AI Coding

This hub is about writing, reviewing and shipping code with AI assistants. That covers editors with AI built in, chat-based pair programmers, and agents that read a repository, run commands and edit files on their own. The question behind every post here is the same: on a real codebase, does this make you faster, and what does it cost you in review time, mistakes and money?

It is written for working developers who already know how to code. You might be choosing between two editors, deciding what your team is allowed to use, or trying to get better output from the assistant you already pay for. You will not find beginner explainers on what a language model is, and you will not find breathless claims that AI writes all the code now.

The approach is hands-on. Tools are used on actual projects, long enough to hit their rough edges, and the verdicts say what a tool is bad at as plainly as what it is good at. Prices come from the vendor's own pricing page, with the date they were checked. There are no invented benchmarks: where a post compares speed or quality, it shows the task and the result rather than a score from nowhere. AI coding tools change every month, so posts carry an updated date and get revisited when a release changes the answer.

Where to start: the Cursor vs GitHub Copilot comparison covers the choice most developers face first, an AI-first editor or an assistant added to the editor you already use. The roundup of the best AI code editors widens that to the rest of the field, and the Claude Code review looks at the terminal-based agent approach. If you build front ends, the v0 vs Bolt vs Lovable comparison looks at tools that generate a whole app from a prompt, and at what you inherit when you take that code over.