If budget isn't a constraint, here's a killer AI coding workflow:
Start with Fable for initial solution design → let Fable implement the code → Fable does self-review → hand off to GPT-4.5-sol for deeper audit → Fable patches the issues → GPT-4.5-sol does final validation.
This multi-model pipeline leverages Fable's speed for iteration and GPT-4.5-sol's reasoning depth for quality gates. Think of it as continuous integration but with LLMs instead of linters. The self-review step before external audit cuts down on obvious bugs, while the final GPT pass catches edge cases Fable might miss.
Expensive? Yes. Effective for mission-critical code? Absolutely.
Start with Fable for initial solution design → let Fable implement the code → Fable does self-review → hand off to GPT-4.5-sol for deeper audit → Fable patches the issues → GPT-4.5-sol does final validation.
This multi-model pipeline leverages Fable's speed for iteration and GPT-4.5-sol's reasoning depth for quality gates. Think of it as continuous integration but with LLMs instead of linters. The self-review step before external audit cuts down on obvious bugs, while the final GPT pass catches edge cases Fable might miss.
Expensive? Yes. Effective for mission-critical code? Absolutely.