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train_28700
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: 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": "Java", "developer_needs": [ "tests_are_truth", "ci_integration", "governance", "security_gates" ], "moe_experts": [ "performance_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
a0aeffe5bec1e8c9a69b3d6e9b70e6e6754f9bf8
train_28701
2026-01-01T00:00:00
Dataset curation pipelines (filter, dedupe, quality)
compare
expert
Task: compare Topic: Dataset curation pipelines (filter, dedupe, quality) Difficulty: expert Target language: SQL Context: High-traffic service with latency SLOs. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Compare: capability, cost, latency, reliability
[]
{ "target_language": "SQL", "developer_needs": [ "tooling", "security_gates", "documentation", "cost_latency_tradeoffs" ], "moe_experts": [ "coding_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
8b59d1bc448e936582d93e2a782a68cdbc4e3068
train_28702
2026-01-01T00:00:00
Reasoning-first coding models and tunable deliberation
explain
expert
Task: explain Topic: Reasoning-first coding models and tunable deliberation Difficulty: expert Target language: 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": [ "governance", "ci_integration", "documentation", "evaluation_metrics" ], "moe_experts": [ "performance_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
71f5347bae08fb1510248c981513664b92c1e905
train_28703
2026-01-01T00:00:00
Self-improving agents and feedback loops
failure_analysis
advanced
Task: failure_analysis Topic: Self-improving agents and feedback loops Difficulty: advanced Target language: 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. 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": [ "documentation", "ci_integration", "tests_are_truth", "cost_latency_tradeoffs" ], "moe_experts": [ "governance_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
b4dbc8ba41849c8c9a382db19bf78790360f5a24
train_28704
2026-01-01T00:00:00
Extended context and repo-scale understanding
eval
intermediate
Task: eval Topic: Extended context and repo-scale understanding 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. Eval: pass@k, time-to-green, regressions, diff size
[]
{ "target_language": "Java", "developer_needs": [ "evaluation_metrics", "cost_latency_tradeoffs", "reproducibility", "security_gates" ], "moe_experts": [ "data_curation_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
b6aff791552b103a75e74408eeebaa9300edebea
train_28705
2026-01-01T00:00:00
Model merging, distillation, and continued pretraining
patch_diff
advanced
Task: patch_diff Topic: Model merging, distillation, and continued pretraining Difficulty: advanced Target language: 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
[]
{ "target_language": "C#", "developer_needs": [ "documentation", "repo_scale_reasoning", "governance", "cost_latency_tradeoffs" ], "moe_experts": [ "governance_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
0a4a9584870107ea5a5f531fdd71c52d9d91fce4
train_28706
2026-01-01T00:00:00
Agentic coding systems (plan→edit→test→reflect)
compare
expert
Task: compare Topic: Agentic coding systems (plan→edit→test→reflect) Difficulty: expert Target language: JavaScript Context: Regulated environment requiring audit trails. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Compare: capability, cost, latency, reliability
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "JavaScript", "developer_needs": [ "governance", "ci_integration", "tests_are_truth", "evaluation_metrics" ], "moe_experts": [ "governance_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
ced3f3f71a3741bde8ae23c3ea66bc4e2e50fb2d
train_28707
2026-01-01T00:00:00
Dataset curation pipelines (filter, dedupe, quality)
review
intermediate
Task: review Topic: Dataset curation pipelines (filter, dedupe, quality) Difficulty: intermediate Target language: Rust Context: Regulated environment requiring audit trails. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Review: correctness, security, performance, governance
[]
{ "target_language": "Rust", "developer_needs": [ "repo_scale_reasoning", "cost_latency_tradeoffs", "governance", "ci_integration" ], "moe_experts": [ "data_curation_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
900ce1500c06587a5753223f28e6ce11c0c55265
train_28708
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: 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": [ "reproducibility", "security_gates", "auditability", "tooling" ], "moe_experts": [ "coding_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
cd7d7d8a81fe2e056438dc183a916cecce22feeb
train_28709
2026-01-01T00:00:00
Multimodal dev workflows (docs, diagrams, traces)
patch_diff
expert
Task: patch_diff Topic: Multimodal dev workflows (docs, diagrams, traces) Difficulty: expert Target language: 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. 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": [ "tests_are_truth", "reproducibility", "repo_scale_reasoning", "documentation" ], "moe_experts": [ "data_curation_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
752a044ac99ed40945fb0b7ffc9c2ca3160f5bc0
train_28710
2026-01-01T00:00:00
Extended context and repo-scale understanding
design
advanced
Task: design Topic: Extended context and repo-scale understanding Difficulty: advanced Target language: 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": [ "governance", "repo_scale_reasoning", "cost_latency_tradeoffs", "documentation" ], "moe_experts": [ "evaluation_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
6538ce37fcc35129b80c5f193bc1bcab050c113b
train_28711
2026-01-01T00:00:00
Mixture-of-Experts (MoE) for code
patch_diff
expert
Task: patch_diff Topic: Mixture-of-Experts (MoE) for code Difficulty: expert 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. 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": [ "cost_latency_tradeoffs", "tooling", "ci_integration", "auditability" ], "moe_experts": [ "coding_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
7efb8c4d041bf08e6fe9c17d12d68e67df613ad8
train_28712
2026-01-01T00:00:00
Multimodal dev workflows (docs, diagrams, traces)
