id
stringlengths
11
11
created
timestamp[s]date
2026-01-01 00:00:00
2026-01-01 00:00:00
topic
stringclasses
14 values
task_type
stringclasses
10 values
difficulty
stringclasses
3 values
instruction
stringlengths
189
248
input
stringclasses
1 value
output
stringclasses
9 values
reasoning_steps
listlengths
0
5
metadata
dict
hash
stringlengths
40
40
train_09400
2026-01-01T00:00:00
Latency, cost, and reliability optimization
patch_diff
advanced
Task: patch_diff Topic: Latency, cost, and reliability optimization Difficulty: advanced Target language: SQL Context: Regulated environment requiring audit trails. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Patch (diff-style): ```diff - if x == 0: - return 1/x + if x == 0: + raise ValueError('division by zero') ``` Acceptance: - Tests pass - No new regressions
[]
{ "target_language": "SQL", "developer_needs": [ "documentation", "security_gates", "ci_integration", "evaluation_metrics" ], "moe_experts": [ "evaluation_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
271a063f07b36e06f1871800ab22090c12ec4ee5
train_09401
2026-01-01T00:00:00
Code-specialized model families and sizing tradeoffs
review
advanced
Task: review Topic: Code-specialized model families and sizing tradeoffs Difficulty: advanced Target language: Python Context: Large monorepo with flaky tests and strict CI. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Review: correctness, security, performance, governance
[]
{ "target_language": "Python", "developer_needs": [ "cost_latency_tradeoffs", "evaluation_metrics", "reproducibility", "tooling" ], "moe_experts": [ "agentic_systems_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
3c4d673780ac9349498c5848f88056ba700a73c1
train_09402
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: JavaScript Context: Offline/local deployment with limited compute. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Loop: Plan → Edit → Test → Reflect → Human gate
[]
{ "target_language": "JavaScript", "developer_needs": [ "security_gates", "cost_latency_tradeoffs", "tooling", "ci_integration" ], "moe_experts": [ "agentic_systems_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
1ddc363e4162e93704dc8e08d3aa8a6869cfe7f1
train_09403
2026-01-01T00:00:00
Reasoning-first coding models and tunable deliberation
patch_diff
expert
Task: patch_diff Topic: Reasoning-first coding models and tunable deliberation Difficulty: expert Target language: 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
[]
{ "target_language": "Bash", "developer_needs": [ "cost_latency_tradeoffs", "reproducibility", "governance", "auditability" ], "moe_experts": [ "governance_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
2e3e71f24b5d30cc9cc704855c9e90ced253569f
train_09404
2026-01-01T00:00:00
SWE-bench style real-repo evaluation
data_pipeline
intermediate
Task: data_pipeline Topic: SWE-bench style real-repo evaluation 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
[]
{ "target_language": "Java", "developer_needs": [ "tooling", "auditability", "documentation", "security_gates" ], "moe_experts": [ "evaluation_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
c16f9d2e15d634cd698d9c41ea7a50ad8a92e190
train_09405
2026-01-01T00:00:00
Self-improving agents and feedback loops
design
expert
Task: design Topic: Self-improving agents and feedback loops Difficulty: expert Target language: C# Context: Regulated environment requiring audit trails. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "C#", "developer_needs": [ "tests_are_truth", "security_gates", "governance", "reproducibility" ], "moe_experts": [ "data_curation_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
6622daca6567d2a3dd54ac54ae56000f25334493
train_09406
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: C# Context: Offline/local deployment with limited compute. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Loop: Plan → Edit → Test → Reflect → Human gate
[]
{ "target_language": "C#", "developer_needs": [ "auditability", "repo_scale_reasoning", "governance", "evaluation_metrics" ], "moe_experts": [ "data_curation_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
d46d09d96663053e2972a2d97b91ac160c1e189c
train_09407
2026-01-01T00:00:00
Extended context and repo-scale understanding
compare
expert
Task: compare Topic: Extended context and repo-scale understanding Difficulty: expert Target language: Python Context: Regulated environment requiring audit trails. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. 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": [ "repo_scale_reasoning", "evaluation_metrics", "auditability", "documentation" ], "moe_experts": [ "performance_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
4932a49c7a45c8bf72d90ae171d6aa39673b68df
train_09408
2026-01-01T00:00:00
SWE-bench style real-repo evaluation
code
intermediate
Task: code Topic: SWE-bench style real-repo evaluation Difficulty: intermediate Target language: TypeScript Context: High-traffic service with latency SLOs. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "TypeScript", "developer_needs": [ "tooling", "security_gates", "repo_scale_reasoning", "evaluation_metrics" ], "moe_experts": [ "performance_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
38092352a439926d0dfc45355cb5e7944a3df2c8
train_09409
2026-01-01T00:00:00
Latency, cost, and reliability optimization
agent_loop
expert
Task: agent_loop Topic: Latency, cost, and reliability optimization 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. 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": [ "reproducibility", "documentation", "tests_are_truth", "evaluation_metrics" ], "moe_experts": [ "data_curation_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
89c072a67e24b89dd9237a6d1669891105299965
train_09410
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: 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": [ "tests_are_truth", "reproducibility", "governance", "auditability" ], "moe_experts": [ "data_curation_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
ca093fc201fe2e1d59f03b5175ac535e24dcfcd8
train_09411
2026-01-01T00:00:00
Tool calling, sandboxes, and CI integration
design
expert
Task: design Topic: Tool calling, sandboxes, and CI integration 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": [ "tooling", "reproducibility", "documentation", "auditability" ], "moe_experts": [ "evaluation_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
