Notes from an AI-native studio.
Plain-language writing on AI systems, automation, and the parts of running an AI-native studio nobody else seems willing to say out loud.
Your AI brain has a folder problem.
A client runs everything — several businesses, including a SaaS build — inside one AI “brain” vault. The AI kept ignoring the project's own rules, and everyone assumed the AI was the problem. It wasn't. The rules were never in the room. Here's what's actually happening, and what to do about it this week.
When AI can spend your money, you need a gateway — not a promise.
The instinct, when an AI tool quietly burns through money it wasn't meant to, is to tell it to stop. That instinct is the trap. A brake the engine can disengage isn't a brake — it's a request. Here's what an actual control looks like, and how we build it.
Your AI agent doesn't know when to stop.
A client recently got a $2,500 surprise bill from a single tool his AI was using. Half a million calls in a month, most of them asking the same questions over and over. Here's what actually went wrong, and the four guardrails that turn an expensive habit into a predictable line item.
Context is the bottleneck, not the model.
Almost every business I audit has the same problem. It isn't capability. It isn't tooling. It's that the AI doesn't know how the business actually thinks.
I charge less than agencies — on purpose.
Pricing in this industry is mostly a function of labor cost. I removed most of the labor, so I removed most of the cost. Here's why I pass the savings on.
What “AI image and video at scale” actually means.
There's a gap between the demo and the production-grade workflow. Here's how I close it, and what I tell clients to expect.
Field notes, occasionally. No spam, ever.
The occasional plain-language note on what's actually working with AI for small businesses. Want on the list? Reach out and I'll add you.