I build automation systems for businesses. Systems that handle real conversations and workflows around the clock, without a human in the loop. I've been doing this professionally for about 7 months now. Early on I moved fast and patched things as they broke. That's fine for a prototype. It doesn't hold up with real clients. What changed my approach wasn't a new model or a better prompt. It was building discipline into how I work with Claude Code, specifically through skills. I've built 18 of them for my own stack so far. ▸Some skills handle how to write automation logic without breaking what's already working in production. ▸Some define how an AI conversation should move through a qualification flow. ▸Some lock in how edge cases get handled so I stop encountering the same failure twice. ▸Some generate consistent reports straight from raw data. Each one is basically a decision I made after getting something wrong, written down so I don't have to make it again. Before → spending the start of every session rebuilding context and still getting inconsistent output. After → first attempt is usually ready for production. The skills are one part of a bigger picture I've started thinking of as the harness. It's not about the systems I build for clients. It's the controlled environment around how I build them. Project structure, rules, what Claude Code is and isn't allowed to do, how context gets fed in before a session even starts. The goal is that the quality of what comes out doesn't depend on how closely I'm paying attention on any given day. And there will be a loop: taking the systems I've already shipped, running them against realistic scenarios, scoring how they actually hold up in my clients' context, and using that signal to improve what I build next. Still learning a lot of this as I go! If you're building AI systems for real use cases, I'd genuinely love to know how you're thinking about the reliability side.

The past eight months at TrueHorizon AI have been a wild ride. We came out of the gates hot, closing 10 deals in a matter of weeks, only to find ourselves drowning in work and missing deadlines shortly after. Two months later, we made the tough call to shut our doors temporarily so we could fix our internal systems before taking on any new discovery calls. Looking back, I’m actually grateful for those couple of months of chaos. The stress, sleepless nights, and constant pressure forced us to grow. We came out of it with a stronger mindset and a deeper appreciation for good systems, good processes, and good people. In this podcast, my co-founders and I sat down for an hour and a half to reflect on the journey so far. Some moments are lighthearted, others carry real lessons, and throughout we share both the wins and the failures that shaped us. My hope is that you’ll be able to take away some nuggets that help you avoid the same mistakes. Give it a listen, and let me know what you think. Cheers, Nate

Yesterday we wrapped up filming the first ever Agentic Arena in NYC. An AI agent building competition between me and the legendary Jack Roberts… It will premiere on YouTube on September 5th at 3pm EST, make sure to tune in!! We’ll have to see if I was able to bring it home for the AIS family!! 😬 Cheers, Nate

In this video, I'm going to show you how to sell AI workflows without starting an Agency. Most people think they need to start an agency to make money with AI, but that's simply not true. I know this, because I've done it myself. So today I'll be giving you my step by step guide on how to sell AI workflows without starting an agency. Enjoy!

In this video I walk through a live step-by-step build of an AI-powered newsletter using no code. All you have to do is set your search topic and the system takes care of the rest. It starts by doing initial research, then an agent plans out the structure of the newsletter. From there, each section gets its own research and is written by different agents. An editor agent pulls everything together, adds the sources so you know exactly where the information came from, and creates a clean final draft. At the end, the system even sends the draft straight to your inbox so you can forward or share it however you like. I recorded this one live so you can see why I’m connecting nodes, how variables work, and how the whole workflow comes together in about half an hour. RESOURCE PACK HERE