Hey all, I'm Rui. 7+ yrs building web apps and AI stuff, based in the Philippines. Before freelancing I did on-device body tracking at Nex. Lately it's mostly LLM features and AI agents. The model is rarely the hard part. Getting it to say "I don't know" instead of guessing takes most of the time. What are you all working on right now? My work: ruijin2026.vercel.app

You've probably heard it everywhere: start a solo AI business, no team, make a million dollars. And honestly, building really is that easy now, about two hours with Claude or any frontier model. But building was never the hard part. Distribution is. This video breaks down what business owners actually say on real sales calls, and how to sell when you have zero portfolio. • The one-person billion-dollar story isn't quite one person: Medvi's founder started with about $22,000 and did $401M in year one, but his brother and contractors work there, the doctors and pharmacy are run by partner companies, and he paid agencies to buy his ads. The part he kept for himself was the brand, marketing and checkout, everything to do with getting and keeping customers. • What actually kills deals: Nick's team reviewed 19 recorded sales calls with accounting firm owners. The top objections were "I have zero idea what you actually do for me," wanting specific proof ("how many accounting firms have you worked with"), and wanting to know what happens after you leave. Their service was priced at $15,000, and almost nobody said that was too expensive, deals died because owners no-showed the follow-up, usually because they'd never seen a real demo. • The fix for having no portfolio: three things get someone to pay you, demonstration, proof, and a guarantee. You won't have proof yet, so lean on the other two, build a small working version from their public website and send a 2-minute walkthrough video before you even ask for a call. A guarantee rarely closes the deal, it just makes saying yes to that first call easy. My take: the most useful number in here is the reply-rate math. 215 cold emails with zero clients sounds like failure, but on a cold list that's roughly where the first interested reply and first booked call are supposed to land. Most people quit or rebuild the tool right at the point they were supposed to just keep sending. 📎 Full guide PDF pinned below: the full reply-rate benchmarks, the two cold offers broken down, exactly what to charge your first five clients, and the real cost math behind pricing a monthly AI cold email retainer.

Hi there I just joined the community. I saw Nick’s video about using Claude extension with your accounting software. Has anyone used it? Where can I find the code?

Hey everyone! I'm starting an AI Automation Agency and trying to understand how to price my services properly. I'd love to hear from people who are already working with clients and selling automations. A few things I'm particularly curious about: - Setup fees: How much do you typically charge for a standard lead follow-up automation? - Monthly retainers: Do you charge a recurring fee for maintenance, monitoring, and fixing errors? - Platform costs: Do you ask clients to pay for their own Make.com or n8n hosting subscriptions, or include them in your package? - Credits and tokens: Who pays for Make.com credits, OpenAI API tokens, and other usage-based costs? Do you bill clients separately or bundle everything together? - Pricing models: Do you charge a fixed project fee, a monthly subscription, or based on usage? - Client ownership: Do you build automations inside the client's accounts or run them through your own accounts? - Scaling costs: How do you handle increased usage and unexpected API or messaging charges as a client's business grows? I'd especially appreciate examples of how you'd price a relatively simple lead follow-up automation for a small business. I'm trying to build a pricing model that's fair to clients while still making the agency profitable. Thanks in advance for sharing your experiences!

I feel like a lot of people get caught up in building cool AI agents without really asking whether the business actually needs one. For example, imagine a business getting 50–100 enquiries every day. The problem might not be getting more leads at all. It could be that they're taking too long to reply, forgetting to follow up, or wasting time dealing with enquiries that aren't a good fit. Now, you could build a complex AI agent to handle the whole process, but honestly, I don't think everything needs AI. A simple workflow using n8n, webhooks, a CRM, and a little LLM logic could probably handle most of it. Something like: - Capture incoming leads automatically. - Use an LLM to understand the enquiry and qualify the lead. - Update the CRM and assign the lead to the right person. - Trigger follow-ups automatically. - Pass anything complicated to a human. The interesting part is figuring out what actually needs AI and what can be handled with simple rules. Using an LLM for everything just adds cost and more potential points of failure. I also think we should focus more on the results these automations produce rather than just how impressive they look. Things like response time, booked appointments, conversion rates, and hours saved are what really matter to a business. I'm curious about something: When you're building automations for clients, do you usually start by finding a problem in their existing workflow and then build a solution around it, or do you start with an automation idea and see whether the business needs it? Would love to hear how you guys approach this.