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AI controls, agent systems, banking governance, production practice. 412 essays, newest first.

  1. AI Controls Architecture

    Risk teams know risk. The open problem is designing controls for systems that are non-deterministic, probabilistic, and attackable in natural language.

  2. Governing Agents the Way Cells Govern Themselves

    Six cell biology mechanisms that reveal what the networking 'control plane' metaphor misses about governing AI agents.

  3. The Risk Without an Engineering Solution

    Every other agentic AI risk has an engineering answer. Prompt injection doesn't. That changes everything about how you design controls.

2026
  1. When the Name Doesn't Fit

    Naming as a design constraint: if a tool resists a name, the tool needs redesigning, not the name.

  2. The rename that built a tool

    I renamed one concept across 130 files. The pain crystallized into a tool that will do the next rename in minutes.

  3. Always latest as a system property

    Most projects pin dependency versions to avoid breakage. We automated the opposite: daily upgrades with automatic rollback.

  4. The dispatch layer was eating the quality, not the model

    We blamed the LLM for a 54% task failure rate. The real culprit was seven layers of dispatch infrastructure between intent and execution.

  5. Governance Is a Design Problem

    Compliance-first governance produces paperwork. Design-first governance produces systems you can actually explain to a regulator.

  6. The Cell Biology Agent Design Manual

    Engineering metaphors give you clean abstractions. Biology gives you resilient ones. Twenty design heuristics from four billion years of R&D.

  7. Split on Access Control, Not Abstraction

    Repo boundaries enforce access control, not abstraction. Directories handle abstraction. If two things have the same visibility requirement, they belong in the same repo.

  8. Budding

    Every other component in the organism had a biological name. Agents didn't. Three failed attempts and a yeast cell later, they do.

  9. Enzyme, Receptor, Cell Type

    Three components of a living system map cleanly to tool, skill, and agent. The biology isn't decoration -- it's the test.

  10. Autopoiesis

    The defining property of life is not metabolism or reproduction -- it's autopoiesis. A system that continuously produces and maintains itself. That's the north star.

  11. Titration

    Force every component to carry a biological name. Study the mechanism. The gap between biology and your system is the design insight.

  12. The Architecture Biopsy

    A method for finding gaps in AI systems that architecture reviews miss. Force a naming constraint, and the breaks reveal what's missing.

  13. Why the Cell

    Atoms have forces. Molecules have shape. Cells have organization. That's why cell biology is the design library.

  14. Force the Level

    Pick one biological level for all your naming. The constraint is the design exercise.

  15. Growing Up

    The LLM isn't dark matter. It isn't borrowed. It's a brain. The organism just needs to grow up.

  16. The Borrowed Brain

    The LLM isn't dark matter. Biology invented general-purpose reasoning. It's called a brain. We're just borrowing one.

  17. The Dark Matter of the Cell

    Everything in my AI system maps to cell biology. Except the LLM. That's the point.

  18. Naming the Unnameable

    I tried to give LLMs a biological name. Every name broke. The failure was the finding.

  19. There Is No LLM in a Cell

    Cells run thousands of simultaneous reactions without general-purpose reasoning. Shape is enough.

  20. Tools Are Instruments, Skills Are Recipes

    The tool/skill/agent distinction isn't just compression ratio — tools are instruments, skills compose them with judgment. Same thing only at the leaf.

  21. The Boundary Is an Assessment

    The tool/skill distinction isn't a property of the capability. It's a property of the context it operates in.

  22. The Test Before the Output

    The line between tool and skill is whether you can write the test before seeing the result.

  23. Judgment Is a Moving Boundary

    The line between tool and skill isn't a property of the task. It's a property of how well you understand the task.

  24. Skills Should Die

    Every AI skill should be trying to make itself unnecessary. The ones that survive are the ones that haven't been understood yet.

  25. The LLM Is the Tool

    When the transformation is predictable, the LLM is just a runtime. A cheaper, more flexible runtime than custom code.

  26. Workflows, Not Containers

    AI coding tools give you boxes to put things in. Biology suggests you should be thinking about how things flow instead.

  27. Naming Is a Design Review

    Every biological name is a testable hypothesis about what your system should do.

  28. Bridge or Seed

    Every skill you build is one of two things. Knowing which changes what you build next.

  29. Your Variable Names Should Be a Toy

    INTERFACE_ONLY is a label. MEMBRANE_EMBEDDED is a toy — it makes you think about WHY those names can't be swapped. The best variable names don't just describe what something is. They make you think about what it does.

  30. Name Your System After Biology, Then Rename It

    Force your software's vocabulary into a biological framework. The gaps between the mapping and your system are design questions you'd never otherwise ask. Then switch to a different framework and ask different questions.