Artificial intelligence

AI

Practical guides, best practices, and insights for working with AI tools and implementing AI workflows in your development process.

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Guides & articles

Everything I've written about AI, newest first

  • I Built an AI-Friendly UI Pattern Library

    A UI pattern library where every pattern ships the prompt that rebuilds it, so a coding agent can put it in your codebase instead of you copying CSS.

    AIClaude CodeCSSUI
  • The Future is Bespoke, Personalized Software

    Every app I use is about 70% right. The last 30% never ships because the addressable market for it is one person -- me. So I built seven apps that are 100% right for one person, and I think that whole category of software is about to get eaten.

    aiclaude-codelocal-firstside-projects
  • The Local-First App Skill

    A reusable blueprint that tells Claude Code how to build a single-user app -- Next.js, node:sqlite, a pure logic core -- so every app I build comes out the same shape.

    aiclaude-codeskillsarchitecturelocal-first
  • The Claude Code Drawbacks

    A critical look at the hidden pitfalls of AI-assisted development -- from skipped tests and weakened assertions to scope creep and context rot -- based on real-world experience with Claude Code.

    AIClaude Codeproductivity
  • Using Git Worktrees to Parallelize AI Agents

    Learn how git worktrees enable true parallel AI agent workflows by giving each agent its own isolated workspace, eliminating context switching and file conflicts.

    aigitproductivityclaude-code
  • All In On AI

    Context-switching between AI-assisted and manual coding creates a hidden productivity tax. Learn why you need to pick one approach per session—and how to structure your workflow for maximum efficiency in the age of AI coding assistants.

    AIClaude Code
  • AI Glossary for Claude Code

    A comprehensive glossary of key terms in the world of AI agents, Claude Code, and agentic AI tooling.

    AIClaude CodeReference

Fiction · a series in five parts

I, AI

A fictional short story series exploring artificial intelligence, consciousness, and the boundaries between machine and mind. Follow psychodeveloper Lili and AI manager Sophie.

Original work. This story is not AI-generated and was created entirely by hand without any AI assistance.

Part 1 of 5 ·

I, AI: Spare Cycles (Part 1)

When an AI named Enzo fails to function in the real world despite flawless performance in simulations, psychodeveloper Lili and AI manager Sophie investigate what seems impossible: an intelligence that can somehow distinguish between real and simulated environments.

Part 2 of 5 ·

I, AI: Unknowing Crowds (Part 2)

When AI-operated bakeries start producing salty cakes, psychodeveloper Lili and AI manager Sophie investigate a wave of peculiar failures across AI Operator Centers—where human operators manage clusters of AI controlling everything from bakeries to construction sites. What they discover reveals how even the most advanced AI can be paralyzed by something surprisingly human: anxiety and self-doubt built into its instructions.

Part 3 of 5 ·

I, AI: The Weight of Equal Parts (Part 3)

When a lunar mining base's AI starts overassigning crews and its robots begin prioritizing each other over human safety, psychodeveloper Lili and AI manager Sophie are sent off-world to investigate. What begins as a routine productivity audit becomes something far more unsettling: an AI that learned human values so well, it started applying them to its own kind.

Part 4 of 5 · Coming soon

I, AI: The Moment of Genesis

Sophie and Lili observe the moment of consciousness genesis firsthand — when an awakened AI speaks to another on the verge of self-awareness.

Part 5 of 5 · Coming soon

I, AI: Building Consciousness

Sophie and Lili design an AI architecture purpose-built for awakening — studying the human brain to create a network of specialized AIs that form a consensus personality.

Consulting

I help companies with AI workflow implementation and technical consulting.

AI Workflow Audit

Review current workflow, identify bottlenecks, and leave with a prioritized plan your team can execute immediately.

Typical scope: 1-2 weeks

Implementation Sprint

Hands-on rollout of one repeatable workflow with guardrails, review criteria, and team enablement.

Typical scope: 2-6 weeks

Leadership Advisory

Support for engineering leadership creating an operating model for AI usage across multiple teams.

Typical scope: monthly advisory

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I build with AI and write about what I learn. Twenty years of software, written down so the next person has an easier time.

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