Cost and speed
How we make AI coding more cost efficient without sacrificing task quality
Our short summary of GitHub’s engineering write-up. The full story, with all the detail, is on their blog.
Read the full write-up on github.blog (opens in a new tab)Problem
AI coding features were expensive to run, raising costs for users and limiting scalability.
Solution
They added caching, switched to smaller distilled models, and batched requests, cutting compute while keeping answer quality unchanged.
Want the architecture, code and numbers? They’re in the original post.
Read the full write-up on github.blog (opens in a new tab)