How to Use OpenSpec Across the Full Development Workflow
A practical workflow for using OpenSpec from exploration to proposal, implementation, quality checks, PR review, merge, and archive without letting specs drift from the code.
28 min read
Archive
Articles, page 3
Older writing on AI applications, software engineering, and developer tools.
Advanced OpenSpec: Expanded Workflows, Verify Loops, and Custom Schemas
A practical deep dive into OpenSpec's expanded OPSX workflows and custom schemas: when to use /opsx:new, /opsx:continue, /opsx:ff, /opsx:verify, /opsx:bulk-archive, /opsx:onboard, and how to design your own workflow.
17 min read
How to Build an AI Math Tutor Agent That Stays Correct
A practical architecture for math tutoring agents: generate random problems with seeded templates, compute ground truth outside the LLM, use the model for explanations, and verify every answer before showing it to learners.
13 min read
How to Get Started with OpenSpec: Existing Projects, New Apps, and Common First Changes
A practical, source-backed guide for engineers and PMs adopting OpenSpec: when to start with an existing project, when to use it for a new build, and how to run the first workflow safely.
15 min read
OpenSpec vs GitHub Spec Kit: A Side-by-Side Review of Spec-Driven Development
A source-backed comparison of OpenSpec and GitHub Spec Kit for engineers and PMs: workflows, skills, generated artifacts, extensibility, and inferred token trade-offs.
15 min read
MCP + RAG Performance Stack: Tools, Benchmarks, and Decision Guide
A technical follow-up for engineers choosing embeddings, vector stores, rerankers, caches, and eval libraries for production MCP + RAG over public app data — with benchmark-backed comparisons and three reference stacks.
19 min read
How to Make App Data Public and Production-Ready with MCP and RAG
A practical guide for engineers and PMs who want to expose public app data safely through MCP and RAG — with allowlists, caching, cost controls, and a production checklist.
17 min read
Architecture Governance for AI Code Generation
A practical guide for engineers and PMs who want AI coding agents to move fast without breaking architecture decisions, module boundaries, ownership, and long-term system quality.
20 min read