An AI engineering studio. Built in public.
Cuecoder is a focused AI engineering studio. The work is narrow and deep: production-grade infrastructure for AI features, with a bias toward what ships. No advisory work. No threads. No frameworks invented just to have a framework.
The output is three things — a SaaS portfolio of AI infrastructure tools, an open-source toolchain under cuecoder/, and a weekly newsletter with field notes from running them. Everything stays under one roof because the lessons compound.
If your team is shipping AI features and stuck on infra, evals, or retrieval — Cuecoder takes on one infrastructure engagement per quarter. Otherwise the fastest way to follow along is the newsletter.
How Cuecoder works.
Ship the eval, not the demo.
Every AI feature begins with the eval suite. If it can't be measured, it isn't shipped. The eval is the spec.
Open-source the toolchain. Sell the leverage.
The pieces every team needs are free under MIT. The pieces that take operational effort are SaaS. Both move together.
Public commits. Public revenue. Public incidents.
Building in the open is a forcing function for taste. Numbers update live. Postmortems are published. The work stays honest.
One toolchain, many products.
Every Cuecoder product runs on cue. The compounding cost of consistency is exactly the moat.
Narrow, deep, slow.
No advisory roles. No moonshots without revenue. No invented complexity. Most weeks Cuecoder ships one thing well.