design
advanced
Task: design Topic: Multimodal dev workflows (docs, diagrams, traces) Difficulty: advanced Target language: Go Context: Regulated environment requiring audit trails. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "Go", "developer_needs": [ "security_gates", "governance", "documentation", "reproducibility" ], "moe_experts": [ "evaluation_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
99e8bdef1b580e37bb65ab670d9fa174454e2dc9
train_28713
2026-01-01T00:00:00
Model merging, distillation, and continued pretraining
agent_loop
advanced
Task: agent_loop Topic: Model merging, distillation, and continued pretraining Difficulty: advanced Target language: 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": [ "security_gates", "repo_scale_reasoning", "governance", "reproducibility" ], "moe_experts": [ "agentic_systems_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
2fd5ef52665b03b31612bfb0242aa094ffec4a42
train_28714
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: 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. 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": [ "governance", "tests_are_truth", "evaluation_metrics", "cost_latency_tradeoffs" ], "moe_experts": [ "evaluation_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
821024411adcba975d08ffec511029a2b587e2d5
train_28715
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: 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": "Bash", "developer_needs": [ "tooling", "governance", "reproducibility", "repo_scale_reasoning" ], "moe_experts": [ "agentic_systems_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
7f71b5765a79eb532b9d0524c8566f209c143a79
train_28716
2026-01-01T00:00:00
Governance, provenance, and licensing for code data
agent_loop
advanced
Task: agent_loop Topic: Governance, provenance, and licensing for code data Difficulty: advanced Target language: Go Context: Large monorepo with flaky tests and strict CI. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Loop: Plan → Edit → Test → Reflect → Human gate
[]
{ "target_language": "Go", "developer_needs": [ "documentation", "governance", "evaluation_metrics", "reproducibility" ], "moe_experts": [ "evaluation_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
d27475797664ba25ec2f2653af8689e83b3396f0
train_28717
2026-01-01T00:00:00
SWE-bench style real-repo evaluation
failure_analysis
advanced
Task: failure_analysis Topic: SWE-bench style real-repo evaluation Difficulty: advanced Target language: SQL Context: Offline/local deployment with limited compute. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Failure: - Initial patch broke edge case Reflection: - Missing zero-input guard Correction: - Add explicit validation + test
[]
{ "target_language": "SQL", "developer_needs": [ "tooling", "reproducibility", "governance", "documentation" ], "moe_experts": [ "security_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
6d84587e58f206bb969094dce3afed5bd5acdfe9
train_28718
2026-01-01T00:00:00
Code-specialized model families and sizing tradeoffs
data_pipeline
expert
Task: data_pipeline Topic: Code-specialized model families and sizing tradeoffs Difficulty: expert Target language: C# Context: Regulated environment requiring audit trails. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. 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", "security_gates", "governance", "tests_are_truth" ], "moe_experts": [ "security_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
a0a0eb09212c1e3011aefe30a33495fadef8bfed
train_28719
2026-01-01T00:00:00
Reasoning-first coding models and tunable deliberation
explain
expert
Task: explain Topic: Reasoning-first coding models and tunable deliberation Difficulty: expert Target language: Rust Context: Regulated environment requiring audit trails. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "Rust", "developer_needs": [ "tooling", "security_gates", "tests_are_truth", "evaluation_metrics" ], "moe_experts": [ "governance_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
c0bad43b8e4c4f93f361c490f867560915ad7da3
train_28720
2026-01-01T00:00:00
Multimodal dev workflows (docs, diagrams, traces)
patch_diff
expert
Task: patch_diff Topic: Multimodal dev workflows (docs, diagrams, traces) Difficulty: expert Target language: 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. 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": "C#", "developer_needs": [ "cost_latency_tradeoffs", "ci_integration", "documentation", "tooling" ], "moe_experts": [ "data_curation_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
0f1f90492109a6b798dcab8acc538b107d28e592
train_28721
2026-01-01T00:00:00
Reasoning-first coding models and tunable deliberation
patch_diff
intermediate
Task: patch_diff Topic: Reasoning-first coding models and tunable deliberation 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. Patch (diff-style): ```diff - if x == 0: - return 1/x + if x == 0: + raise ValueError('division by zero') ``` Acceptance: - Tests pass - No new regressions
[]
{ "target_language": "TypeScript", "developer_needs": [ "tooling", "auditability", "ci_integration", "documentation" ], "moe_experts": [ "evaluation_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
fdef99cf093de1c8ab454cf07710d00c4a0f0b88
train_28722
2026-01-01T00:00:00
Extended context and repo-scale understanding
explain
expert
Task: explain Topic: Extended context and repo-scale understanding Difficulty: expert Target language: Rust Context: 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": "Rust", "developer_needs": [ "security_gates", "evaluation_metrics", "tooling", "tests_are_truth" ], "moe_experts": [ "security_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
efa3936ed32003b3b5cd3ccb84b5865bd7dcd030
train_28723
2026-01-01T00:00:00
Governance, provenance, and licensing for code data
compare
intermediate
Task: compare Topic: Governance, provenance, and licensing for code data Difficulty: intermediate Target language: Bash Context: Research team validating claims against real repos. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Compare: capability, cost, latency, reliability
