The Developer's Guide to Picking the Right Coding LLM at Scale
Six months ago, I was staring at our monthly AI bill — $14,000 and climbing fast. We were using the "premium" model for everything, including trivial code completions. That night, I built a small internal benchmark to figure out which models actually earn their cost. What I learned reshaped how we think about AI tooling, vendor lock-in, and what "production-ready" really means.
Here's the raw truth from my testing rig, what we shipped, and how we cut costs by 70% without touching output quality.
Why I Stopped Trusting Default Recommendations
Every vendor says their model is the best. Every benchmark site ranks things differently. Most "best of" lists are either sponsored or built on vibes. I needed numbers that matched my actual workflow: generating Python services, debugging JavaScript race conditions, implementing TypeScript algorithms, and reviewing Go for security.
