//blog
Notes on shared work-state, overlap between agents, handoffs, and reviewing code that a person did not write.
Learn how to move unfinished coding tasks between agents without losing assumptions, rejected approaches, or context. Keep work alive across sessions.
Why undocumented decisions are the main source of technical debt in AI generated code and what to capture at the moment you make them.
Learn how to write prompts that get code changes you can review and trust, with clear constraints, scoped files, and explicit assumptions.
A step-by-step guide to running parallel coding agents on the same repository using git worktrees, with concrete commands and warnings about what the setup does not solve.
Learn why reviewing and integrating generated work safely matters more than typing speed, and how to judge scope, taste in review, and document decisions so the next person is not guessing.
Compare MCP servers by category to see which ones handle repository access, issue trackers, browser tasks, databases, docs search, and shared state between agents.
Practical steps to cut your agent’s run time by narrowing context, avoiding searches, splitting tasks, and stopping early when it misunderstands.
Compare Cursor and Claude Code on how much work you can hand off at once. Learn where each frustrates you and why running both creates a coordination problem.
A step-by-step method for reviewing AI generated code that focuses on intent, assumptions, and test coverage before syntax.
Five underused ways to plan, share context and end sessions in Claude Code without retyping project instructions or scanning entire repos.
Learn how to split work cleanly so multiple coding agents can run in parallel without stepping on each other. Avoid the interface conflict that silently breaks builds.
A practical guide to coordinating two AI coding agents so they don’t step on each other’s work and the PR review doesn’t become a mess.