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train_19000
2026-01-01T00:00:00
Mixture-of-Experts (MoE) for code
review
expert
Task: review Topic: Mixture-of-Experts (MoE) for code Difficulty: expert Target language: 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. Review: correctness, security, performance, governance
[]
{ "target_language": "Go", "developer_needs": [ "cost_latency_tradeoffs", "security_gates", "documentation", "governance" ], "moe_experts": [ "coding_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
39ffb8c98aa2374368f300b1c73d6ee9d6c8bacb
train_19001
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: 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": [ "ci_integration", "auditability", "governance", "tooling" ], "moe_experts": [ "agentic_systems_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
eb4953a7bb1cc6b72a155babc642bfff25b16fdc
train_19002
2026-01-01T00:00:00
Extended context and repo-scale understanding
failure_analysis
intermediate
Task: failure_analysis Topic: Extended context and repo-scale understanding Difficulty: intermediate Target language: 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. 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": [ "ci_integration", "tooling", "repo_scale_reasoning", "tests_are_truth" ], "moe_experts": [ "security_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
59710642b29fe7278e0a6491174a517ea82c025f
train_19003
2026-01-01T00:00:00
Dataset curation pipelines (filter, dedupe, quality)
review
advanced
Task: review Topic: Dataset curation pipelines (filter, dedupe, quality) Difficulty: advanced Target language: C# Context: 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": "C#", "developer_needs": [ "tests_are_truth", "governance", "ci_integration", "security_gates" ], "moe_experts": [ "security_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
660dc3cb45c792ee4aaffa9d83104671feccc0ae
train_19004
2026-01-01T00:00:00
Code-specialized model families and sizing tradeoffs
review
intermediate
Task: review Topic: Code-specialized model families and sizing tradeoffs 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. Review: correctness, security, performance, governance
[]
{ "target_language": "Python", "developer_needs": [ "tooling", "evaluation_metrics", "documentation", "cost_latency_tradeoffs" ], "moe_experts": [ "agentic_systems_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
5bd04ffe32ee45feac7a8dcbce24d6b4d4a65aa2
train_19005
2026-01-01T00:00:00
Code-specialized model families and sizing tradeoffs
agent_loop
advanced
Task: agent_loop Topic: Code-specialized model families and sizing tradeoffs 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. Loop: Plan → Edit → Test → Reflect → Human gate
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Java", "developer_needs": [ "tooling", "tests_are_truth", "documentation", "cost_latency_tradeoffs" ], "moe_experts": [ "performance_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
d42831b6e9bfd09597a62b1cbca030bd6cdb2614
train_19006
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: 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": "Rust", "developer_needs": [ "evaluation_metrics", "governance", "reproducibility", "tooling" ], "moe_experts": [ "agentic_systems_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
029207d0e0be5efb8375b7a926c66d82a64c9914
train_19007
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: Python Context: High-traffic service with latency SLOs. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Loop: Plan → Edit → Test → Reflect → Human gate
[]
{ "target_language": "Python", "developer_needs": [ "security_gates", "evaluation_metrics", "auditability", "tooling" ], "moe_experts": [ "agentic_systems_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
0bd30101ec58a028069a6e1374177d70642f15d8
train_19008
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: Python Context: Large monorepo with flaky tests and strict CI. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Failure: - Initial patch broke edge case Reflection: - Missing zero-input guard Correction: - Add explicit validation + test
[]
{ "target_language": "Python", "developer_needs": [ "ci_integration", "security_gates", "repo_scale_reasoning", "documentation" ], "moe_experts": [ "agentic_systems_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
bfd5446ad75b418567355c28e5ba5cbf52dc7006
train_19009
2026-01-01T00:00:00
Secure code generation and policy gates
patch_diff
advanced
Task: patch_diff Topic: Secure code generation and policy gates 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. Patch (diff-style): ```diff - if x == 0: - return 1/x + if x == 0: + raise ValueError('division by zero') ``` Acceptance: - Tests pass - No new regressions
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Java", "developer_needs": [ "security_gates", "governance", "cost_latency_tradeoffs", "evaluation_metrics" ], "moe_experts": [ "agentic_systems_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
561b1e0167b58c3407bcb9b2f9601f71a9cff423
train_19010
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: 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": [ "reproducibility", "security_gates", "repo_scale_reasoning", "ci_integration" ], "moe_experts": [ "coding_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
26e9ac969a073ca6be22e8e916beaa4c4449ecca
train_19011
2026-01-01T00:00:00
Tool calling, sandboxes, and CI integration
failure_analysis
expert
Task: failure_analysis Topic: Tool calling, sandboxes, and CI integration Difficulty: expert Target language: SQL Context: 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": "SQL", "developer_needs": [ "ci_integration", "documentation", "auditability", "security_gates" ], "moe_experts": [ "security_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
bedae43e68053d57dd9e31bb15eab562e7d41b0d
train_19012
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: 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. Review: correctness, security, performance, governance
[]
{ "target_language": "SQL", "developer_needs": [ "tests_are_truth", "tooling", "ci_integration", "security_gates" ], "moe_experts": [ "agentic_systems_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
7dae18790b7006890d81afd26cac4c0d1dd85e5c
train_19013
2026-01-01T00:00:00
SWE-bench style real-repo evaluation
agent_loop
advanced
