Ask HN: Have you hit a context ceiling with an LLM? What did you do about it?

For the past few months - since the "long-context" beta feature landed in Cursor - my team has been interacting with Claude 3.5 Sonnet for a wide variety of purposes, from boring code changes to learning about each other and identify our shared goals.

We're a team of 5 musicians with varying degrees of experience in programming (from none at all up to decades of professional experience). We want to build something special to document the indices and historical anchors of bluegrass and other traditional music, and to create economies around them to do better for musicians than the labels and ticketing services have been able/willing to do.

The LLM was like having a sixth member of our team who was able to follow our team members day by day as they have evolved their core competency from guitar and mandolin to javascript and solidity. It's been a wonderful experience.

...but then, late last night, we suddenly started getting "Connection failed" for every message. Through poking and prodding in new chats, and pasting and/or attaching different amounts of the previous chat logs to them, it became obvious that we've hit a context ceiling.

We tried getting our own Anthropic API key, but indeed we hit a token rate limit immediately.

So, my question is: what's next? What needs to evolve or change so that we can have this member of our team who can help interweave the different stages of our journey with respect to programming, music theory, booking shows, etc?

How practical is it for us to write/train our own GPT for this purpose? Is that something to consider in the coming years?