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Topic

ai-tools

18 essays on this topic.

  1. The Anti-Slop Pattern

    Most AI skill prompts say 'make it good.' The ones that actually work say 'here are the 22 things you'll reach for first — reject all of them.'

  2. The Name Collision That Found Two Tools

    When a dispatcher and an executor share a name, you don't have a naming problem. You have an architecture problem.

  3. When the Name Doesn't Fit

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

  4. Workflows, Not Containers

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

  5. Inline Beats Reference for LLM Attention

    When building AI scaffolding, put the knowledge where the decision happens — not in a reference the model is supposed to consult.

  6. The Silence of Missing Skills

    The most dangerous failures in AI scaffolding are the ones that look like nothing happened.

  7. The Immune System Pattern

    What biology already knows about self-healing systems, and why your automation probably isn't one

  8. The Lamp That Knows You

    Disaster recovery for an AI-native workflow isn't about servers — it's about restoring a relationship.

  9. When Your Life OS Becomes the Life

    The real risk of building a personal AI operating system isn't that a better tool appears — it's that your system's complexity becomes the thing you maintain instead of the thing that maintains you.

  10. I Made AI Remember to Remember

    Most AI memory is either always-on or ephemeral. The missing category is prospective: remember until a context arises, then forget.

  11. Default to the Whole Conversation

    When AI tools search conversation history, they should index both sides by default — not just the human's half.

  12. Save Conclusions, Not Just Rules

    When an answer requires multi-step reasoning to reach, save the conclusion — a fresh start won't reliably reproduce the chain.

  13. Hooks Are Life Infrastructure

    Event-driven hooks in AI coding tools aren't just for linting — they're programmable triggers for life routines, habits, and systems.

  14. Your AI Tools Should Watch You Fumble

    The best time to improve a CLI isn't when it breaks — it's when you review the breakage log at the end of a work session.

  15. Building a Bus Alert System in One Session

    How a real need on a Hong Kong bus turned into a GPS-powered alert system in under two hours

  16. The Wrong Metric: Why I Stopped Switching AI Models Mid-Session

    Per-task model routing optimises cost per token. But at personal assistant scale, friction is the real cost.

  17. The Queue Should Live Where Your Thoughts Live

    AI agent results should be push, not pull. The feedback loop should close on mobile. Most tools miss all three — not from ignorance, but because dashboards photograph better.

  18. The Queue That Texts You Back

    Personal AI infrastructure should report results to you, not wait for you to go looking. A small architecture shift changes the whole dynamic.