Category · 4 posts
Deep dives, debugging stories and how things work under the hood.
AI can now write, test and fix code, so what happens to programmers? What AI does well and badly, which tasks and roles are changing, which skills grow in value, and a practical plan to stay valuable as a developer or learner.
A practical comparison of the leading AI coding tools: how Claude Code, Cursor, GitHub Copilot and OpenAI Codex work, what their plans include, which fits beginners, professionals and teams, and how to get reliable code from any of them.
Run an open-source coding model on your own computer with Ollama or LM Studio and connect it to VS Code. What hardware you need, which model sizes fit your RAM, step-by-step setup, realistic expectations versus cloud models, and privacy and security tips.
AI coding agents are fast, confident and context-poor. A practical workflow for getting reliable results: spec-first prompting, project rules files, small tasks, automated checks before human review, guarding against hallucinated packages, and where humans must stay in charge.
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