Sounds like you’ve been bumping into the same wall and asking the same questions.

Since I switched to this layered setup, the amount of “cleaning up after the programmer” dropped a lot. The programmer‑AI has become much more obedient, and most of the real fights now happen with the architect‑AI instead.

You’re absolutely right that it’s hard to front‑load enough architectural thinking. That’s also why this project raced its way to version 12 so quickly – every time the architecture felt wrong, I forced myself to rethink and re‑document it, not just patch the code.

On the token/pricing side, I honestly haven’t thought too hard about the exact math. One way or another, we’re all just helping to pay Nvidia’s bills, right?

Fair point – 30k LOC by itself isn’t “complex” in any absolute sense. In my case the difficulty isn’t the raw size, it’s:

long‑running experiments and measurement contracts that span many modules,

an evolving research agenda (I’m at V12 now, with quite a few pivots along the way),

and the fact that I’m doing all the design + implementation solo.

I agree that when something feels complex at this scale, it’s often a sign the structure needs to be simplified and unified. A big part of what I use the “architect” agent for is exactly that: forcing myself to rewrite and consolidate interfaces instead of just piling on more code.

It’s iterative, not a strict waterfall, but the constraint is “text first, code second”.

A typical loop looks like this:

I talk with Perplexity/ChatGPT to clarify the requirement and trade‑offs.

The “architect” Cursor window writes a short design note: intent, invariants, interfaces, and a checklist of concrete tasks.

The “programmer” Cursor window implements those tasks, one by one, and I run tests / small experiments.

If something feels off, I paste the diff and the behavior back to the architect and we adjust the design note, then iterate.

There is a feedback channel from “programmer” to “architect”, but it goes through me. When the programmer model runs into something that doesn’t fit (“this API doesn’t exist”, “these two modules define similar concepts in different ways”, etc.), I capture that as:

comments in the code (“this conflicts with X”), and

updates to the architecture doc (“rename Y to Z, merge these two concepts”, “deprecate this path”, etc.).

So the architect is not infallible. It gets corrected by reality: tests failing, code being awkward to write, or new edge cases showing up. The main thing the process enforces is that those corrections are written down in prose first, so future changes don’t silently drift away from whatever the system used to be.

In that sense the “programmer” complains the same way human ones do: by making the spec look obviously wrong when you try to implement it.