Every tool in your product development life cycle is now an AI agent trying to do everything. Here is how to stop the chaos, draw the right boundaries, and build an orchestrated pipeline that actually works.
A decade-old side project, six major features, one week. How spec-driven AI-assisted development compressed months of work into a focused sprint on a real codebase with real constraints — and where the AI got it wrong.
Anthropic has shipped more meaningful product features in the last few weeks than most teams ship in a quarter. A theory — and what it tells us about what AI-assisted development actually unlocks when a team uses their own product to build it.
Every long-tenured engineering organization inherits decisions that made sense once and make everything harder now. On building IT strategy that outlasts the people who built it — without freezing the org in amber.
I took a production iOS app, pointed Claude Code at it, and had a fully functional Android app in eight hours over a weekend. Here's exactly how it worked.
My wife started making pour-over coffee. I started building her an app. What used to take weeks of Swift development now takes hours with AI-assisted coding. Here's the story of PourCraft, caffeine dependency, and the moment I realized the game has changed.
From 'users want commute alerts' to 1,800 lines of shipped, App Store-ready code in a single coding session. A deep dive into architecture, edge cases, and what AI-assisted iOS development actually looks like.
Generative AI is accelerating open-source adoption while quietly breaking the economic models that sustain it. This is not a tooling problem. It’s a policy and incentive failure.
Andrej Karpathy put words to something many engineers are quietly feeling: we have been handed a powerful alien tool with no manual. Where the leverage is actually moving up the software stack — and what that means for the people writing code right now.
Software gets slower faster than hardware gets faster. Exploring Wirth's Law and why real progress might not be about adding more, but mastering the art of enough.
By coaching LLMs with timeless software design principles like SOLID, DRY, and YAGNI, you can transform raw code generation into consistently clean, maintainable, and production-ready software.