AI and Home-Cooked Software

Summary

Everyone is worried that AI will replace programmers. They’re missing the real revolution: AI is turning everyone into one. I’ve been noticing a new pattern: people with deep domain knowledge but no coding experience are now building their own tools. Armed with AI assistants, they can create custom workflows in a matter of days, bypassing traditional development cycles. Are these solutions production-ready? Not even close. But they solve urgent, specific problems, and that’s what matters. Tasks that once required weeks of specialized training are quickly becoming weekend projects. This trend is happening even within the AI companies themselves. Anthropic, for example, shared how their own teams use Claude to accelerate their work. Crucially, this isn’t limited to developers. Their post details how non-technical staff now build their own solutions and create custom automations, providing a powerful real-world example of this new paradigm. 🔗Home-Cooked Software Why search for a generic tool when you can build exactly what you need? This question leads to what I call ‘home-cooked software’: small, personal applications we build for ourselves, tailored to our specific needs. Robin Sloan beautifully describes building an app as making “a home-cooked meal,” while Maggie Appleton writes about “barefoot developers” creating software outside traditional industry structures. What’s new isn’t the concept but the speed and accessibility. With AI, a custom export format, a specific workflow, or the perfect integration is now an afternoon’s work. We’re entering an unprecedented era where the barrier between wanting a tool and having it has nearly vanished. But let’s be clear: the journey from a prototype to a production-ready application is as challenging as ever. In my experience, an AI can churn out a first draft in a few hours, which gets you surprisingly far. But the devil is in the details, and the last stretch of the journey – handling edge cases, ensuring security, and deb...