Task: agent_loop Topic: SWE-bench style real-repo evaluation Difficulty: advanced Target language: Go Context: Research team validating claims against real repos. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Loop: Plan → Edit → Test → Reflect → Human gate
[]
{ "target_language": "Go", "developer_needs": [ "security_gates", "reproducibility", "evaluation_metrics", "repo_scale_reasoning" ], "moe_experts": [ "evaluation_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
1be04c48c8332cda3d12713721cdbb2ca3bb05bc
train_19014
2026-01-01T00:00:00
SWE-bench style real-repo evaluation
eval
expert
Task: eval Topic: SWE-bench style real-repo evaluation Difficulty: expert Target language: TypeScript Context: Large monorepo with flaky tests and strict CI. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Eval: pass@k, time-to-green, regressions, diff size
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "TypeScript", "developer_needs": [ "repo_scale_reasoning", "auditability", "documentation", "tests_are_truth" ], "moe_experts": [ "agentic_systems_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
a26bb8ec087505801027e35c3d89229f78c42981
train_19015
2026-01-01T00:00:00
Code-specialized model families and sizing tradeoffs
design
expert
Task: design Topic: Code-specialized model families and sizing tradeoffs 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": [ "tests_are_truth", "repo_scale_reasoning", "governance", "evaluation_metrics" ], "moe_experts": [ "data_curation_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
646530818f0be72511b373b0ad46a831105120f0
train_19016
2026-01-01T00:00:00
Reasoning-first coding models and tunable deliberation
explain
expert
Task: explain Topic: Reasoning-first coding models and tunable deliberation Difficulty: expert Target language: Go Context: Large monorepo with flaky tests and strict CI. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "Go", "developer_needs": [ "documentation", "governance", "repo_scale_reasoning", "tooling" ], "moe_experts": [ "coding_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
f4449c6efe1001d4de53bc93f4906640ca524575
train_19017
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: 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. Review: correctness, security, performance, governance
[]
{ "target_language": "Go", "developer_needs": [ "tests_are_truth", "cost_latency_tradeoffs", "governance", "auditability" ], "moe_experts": [ "data_curation_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
259b1ace6f8b9f32c7f6474872e464bc4138d2f8
train_19018
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: 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": [ "repo_scale_reasoning", "documentation", "ci_integration", "tooling" ], "moe_experts": [ "data_curation_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
10f5b24fe4e43d5823abf3f9d7dd1eaadbceffcb
train_19019
2026-01-01T00:00:00
Agentic coding systems (plan→edit→test→reflect)
patch_diff
advanced
Task: patch_diff Topic: Agentic coding systems (plan→edit→test→reflect) Difficulty: advanced Target language: TypeScript Context: Research team validating claims against real repos. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. 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": [ "security_gates", "cost_latency_tradeoffs", "documentation", "reproducibility" ], "moe_experts": [ "agentic_systems_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
d0a8c71d9c828ee78142dafb26097f29171c24df
train_19020
2026-01-01T00:00:00
Reasoning-first coding models and tunable deliberation
data_pipeline
advanced
Task: data_pipeline Topic: Reasoning-first coding models and tunable deliberation Difficulty: advanced Target language: C# Context: Offline/local deployment with limited compute. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. 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": [ "evaluation_metrics", "tests_are_truth", "tooling", "repo_scale_reasoning" ], "moe_experts": [ "evaluation_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
8613941af692f1afd16d123425c6653ee1308b53
train_19021
2026-01-01T00:00:00
Latency, cost, and reliability optimization
review
expert
Task: review Topic: Latency, cost, and reliability optimization 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. 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": [ "ci_integration", "cost_latency_tradeoffs", "tooling", "repo_scale_reasoning" ], "moe_experts": [ "data_curation_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
3d363f35331700701dd423653455503e7ecb1a30
train_19022
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: SQL Context: Offline/local deployment with limited compute. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Review: correctness, security, performance, governance
[]
{ "target_language": "SQL", "developer_needs": [ "tests_are_truth", "documentation", "evaluation_metrics", "auditability" ], "moe_experts": [ "performance_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
450ff3e9c51be3e91020ade42baa233e78c84641
train_19023
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: High-traffic service with latency SLOs. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "Go", "developer_needs": [ "auditability", "tests_are_truth", "governance", "ci_integration" ], "moe_experts": [ "coding_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
5c01f47e538459b022ce1d58667af79257adfcfa
train_19024
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: 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": [ "auditability", "security_gates", "documentation", "governance" ], "moe_experts": [ "agentic_systems_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
f938c6c13a03e29d8aafb48143aa2f1c0407e889
train_19025
2026-01-01T00:00:00
Agentic coding systems (plan→edit→test→reflect)
design
advanced
Task: design Topic: Agentic coding systems (plan→edit→test→reflect) Difficulty: advanced Target language: Rust Context: Large monorepo with flaky tests and strict CI. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Rust", "developer_needs": [ "tooling", "governance", "auditability", "documentation" ], "moe_experts": [ "agentic_systems_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
f048f79c5f7cc1236f937c415b281c80a3668554
train_19026
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: Python Context: Offline/local deployment with limited compute. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Loop: Plan → Edit → Test → Reflect → Human gate
