You can even not have any data layer all together. The only thing missing from a local LLM is knowledge of current medications by name if you want to just say whatever prescription you’re following.

What part requires perfect precision?

If you want to parse sensor data, you do it in code before the LLM sees it.

For sure, context rot is a problem, but that’s also the easiest thing to control for in this case. If sensor data is relevant to you, having some code to process and reduce it to a dashboard you can read is always a good idea, independently of getting an LLM into the loop.

This becomes more complicated with data you can’t really understand like results from blood tests, for example. But maybe you just don’t summarize any of that.

What we can call a health advisor is not a doctor. In fact, depending on the model, it will actively point you to seek medical help.