Skip to content

Writing

Engineering notes

What we have learned building AI agents, retrieval systems, automation pipelines and production software. Specifics over abstractions — including the parts that did not work.

If a note raises a question about your own stack, tell us what you are building.

17 notes shown.

AI Engineering

Prompt Injection in Agent Systems: Trust Boundaries, Not Detectors

An injection is not a jailbreak and it is not a prompt problem: a model enforces no boundary between the instructions it should obey and the data it should only read. The fix is an access-control one — break the capability combination, resolve the plan before exposure, carry provenance in code, and treat the renderer as an egress boundary.

12 min read
AI Engineering

Agent Step Budgets: Stopping a Run Without Losing the Work

A cap that raises an exception throws away everything the run learned; a cap reported as success hides the gap. Where the step counter belongs, how to see a loop before it reaches the ceiling, and what a truncated run owes the caller.

10 min read
Engineering Practice

Flaky End-to-End Tests: Isolation, Determinism and Quarantine

A test that fails one run in four and passes on re-run is usually a defect with a working alarm. Retries hide the evidence, quarantine files it — and the classification decides which fix you actually need.

9 min read
AI Engineering

Eval Gates in CI: Catching LLM Quality Regressions Before They Ship

A non-deterministic system graded by a non-deterministic judge produces a check that either blocks every merge or is ignored. How we build eval gates that survive: deterministic checks as the gate, a measured noise floor, critical slices that block on a single case, and a judge kept advisory.

10 min read
Engineering Practice

Code Review in the Age of AI-Generated Code

Review used to be a conversation between two people who had both thought about the problem. That contract is broken, and most teams have not replaced it with anything.

9 min read
AI Engineering

Building RAG Systems That Work in Production

Retrieve the chunks for a failing question and read them. Nine times out of ten the answer passage is simply not there — the generator was never the problem.

10 min read