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Python", "developer_needs": [ "ci_integration", "evaluation_metrics", "repo_scale_reasoning", "documentation" ], "moe_experts": [ "evaluation_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
329162e2d5e7423d17163514166161f830bfed5e
train_19027
2026-01-01T00:00:00
Dataset curation pipelines (filter, dedupe, quality)
design
intermediate
Task: design Topic: Dataset curation pipelines (filter, dedupe, quality) Difficulty: intermediate Target language: 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": [ "governance", "security_gates", "auditability", "reproducibility" ], "moe_experts": [ "security_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
fc7771e8ef8e9d8f6309e06df1b82e422593818f
train_19028
2026-01-01T00:00:00
Secure code generation and policy gates
failure_analysis
intermediate
Task: failure_analysis Topic: Secure code generation and policy gates Difficulty: intermediate Target language: Java Context: Large monorepo with flaky tests and strict CI. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Failure: - Initial patch broke edge case Reflection: - Missing zero-input guard Correction: - Add explicit validation + test
[]
{ "target_language": "Java", "developer_needs": [ "auditability", "tests_are_truth", "governance", "security_gates" ], "moe_experts": [ "security_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
1b214b97fca46a3628cf3847e3d2f1ffbd147f5c
train_19029
2026-01-01T00:00:00
Code-specialized model families and sizing tradeoffs
code
advanced
Task: code Topic: Code-specialized model families and sizing tradeoffs Difficulty: advanced Target language: 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": [ "reproducibility", "ci_integration", "governance", "cost_latency_tradeoffs" ], "moe_experts": [ "security_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
73cf9767179918833811b6390e15a92ac85fcd26
train_19030
2026-01-01T00:00:00
Tool calling, sandboxes, and CI integration
data_pipeline
advanced
Task: data_pipeline Topic: Tool calling, sandboxes, and CI integration 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. 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": [ "security_gates", "reproducibility", "tooling", "cost_latency_tradeoffs" ], "moe_experts": [ "evaluation_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
83cdd776448499657509bc3c9fe6f560c62bd2be
train_19031
2026-01-01T00:00:00
Mixture-of-Experts (MoE) for code
patch_diff
advanced
Task: patch_diff Topic: Mixture-of-Experts (MoE) for code 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. Patch (diff-style): ```diff - if x == 0: - return 1/x + if x == 0: + raise ValueError('division by zero') ``` Acceptance: - Tests pass - No new regressions
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "SQL", "developer_needs": [ "ci_integration", "reproducibility", "evaluation_metrics", "tooling" ], "moe_experts": [ "security_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
9f1f336d254a25bbd1f4f53e7cef4dd1165bd391
train_19032
2026-01-01T00:00:00
Latency, cost, and reliability optimization
code
advanced
Task: code 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. Design with risks, metrics, acceptance criteria
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "SQL", "developer_needs": [ "tooling", "repo_scale_reasoning", "tests_are_truth", "reproducibility" ], "moe_experts": [ "data_curation_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
81fce9a22932d3a1a3f5c4cd4b60d4e2d641aaaa
train_19033
2026-01-01T00:00:00
SWE-bench style real-repo evaluation
agent_loop
advanced
Task: agent_loop Topic: SWE-bench style real-repo evaluation Difficulty: advanced Target language: 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. Loop: Plan → Edit → Test → Reflect → Human gate
[]
{ "target_language": "Java", "developer_needs": [ "evaluation_metrics", "reproducibility", "tooling", "repo_scale_reasoning" ], "moe_experts": [ "security_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
88f567a1fea656883b89d1e2690ba1b99d618b35
train_19034
2026-01-01T00:00:00
Code-specialized model families and sizing tradeoffs
code
advanced
Task: code Topic: Code-specialized model families and sizing tradeoffs Difficulty: advanced Target language: 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
[ "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", "tooling", "tests_are_truth", "documentation" ], "moe_experts": [ "agentic_systems_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
e1835a7c2000abf6c4bcdd57400fb44f0bb5fa59
train_19035
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: 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": "JavaScript", "developer_needs": [ "tooling", "evaluation_metrics", "repo_scale_reasoning", "cost_latency_tradeoffs" ], "moe_experts": [ "data_curation_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
d3567f4db57055efbbce3dfcb60d0a970cdb48f5
train_19036
2026-01-01T00:00:00
Model merging, distillation, and continued pretraining
explain
expert
Task: explain Topic: Model merging, distillation, and continued pretraining 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
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "JavaScript", "developer_needs": [ "governance", "cost_latency_tradeoffs", "reproducibility", "tests_are_truth" ], "moe_experts": [ "coding_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
7cdb2ef3c45d31533c2b2eaefbfbd2b1c1baaac4
train_19037
2026-01-01T00:00:00
Agentic coding systems (plan→edit→test→reflect)
patch_diff
intermediate
Task: patch_diff Topic: Agentic coding systems (plan→edit→test→reflect) Difficulty: intermediate Target language: TypeScript Context: Offline/local deployment with limited compute. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Patch (diff-style): ```diff - if x == 0: - return 1/x + if x == 0: + raise ValueError('division by zero') ``` Acceptance: - Tests pass - No new regressions
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "TypeScript", "developer_needs": [ "tooling", "security_gates", "cost_latency_tradeoffs", "evaluation_metrics" ], "moe_experts": [ "data_curation_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
208741c810921ea94fa47d55323ebac8c0ea3b66
train_19038
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: SQL Context: High-traffic service with latency SLOs. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "SQL", "developer_needs": [ "reproducibility", "repo_scale_reasoning", "documentation", "governance" ], "moe_experts": [ "performance_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
