People sometimes ask why I seem to switch AI build tools so often. It is not indecision. It is that the tooling is moving fast enough that standing still is its own risk.
My own path through it: I started with Google AI Studio and the Google AI suite. Moved to Claude Code. Then went through a real stretch of trying almost everything: Windsurf, a long run with Lovable, Replit, Bolt, Emergent, Base44, Adalo. Each one taught me something about what a good AI build workflow actually needs, usually by being missing exactly one thing I only noticed once I hit it. Eventually I came back and settled on Claude Code as the core of how I build.
But settling did not mean picking a single tool. What I actually run today is a hybrid setup across three stacks, not one: a Claude Code stack, a Codex stack, and an OpenCode stack, with a local fallback in place, Ollama, for when I need something that does not depend on any of the hosted services being up.
The reasoning is simple once you have been burned by relying on a single tool. Different stacks are strong in different places, pricing and rate limits change without warning, and a fallback that does not depend on anyone else's infrastructure is the difference between losing an afternoon and losing nothing. It is the same instinct as staging QA honestly: build in the redundancy before you need it, not after.
So the stack keeps changing because I keep learning where each tool's edges are, and because the tools themselves keep shipping meaningful changes every few months. I do not think that is going to slow down soon, and I have stopped treating it as a problem to solve. It is just the current cost of building at the edge of what these tools can do, and having a hybrid setup with a real fallback is how I stopped feeling that cost every time one part of the stack has a bad day.