There is a strange gap in AI right now. It has never been easier to build a demo that looks like magic — and it has never been harder to ship one that survives contact with real users.
A weekend prototype that answers questions over your documents is a pip install and forty lines away. Turning that into something that is fast, correct, observable, and affordable at scale is a different discipline entirely. That discipline is AI engineering, and it is what PieceOfCode is about.
What we actually do
We are a small studio that designs and builds production-grade AI systems: retrieval pipelines, autonomous agents, and the infrastructure that keeps them honest. We care about the parts that don't demo well but decide whether a system is trustworthy:
- Evaluation harnesses that catch regressions before your users do
- Retrieval that stays relevant as your corpus grows past the toy dataset
- Agents with guardrails, budgets, and a clear failure story
- Latency and cost budgets treated as first-class requirements
Building in public
Every system we build teaches us something worth writing down. So we write it down — here. No gated whitepapers, no "book a demo to learn more." Just the working piece of code, the reasoning behind it, and the trade-offs we made.
If that sounds like the kind of engineering you want on your side, start a conversation. Otherwise, stick around and read — that's what this site is for.