e2105f492a100522dd51fbfe7519f82
train_17553
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: 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": [ "governance", "auditability", "cost_latency_tradeoffs", "tests_are_truth" ], "moe_experts": [ "data_curation_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
fa9fe2d9ce0ccef9e21634a2ec68658e817e8bcc
train_17554
2026-01-01T00:00:00
Self-improving agents and feedback loops
eval
advanced
Task: eval Topic: Self-improving agents and feedback loops Difficulty: advanced Target language: 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. Eval: pass@k, time-to-green, regressions, diff size
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "JavaScript", "developer_needs": [ "repo_scale_reasoning", "governance", "tests_are_truth", "evaluation_metrics" ], "moe_experts": [ "data_curation_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
4665c42ff26b6988aaa18cbd70687ca6eb532b4d
train_17555
2026-01-01T00:00:00
Self-improving agents and feedback loops
failure_analysis
expert
Task: failure_analysis Topic: Self-improving agents and feedback loops 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. 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": [ "cost_latency_tradeoffs", "auditability", "tests_are_truth", "ci_integration" ], "moe_experts": [ "agentic_systems_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
9e4103bfc0585fb48f26c1e95ddefd37129b6b6c
train_17556
2026-01-01T00:00:00
Multimodal dev workflows (docs, diagrams, traces)
code
intermediate
Task: code Topic: Multimodal dev workflows (docs, diagrams, traces) Difficulty: intermediate Target language: 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": [ "documentation", "ci_integration", "reproducibility", "tooling" ], "moe_experts": [ "performance_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
d31eb95c19a7c5a2488f2ce7d9c7fef9595613d5
train_17557
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: 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": [ "evaluation_metrics", "reproducibility", "tests_are_truth", "auditability" ], "moe_experts": [ "data_curation_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
e0846070d2495549092a1f7ee15ce1a3c4f60b6f
train_17558
2026-01-01T00:00:00
SWE-bench style real-repo evaluation
design
advanced
Task: design Topic: SWE-bench style real-repo evaluation Difficulty: advanced Target language: Python Context: Research team validating claims against real repos. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "Python", "developer_needs": [ "reproducibility", "auditability", "repo_scale_reasoning", "cost_latency_tradeoffs" ], "moe_experts": [ "security_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
1597047005f07f8fa9231379a0e9641b04901676
train_17559
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: 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. Patch (diff-style): ```diff - if x == 0: - return 1/x + if x == 0: + raise ValueError('division by zero') ``` Acceptance: - Tests pass - No new regressions
[]
{ "target_language": "Python", "developer_needs": [ "auditability", "governance", "tooling", "reproducibility" ], "moe_experts": [ "evaluation_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
3259e656c0c3013c1944063645faa44979e26aa9
train_17560
2026-01-01T00:00:00
Secure code generation and policy gates
design
intermediate
Task: design Topic: Secure code generation and policy gates Difficulty: intermediate Target language: Rust Context: Offline/local deployment with limited compute. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "Rust", "developer_needs": [ "reproducibility", "repo_scale_reasoning", "tests_are_truth", "security_gates" ], "moe_experts": [ "evaluation_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
83ea076be2b7ea4fb661f8f0e227278e37133ea4
train_17561
2026-01-01T00:00:00
Mixture-of-Experts (MoE) for code
failure_analysis
intermediate
Task: failure_analysis Topic: Mixture-of-Experts (MoE) for code Difficulty: intermediate Target language: Go Context: Offline/local deployment with limited compute. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. 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": [ "evaluation_metrics", "auditability", "tooling", "security_gates" ], "moe_experts": [ "performance_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
4a214d75b27326e37a45e963669b6ddfe43d2c72
train_17562
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: High-traffic service with latency SLOs. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Review: correctness, security, performance, governance
[]