7df81114d198fab3151a3ce988045b579b09df01
train_19039
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: Python Context: Offline/local deployment with limited compute. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Loop: Plan → Edit → Test → Reflect → Human gate
[]
{ "target_language": "Python", "developer_needs": [ "tooling", "cost_latency_tradeoffs", "evaluation_metrics", "reproducibility" ], "moe_experts": [ "governance_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
54e22fe218a9e3f1112f67564a36a39279d68fe9
train_19040
2026-01-01T00:00:00
Latency, cost, and reliability optimization
compare
expert
Task: compare Topic: Latency, cost, and reliability optimization 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. Compare: capability, cost, latency, reliability
[]
{ "target_language": "Go", "developer_needs": [ "tests_are_truth", "evaluation_metrics", "documentation", "cost_latency_tradeoffs" ], "moe_experts": [ "agentic_systems_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
ef589e6a9d74704efe6bb12bb6a22c9b1d7cd7a8
train_19041
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: SQL Context: High-traffic service with latency SLOs. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Review: correctness, security, performance, governance
[]
{ "target_language": "SQL", "developer_needs": [ "governance", "evaluation_metrics", "tests_are_truth", "ci_integration" ], "moe_experts": [ "performance_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
408052fb7e92ea3842ee4e75e6ee9d4f784e9d69
train_19042
2026-01-01T00:00:00
Code-specialized model families and sizing tradeoffs
data_pipeline
intermediate
Task: data_pipeline Topic: Code-specialized model families and sizing tradeoffs Difficulty: intermediate Target language: Go Context: High-traffic service with latency SLOs. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. 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": [ "documentation", "security_gates", "evaluation_metrics", "ci_integration" ], "moe_experts": [ "agentic_systems_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
71884849d0420b4d8e387fda9afd3ccf69ad29c4
train_19043
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: 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": [ "evaluation_metrics", "security_gates", "cost_latency_tradeoffs", "reproducibility" ], "moe_experts": [ "evaluation_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
573dceb0a72f501090321fc5a328d0f114ede93c
train_19044
2026-01-01T00:00:00
Dataset curation pipelines (filter, dedupe, quality)
compare
intermediate
Task: compare Topic: Dataset curation pipelines (filter, dedupe, quality) Difficulty: intermediate Target language: TypeScript Context: Regulated environment requiring audit trails. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Compare: capability, cost, latency, reliability
[]
{ "target_language": "TypeScript", "developer_needs": [ "repo_scale_reasoning", "evaluation_metrics", "documentation", "auditability" ], "moe_experts": [ "agentic_systems_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
37f0a41a789e605e4107019c05dd43529fcaac81
train_19045
2026-01-01T00:00:00
Extended context and repo-scale understanding
patch_diff
advanced
Task: patch_diff Topic: Extended context and repo-scale understanding Difficulty: advanced Target language: 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. Patch (diff-style): ```diff - if x == 0: - return 1/x + if x == 0: + raise ValueError('division by zero') ``` Acceptance: - Tests pass - No new regressions
[]
{ "target_language": "Python", "developer_needs": [ "tooling", "security_gates", "documentation", "repo_scale_reasoning" ], "moe_experts": [ "agentic_systems_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
da71eb8da6fb83b2bcb4b98f82d3d64eadff96a6
train_19046
2026-01-01T00:00:00
Latency, cost, and reliability optimization
compare
expert
Task: compare Topic: Latency, cost, and reliability optimization 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": [ "reproducibility", "ci_integration", "auditability", "security_gates" ], "moe_experts": [ "performance_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
29375ad93912c9f22bff34b837cddbaf79de6670
train_19047
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: Bash Context: Research team validating claims against real repos. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Review: correctness, security, performance, governance
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Bash", "developer_needs": [ "cost_latency_tradeoffs", "ci_integration", "tooling", "auditability" ], "moe_experts": [ "governance_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
7e59645475f3ed9608d6fe900b90dc0bfbfefd90
train_19048
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: 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": [ "tooling", "auditability", "ci_integration", "cost_latency_tradeoffs" ], "moe_experts": [ "coding_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
0c23458e4fcb217c4bbef4858c50041a765dd9c5
train_19049
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: 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. Review: correctness, security, performance, governance
[]
{ "target_language": "Go", "developer_needs": [ "cost_latency_tradeoffs", "tooling", "auditability", "security_gates" ], "moe_experts": [ "evaluation_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
395bd542f6a8a0d5bdcf532fbddc415da9d9683f
train_19050
2026-01-01T00:00:00
Secure code generation and policy gates
eval
expert
Task: eval Topic: Secure code generation and policy gates Difficulty: expert Target language: TypeScript Context: Research team validating claims against real repos. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Eval: pass@k, time-to-green, regressions, diff size
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "TypeScript", "developer_needs": [ "auditability", "evaluation_metrics", "reproducibility", "governance" ], "moe_experts": [ "coding_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
9b5c2a3387ff0aa4e486d50d6293a34b5fbf5aad
train_19051
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: Regulated environment requiring audit trails. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Review: correctness, security, performance, governance
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Go", "developer_needs": [ "evaluation_metrics", "tooling", "repo_scale_reasoning", "tests_are_truth" ], "moe_experts": [ "governance_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