aece5cd83cbe25c14c74fd7995ee22522f2fad06
train_09412
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: 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. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "Java", "developer_needs": [ "security_gates", "evaluation_metrics", "tooling", "governance" ], "moe_experts": [ "evaluation_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
f8a3f89c15751998dfc8c5dd3a4b053002f70fd3
train_09413
2026-01-01T00:00:00
Multimodal dev workflows (docs, diagrams, traces)
compare
intermediate
Task: compare Topic: Multimodal dev workflows (docs, diagrams, traces) Difficulty: intermediate Target language: Rust Context: Large monorepo with flaky tests and strict CI. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Compare: capability, cost, latency, reliability
[]
{ "target_language": "Rust", "developer_needs": [ "cost_latency_tradeoffs", "tests_are_truth", "security_gates", "repo_scale_reasoning" ], "moe_experts": [ "data_curation_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
542bd5144fbfb125b86d3123a4951b3715b6ab79
train_09414
2026-01-01T00:00:00
Secure code generation and policy gates
eval
advanced
Task: eval Topic: Secure code generation and policy gates Difficulty: advanced Target language: C# Context: 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": "C#", "developer_needs": [ "tests_are_truth", "repo_scale_reasoning", "documentation", "reproducibility" ], "moe_experts": [ "evaluation_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
196e961a9294cf665d391accd06b23b435c32b01
train_09415
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: 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": [ "reproducibility", "ci_integration", "security_gates", "tooling" ], "moe_experts": [ "performance_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
b45881ae4e64b63e13b86c2cb75b74e45f1795c7
train_09416
2026-01-01T00:00:00
Agentic coding systems (plan→edit→test→reflect)
review
advanced
Task: review Topic: Agentic coding systems (plan→edit→test→reflect) Difficulty: advanced Target language: Python Context: Regulated environment requiring audit trails. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Review: correctness, security, performance, governance
[]
{ "target_language": "Python", "developer_needs": [ "evaluation_metrics", "tests_are_truth", "governance", "cost_latency_tradeoffs" ], "moe_experts": [ "evaluation_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
3773e91c40cf9fc8d61d240f72e48bde73e759b4
train_09417
2026-01-01T00:00:00
Governance, provenance, and licensing for code data
review
advanced
Task: review Topic: Governance, provenance, and licensing for code data Difficulty: advanced Target language: 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. Review: correctness, security, performance, governance
[]
{ "target_language": "JavaScript", "developer_needs": [ "reproducibility", "cost_latency_tradeoffs", "governance", "ci_integration" ], "moe_experts": [ "security_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
75b728fb9eb9418cb096420b11dca5feed9b0d1a
train_09418
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: 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": [ "documentation", "evaluation_metrics", "security_gates", "ci_integration" ], "moe_experts": [ "performance_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
624aec2566fe43938c5953a7768401ea74793858
train_09419
2026-01-01T00:00:00
Dataset curation pipelines (filter, dedupe, quality)
failure_analysis
intermediate
Task: failure_analysis Topic: Dataset curation pipelines (filter, dedupe, quality) 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. Failure: - Initial patch broke edge case Reflection: - Missing zero-input guard Correction: - Add explicit validation + test
[]
{ "target_language": "TypeScript", "developer_needs": [ "security_gates", "ci_integration", "documentation", "tests_are_truth" ], "moe_experts": [ "data_curation_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
df84a920525517e34858a39906ee28f8004216b5
train_09420
2026-01-01T00:00:00
Multimodal dev workflows (docs, diagrams, traces)
data_pipeline
advanced
Task: data_pipeline Topic: Multimodal dev workflows (docs, diagrams, traces) Difficulty: advanced Target language: 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. Pipeline: Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "TypeScript", "developer_needs": [ "ci_integration", "cost_latency_tradeoffs", "repo_scale_reasoning", "governance" ], "moe_experts": [ "data_curation_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
40b8349662050a3cd7953f6f88b34d1a2d6c0355
train_09421
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: 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
[ "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", "repo_scale_reasoning", "ci_integration", "evaluation_metrics" ], "moe_experts": [ "evaluation_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
83bca8180894f7bacebbccf2ef7acbadef4d974b
train_09422
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: Large monorepo with flaky tests and strict CI. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Review: correctness, security, performance, governance
[]
{ "target_language": "SQL", "developer_needs": [ "reproducibility", "governance", "evaluation_metrics", "cost_latency_tradeoffs" ], "moe_experts": [ "evaluation_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
01b8a29eefd1a1a97138ce94235284e300c53509
train_09423
2026-01-01T00:00:00
Governance, provenance, and licensing for code data
code
intermediate
Task: code Topic: Governance, provenance, and licensing for code data Difficulty: intermediate Target language: SQL Context: High-traffic service with latency SLOs. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "SQL", "developer_needs": [ "reproducibility", "security_gates", "auditability", "ci_integration" ], "moe_experts": [ "data_curation_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
1e07e2653ccc541c124be7b2ceec15fe0ed8e8af
train_09424
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: 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": [ "reproducibility", "security_gates", "repo_scale_reasoning", "documentation" ], "moe_experts": [ "coding_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