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Bash", "developer_needs": [ "evaluation_metrics", "cost_latency_tradeoffs", "tests_are_truth", "documentation" ], "moe_experts": [ "data_curation_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
fd4556bc4a1db05db2ce505c057126f2594ad562
train_28724
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: TypeScript Context: Offline/local deployment with limited compute. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "TypeScript", "developer_needs": [ "security_gates", "repo_scale_reasoning", "auditability", "documentation" ], "moe_experts": [ "security_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
e6e0327fe735d1c66fb9e74229e9e41db155ab41
train_28725
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: Bash Context: Research team validating claims against real repos. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Eval: pass@k, time-to-green, regressions, diff size
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Bash", "developer_needs": [ "auditability", "security_gates", "tests_are_truth", "reproducibility" ], "moe_experts": [ "coding_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
ad06a23af4b9925be759ecfd519796411c8c9694
train_28726
2026-01-01T00:00:00
Self-improving agents and feedback loops
explain
intermediate
Task: explain Topic: Self-improving agents and feedback loops 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", "security_gates", "documentation", "ci_integration" ], "moe_experts": [ "evaluation_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
3de555f230bc051c7b925b94d9c3ce8083e34fd4
train_28727
2026-01-01T00:00:00
Mixture-of-Experts (MoE) for code
data_pipeline
intermediate
Task: data_pipeline Topic: Mixture-of-Experts (MoE) for code Difficulty: intermediate Target language: JavaScript Context: High-traffic service with latency SLOs. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Pipeline: Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
[]
{ "target_language": "JavaScript", "developer_needs": [ "documentation", "auditability", "security_gates", "repo_scale_reasoning" ], "moe_experts": [ "data_curation_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
41cf59f1b0555f4a031e5cbd6c36eb9d00f3aa01
train_28728
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: 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. Compare: capability, cost, latency, reliability
[]
{ "target_language": "Python", "developer_needs": [ "documentation", "reproducibility", "repo_scale_reasoning", "cost_latency_tradeoffs" ], "moe_experts": [ "agentic_systems_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
697fe197b4c69042535501b398b7ffccad9bdb55
train_28729
2026-01-01T00:00:00
Reasoning-first coding models and tunable deliberation
patch_diff
intermediate
Task: patch_diff Topic: Reasoning-first coding models and tunable deliberation Difficulty: intermediate Target language: Rust Context: Regulated environment requiring audit trails. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Patch (diff-style): ```diff - if x == 0: - return 1/x + if x == 0: + raise ValueError('division by zero') ``` Acceptance: - Tests pass - No new regressions
[]
{ "target_language": "Rust", "developer_needs": [ "reproducibility", "repo_scale_reasoning", "tooling", "auditability" ], "moe_experts": [ "security_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
a06d003b53451481a8b3ef43a35c93025662eb1d
train_28730
2026-01-01T00:00:00
Model merging, distillation, and continued pretraining
design
expert
Task: design Topic: Model merging, distillation, and continued pretraining 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
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "JavaScript", "developer_needs": [ "tests_are_truth", "cost_latency_tradeoffs", "governance", "reproducibility" ], "moe_experts": [ "governance_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
235b968d3c49bb14166464265ec8165034f496ff
train_28731
2026-01-01T00:00:00
Latency, cost, and reliability optimization
review
intermediate
Task: review Topic: Latency, cost, and reliability optimization 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. Review: correctness, security, performance, governance
[]
{ "target_language": "JavaScript", "developer_needs": [ "repo_scale_reasoning", "evaluation_metrics", "documentation", "tooling" ], "moe_experts": [ "coding_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
726c2d538f43c8deca2111426f24f41841aa542b
train_28732
2026-01-01T00:00:00
Latency, cost, and reliability optimization
eval
intermediate
Task: eval Topic: Latency, cost, and reliability optimization Difficulty: intermediate Target language: JavaScript Context: 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": "JavaScript", "developer_needs": [ "documentation", "tooling", "ci_integration", "reproducibility" ], "moe_experts": [ "performance_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
fbc2b8ab0d76eb7651c0820a019ca58fcf461ce6
train_28733
2026-01-01T00:00:00
Tool calling, sandboxes, and CI integration
compare
advanced
Task: compare Topic: Tool calling, sandboxes, and CI integration Difficulty: advanced Target language: JavaScript Context: Regulated environment requiring audit trails. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Compare: capability, cost, latency, reliability
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "JavaScript", "developer_needs": [ "repo_scale_reasoning", "security_gates", "evaluation_metrics", "ci_integration" ], "moe_experts": [ "coding_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
75d026f0b4769b35565182c76473a7e1ba52e7a1
train_28734
2026-01-01T00:00:00
SWE-bench style real-repo evaluation
explain
advanced
Task: explain Topic: SWE-bench style real-repo evaluation Difficulty: advanced Target language: Rust Context: Large monorepo with flaky tests and strict CI. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "Rust", "developer_needs": [ "tooling", "security_gates", "tests_are_truth", "governance" ], "moe_experts": [ "agentic_systems_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
53afac17f669932faded1300f904682bec59647d
train_28735
