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Long-form on modern production systems.

Essays on the practices, patterns, and principles that make software production durable. Filed by topic, written to be referenced more than once.

  1. AI Engineering

    Fail Fast, Consolidate Faster

    Modern organizations have become very good at trying new technology and much less disciplined at absorbing it. In the AI era, the risk is not experimentation itself, but experimentation without consolidation.

  2. Platforms

    Platforms Are Paved Roads, Not Walled Gardens

    Internal platforms succeed when they pave the road most teams want to walk and fail when they wall off every other path. A platform that cannot be bypassed is a platform nobody trusts. The work is making the default obvious and keeping the exit honest.

  3. AI Engineering

    AI Engineering Needs Audit, Not Faith

    Useful AI in engineering keeps the same property useful tests have: a human can read what happened, where it went wrong, and decide what to do next. The argument is not that AI is dangerous. It is that anything shipping to production has to be inspectable when it fails.

  4. SRE

    SLOs Are a Reliability Question, Not a Number

    A service-level objective is not a number on a dashboard. It is an answer to the question 'how reliable is reliable enough — and to whom?' Without that framing, the math becomes reliability theater.

  5. DevOps

    DevOps Is a Production Line

    DevOps is not a tooling movement. It is the cultural import of a hundred years of production engineering into software — and reading it that way makes the discipline coherent again.