b2d66175c49d98f2491e806b365fd77ff0662b24
train_09425
2026-01-01T00:00:00
Reasoning-first coding models and tunable deliberation
review
advanced
Task: review Topic: Reasoning-first coding models and tunable deliberation Difficulty: advanced Target language: Rust Context: Offline/local deployment with limited compute. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. 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", "tests_are_truth", "reproducibility", "tooling" ], "moe_experts": [ "security_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
cbaa0b90478f68b80b527e0b60a39e8a0b34fb46
train_09426
2026-01-01T00:00:00
Multimodal dev workflows (docs, diagrams, traces)
design
expert
Task: design Topic: Multimodal dev workflows (docs, diagrams, traces) Difficulty: expert Target language: TypeScript Context: Regulated environment requiring audit trails. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "TypeScript", "developer_needs": [ "tooling", "auditability", "documentation", "reproducibility" ], "moe_experts": [ "evaluation_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
c4c2363e8606165dcf50c10b1c701ae8d6ab2eed
train_09427
2026-01-01T00:00:00
Agentic coding systems (plan→edit→test→reflect)
code
expert
Task: code Topic: Agentic coding systems (plan→edit→test→reflect) Difficulty: expert Target language: 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": [ "ci_integration", "cost_latency_tradeoffs", "security_gates", "auditability" ], "moe_experts": [ "coding_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
6fc126fff15285ec48d349477afce6e1b832e167
train_09428
2026-01-01T00:00:00
Tool calling, sandboxes, and CI integration
compare
expert
Task: compare Topic: Tool calling, sandboxes, and CI integration Difficulty: expert Target language: Go Context: Regulated environment requiring audit trails. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Compare: capability, cost, latency, reliability
[]
{ "target_language": "Go", "developer_needs": [ "cost_latency_tradeoffs", "repo_scale_reasoning", "ci_integration", "reproducibility" ], "moe_experts": [ "security_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
d6015ae33fa8444b36a75079fcdb73735ad8bc51
train_09429
2026-01-01T00:00:00
SWE-bench style real-repo evaluation
eval
intermediate
Task: eval Topic: SWE-bench style real-repo evaluation 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. Eval: pass@k, time-to-green, regressions, diff size
[]
{ "target_language": "SQL", "developer_needs": [ "cost_latency_tradeoffs", "documentation", "tooling", "reproducibility" ], "moe_experts": [ "security_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
b63e3176505ca874536b1d17c380520b4403d20e
train_09430
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: 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": "Python", "developer_needs": [ "governance", "cost_latency_tradeoffs", "tooling", "security_gates" ], "moe_experts": [ "governance_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
339ecdbc2ca38fdc9c300b8ce8dbb8fe7feac0c9
train_09431
2026-01-01T00:00:00
Tool calling, sandboxes, and CI integration
compare
expert
Task: compare Topic: Tool calling, sandboxes, and CI integration Difficulty: expert Target language: Java Context: High-traffic service with latency SLOs. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Compare: capability, cost, latency, reliability
[]
{ "target_language": "Java", "developer_needs": [ "reproducibility", "governance", "tests_are_truth", "tooling" ], "moe_experts": [ "governance_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
938a628191983e506e7bd075c5ca7b78dcdb11f4
train_09432
2026-01-01T00:00:00
Self-improving agents and feedback loops
review
advanced
Task: review Topic: Self-improving agents and feedback loops Difficulty: advanced Target language: Python Context: Offline/local deployment with limited compute. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Review: correctness, security, performance, governance
[]
{ "target_language": "Python", "developer_needs": [ "security_gates", "documentation", "repo_scale_reasoning", "tests_are_truth" ], "moe_experts": [ "data_curation_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
1fbcc2b88d349fcc12f298c9b1717988d74502e3
train_09433
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: Go Context: High-traffic service with latency SLOs. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Eval: pass@k, time-to-green, regressions, diff size
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Go", "developer_needs": [ "tooling", "cost_latency_tradeoffs", "governance", "repo_scale_reasoning" ], "moe_experts": [ "evaluation_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
4568a6a944678b12a5cf11e1d270ab29b1edeaaa
train_09434
2026-01-01T00:00:00
Latency, cost, and reliability optimization
design
advanced
Task: design Topic: Latency, cost, and reliability optimization Difficulty: advanced Target language: Rust Context: Research team validating claims against real repos. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "Rust", "developer_needs": [ "tests_are_truth", "security_gates", "evaluation_metrics", "governance" ], "moe_experts": [ "governance_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
53247b8a7fff1b6c0790f2e76d419f7333cceeb0
train_09435
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: 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. 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": "C#", "developer_needs": [ "repo_scale_reasoning", "documentation", "reproducibility", "auditability" ], "moe_experts": [ "evaluation_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
3b773a20c817c41cb81f3c5fdb1004cc0b7cc8f9
train_09436
2026-01-01T00:00:00
Multimodal dev workflows (docs, diagrams, traces)
compare
advanced
Task: compare Topic: Multimodal dev workflows (docs, diagrams, traces) Difficulty: advanced Target language: Java Context: High-traffic service with latency SLOs. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Compare: capability, cost, latency, reliability
[]
{ "target_language": "Java", "developer_needs": [ "repo_scale_reasoning", "cost_latency_tradeoffs", "tests_are_truth", "security_gates" ], "moe_experts": [ "performance_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
