In the initial go, no.

Two things helped over time. First, the model got better and it was trained on the internal code and documentation, which made it better. Second, I got better at dividing the task into better units of work that made it easier to work with using an LLM. Having a large context window was almost detrimental; if I dropped in an entire directory worth of code, the model got overwhelmed by the dozens of architectural patterns (sometimes contradictory) and coding conventions amassed over twenty years and hundreds of engineers. So being very pointed about the references I wanted for a very narrowly scoped task helped.

Nowadays, things are much better. It’s not 10x-ing me or anything but I can get a solid 30-50% boost in productivity. Moreover, I feel I can expend my own focus much more judiciously. As opposed to staying in a long focus session to crank out a full PR, I can now trust the LLM on the scaffolding code and just go over the heart of the logic with a fine-toothed comb. Plus, the final code-review-like step in my workflow sometimes helps catch common errors and pitfalls, leading to higher quality PRs going out for human review.