Stop defaulting to one model. Your AI stack should be a toolkit, not a loyalty pledge.

I see developers do this constantly. Pick a model, get comfortable, route everything through it. Every planning session, every line of code, every UI component. That is leaving real money on the table.

Here is the methodology I have settled on.

Start in plan mode. Always. Before a single line of code I use Claude to think through the problem properly. A solid plan means I can hand the actual build to a cheaper model and trust it to execute. Sonnet 4.6 at $3/$15 per million tokens handles most planning tasks well. Save Opus for genuinely complex architecture work.

Gemini for UI and front-end. It has a genuine feel for aesthetics. Consistently produces cleaner UI work faster than anything else I have tried, at solid value.

GPT-5.5 for backend challenges. Built for messy multi-part tasks where you need it to plan, use tools, check its own work, and keep going. Earns its place on hard multi-file problems, but at $5/$30 per million tokens I only reach for it when the problem actually warrants it.

Composer 2.5 as my everyday engine. Near Opus-level coding benchmarks at roughly one-tenth the token cost. Cursor-only, but for day-to-day implementation it is my default. A solid plan from Claude means Composer can execute without burning expensive tokens on reasoning it should not need to do.

Testing goes inside the loop, not onto the end. Test generation is part of every prompt. Write the tests alongside the code, run them in the same agent loop. Catching failures mid-session costs almost nothing. Catching them after three more features are built on top is a different story.

One to watch: Anthropic just released Fable 5, the first publicly available Mythos-class model. Too early for a firm verdict, but the benchmarks are turning heads.

Plan smart. Build cheap. Test continuously. Route the hard stuff to whoever handles it best.