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: 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": [ "evaluation_metrics", "reproducibility", "documentation", "auditability" ], "moe_experts": [ "data_curation_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
aedcc472a66373e528806de6810cce5b74d77965
train_28736
2026-01-01T00:00:00
Governance, provenance, and licensing for code data
failure_analysis
advanced
Task: failure_analysis Topic: Governance, provenance, and licensing for code data Difficulty: advanced Target language: SQL Context: Research team validating claims against real repos. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Failure: - Initial patch broke edge case Reflection: - Missing zero-input guard Correction: - Add explicit validation + test
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "SQL", "developer_needs": [ "reproducibility", "cost_latency_tradeoffs", "documentation", "tests_are_truth" ], "moe_experts": [ "data_curation_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
03fb1d03d3c0baec99e4cddfdd47f2505cd38686
train_28737
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: Java Context: Regulated environment requiring audit trails. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "Java", "developer_needs": [ "tests_are_truth", "cost_latency_tradeoffs", "documentation", "reproducibility" ], "moe_experts": [ "evaluation_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
5c77e79343dbbe4337c29aa40f47bc36b91152b7
train_28738
2026-01-01T00:00:00
Mixture-of-Experts (MoE) for code
design
expert
Task: design Topic: Mixture-of-Experts (MoE) for code Difficulty: expert 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": [ "ci_integration", "reproducibility", "auditability", "tooling" ], "moe_experts": [ "security_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
ded5c643a9d74d88f7eac911892c28d7a41fae50
train_28739
2026-01-01T00:00:00
Extended context and repo-scale understanding
eval
advanced
Task: eval Topic: Extended context and repo-scale understanding Difficulty: advanced Target language: 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", "ci_integration", "auditability", "cost_latency_tradeoffs" ], "moe_experts": [ "agentic_systems_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
beb0c88644d0829b65e069c641f30f7866b9a76d
train_28740
2026-01-01T00:00:00
Dataset curation pipelines (filter, dedupe, quality)
failure_analysis
expert
Task: failure_analysis Topic: Dataset curation pipelines (filter, dedupe, quality) 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. Failure: - Initial patch broke edge case Reflection: - Missing zero-input guard Correction: - Add explicit validation + test
[]
{ "target_language": "JavaScript", "developer_needs": [ "repo_scale_reasoning", "tests_are_truth", "security_gates", "cost_latency_tradeoffs" ], "moe_experts": [ "coding_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
83f3009b061f222c4c6de94f578764bad7f8e3ee
train_28741
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: JavaScript Context: Regulated environment requiring audit trails. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Compare: capability, cost, latency, reliability
[]
{ "target_language": "JavaScript", "developer_needs": [ "cost_latency_tradeoffs", "tests_are_truth", "documentation", "auditability" ], "moe_experts": [ "evaluation_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
7010014d311694a54d7cce8930a7e79f3e6099ae
train_28742
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: 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. Review: correctness, security, performance, governance
[]
{ "target_language": "Rust", "developer_needs": [ "tests_are_truth", "auditability", "documentation", "ci_integration" ], "moe_experts": [ "agentic_systems_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
28592c001adff9f05b75048baf3f9772116ebdb7
train_28743
2026-01-01T00:00:00
SWE-bench style real-repo evaluation
code
expert
Task: code Topic: SWE-bench style real-repo evaluation Difficulty: expert Target language: Go Context: High-traffic service with latency SLOs. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Go", "developer_needs": [ "auditability", "documentation", "reproducibility", "ci_integration" ], "moe_experts": [ "agentic_systems_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
7d2f24dbc5f59788b75ca5b2cb0895a6eb885c01
train_28744
2026-01-01T00:00:00
Extended context and repo-scale understanding
data_pipeline
expert
Task: data_pipeline Topic: Extended context and repo-scale understanding Difficulty: expert Target language: 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": [ "repo_scale_reasoning", "governance", "evaluation_metrics", "cost_latency_tradeoffs" ], "moe_experts": [ "coding_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
c7f31c36d34e33ad722680004d4d85babc440d18
train_28745
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: 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": [ "security_gates", "tests_are_truth", "reproducibility", "ci_integration" ], "moe_experts": [ "performance_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
4be949a18feec5d4a0779cb8a3324bec82286445
train_28746
2026-01-01T00:00:00
Model merging, distillation, and continued pretraining
data_pipeline
intermediate
Task: data_pipeline Topic: Model merging, distillation, and continued pretraining Difficulty: intermediate Target language: 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. 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": [ "ci_integration", "governance", "cost_latency_tradeoffs", "documentation" ], "moe_experts": [ "data_curation_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
2b34f1a822a825dfe70f6b8fca274531b03cb230
train_28747
2026-01-01T00:00:00
SWE-bench style real-repo evaluation
review
advanced
Task: review Topic: SWE-bench style real-repo evaluation 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. Review: correctness, security, performance, governance
[]
{ "target_language": "Go", "developer_needs": [ "evaluation_metrics", "ci_integration", "tooling", "cost_latency_tradeoffs" ], "moe_experts": [ "performance_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
042e7a645ab11133703c8d67a7b73f3ba38835e0
train_28748
2026-01-01T00:00:00