0a04dbc0bb74e8e9f54a0206361c00b1d46a4f65
train_09437
2026-01-01T00:00:00
Governance, provenance, and licensing for code data
code
intermediate
Task: code Topic: Governance, provenance, and licensing for code data Difficulty: intermediate Target language: TypeScript Context: Research team validating claims against real repos. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "TypeScript", "developer_needs": [ "reproducibility", "security_gates", "tooling", "evaluation_metrics" ], "moe_experts": [ "evaluation_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
10a9015957c2f3d8ffa71f7806987016c2e4f482
train_09438
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: 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": [ "ci_integration", "reproducibility", "tests_are_truth", "auditability" ], "moe_experts": [ "security_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
4e7e1104c6c025c026ae43c0eda2634b625641a2
train_09439
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: 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. 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": [ "reproducibility", "governance", "security_gates", "tooling" ], "moe_experts": [ "agentic_systems_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
3b732ada121f25c04ec7c3f7cf3d336159823a26
train_09440
2026-01-01T00:00:00
Multimodal dev workflows (docs, diagrams, traces)
failure_analysis
expert
Task: failure_analysis Topic: Multimodal dev workflows (docs, diagrams, traces) 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
[]
{ "target_language": "JavaScript", "developer_needs": [ "auditability", "evaluation_metrics", "tests_are_truth", "documentation" ], "moe_experts": [ "agentic_systems_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
535b1f435d1b2109366c548bcdb295feca6dda95
train_09441
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: C# Context: Research team validating claims against real repos. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Pipeline: Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
[]
{ "target_language": "C#", "developer_needs": [ "evaluation_metrics", "auditability", "tooling", "tests_are_truth" ], "moe_experts": [ "data_curation_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
6180aebc513b02935d45e333da0f508a12f646f2
train_09442
2026-01-01T00:00:00
Governance, provenance, and licensing for code data
design
advanced
Task: design Topic: Governance, provenance, and licensing for code data Difficulty: advanced Target language: 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": [ "cost_latency_tradeoffs", "tests_are_truth", "security_gates", "ci_integration" ], "moe_experts": [ "evaluation_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
48e91fd54557a76e782766945ce6400965e5f833
train_09443
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: TypeScript Context: Regulated environment requiring audit trails. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Pipeline: Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
[]
{ "target_language": "TypeScript", "developer_needs": [ "tooling", "governance", "evaluation_metrics", "reproducibility" ], "moe_experts": [ "evaluation_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
8a9f38f0c31521bcd382f88f57b834fc6e2f9e92
train_09444
2026-01-01T00:00:00
Extended context and repo-scale understanding
explain
intermediate
Task: explain Topic: Extended context and repo-scale understanding Difficulty: intermediate Target language: Python Context: Large monorepo with flaky tests and strict CI. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Python", "developer_needs": [ "tooling", "tests_are_truth", "governance", "ci_integration" ], "moe_experts": [ "data_curation_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
9b8727937fc2f7abb8533d971ba41ae703dd20f8
train_09445
2026-01-01T00:00:00
Latency, cost, and reliability optimization
agent_loop
expert
Task: agent_loop Topic: Latency, cost, and reliability optimization 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. Loop: Plan → Edit → Test → Reflect → Human gate
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Bash", "developer_needs": [ "tooling", "repo_scale_reasoning", "ci_integration", "cost_latency_tradeoffs" ], "moe_experts": [ "evaluation_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
0a1337ac8dc0f5b1fd2e129251c49b001f5166d7
train_09446
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: 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. Eval: pass@k, time-to-green, regressions, diff size
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Rust", "developer_needs": [ "ci_integration", "documentation", "security_gates", "reproducibility" ], "moe_experts": [ "agentic_systems_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
f4830c28ad83d0e531b80e84c65db402503101c7
train_09447
2026-01-01T00:00:00
Self-improving agents and feedback loops
data_pipeline
advanced
Task: data_pipeline Topic: Self-improving agents and feedback loops Difficulty: advanced Target language: JavaScript Context: High-traffic service with latency SLOs. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Pipeline: Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "JavaScript", "developer_needs": [ "repo_scale_reasoning", "governance", "security_gates", "reproducibility" ], "moe_experts": [ "agentic_systems_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
61d9a6a7f69eaf30ba6b1afd5145bfea6f1d4e8f
train_09448
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: 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": [ "ci_integration", "reproducibility", "auditability", "security_gates" ], "moe_experts": [ "coding_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
4f0d27cfd96ef7b356d5aeaf8e45a1d7d3933a41
train_09449
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: JavaScript Context: Offline/local deployment with limited compute. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "JavaScript", "developer_needs": [ "reproducibility", "security_gates", "governance", "evaluation_metrics" ], "moe_experts": [ "security_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
e93b099a4c244f1d31e8a65c0ce5045d4bb117b6
train_09450
2026-01-01T00:00:00
Multimodal dev workflows (docs, diagrams, traces)
data_pipeline
advanced
