No single model is best at everything, and switching between them by hand is its own tax. This is the stack I settled on for letting Codex, Claude, and GPT each do what they're good at, behind one consistent workflow.

The idea

Treat the models as interchangeable engines behind a stable interface. The workflow — how I describe a task, review a diff, and verify it — stays the same regardless of which model is doing the work. Only the engine changes.

Roles

• Planning & long-context reasoning goes to the model that holds the most context without losing the thread.
• Tight, iterative edits go to whichever model is fastest to verify against a live preview.
• Verification is never skipped — every change is run and observed, not trusted.

task → plan → edit → run → observe → repeat

Why it holds up

Because the workflow is the constant and the model is the variable, swapping in a better model later costs nothing. The investment is in the process, not in any one provider — which is the whole point.