Secure code generation and policy gates
design
expert
Task: design Topic: Secure code generation and policy gates Difficulty: expert Target language: 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": [ "repo_scale_reasoning", "tooling", "evaluation_metrics", "ci_integration" ], "moe_experts": [ "evaluation_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
aad899140928212e4b3b12236bfa9384bee356f3
train_28749
2026-01-01T00:00:00
Extended context and repo-scale understanding
eval
expert
Task: eval Topic: Extended context and repo-scale understanding Difficulty: expert Target language: Go Context: High-traffic service with latency SLOs. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Eval: pass@k, time-to-green, regressions, diff size
[]
{ "target_language": "Go", "developer_needs": [ "cost_latency_tradeoffs", "tooling", "ci_integration", "documentation" ], "moe_experts": [ "performance_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
69dba35c2384177e4ccf7abccb57c5c07b326dfe
train_28750
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: 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. 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": [ "auditability", "security_gates", "cost_latency_tradeoffs", "tests_are_truth" ], "moe_experts": [ "governance_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
0db7c45a7648daef0214e36a24bc392fe0a68898
train_28751
2026-01-01T00:00:00
Multimodal dev workflows (docs, diagrams, traces)
review
advanced
Task: review Topic: Multimodal dev workflows (docs, diagrams, traces) 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. 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": [ "tooling", "ci_integration", "cost_latency_tradeoffs", "auditability" ], "moe_experts": [ "data_curation_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
5bee3cd29b78430fcd3d22dd274a8b9a64c6925b
train_28752
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: SQL Context: High-traffic service with latency SLOs. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "SQL", "developer_needs": [ "governance", "security_gates", "evaluation_metrics", "documentation" ], "moe_experts": [ "evaluation_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
05af232cfa91edfb290e8ea80df7f61079625e61
train_28753
2026-01-01T00:00:00
Agentic coding systems (plan→edit→test→reflect)
agent_loop
expert
Task: agent_loop Topic: Agentic coding systems (plan→edit→test→reflect) Difficulty: expert Target language: Go Context: 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", "ci_integration", "repo_scale_reasoning", "tooling" ], "moe_experts": [ "performance_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
028e45a913e687bf97f0e00d13d329530970a9ee
train_28754
2026-01-01T00:00:00
Dataset curation pipelines (filter, dedupe, quality)
compare
advanced
Task: compare Topic: Dataset curation pipelines (filter, dedupe, quality) Difficulty: advanced Target language: Bash Context: Research team validating claims against real repos. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Compare: capability, cost, latency, reliability
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Bash", "developer_needs": [ "documentation", "governance", "ci_integration", "reproducibility" ], "moe_experts": [ "coding_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
65f5120ce441973df1e1abda48156fdd0ffae285
train_28755
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: 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
[]
{ "target_language": "Bash", "developer_needs": [ "security_gates", "tests_are_truth", "reproducibility", "evaluation_metrics" ], "moe_experts": [ "performance_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
040641173cd03d3517c46b817f9466f86324b18e
train_28756
2026-01-01T00:00:00
Latency, cost, and reliability optimization
eval
advanced
Task: eval Topic: Latency, cost, and reliability optimization Difficulty: advanced Target language: Java Context: Large monorepo with flaky tests and strict CI. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Eval: pass@k, time-to-green, regressions, diff size
[]
{ "target_language": "Java", "developer_needs": [ "security_gates", "documentation", "tests_are_truth", "auditability" ], "moe_experts": [ "coding_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
97e8a630067669175c2a0d047ceb6b9494d8fa27
train_28757
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: 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": [ "tooling", "auditability", "documentation", "ci_integration" ], "moe_experts": [ "performance_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
7a9aa53c7fc57fcaae65bbb8a5fabeaa2c4fb331
train_28758
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: Bash Context: Regulated environment requiring audit trails. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Review: correctness, security, performance, governance
[]
{ "target_language": "Bash", "developer_needs": [ "tooling", "governance", "documentation", "ci_integration" ], "moe_experts": [ "coding_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
6c5a8c09498eeca6996f0664dbe00c80e21555bd
train_28759
2026-01-01T00:00:00
Reasoning-first coding models and tunable deliberation
compare
advanced
Task: compare Topic: Reasoning-first coding models and tunable deliberation Difficulty: advanced Target language: Python Context: High-traffic service with latency SLOs. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Compare: capability, cost, latency, reliability
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Python", "developer_needs": [ "governance", "evaluation_metrics", "cost_latency_tradeoffs", "ci_integration" ], "moe_experts": [ "evaluation_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
c14222e2d95ab5a53e0920ca5d8372680e4dfaf3
train_28760
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: 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", "tests_are_truth", "governance", "repo_scale_reasoning" ], "moe_experts": [ "governance_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
67d87a9c5d73519068b5cc9301459e7621eaffab
train_28761
2026-01-01T00:00:00
Extended context and repo-scale understanding
eval
intermediate
