About

Production AI Field Notes is about the engineering that starts after the demo works.

Most AI writing stops at the impressive part. A model answers a hard question, a retrieval pipeline returns something relevant, an agent finishes a multi-step task, and the post ends there. The problems worth writing about begin one step later: the request that fails, the document that went stale six weeks ago, the tool call that should never have been permitted, the bill that quietly tripled.

These notes are about that second half.

How they are written

Each note takes a single production decision and works through it. What usually breaks, why the obvious fix often makes things worse, and what a team can realistically do about it on a Tuesday afternoon.

They are short on purpose. A few minutes of reading, one idea, no attempt at completeness. Nothing here depends on the note before it, although the sequence does build if you read it in order.

There is no vendor angle. Where a specific tool genuinely matters I name it. Where the choice does not matter, I say that instead.

Who writes this

I am Vamsi Krishna Annamreddy. I build AI systems, and I write these notes as I go, largely to force myself to be precise about things I would otherwise wave a hand at.

The series started as a daily discipline: one decision, one note, sixty days. Writing it changed how I build, which is the strongest argument I know for writing anything down.

Where to start

New here? Start Here organises all sixty notes into ten chapters. Read them in order, or jump straight to the chapter that matches whatever is currently on fire.

Prefer to browse by date? The archive has everything.

Getting in touch

If one of these notes changes how you build something, I would genuinely like to hear about it. If you think one of them is wrong, I would like to hear that even more. Corrections get made and credited.