Your AI Architect: one person who owns the plan, builds the pieces, and runs your stack.
IBM’s 2026 survey of 2,000 CEOs found three quarters of large companies are hiring a Chief AI Officer this year. For a 50-person organization that math is nonsense. But the underlying problem is real, and it’s actually worse at your scale: most of your team could probably use AI productively, but nobody is connecting them to the workflows that need it.
An AI Architect is a fractional AI lead for organizations too small to justify a full-time Chief AI Officer: the person who owns the map, builds the pieces, and tells you the truth about what you actually need. It’s an operating role, not an honorary title — the architect here also swings the hammer. A monthly engagement layered on a relationship where we run your systems, whether that’s a maintenance plan or a custom build: monitoring of the automations we’ve built, a working session with your team on a cadence, and new automations shipped on a defined schedule. The job of a CAIO, sized for an organization your shape. (This offering launched as “AI Operator-in-Residence.” A client renamed it, and the client was right.)
Six things, every month.
Health checks on every production automation in your stack. Failed-run alerts, cost tracking, drift detection. Light remediation is included; major rebuilds are quoted separately. The automation we shipped six months ago doesn’t quietly stop working without anyone noticing.
A live session with your designated AI champion and relevant team leads. We review what’s running, surface new workflow candidates from what came up that month, and prioritize the next build. On the calendar. Not a slack ping that gets ignored.
You name one internal champion at onboarding. They’re the institutional memory; we’re the operator. Both of us show up to every working session. After 12 months, your champion has watched a year of decisions and can carry more of the load. We get smaller as your team gets stronger.
Every session surfaces new candidates. We keep a running backlog ranked by hours saved per month and implementation complexity, so you can always see what’s next and why. The roadmap is alive, not a slide deck from last quarter.
Every three months, a written roadmap update: automations shipped, time saved, what’s next, what to deprecate. Designed to forward to anyone asking what’s happening with AI at your organization.
A Slack or Teams channel where your champion can ping with quick questions during business hours. Not a help desk. A working channel for the things that don’t need a meeting.
Honest about the edges.
The monthly fee covers monitoring, the working sessions, triage, the roadmap, and your tier’s build capacity: light items from the queue at Counsel, one always-moving build track at Architect, parallel tracks at Embedded. Larger builds are quoted as project work the same way they always have been.
The written quarterly roadmap is part of the deliverable. Custom executive presentations, board decks tailored to your board, or RFP responses are real work and are quoted separately when they come up.
This engagement requires a relationship where we actually run something in your stack — a maintenance retainer, or a build we operate for you. The reason is structural: the architect role is incoherent without ongoing access to the systems we’re advising on. If we’ve never touched your stack, the front door is the AI Stack Audit: $750, about a week, and you get a tool-spend cut list, a map of where your team’s hours actually go, and the top automation candidates ranked. Its output becomes month one of any tier.
Start with the audit. Pick a tier by team shape, not company size.
For organizations with one or two production automations running, a single team in scope, and a steady-guidance posture on AI. You get monitoring, the monthly working session, the ranked backlog, and the quarterly roadmap, with small build items worked from the queue. Larger builds are quoted as project work. Best for teams that want trusted counsel before committing to a build cadence.
The recommended tier, and where most engagements land. One build track stays in motion month to month while everything else queues behind it, so every month ships something you can see. Includes everything in Counsel, on a biweekly cadence, plus a standing tech-stack and cost analysis: what you’re overpaying for, what to cut, and what to fold into systems that earn their keep. Most clients fund a real chunk of this tier out of cancelled software.
For organizations moving on several fronts at once: two or more teams, three to five production automations, a roadmap that won’t wait its turn. Everything in Architect, run in parallel instead of in sequence, with first priority on turnaround when something breaks or a deadline moves.
For organizations with five or more production workflows, multiple stakeholders, or regulated-industry overhead (NDAs, data-handling protocols, vendor security review). Weekly working sessions, dedicated operator capacity, custom monitoring and reporting. Quoted per scope after a discovery call.
Shipped code, not slide decks. A working session, not a quarterly check-in.
Most “fractional CAIO” offers in the market are advisory. Slide decks, frameworks, quarterly check-ins. That doesn’t close the gap IBM measured. The 61 points between “could use AI” and “does use AI” only closes when someone is in your building, on your stack, shipping the thing.
I’ve been doing this for clients for the last two years, project by project. The AI Architect engagement is the recurring-revenue version of the work, named and priced openly. The leverage that makes the math work at this price point is not magic. It’s ten years of design discipline plus a Claude-orchestrated operations layer running underneath every client engagement. Same leverage that runs the website you’re reading.
If you’ve hired a consultant who delivered a deck and left, you know what this is not. If you’ve had an internal AI champion get pulled back into their day job two months in, you know why an outside operator with recurring time is different.
The operator pattern is already running. The SKU is new.
The operator role isn’t a theory. The clearest current proof point is the inbound-feedback pipeline running for Mountain Mike’s Pizza: 330 active stores, thousands of customer emails a month, automated classification by category and severity, human in the loop, all on n8n and Claude. The pattern of “name the workflow, build the thing, monitor it, iterate” is what the AI Architect engagement productizes. The offering launched in May 2026 as AI Operator-in-Residence; the first engagements are in flight under the new name. See the MMP case study for the broader engagement context.
Aaron has provided super fast response time, quality work and an amazing rate. We are beyond pleased with Aaron’s impeccable service. He is extremely knowledgeable and helpful in assisting us in managing our website internally.Carol DeNembo / CMO / Mountain Mike’s Pizza
Schedule a call. We’ll walk your stack and pick a tier in fifteen minutes.
Bring a rough sense of where AI shows up in your work today and the workflows you wish ran themselves. I’ll suggest the right tier on the call, or tell you honestly if your organization isn’t the right shape for this yet.
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