40b99b7ee917e682b922390d8e1eccb79a39f1d4
train_19052
2026-01-01T00:00:00
Self-improving agents and feedback loops
review
intermediate
Task: review Topic: Self-improving agents and feedback loops 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. Review: correctness, security, performance, governance
[]
{ "target_language": "TypeScript", "developer_needs": [ "reproducibility", "governance", "repo_scale_reasoning", "auditability" ], "moe_experts": [ "evaluation_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
53eabb4dc28ecbb3b9f8eb53ccf891ecd74b2f69
train_19053
2026-01-01T00:00:00
Latency, cost, and reliability optimization
compare
intermediate
Task: compare Topic: Latency, cost, and reliability optimization Difficulty: intermediate Target language: Bash Context: Large monorepo with flaky tests and strict CI. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. 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": [ "security_gates", "repo_scale_reasoning", "cost_latency_tradeoffs", "tests_are_truth" ], "moe_experts": [ "governance_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
c83453c3d0f32664877daa616fb15109cea98205
train_19054
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: JavaScript Context: Research team validating claims against real repos. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "JavaScript", "developer_needs": [ "cost_latency_tradeoffs", "security_gates", "ci_integration", "auditability" ], "moe_experts": [ "performance_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
c3d884570ac6bce9e536b3f9347a3ff4b7a0596f
train_19055
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: Python Context: Large monorepo with flaky tests and strict CI. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Failure: - Initial patch broke edge case Reflection: - Missing zero-input guard Correction: - Add explicit validation + test
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Python", "developer_needs": [ "governance", "reproducibility", "security_gates", "ci_integration" ], "moe_experts": [ "agentic_systems_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
79ce9f41414f5287d48a4d84d9bf8dbbf1c51035
train_19056
2026-01-01T00:00:00
Tool calling, sandboxes, and CI integration
data_pipeline
advanced
Task: data_pipeline Topic: Tool calling, sandboxes, and CI integration Difficulty: advanced Target language: Go Context: Offline/local deployment with limited compute. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Pipeline: Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Go", "developer_needs": [ "repo_scale_reasoning", "cost_latency_tradeoffs", "reproducibility", "tests_are_truth" ], "moe_experts": [ "data_curation_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
aa1db1df4d64f97f3ae6709757f75d686de161b4
train_19057
2026-01-01T00:00:00
Code-specialized model families and sizing tradeoffs
patch_diff
advanced
Task: patch_diff Topic: Code-specialized model families and sizing tradeoffs Difficulty: advanced Target language: 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. 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": "Go", "developer_needs": [ "ci_integration", "governance", "cost_latency_tradeoffs", "evaluation_metrics" ], "moe_experts": [ "governance_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
6d878322b5d880d82f7d8a991e1ea548ebee19f1
train_19058
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: TypeScript Context: Research team validating claims against real repos. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "TypeScript", "developer_needs": [ "security_gates", "tooling", "repo_scale_reasoning", "reproducibility" ], "moe_experts": [ "agentic_systems_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
97205390dc1b44cac0ac1261cb5cb5a377c41ade
train_19059
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: 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": [ "cost_latency_tradeoffs", "ci_integration", "documentation", "evaluation_metrics" ], "moe_experts": [ "agentic_systems_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
4f9b775a88bf6ac01394021d7a7f0da09e9e1196
train_19060
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: Offline/local deployment with limited compute. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Pipeline: Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
[]
{ "target_language": "C#", "developer_needs": [ "documentation", "evaluation_metrics", "auditability", "repo_scale_reasoning" ], "moe_experts": [ "coding_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
a2709a9b48119cd5e3cf3e86b56c3fb7b01a548c
train_19061
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: 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", "auditability", "repo_scale_reasoning", "tooling" ], "moe_experts": [ "security_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
65a03680d08dbfbe8e8ab25c368180ecb7c4a962
train_19062
2026-01-01T00:00:00
Latency, cost, and reliability optimization
code
advanced
Task: code Topic: Latency, cost, and reliability optimization Difficulty: advanced Target language: Rust Context: High-traffic service with latency SLOs. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "Rust", "developer_needs": [ "ci_integration", "reproducibility", "cost_latency_tradeoffs", "evaluation_metrics" ], "moe_experts": [ "agentic_systems_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
b5c799b64bb68c0092bbc2c0c1b79e958b2732cf
train_19063
2026-01-01T00:00:00
Model merging, distillation, and continued pretraining
explain
intermediate
Task: explain Topic: Model merging, distillation, and continued pretraining 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. Design with risks, metrics, acceptance criteria
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "C#", "developer_needs": [ "repo_scale_reasoning", "reproducibility", "tests_are_truth", "security_gates" ], "moe_experts": [ "coding_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
432572baab6fd1c72bea46a4e500a2362363b585
train_19064
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: 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": [ "reproducibility", "tests_are_truth", "security_gates", "documentation" ], "moe_experts": [ "governance_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
82f1d237a9804af159e234a233a7246514278e21
train_19065
2026-01-01T00:00:00
Self-improving agents and feedback loops
explain
advanced
