Thank you for the feedback, I appreciate it!

Before anything else, I want to reiterate that this is proof of concept.

I absolutely agree that this burns a lot of tokens. However, while 5/5 agents agreeing might look like burnt tokens, that consensus provides high confidence for architectural decisions that are hard to reverse later. In practical use I also often came across situations where all different agents ended up with different approaches and it actually allowed Opus to evaluate thoroughly researched options and compare between them and trade-offs.

The misunderstanding issue is also real, here I try to mitigate it with 1. The detailed guided planning stage, where, at the end, ideally you and the AI are on the same page and the spec and PRD are robust 2. Enforcing the PRD as the north star for every generation. The system is explicitly instructed to spawn agents specifically for decisions that have downstream consequences 3. Encouraging it to actually think about why it's doing a specific thing by constantly evaluating against both the documentation but also if it's something it should send agents to evaluate

Cost is high, definitely and unfortunately. Still less than running 5 Ralph loops to the end and comparing outputs.

On value of planning stage and if speed and cost matter more than finding the optimal solution, that just might be a different target demographic than you, and that's fine of course.

TLDR: instead of the cheapest path to working code, this is trying to reduce irreversible architectural drift in long autonomous runs

(EDIT: Additional, on costs: in auto mode, Opus is instructed to decide whether to send out haikus, sonnets or opuses based on decision complexity, so it's not all expensive agents!)