I run my businesses with a team of AI agents I built. Now I build them for yours.

My first business was music, and I made my living from it until AI arrived and the industry I knew was gone. Most people in my position tried to compete with AI, but I decided to put it to work, so I stopped asking what AI could write and started asking what it could run.

So I started building. I set up a team of AI agents and gave each one jobs I used to do by hand, like release prep, posting, code passes and reports. They work around the clock and get better every week, and I still make the calls.

I never hired that team. I built it.

Real businesses, not demos

Other AI services will show you demos with a lot of flashy cuts. I'd rather show you the businesses I built with my agents, and what the agents do in each one.

• The Pixel Philharmonic, an orchestral music channel on YouTube, with 5.38 million views in the last twelve months and more than a quarter of a million hours watched. I write the music, and the agents handle release prep, titles, scheduling, posting and analytics.
• PixelRadio, our own music streaming service for the whole catalogue of 339 tracks on the web and on Android. The agents wrote the code and add each new release.
• Bravemech: The Century War, a mech action RPG that I design and direct, in Early Access with a free demo on Steam and still being built. The agents take implementation passes on the code, the art, the store copy and the patch notes. So far it has 125,738 Steam store impressions and 12,800 store page visits.

None of this replaced me. The agents do the jobs an employee would, and I decide what we make, what is good enough and what ships. That's the same setup I build for clients, from a restaurant to a property developer.

Before AI, one person couldn't have kept this many projects moving. I can, because the routine work is assigned to agents and I check what they hand back.

Working businesses, not experiments

These businesses have real customers, release schedules and reports, so the agents' work gets tested against real results every week. Clients get the same setup. We take the routine work that eats their week, give it to an agent with a named job, and their staff approve what goes out.

The harder question was how you keep that work accurate when nobody is watching every step. The answer is internal systems, meaning knowledge that stays current, numbers checked against the record and customers answered in minutes at any hour, and the first job usually takes a few weeks to build.

Why you can trust it

Most people don't trust AI yet, and I think they're right not to. A language model on its own is guessing, so ask it how much a client owes you and it gives you a confident number, and ask again and you might get a different one.

Your AgentSmith is different because of harness engineering. The model decides what needs to be done, and the harness makes real tools do the work. Our agent isn't allowed to guess a balance. It has to pull the actual invoices from your accounting system, add them up with real code and check the total against the ledger before anyone sees it. If a check fails, it stops and flags it instead of making something up.

Why I do this

I know what it feels like to face an uncertain future because of AI. I want to help your business catch up to what AI can already do, without the guesswork and without you having to become technical.

So here is the offer. Show us the problem you have been living with, we will build the system that solves it, and we will run it with you.