Obaron started as a Docs Readiness Audit — a measurement instrument for whether AI agents could find and use a company’s content. The rubric was real. The score was useful. Customers who ran it learned things.
But the same conversation kept happening on the other side of the report: okay, now what? A scan tells you what’s wrong. It doesn’t change how the work gets done. The thing the buyer actually needed was someone to wire the tools into the week — and then stand by them while they ran.
So as of 2026-05-15, Obaron is that. An AI automation practice for SMBs and founders. We automate the dull work so you can do the amazing work.
What changed
The rubric isn’t the product anymore. The install is.
The frame I keep reaching for — and that the longer personal version of this walks through more fully — is the dull work and the amazing work. The dull work has rules and patterns. Triage this, sort that, draft the follow-up, pull the weekly numbers. A machine that can follow rules can do all of it well enough that the time you get back is real. The amazing work requires you specifically — your read of the customer, your taste, the conversation that only lands with a real person on the other end.
AI doesn’t touch that. It clears the path to it. That’s the whole point.
Three arms, one through-line
Obaron now runs on three arms:
Practice (concierge). We install the automation — voice systems, capture pipelines, intake automation, ops orchestration — with a per-customer Discord or IG bot as the interface. Concierge setup, monthly retainer — book a discovery call and we’ll scope it. A few partners at a time today. That’s current capacity, hands-on with every install, not a permanent cap.
Scanner. Deterministic tools for what AI can see and act on across your surfaces. Image Check + Fix is in internal preview right now. Accessibility Check is in build. Messaging Alignment and AEO Checks are in design. Per-page metered. The “+Fix” pattern is the concierge remediation companion to a Check — the hand-done version of fixing what the Check found.
Obaron Academy. Training for small teams actually deploying Claude in their business. Anthropic-first curriculum, in development.
The legacy AEO Audit pipeline is still live at obaron.ai — it’s the infrastructure the scanner platform is refactoring on top of. The methodology work that lived in the older posts on this blog (archived now, with banners) seeded the engine. It didn’t go away. It became the substrate.
Obaron is the guinea pig
The dogfood discipline matters. Every Check runs on Obaron’s own surfaces before it ships to a customer. The inbox triage running on my own work right now is the same pattern I’d install for someone else. The approval queue is the discipline I teach, applied to me first: AI drafts. You decide what ships.
That’s not a marketing posture. It’s the only honest way to know whether the install actually works.
The shape of the opportunity
A vegan cheese company recently saved $40,000 a month by running an agent that catches shipping overcharges. Not a moonshot. Not a model breakthrough. Someone mapped a recurring task that lived at the bottom of the priority list, wired an agent to it, and the money was sitting there.
That’s the shape of every install we’re doing. The tools are good enough. What’s missing is the install.
What you’ll see here
This blog goes back into motion now that the shape is clearer. Expect:
- Notes from real installs (with customer permission and details abstracted).
- Check releases — what the Check sees, what the Fix companion does, what we’re still figuring out.
- Working-in-public posts on the scanner platform refactor and the Academy curriculum.
Less methodology-internals essays. More what-shipped, what-broke, what-we-learned.
If you want to know what an install looks like for your business, book a discovery call. We start by mapping your week.