"A production AI stack in TypeScript: what I actually use"
Your product is built in TypeScript and now you want AI features in it. Everyone tells you AI means Python, so you're weighing up a second stack, a second deployment pipeline, and a team split down the middle. You probably don't need any of that — here is the TypeScript stack I actually run in production.
Your product runs on Node, your team writes TypeScript, and now you want to put AI features into it. The advice you'll hear is that AI means Python, so you start pricing up a second service, a second deployment pipeline, and a seam between two codebases that someone has to maintain forever. Before you do that, it's worth being clear about what production AI work actually involves — because for most product teams, it's work TypeScript is genuinely good at.
Have an AI feature stuck between demo and production?
The gap — reliability, evals, cost control, the plumbing that keeps it running unattended — is exactly the work I do. If that sounds familiar, a short conversation is usually enough to point you the right way.
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