Task: eval Topic: Extended context and repo-scale understanding 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. Eval: pass@k, time-to-green, regressions, diff size
[]
{ "target_language": "TypeScript", "developer_needs": [ "ci_integration", "tooling", "cost_latency_tradeoffs", "security_gates" ], "moe_experts": [ "security_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
b505cdd343aad2730fbe64fa23f01446a6b75069
train_28762
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: 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": [ "repo_scale_reasoning", "tests_are_truth", "cost_latency_tradeoffs", "tooling" ], "moe_experts": [ "data_curation_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
d6debb5cbd3657b50c3187283cb91310bb6cb04d
train_28763
2026-01-01T00:00:00
Multimodal dev workflows (docs, diagrams, traces)
explain
intermediate
Task: explain Topic: Multimodal dev workflows (docs, diagrams, traces) Difficulty: intermediate Target language: 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": [ "tooling", "governance", "security_gates", "repo_scale_reasoning" ], "moe_experts": [ "agentic_systems_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
d9ee809ca90fa5ee163872bbefa52d0afba37536
train_28764
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: JavaScript Context: Large monorepo with flaky tests and strict CI. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Failure: - Initial patch broke edge case Reflection: - Missing zero-input guard Correction: - Add explicit validation + test
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "JavaScript", "developer_needs": [ "security_gates", "tests_are_truth", "tooling", "cost_latency_tradeoffs" ], "moe_experts": [ "coding_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
68af15e343752f5b5409014e911cc0fd765a3ae8
train_28765
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: 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. Compare: capability, cost, latency, reliability
[]
{ "target_language": "Go", "developer_needs": [ "auditability", "evaluation_metrics", "governance", "repo_scale_reasoning" ], "moe_experts": [ "performance_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
e16848fa009f266879e207b7ec4f6344040449db
train_28766
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": [ "evaluation_metrics", "auditability", "tests_are_truth", "reproducibility" ], "moe_experts": [ "evaluation_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
330485acdfbce80307c363790e38ddfba30aa4e0
train_28767
2026-01-01T00:00:00
SWE-bench style real-repo evaluation
patch_diff
advanced
Task: patch_diff Topic: SWE-bench style real-repo evaluation Difficulty: advanced Target language: Bash Context: Large monorepo with flaky tests and strict CI. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Patch (diff-style): ```diff - if x == 0: - return 1/x + if x == 0: + raise ValueError('division by zero') ``` Acceptance: - Tests pass - No new regressions
[]
{ "target_language": "Bash", "developer_needs": [ "evaluation_metrics", "governance", "tooling", "ci_integration" ], "moe_experts": [ "security_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
851331882e1635ea42b38f98619faeddee95aa77
train_28768
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: 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": [ "repo_scale_reasoning", "documentation", "evaluation_metrics", "auditability" ], "moe_experts": [ "coding_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
e0a919d8133801aa3234651230d2630a8e4029f9
train_28769
2026-01-01T00:00:00
Tool calling, sandboxes, and CI integration
design
intermediate
Task: design Topic: Tool calling, sandboxes, and CI integration Difficulty: intermediate Target language: Python Context: 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": "Python", "developer_needs": [ "repo_scale_reasoning", "evaluation_metrics", "security_gates", "ci_integration" ], "moe_experts": [ "coding_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
d7e2a7cce9b6b3920bc67792c57751aad8113600
train_28770
2026-01-01T00:00:00
Self-improving agents and feedback loops
review
expert
Task: review 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. Review: correctness, security, performance, governance
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Go", "developer_needs": [ "governance", "documentation", "repo_scale_reasoning", "reproducibility" ], "moe_experts": [ "security_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
253b999e4f81d76f717bcc6521e9988b8e238918
train_28771
2026-01-01T00:00:00
Model merging, distillation, and continued pretraining
failure_analysis
intermediate
Task: failure_analysis Topic: Model merging, distillation, and continued pretraining Difficulty: intermediate Target language: Bash Context: Research team validating claims against real repos. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Failure: - Initial patch broke edge case Reflection: - Missing zero-input guard Correction: - Add explicit validation + test
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Bash", "developer_needs": [ "auditability", "tests_are_truth", "documentation", "repo_scale_reasoning" ], "moe_experts": [ "governance_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
bcd37e5ea1cfe178540453b6db8b6deff36b291b
train_28772
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: 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
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Go", "developer_needs": [ "security_gates", "auditability", "tooling", "ci_integration" ], "moe_experts": [ "security_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
bd7c1adbcbaef5122182303fa63d74e9e28fa08b
train_28773
2026-01-01T00:00:00
Latency, cost, and reliability optimization
data_pipeline
advanced
Task: data_pipeline Topic: Latency, cost, and reliability optimization Difficulty: advanced Target language: Bash Context: Research team validating claims against real repos. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Pipeline: Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Bash", "developer_needs": [ "ci_integration", "security_gates", "auditability", "tooling" ], "moe_experts": [ "evaluation_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
