*Most AI dev tools have the same bad habit: *
send everything to the biggest model available and hope the bill feels reasonable later.
That works for demos. It doesn't work when you're actually building something.
A five-line hello world should not cost the same as reviewing auth middleware touching JWTs, SQL, async flows, and environment variables. But a lot of tools treat every snippet like a production incident. Same model, same cost, every time — regardless of what the code actually is.
That was the problem we kept running into while building Refyn. We were working under real time pressure, and the fastest way to burn both budget and reliability was dumb routing. We'd already watched Gemini fail completely — four supposedly valid API keys from three different Google accounts, all returning "API key not valid." To this day we don't know why. Then a Groq model got decommissioned mid-testing, mid-session, with a 400 error and no warning. After that, "just send everything to one model" stopped sounding simple. It started sounding fragile.