Task: explain Topic: Self-improving agents and feedback loops 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
[]
{ "target_language": "C#", "developer_needs": [ "tooling", "repo_scale_reasoning", "cost_latency_tradeoffs", "auditability" ], "moe_experts": [ "performance_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
e46351c0cd907d30221dbfc0f5dd6209ae391733
train_19066
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: 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
[]
{ "target_language": "Bash", "developer_needs": [ "auditability", "cost_latency_tradeoffs", "tooling", "repo_scale_reasoning" ], "moe_experts": [ "evaluation_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
0ea99f6fa8c7d3dcc2ab959324a9938e44bfe6bd
train_19067
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: Go Context: High-traffic service with latency SLOs. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Compare: capability, cost, latency, reliability
[]
{ "target_language": "Go", "developer_needs": [ "documentation", "security_gates", "evaluation_metrics", "cost_latency_tradeoffs" ], "moe_experts": [ "security_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
f1a4f50faff10f12454b6adade0b9d39fdabe8ec
train_19068
2026-01-01T00:00:00
Dataset curation pipelines (filter, dedupe, quality)
code
expert
Task: code Topic: Dataset curation pipelines (filter, dedupe, quality) 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. Design with risks, metrics, acceptance criteria
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Go", "developer_needs": [ "reproducibility", "tests_are_truth", "governance", "tooling" ], "moe_experts": [ "performance_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
82eab93b9b93242c0b57bff4e6e528cb0d6c5efb
train_19069
2026-01-01T00:00:00
Latency, cost, and reliability optimization
review
advanced
Task: review Topic: Latency, cost, and reliability optimization 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": [ "cost_latency_tradeoffs", "ci_integration", "evaluation_metrics", "documentation" ], "moe_experts": [ "coding_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
5a4d7f25f0cc46af75086dad1e7bc9e6255cf4d3
train_19070
2026-01-01T00:00:00
Mixture-of-Experts (MoE) for code
explain
advanced
Task: explain Topic: Mixture-of-Experts (MoE) for code Difficulty: advanced 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": [ "security_gates", "ci_integration", "tests_are_truth", "documentation" ], "moe_experts": [ "performance_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
ec40d0a2216161bf6c6df1b013c4c88ce410e423
train_19071
2026-01-01T00:00:00
Extended context and repo-scale understanding
data_pipeline
intermediate
Task: data_pipeline Topic: Extended context and repo-scale understanding Difficulty: intermediate Target language: 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. Pipeline: Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
[]
{ "target_language": "Python", "developer_needs": [ "tooling", "security_gates", "cost_latency_tradeoffs", "ci_integration" ], "moe_experts": [ "coding_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
04331a9d10204184031c8f54045f9f277b25fc6e
train_19072
2026-01-01T00:00:00
Latency, cost, and reliability optimization
compare
expert
Task: compare 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. Compare: capability, cost, latency, reliability
[]
{ "target_language": "Bash", "developer_needs": [ "security_gates", "cost_latency_tradeoffs", "reproducibility", "repo_scale_reasoning" ], "moe_experts": [ "performance_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
23422ac6a94a4d86f98b54934196ba215ee346d3
train_19073
2026-01-01T00:00:00
Multimodal dev workflows (docs, diagrams, traces)
explain
expert
Task: explain Topic: Multimodal dev workflows (docs, diagrams, traces) Difficulty: expert Target language: 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
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Rust", "developer_needs": [ "reproducibility", "ci_integration", "governance", "auditability" ], "moe_experts": [ "performance_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
47f97d79a6eec426ec99258892dba3f094733a4b
train_19074
2026-01-01T00:00:00
Secure code generation and policy gates
eval
intermediate
Task: eval Topic: Secure code generation and policy gates Difficulty: intermediate Target language: 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": [ "tooling", "tests_are_truth", "auditability", "security_gates" ], "moe_experts": [ "evaluation_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
bb1afe56c68709727227007a8d70f384b4705c22
train_19075
2026-01-01T00:00:00
Model merging, distillation, and continued pretraining
eval
advanced
Task: eval Topic: Model merging, distillation, and continued pretraining Difficulty: advanced Target language: Rust Context: Research team validating claims against real repos. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Eval: pass@k, time-to-green, regressions, diff size
[]
{ "target_language": "Rust", "developer_needs": [ "governance", "security_gates", "ci_integration", "cost_latency_tradeoffs" ], "moe_experts": [ "data_curation_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
83a6e8c8ad16b50f012564f4ae0130fc4673433d
train_19076
2026-01-01T00:00:00
Agentic coding systems (plan→edit→test→reflect)
explain
expert
Task: explain Topic: Agentic coding systems (plan→edit→test→reflect) 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. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "Go", "developer_needs": [ "tooling", "tests_are_truth", "evaluation_metrics", "governance" ], "moe_experts": [ "evaluation_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
ed8605368458eed55dc1d302be217caa5673b42b
train_19077
2026-01-01T00:00:00
Self-improving agents and feedback loops
code
advanced
Task: code Topic: Self-improving agents and feedback loops Difficulty: advanced Target language: Java Context: Regulated environment requiring audit trails. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "Java", "developer_needs": [ "auditability", "tests_are_truth", "tooling", "reproducibility" ], "moe_experts": [ "agentic_systems_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
b14d44965781586abd1faf57aed3105b905ff8dc
train_19078
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: 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. Eval: pass@k, time-to-green, regressions, diff size
[]
{ "target_language": "JavaScript", "developer_needs": [ "tests_are_truth", "security_gates", "reproducibility", "ci_integration" ], "moe_experts": [ "coding_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
