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How to choose an AI coding tool by what people actually ship
There are many AI coding tools and new ones appear constantly. Marketing pages all sound alike. A better signal is what people have actually made with a tool, and what they said about it while they were doing it.
Look for evidence, not claims
Read the entries of builders who used the tool on something real. Notice what they were doing, how long it took, and what went wrong.
Match the tool to the task
- Quick prototype: favour speed and low setup.
- Long-running project: favour tools that handle context and many files well.
- Team work: favour tools that fit shared repositories and review.
Check how recently it was used
A tool people used last week is a better bet than one people used a year ago. Recency tells you it is still working for someone.
Try one on a small project
Give a tool one small, real task. You will learn more in an afternoon than from a week of reading comparisons.
Write down what you find
Note what the tool was good and bad at. Your entries help the next builder, and a tool page that collects them becomes more useful over time.
Keep your own build log
Write numbered entries, follow other builders, and let people watch your idea become real.
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