Are AI coding tools expensive because of tokens, or because of messy context?

I’m working on Mazora, and the more I talk to people building with Cursor, Claude Code, Codex, Lovable, and Bolt, the more I think the problem is not always the model.

Sometimes the real problem is context drift.

You start with a rough idea.
Then a few prompts.
Then some generated files.
Then fixes.
Then more prompts.
Then suddenly the product logic lives across chats, docs, screenshots, and your head.

At that point, the agent keeps re-learning the same thing:

• who the users are

• what each role can do

• how the flows work

• what rules and permissions exist

• what edge cases matter

• what it should not invent

That means more retries, more corrections, and more wasted tokens.

Mazora is my attempt to solve that layer: turn a messy MVP into a reusable context blueprint and Agent Context Pack before the next AI coding session.

Curious how others handle this:

Do you keep a structured context doc for your AI coding agents, or do you mostly re-explain things every session?