You don't need to understand how the model works internally to make an agentic coding tool. You just need to understand how the APIs work to interface with the model and then comprehend how the model behaves given different prompts so you can use it effectively to get things done. No Machine Learning previous experience necessary.

Start small, hit issues, fix them, add features, iterate, just like any other software.

There's also a handful of smaller open source agentic tools out there which you can start from, or just join their community, rather than writing your own.

It's hardly a subset. Most devs that use it have no idea how it works under the hood. If a large portion of them did, then maybe they'd cut out the "It REALLY IS THINKING!!!" posting

what you are doing is largely a free text=> structured api call and back, more than anything else.

ML related stuff isnt going to matter a ton since for most cases an LLM inference is you making an API call

web scraping is probably the most similar thing