repoGitHubTrust 82 · PrimaryPublished 1mo agoLive · 1mo ago
zhu1090093659/spec_driven_develop
Spec-driven development workflow for AI coding agents: architecture-first planning, task decomposition, GitHub Issue/PR tracking, Deep Discuss, and adaptive control for Claude Code, Codex, Cursor, and other Markdown-capable agents.
Lineage graph
Paper → model → repo connections mined from source citations (Tier-1 exact match).
Why these links exist
Every edge carries a method, confidence, and the source snippet that justified it — so bad links are debuggable.
- PossiblePossibly related (embedding) · 64%Cheap Code, Costly Judgment: A Case Study on Governable Agentic Software Engineering →
- PossiblePossibly related (embedding) · 63%SWE-INTERACT: Reimagining SWE Benchmarks as User-Driven Long-Horizon Coding Sessions →
- PossiblePossibly related (embedding) · 62%LLM for EDA in Front-End Design: Challenges and Opportunities →
- PossiblePossibly related (embedding) · 61%AgentCore-8B →
- PossiblePossibly related (embedding) · 60%Reasoning effort, not tool access, buys first-try reliability in agentic code generation: an observational study →
- PossiblePossibly related (embedding) · 59%Agent Seer: Synthesizing Scenarios from Specification Understanding - Apple Machine Learning Research →
- PossiblePossibly related (embedding) · 55%Octave and MAIRE collaborate on the application of AI across engineering and construction workflows - AiThority →
- PossiblePossibly related (embedding) · 54%Spec-Driven Development vs Vibe Coding: The Enterprise Framework for Scaling AI Software Delivery and Proving Its ROI - Security Boulevard →
Implements
paperCheap Code, Costly Judgment: A Case Study on Governable Agentic Software EngineeringpaperSWE-INTERACT: Reimagining SWE Benchmarks as User-Driven Long-Horizon Coding SessionspaperLLM for EDA in Front-End Design: Challenges and OpportunitiespaperReasoning effort, not tool access, buys first-try reliability in agentic code generation: an observational study
Related to
Covers (incoming)
newsAgent Seer: Synthesizing Scenarios from Specification Understanding - Apple Machine Learning ResearchnewsOctave and MAIRE collaborate on the application of AI across engineering and construction workflows - AiThoritynewsSpec-Driven Development vs Vibe Coding: The Enterprise Framework for Scaling AI Software Delivery and Proving Its ROI - Security BoulevardnewsDeepMind CEO calls for an independent standards body to regulate frontier AI
Related across the graph
newsOctave and MAIRE collaborate on the application of AI across engineering and construction workflows - AiThoritynewsDeepMind CEO calls for an independent standards body to regulate frontier AIpaperLLM for EDA in Front-End Design: Challenges and OpportunitiespaperCheap Code, Costly Judgment: A Case Study on Governable Agentic Software EngineeringpaperReasoning effort, not tool access, buys first-try reliability in agentic code generation: an observational studymodelAgentCore-8BpaperSWE-INTERACT: Reimagining SWE Benchmarks as User-Driven Long-Horizon Coding SessionsnewsAgent Seer: Synthesizing Scenarios from Specification Understanding - Apple Machine Learning ResearchnewsSpec-Driven Development vs Vibe Coding: The Enterprise Framework for Scaling AI Software Delivery and Proving Its ROI - Security Boulevard