7a43e6eb762e846dfef6f9260659a8a3e434b146
train_19079
2026-01-01T00:00:00
Agentic coding systems (plan→edit→test→reflect)
patch_diff
intermediate
Task: patch_diff Topic: Agentic coding systems (plan→edit→test→reflect) 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
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "JavaScript", "developer_needs": [ "documentation", "repo_scale_reasoning", "cost_latency_tradeoffs", "evaluation_metrics" ], "moe_experts": [ "coding_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
1ec397d1a836e7b21e63220ffb49df71e3bb6f17
train_19080
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: Bash Context: Research team validating claims against real repos. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Patch (diff-style): ```diff - if x == 0: - return 1/x + if x == 0: + raise ValueError('division by zero') ``` Acceptance: - Tests pass - No new regressions
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Bash", "developer_needs": [ "documentation", "tooling", "auditability", "reproducibility" ], "moe_experts": [ "governance_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
03db175ca0eb15046f7d5f89e05f52bb0aea6161
train_19081
2026-01-01T00:00:00
Secure code generation and policy gates
code
expert
Task: code Topic: Secure code generation and policy gates Difficulty: expert Target language: 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": [ "repo_scale_reasoning", "ci_integration", "auditability", "tooling" ], "moe_experts": [ "coding_expert", "security_expert" ], "governance": { "audit_required": true, "tests_required": true } }
cfc0920552c554f9f803bb5cd8f63be7e31aa148
train_19082
2026-01-01T00:00:00
Model merging, distillation, and continued pretraining
code
intermediate
Task: code Topic: Model merging, distillation, and continued pretraining Difficulty: intermediate Target language: 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. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "JavaScript", "developer_needs": [ "tooling", "evaluation_metrics", "cost_latency_tradeoffs", "reproducibility" ], "moe_experts": [ "coding_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
fc23fda4c2757e055b488fa7010c63fd2b72189c
train_19083
2026-01-01T00:00:00
Agentic coding systems (plan→edit→test→reflect)
patch_diff
intermediate
Task: patch_diff Topic: Agentic coding systems (plan→edit→test→reflect) 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. Patch (diff-style): ```diff - if x == 0: - return 1/x + if x == 0: + raise ValueError('division by zero') ``` Acceptance: - Tests pass - No new regressions
[]
{ "target_language": "Bash", "developer_needs": [ "ci_integration", "tests_are_truth", "tooling", "reproducibility" ], "moe_experts": [ "security_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
1979ff7244e1a4553418793392f21788322f93a7
train_19084
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: 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
[]
{ "target_language": "Bash", "developer_needs": [ "tests_are_truth", "auditability", "tooling", "ci_integration" ], "moe_experts": [ "governance_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
2d203de9227da61dc39fbba059c42b77cbebfecf
train_19085
2026-01-01T00:00:00
Reasoning-first coding models and tunable deliberation
explain
intermediate
Task: explain Topic: Reasoning-first coding models and tunable deliberation 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
[]
{ "target_language": "Bash", "developer_needs": [ "documentation", "auditability", "repo_scale_reasoning", "reproducibility" ], "moe_experts": [ "data_curation_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
fca39fd0a686fab314141c833e52540ea04b59bf
train_19086
2026-01-01T00:00:00
Agentic coding systems (plan→edit→test→reflect)
patch_diff
intermediate
Task: patch_diff Topic: Agentic coding systems (plan→edit→test→reflect) 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. 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": [ "security_gates", "repo_scale_reasoning", "cost_latency_tradeoffs", "auditability" ], "moe_experts": [ "coding_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
d2981329004699cfa09f42ff6954a160d229d221
train_19087
2026-01-01T00:00:00
Tool calling, sandboxes, and CI integration
patch_diff
expert
Task: patch_diff Topic: Tool calling, sandboxes, and CI integration Difficulty: expert Target language: 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. Patch (diff-style): ```diff - if x == 0: - return 1/x + if x == 0: + raise ValueError('division by zero') ``` Acceptance: - Tests pass - No new regressions
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "Python", "developer_needs": [ "documentation", "repo_scale_reasoning", "evaluation_metrics", "tooling" ], "moe_experts": [ "security_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
3b146308eaf0ec9248fd4508f86b5cebf5a5065f
train_19088
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: 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": [ "governance", "cost_latency_tradeoffs", "auditability", "documentation" ], "moe_experts": [ "performance_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
5414e832e91f17d4de854d03198e4c412fcf9eca
train_19089
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: High-traffic service with latency SLOs. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "JavaScript", "developer_needs": [ "tests_are_truth", "auditability", "evaluation_metrics", "ci_integration" ], "moe_experts": [ "security_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
e0ee6400e225d6e44c660300ec2e242230418281
train_19090
2026-01-01T00:00:00
Agentic coding systems (plan→edit→test→reflect)
compare
expert
Task: compare Topic: Agentic coding systems (plan→edit→test→reflect) Difficulty: expert Target language: Java Context: 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": "Java", "developer_needs": [ "security_gates", "reproducibility", "tooling", "auditability" ], "moe_experts": [ "data_curation_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
1b63a964afb1cd5939bca4b2258af7bebd774881
train_19091
2026-01-01T00:00:00
Multimodal dev workflows (docs, diagrams, traces)
explain
expert
Task: explain Topic: Multimodal dev workflows (docs, diagrams, traces) Difficulty: expert Target language: Python Context: Research team validating claims against real repos. Produce expert-level, production-ready artifacts.
