I’ve got 15 years of coding experience at some of the biggest tech companies. My personal opinion is that most people have no clue how good these AI coding systems already are. If you use something like RepoPrompt, where you selectively choose which files to include in the prompt, and then also provide a clear description of what changes you want to make—along with a significant portion of the source code—a model like O1Pro will nail the solution the first time.

The real issue is that people are not providing proper context to the models. Take any random coding library you’re interfacing with, like a Postgres database connection client. The LLM isn’t going to inherently know all of the different configurations and nuances of that client. However, if you pass in the source code for the client along with the relevant portions of your own codebase, you’re equipping the model with the exact information it needs.

Every time you do this, including a large prompt size—maybe 50,000 to 100,000 tokens—you dramatically improve the model’s ability to generate an accurate and useful response. With a strong model like O1Pro, the results can be exceptional. The key isn’t that these models are incapable; it’s that users aren’t feeding them the right data.