{ "target_language": "SQL", "developer_needs": [ "auditability", "reproducibility", "tests_are_truth", "documentation" ], "moe_experts": [ "data_curation_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
0fa6322716f4bada2d48159626da4f077f3f9e7b
train_17563
2026-01-01T00:00:00
Dataset curation pipelines (filter, dedupe, quality)
data_pipeline
intermediate
Task: data_pipeline Topic: Dataset curation pipelines (filter, dedupe, quality) Difficulty: intermediate Target language: JavaScript Context: 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": "JavaScript", "developer_needs": [ "ci_integration", "security_gates", "tooling", "auditability" ], "moe_experts": [ "governance_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
70b11b84be0213249f39ff2d20b2e07372c4a91f
train_17564
2026-01-01T00:00:00
Latency, cost, and reliability optimization
compare
advanced
Task: compare Topic: Latency, cost, and reliability optimization 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. Compare: capability, cost, latency, reliability
[]
{ "target_language": "TypeScript", "developer_needs": [ "documentation", "reproducibility", "tests_are_truth", "evaluation_metrics" ], "moe_experts": [ "coding_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
1e1f25f8216675a76e0a36de7e4e0b2688c92baf
train_17565
2026-01-01T00:00:00
Agentic coding systems (plan→edit→test→reflect)
design
intermediate
Task: design Topic: Agentic coding systems (plan→edit→test→reflect) Difficulty: intermediate Target language: 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", "tests_are_truth", "tooling", "evaluation_metrics" ], "moe_experts": [ "coding_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
06a8ef35f7e91a926c8c0b31a78c6f08979284bb
train_17566
2026-01-01T00:00:00
Multimodal dev workflows (docs, diagrams, traces)
review
intermediate
Task: review Topic: Multimodal dev workflows (docs, diagrams, traces) 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
[ "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", "tests_are_truth", "repo_scale_reasoning" ], "moe_experts": [ "data_curation_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
87c6a2b977b8c8173193b735032dd35e3f240c7b
train_17567
2026-01-01T00:00:00
Governance, provenance, and licensing for code data
failure_analysis
expert
Task: failure_analysis Topic: Governance, provenance, and licensing for code data 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. Failure: - Initial patch broke edge case Reflection: - Missing zero-input guard Correction: - Add explicit validation + test
[]
{ "target_language": "Rust", "developer_needs": [ "documentation", "ci_integration", "repo_scale_reasoning", "auditability" ], "moe_experts": [ "performance_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
23a1a42b97b53afad135f5e65529298b0bc9c9fd
train_17568
2026-01-01T00:00:00
Tool calling, sandboxes, and CI integration
failure_analysis
advanced
Task: failure_analysis Topic: Tool calling, sandboxes, and CI integration Difficulty: advanced Target language: 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
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Python", "developer_needs": [ "ci_integration", "documentation", "security_gates", "evaluation_metrics" ], "moe_experts": [ "evaluation_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
e16b164e9c39f9f4b8279e86979abe0bd3ced9e5
train_17569
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: 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. 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": "C#", "developer_needs": [ "tooling", "tests_are_truth", "governance", "auditability" ], "moe_experts": [ "evaluation_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
bb2819a33139d6aa121511845d582806a1b45288
train_17570
2026-01-01T00:00:00
Self-improving agents and feedback loops
agent_loop
advanced
Task: agent_loop Topic: Self-improving agents and feedback loops Difficulty: advanced Target language: 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": [ "cost_latency_tradeoffs", "repo_scale_reasoning", "auditability", "security_gates" ], "moe_experts": [ "performance_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
e7d99fc793a1c140a82bf6bfdd55631b7da4fbff
train_17571
2026-01-01T00:00:00
Tool calling, sandboxes, and CI integration
eval
expert
Task: eval Topic: Tool calling, sandboxes, and CI integration 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. Eval: pass@k, time-to-green, regressions, diff size
[]
{ "target_language": "SQL", "developer_needs": [ "reproducibility", "tests_are_truth", "governance", "tooling" ], "moe_experts": [ "agentic_systems_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
f8b8782017fa9d5cec080c4f7ff721fdebbfa4ee
train_17572
2026-01-01T00:00:00
Dataset curation pipelines (filter, dedupe, quality)
