Let's build some systems! #AISChallenge

I've just completed the Claude for Non Coders and it's opened up a new world to me! Thank you Nate! Excited to build my AI system along y'all

Officially locked in the new domain for our website. ​Website is getting updated today to showcase exactly how our AI receptionists function. If you manage a local clinic or practice, you can now check out the tech and book a custom voice agent demo directly on the site. ​Landing page is live. Back to the outreach. http://veloroai.agency/

Hey guys, I am on the Claude Pro plan and am building my second brain. That is the main reason I haven't dove right in to Nate's course yet. Do you guys have any insight into how to maximize my token usage and speed this up with background processes as much as possible? Really any tips on how to save tokens and only utilize Claude Code for synthesis? I have followed Nate's advice on token saving tips in his videos and that has helped tremendously already; I am jw if there are any other things I can do to save even more?

I'm the AI consultant for an Australian mortgage brokerage (Sydney, small team). I want an internal assistant every employee can ask about how the company works — our processes/SOPs, which lenders suit which client scenarios, fees, compliance rules, who does what. Where I've got to so far: - Anchor use case: internal SOP/process assistant. Not client-facing. - Access: private login-gated web chat portal — staff sign in with their company email, public can't get in. - Guardrail: it must cite its source and say "I don't have that documented — ask X" rather than guess. We're regulated; a confident wrong answer about lender policy is worse than no answer. - The discovery that changed everything: I audited our Google Drive expecting SOPs. There were almost none — it's all marketing material. The real process knowledge is in the director's head. The bottleneck is content, not tech. - My plan: one curated company knowledge-base doc as the agent's brain (small enough to fit in the model's context, so no vector DB), an admin screen to edit it, and logging every question the agent can't answer — that log becomes the prioritised list of what to document next, so it bootstraps itself. What I'd love input on: 1. Is "whole KB in the system prompt, skip RAG" sane for a small company KB? At what size does that break and force vector search? 2. How did you get knowledge out of people's heads? This is my real blocker. Interviews? Recording client calls and mining them? What actually worked? 3. Anyone shipped this with no-code (Custom GPT / Claude Project / n8n) vs. a custom app? Where's the line where custom becomes worth it? 4. For a small team, is a login-gated custom app overkill vs. just sharing a Claude Project with team seats? 5. War stories: what killed adoption of an internal agent? What made staff actually trust it? Stack: Next.js + Supabase + Vercel, Claude API. Happy to share back what I learn.