Writoria 
You wrote the instructions. You created an AGENTS.md, CLAUDE.md, or Copilot instruction file. You documented the architecture, commands, conventions, testing rules, and everything the coding agent should avoid. Then you gave the agent a task. And it ignored part of the instructions anyway. The obvious conclusion is that the AI coding agent is bad at … Read more
AI coding agents work better when they do not have to rediscover your repository rules in every conversation. Files such as AGENTS.md, .github/copilot-instructions.md, and CLAUDE.md let teams store persistent instructions about architecture, commands, conventions, testing, and workflow expectations. The difficult part is deciding what belongs in each file. Copying the same long instruction manual into … Read more
Reviewing AI-generated code requires more than checking whether it compiles or passes the tests created by the same AI. A convincing implementation can still misunderstand the requirement, weaken authorization, mishandle unusual inputs, duplicate existing logic, or introduce failures that appear only under real production conditions. A reliable AI-generated code review separates implementation from verification. The … Read more
An effective AI coding workflow does not begin with “write the code.” It begins with a clear task brief, defined boundaries, repository context, acceptance criteria, and a test plan. The AI can then propose a solution, implement a controlled change, run validation, and prepare a pull request that a human can review with confidence. The … Read more