e1f49ebadbcd3ddcc816ae3cdadbfa9014fd734c
train_28774
2026-01-01T00:00:00
Tool calling, sandboxes, and CI integration
patch_diff
advanced
Task: patch_diff Topic: Tool calling, sandboxes, and CI integration 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": [ "repo_scale_reasoning", "tooling", "evaluation_metrics", "reproducibility" ], "moe_experts": [ "security_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
f66903cbb736fb5776799dbb1c75cd651d57dddd
train_28775
2026-01-01T00:00:00
Reasoning-first coding models and tunable deliberation
agent_loop
expert
Task: agent_loop Topic: Reasoning-first coding models and tunable deliberation Difficulty: expert Target language: Bash Context: Large monorepo with flaky tests and strict CI. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Loop: Plan → Edit → Test → Reflect → Human gate
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Bash", "developer_needs": [ "governance", "evaluation_metrics", "ci_integration", "repo_scale_reasoning" ], "moe_experts": [ "governance_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
a41383309d501e394bfa67613cc1de414a345f0d
train_28776
2026-01-01T00:00:00
Agentic coding systems (plan→edit→test→reflect)
code
intermediate
Task: code Topic: Agentic coding systems (plan→edit→test→reflect) Difficulty: intermediate Target language: Go Context: Large monorepo with flaky tests and strict CI. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Go", "developer_needs": [ "tests_are_truth", "auditability", "tooling", "documentation" ], "moe_experts": [ "data_curation_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
95fdf1f3faa0f78ab7594b9ed19cb8f3fb9292c1
train_28777
2026-01-01T00:00:00
Multimodal dev workflows (docs, diagrams, traces)
data_pipeline
expert
Task: data_pipeline Topic: Multimodal dev workflows (docs, diagrams, traces) Difficulty: expert Target language: 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. 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": [ "security_gates", "ci_integration", "documentation", "tooling" ], "moe_experts": [ "governance_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
94005a5a9be762d985e2c5001d76ffc8db895914
train_28778
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: 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", "reproducibility", "repo_scale_reasoning", "security_gates" ], "moe_experts": [ "governance_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
a465c792f7fcb602165429407c494b56a54a7de1
train_28779
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: 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. 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": [ "ci_integration", "documentation", "cost_latency_tradeoffs", "security_gates" ], "moe_experts": [ "security_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
f79f13bd0c3e0d25178890930fad9df6251b33c3
train_28780
2026-01-01T00:00:00
Secure code generation and policy gates
review
advanced
Task: review Topic: Secure code generation and policy gates Difficulty: advanced Target language: C# Context: Offline/local deployment with limited compute. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Review: correctness, security, performance, governance
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "C#", "developer_needs": [ "security_gates", "tooling", "cost_latency_tradeoffs", "auditability" ], "moe_experts": [ "governance_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
1d32a3e5e7e1edba8f5815c8d53855c5acc3475b
train_28781
2026-01-01T00:00:00
Self-improving agents and feedback loops
explain
intermediate
Task: explain Topic: Self-improving agents and feedback loops Difficulty: intermediate Target language: Rust Context: High-traffic service with latency SLOs. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Rust", "developer_needs": [ "reproducibility", "repo_scale_reasoning", "documentation", "tooling" ], "moe_experts": [ "performance_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
2b137c38925f05cd6d1f23663ab9df64307b3d2e
train_28782
2026-01-01T00:00:00
Tool calling, sandboxes, and CI integration
design
advanced
Task: design Topic: Tool calling, sandboxes, and CI integration 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. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "Rust", "developer_needs": [ "documentation", "tests_are_truth", "reproducibility", "tooling" ], "moe_experts": [ "evaluation_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
8b4c57d1d5703614f4cec356c8b3ccd48c73dcb2
train_28783
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: 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
[]
{ "target_language": "Bash", "developer_needs": [ "auditability", "reproducibility", "tooling", "governance" ], "moe_experts": [ "evaluation_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
6ca9924550791871bffc916554ad54e4a2633fb1
train_28784
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: 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. 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": [ "reproducibility", "repo_scale_reasoning", "tooling", "documentation" ], "moe_experts": [ "security_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
d33d5af8c4f58d571cee69bbabdd0c2df2f90ad6
train_28785
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: 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. Compare: capability, cost, latency, reliability
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Java", "developer_needs": [ "cost_latency_tradeoffs", "auditability", "ci_integration", "tooling" ], "moe_experts": [ "data_curation_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
63b42f02d5f739ea7b2138b6ae154ce78b6b8a7c
train_28786
2026-01-01T00:00:00
Governance, provenance, and licensing for code data
review
expert
Task: review Topic: Governance, provenance, and licensing for code data 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. Review: correctness, security, performance, governance
[]
{ "target_language": "TypeScript", "developer_needs": [ "auditability", "reproducibility", "security_gates", "evaluation_metrics" ], "moe_experts": [ "coding_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