eval
intermediate
Task: eval Topic: Dataset curation pipelines (filter, dedupe, quality) Difficulty: intermediate Target language: Go Context: High-traffic service with latency SLOs. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Eval: pass@k, time-to-green, regressions, diff size
[]
{ "target_language": "Go", "developer_needs": [ "evaluation_metrics", "cost_latency_tradeoffs", "security_gates", "tooling" ], "moe_experts": [ "coding_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
1ddbdc4fc913b7f550ed2b1df2353229fb8730cb
train_17573
2026-01-01T00:00:00
Mixture-of-Experts (MoE) for code
review
intermediate
Task: review Topic: Mixture-of-Experts (MoE) for code Difficulty: intermediate Target language: C# Context: Research team validating claims against real repos. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Review: correctness, security, performance, governance
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "C#", "developer_needs": [ "auditability", "ci_integration", "cost_latency_tradeoffs", "security_gates" ], "moe_experts": [ "evaluation_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
d39b4bd88d83cbc9e80f64748e3798d81e17ea21
train_17574
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: 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": [ "repo_scale_reasoning", "tooling", "reproducibility", "governance" ], "moe_experts": [ "evaluation_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
b1c8d7009406d784fdb651cdc16f7aa59024e22a
train_17575
2026-01-01T00:00:00
Mixture-of-Experts (MoE) for code
code
expert
Task: code Topic: Mixture-of-Experts (MoE) for code Difficulty: expert Target language: Python Context: 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. 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", "documentation", "auditability", "security_gates" ], "moe_experts": [ "data_curation_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
27e24dc5e095bb40ed90f66d42b17fdcd1331446
train_17576
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: TypeScript Context: Regulated environment requiring audit trails. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Eval: pass@k, time-to-green, regressions, diff size
[]
{ "target_language": "TypeScript", "developer_needs": [ "repo_scale_reasoning", "ci_integration", "auditability", "documentation" ], "moe_experts": [ "performance_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
1b6b6bc53168ace5ec085c2ee979d660afcf0c69
train_17577
2026-01-01T00:00:00
Agentic coding systems (plan→edit→test→reflect)
data_pipeline
expert
Task: data_pipeline Topic: Agentic coding systems (plan→edit→test→reflect) Difficulty: expert Target language: Bash Context: 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": "Bash", "developer_needs": [ "ci_integration", "reproducibility", "auditability", "documentation" ], "moe_experts": [ "governance_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
38de7fc3aad5f3dc049a740dfc9a6fc318f3047d
train_17578
2026-01-01T00:00:00
Latency, cost, and reliability optimization
explain
advanced
Task: explain Topic: Latency, cost, and reliability optimization Difficulty: advanced Target language: TypeScript Context: Large monorepo with flaky tests and strict CI. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "TypeScript", "developer_needs": [ "tooling", "documentation", "security_gates", "reproducibility" ], "moe_experts": [ "coding_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
e0bec71f571d932cddd6f10940f15dd5577823da
train_17579
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: 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": [ "tooling", "tests_are_truth", "security_gates", "auditability" ], "moe_experts": [ "governance_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
97336b9f05ebfc3d1e069311882130ba4e7974bb
train_17580
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: Python Context: High-traffic service with latency SLOs. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Failure: - Initial patch broke edge case Reflection: - Missing zero-input guard Correction: - Add explicit validation + test
[]
{ "target_language": "Python", "developer_needs": [ "evaluation_metrics", "auditability", "documentation", "governance" ], "moe_experts": [ "evaluation_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
ad99951672bab98f68c0fa830576c73b498d9247
train_17581
2026-01-01T00:00:00
SWE-bench style real-repo evaluation
agent_loop
expert
Task: agent_loop Topic: SWE-bench style real-repo evaluation Difficulty: expert Target language: 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", "tooling", "governance", "ci_integration" ], "moe_experts": [ "security_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