Task: data_pipeline Topic: Multimodal dev workflows (docs, diagrams, traces) Difficulty: advanced Target language: Rust Context: Research team validating claims against real repos. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Pipeline: Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
[]
{ "target_language": "Rust", "developer_needs": [ "security_gates", "tooling", "ci_integration", "evaluation_metrics" ], "moe_experts": [ "agentic_systems_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
e0b12d2e86d43629ee236be116f16f0afe34aa4a
train_09451
2026-01-01T00:00:00
SWE-bench style real-repo evaluation
eval
advanced
Task: eval Topic: SWE-bench style real-repo evaluation Difficulty: advanced Target language: Bash Context: Research team validating claims against real repos. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. 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": [ "tests_are_truth", "documentation", "repo_scale_reasoning", "evaluation_metrics" ], "moe_experts": [ "performance_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
83f60acd9fb32fc158de1f68ad70250f69ea2f8c
train_09452
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: 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. Pipeline: Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Python", "developer_needs": [ "evaluation_metrics", "auditability", "tooling", "cost_latency_tradeoffs" ], "moe_experts": [ "coding_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
c6d89f99e561ec5bd1d7462003f09ddd67045ad8
train_09453
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: SQL Context: Large monorepo with flaky tests and strict CI. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "SQL", "developer_needs": [ "security_gates", "ci_integration", "reproducibility", "cost_latency_tradeoffs" ], "moe_experts": [ "data_curation_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
253a05b716a12460724a5f0d69076cfc7c62989d
train_09454
2026-01-01T00:00:00
Latency, cost, and reliability optimization
design
advanced
Task: design Topic: Latency, cost, and reliability optimization Difficulty: advanced Target language: C# Context: 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": [ "ci_integration", "governance", "reproducibility", "tooling" ], "moe_experts": [ "evaluation_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
4d67de2d229fccfcde35a90cbd2a2c2d0ebabf0d
train_09455
2026-01-01T00:00:00
Governance, provenance, and licensing for code data
data_pipeline
intermediate
Task: data_pipeline Topic: Governance, provenance, and licensing for code data Difficulty: intermediate Target language: TypeScript Context: 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": "TypeScript", "developer_needs": [ "auditability", "tooling", "documentation", "cost_latency_tradeoffs" ], "moe_experts": [ "governance_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
c366165cf313eb3ec64c7908151fb0895bd57275
train_09456
2026-01-01T00:00:00
Secure code generation and policy gates
patch_diff
expert
Task: patch_diff Topic: Secure code generation and policy gates Difficulty: expert Target language: JavaScript Context: Offline/local deployment with limited compute. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Patch (diff-style): ```diff - if x == 0: - return 1/x + if x == 0: + raise ValueError('division by zero') ``` Acceptance: - Tests pass - No new regressions
[]
{ "target_language": "JavaScript", "developer_needs": [ "governance", "evaluation_metrics", "reproducibility", "ci_integration" ], "moe_experts": [ "agentic_systems_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
be22701009bca377bf00fb01a84b56f8d02a88f0
train_09457
2026-01-01T00:00:00
SWE-bench style real-repo evaluation
explain
expert
Task: explain Topic: SWE-bench style real-repo evaluation Difficulty: expert Target language: 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": [ "evaluation_metrics", "cost_latency_tradeoffs", "reproducibility", "repo_scale_reasoning" ], "moe_experts": [ "data_curation_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
3a628556eded50f88c9d445f5ab70d7e239143e3
train_09458
2026-01-01T00:00:00
Code-specialized model families and sizing tradeoffs
review
expert
Task: review Topic: Code-specialized model families and sizing tradeoffs Difficulty: expert Target language: 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", "repo_scale_reasoning", "documentation" ], "moe_experts": [ "agentic_systems_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
61ccad6127a8eace58857f3d29fcc8237a1fc2b8
train_09459
2026-01-01T00:00:00
Tool calling, sandboxes, and CI integration
code
intermediate
Task: code Topic: Tool calling, sandboxes, and CI integration Difficulty: intermediate Target language: 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": [ "evaluation_metrics", "tests_are_truth", "ci_integration", "reproducibility" ], "moe_experts": [ "data_curation_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
da14a12e7b4d9c53335c1457c3806c8e1614130c
train_09460
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: C# Context: High-traffic service with latency SLOs. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Compare: capability, cost, latency, reliability
[]
{ "target_language": "C#", "developer_needs": [ "reproducibility", "governance", "evaluation_metrics", "tooling" ], "moe_experts": [ "performance_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
0541f5b24583090bec8a237a248a1ddf59ea4399
train_09461
2026-01-01T00:00:00
Extended context and repo-scale understanding
review
expert
Task: review Topic: Extended context and repo-scale understanding Difficulty: expert Target language: C# Context: Large monorepo with flaky tests and strict CI. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Review: correctness, security, performance, governance
[]
{ "target_language": "C#", "developer_needs": [ "reproducibility", "repo_scale_reasoning", "evaluation_metrics", "documentation" ], "moe_experts": [ "agentic_systems_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
68f630f8f6cb042281133e33f9a2774fcc9e5c12
train_09462
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: 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": [ "repo_scale_reasoning", "tooling", "cost_latency_tradeoffs", "documentation" ], "moe_experts": [ "performance_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
d1025f47f5057afddaf850ecebd8b101b813b362
train_09463
2026-01-01T00:00:00
