Everyone wants cheaper AI. Few know how to build it. Here's the uncomfortable truth: throwing GPUs at problems is expensive and lazy. I've seen teams spend millions on infrastructure when a smarter architecture would've cost 70% less and performed better. 💰 Recently, I implemented a multi-agent solution with 30% lower LLM costs that actually improved quality by 50%. How? By understanding where precision matters and where "good enough" is perfectly fine. Not every task needs