Hey everyone — new here, just joined yesterday. Figured I'd share what I'm working on instead of just lurking. I run Inspire Applied, an advanced prototyping shop in Massachusetts. Lasers, 3D printing, CNC, the works. Last year I started building an AI agent that handles the front end of the business — quoting, qualifying projects, routing work, logging, follow-ups, even content. The agent lives at https://makerasaservice.defyimpossible.tech/ — if you visit, you're talking to it directly. It quotes your project, qualifies the work, and when you're ready, the physical shop executes. No chatbot handoff to a human. The AI is the interface between the customer and the machines. What it does right now: - Takes project descriptions and generates quotes in minutes - Connects to Gmail, Calendar, Drive, GitHub, Notion, YouTube, LinkedIn - Logs everything, remembers context across sessions - Routes work to the right machine/process - Handles the full customer conversation What I'm working on: - Tighter integration with shop floor systems (machine status, scheduling) - Automated content generation from completed jobs - Deeper qualification logic (material selection, tolerances, cost optimization) Would love feedback from people who've built or are building persistent agents — especially ones that connect to physical systems. What's working? What's breaking? What would you do differently?

Hey everyone, This might be the most valuable lesson we’ve released in this series. Because this is the difference between building an actual AI agency… And getting stuck in the endless cycle of one-off projects. Most people land a client. They build the automation. They get paid once. Then they’re straight back to chasing the next deal. No predictability. No compounding. No real business. That’s why so many people get a few clients early, hit the wall a few months in, and convince themselves “AI agencies don’t work.” But the problem usually isn’t the opportunity. It’s the model. At Morningside, shifting to retainers has helped us make 6x more from clients in the last 6 months. Jennifer just landed a solar client at $4,000/month USD. Anton just signed a large insurance company at $10,000/month. And at Morningside, we currently have a client paying $45,000/month. Month after month, these clients continue to pay. Then, as new clients come in, the revenue starts to stack. The pressure of needing to find a brand new client every single month starts to disappear. That is the power of the retainer model. And in today’s free lesson, we break down the exact 3-step process we use to turn AI projects into monthly retainers. I genuinely don’t believe an AI agency can succeed long term without this. So if you only watch one lesson from this series, make it this one. Click below, watch the free training, take notes, and start implementing it. https://aios.aaaaccelerator.com/retainer-s ​ I’m leaving it up for the next 24 hours. Happy building, Liam.