Reasoning-first coding models and tunable deliberation
eval
intermediate
Task: eval Topic: Reasoning-first coding models and tunable deliberation Difficulty: intermediate Target language: JavaScript Context: Research team validating claims against real repos. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Eval: pass@k, time-to-green, regressions, diff size
[]
{ "target_language": "JavaScript", "developer_needs": [ "repo_scale_reasoning", "cost_latency_tradeoffs", "tooling", "governance" ], "moe_experts": [ "performance_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
896779aa8bc0725402b1ef746f8c4078313dce5f
train_09464
2026-01-01T00:00:00
Latency, cost, and reliability optimization
design
advanced
Task: design Topic: Latency, cost, and reliability optimization Difficulty: advanced Target language: Python Context: Offline/local deployment with limited compute. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "Python", "developer_needs": [ "cost_latency_tradeoffs", "repo_scale_reasoning", "ci_integration", "documentation" ], "moe_experts": [ "agentic_systems_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
cac5ebd5d0795e1e559bba0fac54c744da1d1af4
train_09465
2026-01-01T00:00:00
Code-specialized model families and sizing tradeoffs
eval
intermediate
Task: eval Topic: Code-specialized model families and sizing tradeoffs Difficulty: intermediate Target language: Python Context: High-traffic service with latency SLOs. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Eval: pass@k, time-to-green, regressions, diff size
[]
{ "target_language": "Python", "developer_needs": [ "evaluation_metrics", "security_gates", "repo_scale_reasoning", "tests_are_truth" ], "moe_experts": [ "security_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
ad636e77bd282ccc8a233973407450ec46b2e406
train_09466
2026-01-01T00:00:00
Agentic coding systems (plan→edit→test→reflect)
review
intermediate
Task: review Topic: Agentic coding systems (plan→edit→test→reflect) 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. Review: correctness, security, performance, governance
[]
{ "target_language": "TypeScript", "developer_needs": [ "governance", "tooling", "cost_latency_tradeoffs", "documentation" ], "moe_experts": [ "coding_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
2be4d25d34abbcc007e124920f92ba9f5fc910ab
train_09467
2026-01-01T00:00:00
Latency, cost, and reliability optimization
agent_loop
expert
Task: agent_loop Topic: Latency, cost, and reliability optimization 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. 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": [ "repo_scale_reasoning", "auditability", "tooling", "reproducibility" ], "moe_experts": [ "data_curation_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
357289dedfa6831c79c6292d23e8bae32d210085
train_09468
2026-01-01T00:00:00
Multimodal dev workflows (docs, diagrams, traces)
code
advanced
Task: code Topic: Multimodal dev workflows (docs, diagrams, traces) 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
[]
{ "target_language": "TypeScript", "developer_needs": [ "ci_integration", "evaluation_metrics", "documentation", "cost_latency_tradeoffs" ], "moe_experts": [ "performance_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
e4e8b8e8ae74c7d471121e3f4a9fc8c00fed8fba
train_09469
2026-01-01T00:00:00
Latency, cost, and reliability optimization
eval
advanced
Task: eval Topic: Latency, cost, and reliability optimization Difficulty: advanced Target language: Bash Context: Offline/local deployment with limited compute. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Eval: pass@k, time-to-green, regressions, diff size
[ "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", "tooling", "documentation", "repo_scale_reasoning" ], "moe_experts": [ "coding_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
af2b6e38d7ad66803bbafa7d47aed277a272a78a
train_09470
2026-01-01T00:00:00
Reasoning-first coding models and tunable deliberation
compare
intermediate
Task: compare Topic: Reasoning-first coding models and tunable deliberation Difficulty: intermediate Target language: Python Context: Offline/local deployment with limited compute. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Compare: capability, cost, latency, reliability
[]
{ "target_language": "Python", "developer_needs": [ "evaluation_metrics", "auditability", "repo_scale_reasoning", "security_gates" ], "moe_experts": [ "performance_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
84dc69c88b1b0d29131081ba7559b36fee02e3ef
train_09471
2026-01-01T00:00:00
Dataset curation pipelines (filter, dedupe, quality)
data_pipeline
expert
Task: data_pipeline Topic: Dataset curation pipelines (filter, dedupe, quality) 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. Pipeline: Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
[]
{ "target_language": "TypeScript", "developer_needs": [ "auditability", "tests_are_truth", "repo_scale_reasoning", "security_gates" ], "moe_experts": [ "data_curation_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
62b6a5e234c205b287efbd58a80390f4373d7bf9
train_09472
2026-01-01T00:00:00
Code-specialized model families and sizing tradeoffs
explain
expert
Task: explain Topic: Code-specialized model families and sizing tradeoffs 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
[]
{ "target_language": "Python", "developer_needs": [ "cost_latency_tradeoffs", "evaluation_metrics", "documentation", "reproducibility" ], "moe_experts": [ "evaluation_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
a20997bc106c7c38d6f00ced1a2986852d303ade
train_09473
2026-01-01T00:00:00
Multimodal dev workflows (docs, diagrams, traces)
eval
advanced
Task: eval Topic: Multimodal dev workflows (docs, diagrams, traces) 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": [ "reproducibility", "governance", "auditability", "ci_integration" ], "moe_experts": [ "governance_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
f5bac0c568f4b9bbecb350a7cb8af6ed32c424b2
train_09474
2026-01-01T00:00:00
Agentic coding systems (plan→edit→test→reflect)
review
expert
Task: review Topic: Agentic coding systems (plan→edit→test→reflect) Difficulty: expert Target language: 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. Review: correctness, security, performance, governance
[]
