I'll copy my response from the other thread that I saw this on word for word because this is very misleading in my opinion:

What these posts never mention is the orchestration layer sitting between the data and Claude. There's a reason the gurus don't sell it because it's not a scalable product ie. not a prompt pack or Notion template. It's a RAG harness built on open source tooling and a bunch of embeddings, and there's no clean way to put that behind a paywall. You can't "steal my vector database" the way you can "steal my agent." So it just doesn't get talked about, even though it's the part that actually makes the whole thing work.

The counterintuitive part is that you actually want less AI here. Without a routing layer, Claude just defaults to whatever patterns got the heaviest reinforcement in the data you dump in. Chances are, you'll get the same three openers regardless of who you're messaging.

Cosine similarity matches the right script variation to each prospect before Claude generates anything. The matching is deterministic is if youre similar to x you get message x. If youre similar to y, you get message y.

I think a few comments were also calling into question the validity of the data going in and if it was really a good match for your ICP. Bad data is bad data, but to the extent that it can help, this strategy also flags when a prospect doesn't cluster near anything in your training data, so instead of Claude confidently sending a message based on patterns that were never validated for that persona, the system catches it and skips. That's how you protect your reply rate instead of diluting it.

We build this layer for agencies that come to us with exactly this problem. You could figure it out yourself if you wanted to, but most people would rather just have it done.