330485acdfbce80307c363790e38ddfba30aa4e0
train_17582
2026-01-01T00:00:00
Self-improving agents and feedback loops
patch_diff
advanced
Task: patch_diff Topic: Self-improving agents and feedback loops Difficulty: advanced Target language: Bash Context: Offline/local deployment with limited compute. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. 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": [ "auditability", "tests_are_truth", "repo_scale_reasoning", "security_gates" ], "moe_experts": [ "agentic_systems_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
463ef235f949682101474b1f40ab45f152a44e66
train_17583
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: 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. 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": [ "tooling", "reproducibility", "repo_scale_reasoning", "tests_are_truth" ], "moe_experts": [ "data_curation_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
6db4153a71d519cc68e8c5155965ada392a817c7
train_17584
2026-01-01T00:00:00
Dataset curation pipelines (filter, dedupe, quality)
eval
advanced
Task: eval Topic: Dataset curation pipelines (filter, dedupe, quality) 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. Eval: pass@k, time-to-green, regressions, diff size
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Java", "developer_needs": [ "tooling", "evaluation_metrics", "repo_scale_reasoning", "reproducibility" ], "moe_experts": [ "evaluation_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
e9827c06b35bd4161421a911040357fac51ca557
train_17585
2026-01-01T00:00:00
Secure code generation and policy gates
review
expert
Task: review Topic: Secure code generation and policy gates Difficulty: expert Target language: Bash Context: Research team validating claims against real repos. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Review: correctness, security, performance, governance
[]
{ "target_language": "Bash", "developer_needs": [ "ci_integration", "tests_are_truth", "governance", "documentation" ], "moe_experts": [ "coding_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
fad3f353da4a91306839745f47bec11de1944f94
train_17586
2026-01-01T00:00:00
Governance, provenance, and licensing for code data
failure_analysis
intermediate
Task: failure_analysis Topic: Governance, provenance, and licensing for code data Difficulty: intermediate Target language: 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. Failure: - Initial patch broke edge case Reflection: - Missing zero-input guard Correction: - Add explicit validation + test
[]
{ "target_language": "TypeScript", "developer_needs": [ "reproducibility", "security_gates", "evaluation_metrics", "repo_scale_reasoning" ], "moe_experts": [ "governance_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
e744c1e07b81c45fafc4f4b2650ac2f09d62c192
train_17587
2026-01-01T00:00:00
Multimodal dev workflows (docs, diagrams, traces)
explain
advanced
Task: explain Topic: Multimodal dev workflows (docs, diagrams, traces) 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": [ "tooling", "auditability", "repo_scale_reasoning", "governance" ], "moe_experts": [ "performance_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
905ce2261772d7f2029fea94179f642912b9d8c6
train_17588
2026-01-01T00:00:00
Extended context and repo-scale understanding
code
expert
Task: code Topic: Extended context and repo-scale understanding Difficulty: expert Target language: 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": [ "ci_integration", "reproducibility", "evaluation_metrics", "cost_latency_tradeoffs" ], "moe_experts": [ "evaluation_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
0746a0b81e7f1882159cb5d7f3ef49a6937ccad2
train_17589
2026-01-01T00:00:00
Tool calling, sandboxes, and CI integration
agent_loop
intermediate
Task: agent_loop Topic: Tool calling, sandboxes, and CI integration 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. Loop: Plan → Edit → Test → Reflect → Human gate
[]
{ "target_language": "Rust", "developer_needs": [ "ci_integration", "reproducibility", "tooling", "security_gates" ], "moe_experts": [ "security_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
d64ded8315be8d18059a8439daf049670c61fee0
train_17590
2026-01-01T00:00:00
Self-improving agents and feedback loops
agent_loop
advanced
Task: agent_loop Topic: Self-improving agents and feedback loops Difficulty: advanced Target language: 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": [ "ci_integration", "governance", "tooling", "tests_are_truth" ], "moe_experts": [ "agentic_systems_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
7df4fced932a9ce3f5eea8ced3ea9a985ab0341e