{ "target_language": "Bash", "developer_needs": [ "governance", "ci_integration", "cost_latency_tradeoffs", "documentation" ], "moe_experts": [ "performance_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
d6bef0c3acf737f6d34e63e8da19230db31fd140
train_09475
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: Rust Context: Research team validating claims against real repos. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Rust", "developer_needs": [ "repo_scale_reasoning", "auditability", "documentation", "tooling" ], "moe_experts": [ "data_curation_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
0578bcdbc7a030635cb558447e7a051f01f269b8
train_09476
2026-01-01T00:00:00
Reasoning-first coding models and tunable deliberation
failure_analysis
intermediate
Task: failure_analysis Topic: Reasoning-first coding models and tunable deliberation 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. 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": "Java", "developer_needs": [ "ci_integration", "cost_latency_tradeoffs", "auditability", "tests_are_truth" ], "moe_experts": [ "data_curation_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
e8948e54f30c06b7b88d77e33af440b59adc57c2
train_09477
2026-01-01T00:00:00
Tool calling, sandboxes, and CI integration
design
expert
Task: design Topic: Tool calling, sandboxes, and CI integration 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", "documentation", "tests_are_truth", "reproducibility" ], "moe_experts": [ "governance_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
f056bc43efe55d233a65e4aa2b0544bd5c4aec90
train_09478
2026-01-01T00:00:00
Reasoning-first coding models and tunable deliberation
explain
advanced
Task: explain Topic: Reasoning-first coding models and tunable deliberation Difficulty: advanced Target language: C# Context: 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": "C#", "developer_needs": [ "governance", "tooling", "auditability", "ci_integration" ], "moe_experts": [ "governance_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
cc76bfd73d0798278e1b76b4f593706f6fc64103
train_09479
2026-01-01T00:00:00
Dataset curation pipelines (filter, dedupe, quality)
data_pipeline
advanced
Task: data_pipeline Topic: Dataset curation pipelines (filter, dedupe, quality) Difficulty: advanced Target language: Go Context: High-traffic service with latency SLOs. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Pipeline: Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Go", "developer_needs": [ "governance", "reproducibility", "repo_scale_reasoning", "tests_are_truth" ], "moe_experts": [ "agentic_systems_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
6f239373ce1f5c7ece1bbe8535d0c408954f9265
train_09480
2026-01-01T00:00:00
Extended context and repo-scale understanding
compare
intermediate
Task: compare Topic: Extended context and repo-scale understanding Difficulty: intermediate Target language: 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": [ "cost_latency_tradeoffs", "auditability", "repo_scale_reasoning", "governance" ], "moe_experts": [ "data_curation_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
4206c5102522007c1ea93284dbbbc97524626b16
train_09481
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: Python Context: Large monorepo with flaky tests and strict CI. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Review: correctness, security, performance, governance
[]
{ "target_language": "Python", "developer_needs": [ "security_gates", "ci_integration", "evaluation_metrics", "cost_latency_tradeoffs" ], "moe_experts": [ "evaluation_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
a32d77c89b5b2e532434c3a734672399ade09b6b
train_09482
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: JavaScript Context: High-traffic service with latency SLOs. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Failure: - Initial patch broke edge case Reflection: - Missing zero-input guard Correction: - Add explicit validation + test
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "JavaScript", "developer_needs": [ "cost_latency_tradeoffs", "documentation", "ci_integration", "tooling" ], "moe_experts": [ "performance_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
db4803ffbc6faea6a0712fa0e841c953d88ff731
train_09483
2026-01-01T00:00:00
Self-improving agents and feedback loops
eval
expert
Task: eval Topic: Self-improving agents and feedback loops Difficulty: expert Target language: SQL Context: Research team validating claims against real repos. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Eval: pass@k, time-to-green, regressions, diff size
[]
{ "target_language": "SQL", "developer_needs": [ "documentation", "reproducibility", "cost_latency_tradeoffs", "governance" ], "moe_experts": [ "performance_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
0544610cc00d2c14fee43b7935985133ec9d95e1
train_09484
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: 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
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Bash", "developer_needs": [ "ci_integration", "evaluation_metrics", "governance", "documentation" ], "moe_experts": [ "coding_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
059b678fed635ee528dba9c7e12c718c09554a47
train_09485
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: 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
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "TypeScript", "developer_needs": [ "auditability", "tooling", "tests_are_truth", "ci_integration" ], "moe_experts": [ "security_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
db50ad2a22f650cafe615ef3eafaa2475cd11228
train_09486
2026-01-01T00:00:00
Latency, cost, and reliability optimization
design
advanced
Task: design Topic: Latency, cost, and reliability optimization Difficulty: advanced Target language: TypeScript Context: Regulated environment requiring audit trails. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "TypeScript", "developer_needs": [ "security_gates", "ci_integration", "documentation", "governance" ], "moe_experts": [ "security_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
bfc6f4aa4ba246a63b5206e06a1465f51744a6af
train_09487
2026-01-01T00:00:00
Model merging, distillation, and continued pretraining
patch_diff
expert