47fb9d3a60215deaee9df411f19ed0abcebc1463
train_28787
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: 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": [ "tooling", "governance", "repo_scale_reasoning", "security_gates" ], "moe_experts": [ "performance_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
ad981a4919ebe1c9e9cf20d96021f979c4a20464
train_28788
2026-01-01T00:00:00
Dataset curation pipelines (filter, dedupe, quality)
compare
expert
Task: compare Topic: Dataset curation pipelines (filter, dedupe, quality) Difficulty: expert Target language: Python Context: Offline/local deployment with limited compute. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Compare: capability, cost, latency, reliability
[]
{ "target_language": "Python", "developer_needs": [ "tests_are_truth", "reproducibility", "security_gates", "repo_scale_reasoning" ], "moe_experts": [ "governance_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
77d686e2b208c7f3289d2b734fc5bd81f1fe0d44
train_28789
2026-01-01T00:00:00
Latency, cost, and reliability optimization
review
expert
Task: review Topic: Latency, cost, and reliability optimization 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. Review: correctness, security, performance, governance
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Bash", "developer_needs": [ "tests_are_truth", "evaluation_metrics", "tooling", "security_gates" ], "moe_experts": [ "governance_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
5e8c0772a9436d01ce445490e1675a82d1d14dfa
train_28790
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: 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. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "Bash", "developer_needs": [ "cost_latency_tradeoffs", "tooling", "reproducibility", "governance" ], "moe_experts": [ "data_curation_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
8d2e203c10288c2992cbc29de070acfaef77e0d1
train_28791
2026-01-01T00:00:00
Agentic coding systems (plan→edit→test→reflect)
explain
intermediate
Task: explain Topic: Agentic coding systems (plan→edit→test→reflect) 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. Design with risks, metrics, acceptance criteria
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Bash", "developer_needs": [ "repo_scale_reasoning", "cost_latency_tradeoffs", "tests_are_truth", "security_gates" ], "moe_experts": [ "governance_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
0ac06a0efa45f1c9f0f397c80c670a92d26adc35
train_28792
2026-01-01T00:00:00
SWE-bench style real-repo evaluation
review
advanced
Task: review Topic: SWE-bench style real-repo evaluation 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. Review: correctness, security, performance, governance
[]
{ "target_language": "TypeScript", "developer_needs": [ "tests_are_truth", "auditability", "ci_integration", "reproducibility" ], "moe_experts": [ "evaluation_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
34ac40b0bb9dd99dede230143f196566b7a61b21
train_28793
2026-01-01T00:00:00
Reasoning-first coding models and tunable deliberation
compare
expert
Task: compare Topic: Reasoning-first coding models and tunable deliberation Difficulty: expert Target language: 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. 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": [ "auditability", "tests_are_truth", "repo_scale_reasoning", "evaluation_metrics" ], "moe_experts": [ "performance_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
e12617bbe578b22cea279772afbf680d2fc5b14d
train_28794
2026-01-01T00:00:00
Self-improving agents and feedback loops
data_pipeline
intermediate
Task: data_pipeline Topic: Self-improving agents and feedback loops Difficulty: intermediate Target language: 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": [ "cost_latency_tradeoffs", "repo_scale_reasoning", "ci_integration", "tooling" ], "moe_experts": [ "governance_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
88b785d3ea42f4f2098cad00201321b5092f43e7
train_28795
2026-01-01T00:00:00
Mixture-of-Experts (MoE) for code
design
intermediate
Task: design 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. 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": [ "evaluation_metrics", "ci_integration", "auditability", "repo_scale_reasoning" ], "moe_experts": [ "evaluation_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
9a8b8818f469a8722c14aaa678bb7534d4b9f79e
train_28796
2026-01-01T00:00:00
Secure code generation and policy gates
explain
intermediate
Task: explain Topic: Secure code generation and policy gates Difficulty: intermediate Target language: Bash Context: Offline/local deployment with limited compute. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "Bash", "developer_needs": [ "governance", "security_gates", "reproducibility", "evaluation_metrics" ], "moe_experts": [ "data_curation_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
82178c6956c1346473fc8646dfff647c484eed8c
train_28797
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: 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": [ "cost_latency_tradeoffs", "tooling", "security_gates", "auditability" ], "moe_experts": [ "coding_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
75c812bb4fc6222d419987550d1fb07711ddbe3a
train_28798
2026-01-01T00:00:00
Mixture-of-Experts (MoE) for code
failure_analysis
expert
Task: failure_analysis Topic: Mixture-of-Experts (MoE) for code 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": [ "tests_are_truth", "governance", "security_gates", "evaluation_metrics" ], "moe_experts": [ "coding_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
afe91da01786c5b5e462e852af57be94ecae79a6
train_28799
2026-01-01T00:00:00
Latency, cost, and reliability optimization
explain
expert
Task: explain Topic: Latency, cost, and reliability optimization Difficulty: expert Target language: Java Context: Offline/local deployment with limited compute. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Java", "developer_needs": [ "auditability", "evaluation_metrics", "governance", "tests_are_truth" ], "moe_experts": [ "coding_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
8b33983fb09f205a8387c24be9d26463359405ac