Facts: - Modern AI coding prioritizes correctness, evaluation, and governance. - Agentic loops with test gates outperform single-pass generation. Design with risks, metrics, acceptance criteria
[]
{ "target_language": "Python", "developer_needs": [ "repo_scale_reasoning", "tests_are_truth", "cost_latency_tradeoffs", "auditability" ], "moe_experts": [ "data_curation_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
1115301701af81904a8bc8322df46bd8e6d2e46d
train_19092
2026-01-01T00:00:00
Self-improving agents and feedback loops
review
intermediate
Task: review Topic: Self-improving agents and feedback loops 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. Review: correctness, security, performance, governance
[]
{ "target_language": "JavaScript", "developer_needs": [ "documentation", "tooling", "tests_are_truth", "ci_integration" ], "moe_experts": [ "security_expert", "governance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
275acc72a34e7febdb8fd6784f74ec16d4da1a15
train_19093
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: 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
[]
{ "target_language": "JavaScript", "developer_needs": [ "security_gates", "evaluation_metrics", "repo_scale_reasoning", "auditability" ], "moe_experts": [ "security_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
460736a27f3ae3ab128a91c5bddf0ba4b1f20dea
train_19094
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: 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": "Bash", "developer_needs": [ "security_gates", "tooling", "reproducibility", "auditability" ], "moe_experts": [ "agentic_systems_expert", "data_curation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
6cfa467cf7a919dfaad892e589d5da6ace8daa46
train_19095
2026-01-01T00:00:00
Dataset curation pipelines (filter, dedupe, quality)
patch_diff
intermediate
Task: patch_diff Topic: Dataset curation pipelines (filter, dedupe, quality) Difficulty: intermediate Target language: 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. Patch (diff-style): ```diff - if x == 0: - return 1/x + if x == 0: + raise ValueError('division by zero') ``` Acceptance: - Tests pass - No new regressions
[]
{ "target_language": "Python", "developer_needs": [ "cost_latency_tradeoffs", "repo_scale_reasoning", "documentation", "tests_are_truth" ], "moe_experts": [ "performance_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
8146f329db9697bd54f5a0b9406427bc3622b177
train_19096
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: 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. Eval: pass@k, time-to-green, regressions, diff size
[]
{ "target_language": "TypeScript", "developer_needs": [ "ci_integration", "repo_scale_reasoning", "cost_latency_tradeoffs", "tests_are_truth" ], "moe_experts": [ "evaluation_expert", "coding_expert" ], "governance": { "audit_required": true, "tests_required": true } }
a62cc853dbedd770222b05aa37d7da84cc34be68
train_19097
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: 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. Loop: Plan → Edit → Test → Reflect → Human gate
[]
{ "target_language": "C#", "developer_needs": [ "tests_are_truth", "tooling", "documentation", "auditability" ], "moe_experts": [ "governance_expert", "agentic_systems_expert" ], "governance": { "audit_required": true, "tests_required": true } }
8c022c49c0861bdafe7f041fde1612ad3461509e
train_19098
2026-01-01T00:00:00
Mixture-of-Experts (MoE) for code
explain
intermediate
Task: explain Topic: Mixture-of-Experts (MoE) for code 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
[ "Identify failing behavior via tests", "Minimize change surface", "Apply patch", "Run targeted + full suite", "Verify no regressions" ]
{ "target_language": "TypeScript", "developer_needs": [ "documentation", "security_gates", "ci_integration", "tooling" ], "moe_experts": [ "agentic_systems_expert", "evaluation_expert" ], "governance": { "audit_required": true, "tests_required": true } }
69a09690fcb9f006a5938eadb051cc9444d7c6ff
train_19099
2026-01-01T00:00:00
Tool calling, sandboxes, and CI integration
patch_diff
expert
Task: patch_diff Topic: Tool calling, sandboxes, and CI integration Difficulty: expert Target language: 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. Patch (diff-style): ```diff - if x == 0: - return 1/x + if x == 0: + raise ValueError('division by zero') ``` Acceptance: - Tests pass - No new regressions
[]
{ "target_language": "Java", "developer_needs": [ "evaluation_metrics", "repo_scale_reasoning", "cost_latency_tradeoffs", "documentation" ], "moe_experts": [ "governance_expert", "performance_expert" ], "governance": { "audit_required": true, "tests_required": true } }
58e36ef314bc7d3d57365693253ec3cb49349a1e