Task: patch_diff Topic: Model merging, distillation, and continued pretraining 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. Patch (diff-style): ```diff - if x == 0: - return 1/x + if x == 0: + raise ValueError('division by zero') ``` Acceptance: - Tests pass - No new regressions
[]
{ "target_language": "SQL", "developer_needs": [ "documentation", "ci_integration", "tooling", "evaluation_metrics" ], "moe_experts": [ "data_curation_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
f2b185780732c289f517cb3553fbe11f7aa7f5ca
train_09488
2026-01-01T00:00:00
Model merging, distillation, and continued pretraining
eval
intermediate
Task: eval Topic: Model merging, distillation, and continued pretraining Difficulty: intermediate Target language: Python Context: Offline/local deployment with limited compute. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Eval: pass@k, time-to-green, regressions, diff size
[]
{ "target_language": "Python", "developer_needs": [ "reproducibility", "ci_integration", "evaluation_metrics", "cost_latency_tradeoffs" ], "moe_experts": [ "governance_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
56890cd948a09dfca13a73d69e6077fb4eb9e8b4
train_09489
2026-01-01T00:00:00
Latency, cost, and reliability optimization
code
intermediate
Task: code Topic: Latency, cost, and reliability optimization Difficulty: intermediate Target language: C# Context: High-traffic service with latency SLOs. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "C#", "developer_needs": [ "evaluation_metrics", "documentation", "tests_are_truth", "ci_integration" ], "moe_experts": [ "governance_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
cdc173b23a1b83f706773cfe3a9dfe82d9684ec5
train_09490
2026-01-01T00:00:00
Dataset curation pipelines (filter, dedupe, quality)
patch_diff
advanced
Task: patch_diff Topic: Dataset curation pipelines (filter, dedupe, quality) 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. 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": [ "governance", "tests_are_truth", "evaluation_metrics", "security_gates" ], "moe_experts": [ "data_curation_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
8f26f66928460ea15d250577189cf8cbb5d9258d
train_09491
2026-01-01T00:00:00
SWE-bench style real-repo evaluation
data_pipeline
intermediate
Task: data_pipeline Topic: SWE-bench style real-repo evaluation 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": [ "repo_scale_reasoning", "evaluation_metrics", "cost_latency_tradeoffs", "ci_integration" ], "moe_experts": [ "performance_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
c16f9d2e15d634cd698d9c41ea7a50ad8a92e190
train_09492
2026-01-01T00:00:00
Dataset curation pipelines (filter, dedupe, quality)
explain
intermediate
Task: explain Topic: Dataset curation pipelines (filter, dedupe, quality) Difficulty: intermediate Target language: 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", "repo_scale_reasoning", "ci_integration", "tests_are_truth" ], "moe_experts": [ "governance_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
56bd5ec8d394785fe4413900efeb81309c7a773f
train_09493
2026-01-01T00:00:00
Secure code generation and policy gates
compare
intermediate
Task: compare Topic: Secure code generation and policy gates Difficulty: intermediate Target language: 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": [ "security_gates", "documentation", "auditability", "governance" ], "moe_experts": [ "coding_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
b3f614984ec3bf8b56e1b93c53a5bb433eecbd9c
train_09494
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: 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. 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": [ "reproducibility", "security_gates", "tooling", "repo_scale_reasoning" ], "moe_experts": [ "governance_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
6b464b89e9944f0f157397f195eda20614f07e62
train_09495
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: Java Context: Large monorepo with flaky tests and strict CI. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Loop: Plan → Edit → Test → Reflect → Human gate
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Java", "developer_needs": [ "ci_integration", "reproducibility", "evaluation_metrics", "security_gates" ], "moe_experts": [ "performance_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
13f25c4af3d70a5684820c9403007bf98e03410c
train_09496
2026-01-01T00:00:00
Agentic coding systems (plan→edit→test→reflect)
code
advanced
Task: code Topic: Agentic coding systems (plan→edit→test→reflect) Difficulty: advanced Target language: SQL Context: High-traffic service with latency SLOs. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "SQL", "developer_needs": [ "reproducibility", "cost_latency_tradeoffs", "tooling", "documentation" ], "moe_experts": [ "evaluation_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
22794a233163b37a3c2e71ee822cff585b6971b1
train_09497
2026-01-01T00:00:00
Model merging, distillation, and continued pretraining
review
expert
Task: review Topic: Model merging, distillation, and continued pretraining Difficulty: expert Target language: C# Context: Large monorepo with flaky tests and strict CI. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Review: correctness, security, performance, governance
[]
{ "target_language": "C#", "developer_needs": [ "tooling", "ci_integration", "auditability", "documentation" ], "moe_experts": [ "security_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
47a54125cb70508d4c06b101b72ca66f1ee4a4b3
train_09498
2026-01-01T00:00:00
Self-improving agents and feedback loops
agent_loop
intermediate
Task: agent_loop Topic: Self-improving agents and feedback loops 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. 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", "documentation" ], "moe_experts": [ "data_curation_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
8010fe499f95803b204053552a4e46e51ceace6c
train_09499
2026-01-01T00:00:00
Secure code generation and policy gates
design
advanced
Task: design Topic: Secure code generation and policy gates Difficulty: advanced Target language: 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": [ "ci_integration", "tooling", "cost_latency_tradeoffs", "auditability" ], "moe_experts": [ "security_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
57c38ec0d62d59d82d625c84f9355b7de20f46d8