train_17591
2026-01-01T00:00:00
Latency, cost, and reliability optimization
patch_diff
expert
Task: patch_diff Topic: Latency, cost, and reliability optimization Difficulty: expert Target language: Bash Context: Offline/local deployment with limited compute. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. 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", "governance", "ci_integration", "cost_latency_tradeoffs" ], "moe_experts": [ "data_curation_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
8298127615672d21875221d832a2bc08d2b51753
train_17592
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: Java Context: High-traffic service with latency SLOs. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Review: correctness, security, performance, governance
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Java", "developer_needs": [ "documentation", "evaluation_metrics", "ci_integration", "tooling" ], "moe_experts": [ "coding_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
c4eab1281cb5540c3a86cd54193092f2b43cf326
train_17593
2026-01-01T00:00:00
Agentic coding systems (plan→edit→test→reflect)
failure_analysis
expert
Task: failure_analysis Topic: Agentic coding systems (plan→edit→test→reflect) Difficulty: expert Target language: Rust Context: Research team validating claims against real repos. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Failure: - Initial patch broke edge case Reflection: - Missing zero-input guard Correction: - Add explicit validation + test
[]
{ "target_language": "Rust", "developer_needs": [ "documentation", "auditability", "security_gates", "tests_are_truth" ], "moe_experts": [ "data_curation_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
074205342f77336b6fe5f0db334551ade8cac605
train_17594
2026-01-01T00:00:00
Tool calling, sandboxes, and CI integration
explain
advanced
Task: explain Topic: Tool calling, sandboxes, and CI integration Difficulty: advanced Target language: SQL Context: 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": [ "cost_latency_tradeoffs", "security_gates", "reproducibility", "documentation" ], "moe_experts": [ "data_curation_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
7b8385034f99bcf103606b5419a46615da443cc9
train_17595
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: 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
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "SQL", "developer_needs": [ "auditability", "tooling", "reproducibility", "governance" ], "moe_experts": [ "security_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
b9c0a0fc9d149d5b6ad74c5b20ea4233c472f519
train_17596
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: Python Context: Offline/local deployment with limited compute. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "Python", "developer_needs": [ "repo_scale_reasoning", "governance", "documentation", "tests_are_truth" ], "moe_experts": [ "agentic_systems_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
3e7034ec50e3f3168dd31faff7f6ebf954c91080
train_17597
2026-01-01T00:00:00
Self-improving agents and feedback loops
patch_diff
intermediate
Task: patch_diff Topic: Self-improving agents and feedback loops 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. Patch (diff-style): ```diff - if x == 0: - return 1/x + if x == 0: + raise ValueError('division by zero') ``` Acceptance: - Tests pass - No new regressions
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "C#", "developer_needs": [ "documentation", "governance", "ci_integration", "cost_latency_tradeoffs" ], "moe_experts": [ "agentic_systems_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
eee71e69f01db1d0d85c756e9abb30c995d8134f
train_17598
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: 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. 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": [ "security_gates", "governance", "auditability", "documentation" ], "moe_experts": [ "data_curation_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
53d847bf7cb7b09b1d3a6596988f54eb84266e49
train_17599
2026-01-01T00:00:00
Tool calling, sandboxes, and CI integration
eval
advanced
Task: eval Topic: Tool calling, sandboxes, and CI integration Difficulty: advanced Target language: TypeScript Context: Research team validating claims against real repos. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Eval: pass@k, time-to-green, regressions, diff size
[]
{ "target_language": "TypeScript", "developer_needs": [ "repo_scale_reasoning", "documentation", "tests_are_truth", "governance" ], "moe_experts": [ "agentic_systems_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
c86c24b6ba5249921a1ccef71ba7703a74ab8f44