You bought the seats. A couple of people poke at it like a search bar, one enthusiast went deep, and somehow teaching everyone else became your job on top of running the business. I spend two days with 5–50 person service teams getting every person working on their own real tasks — so your people get their week back, and you get out of the trainer's seat.
I've shipped production systems that run unattended for real businesses — and none of it from a computer-science background. No engineering degree, no dev job before this. I learned it the same way the people in your room will have to, which is exactly why it works on someone who has already decided they're "not technical." The building isn't what I sell. It's how I can tell which of your workflows is actually worth the trouble.
Most AI training is a good day that fades by week three. This is built as a 90-day arc instead: the intensive installs the capability, the support keeps it from decaying.
Two days with your team: everyone onboarded, personalized, and connecting the tools they already use to get real work done. $6,000.
See what's involved →Monthly office hours, one workflow review, onboarding for anyone you hire, and a quarterly refresh. $1,500/mo, three-month minimum.
See what's included →Sometimes a workflow turns out to be worth building for real. I do that too — scoped case by case, and never as a substitute for teaching your team to think. See what I've shipped →
Model capability has run miles ahead of the organizations using it. Buying more seats won't close that gap, because the gap isn't the software — it's that nobody has sat down with your people and connected any of it to the work they actually do. That's the whole job.
If a process is broken, automating it just breaks it faster. Most of the value in the room comes from finding the shortest honest path from A to B first. That's the harder half, and it's the half most AI training skips entirely.
AI content that makes people feel stupid is a large part of why adoption stalls in the first place. The daily power user and the person who has been quietly avoiding it sit in the same room, and neither one gets talked down to.
Every engagement is built so your team keeps going without me — that's the point of it, not a nice side effect. If you still need me in the room for it to work, I haven't finished the job.
Tell me what's actually going on — who's using AI, who isn't, and what you've already tried. The first conversation is free, and you'll leave with a straight read on what would move the needle, whether we end up working together or not.
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Two things, in order. The Team AI Adoption Intensive gets everyone on your team working with AI on their own real tasks. Adoption Support is what keeps that true three months later, when the questions have changed and you’ve hired two people. Every engagement starts with a free call.
Two days with your team, built around the work they actually do. Everyone leaves set up, personalized, and holding a real workflow of their own.
Jump to details →Office hours, a monthly workflow review, onboarding for anyone you hire, and a quarterly refresh. Three-month minimum, then month to month.
Jump to details →The same thing for one person instead of a team. A dedicated weekly slot, built around what you want to get good at, worked against your own day-to-day. Up to six hours a month.
Jump to details →Two days that get every person on your team using AI on their own real work — not a lecture about AI, and not a prompt library. Their workflows, their questions, live in the room.
Right now your team has logins nobody really uses. Not for lack of interest — nobody has connected the tool to the work they actually do all week, and most of them quietly assume they’re doing it wrong.
A free 30-minute call: your team, your tools, and what “good” would actually look like.
I build the whole thing around your real workflows. Your team’s only homework is showing up.
Everyone logged in, set up, and comfortable — including the person who’s been avoiding it — with a shared team project built live.
Everyone personalizes AI to their own voice and work, sees real automations demoed, then builds a workflow of their own.
$6,000 · up to 12 people · discovery, tailoring and follow-up included. Larger teams and multi-site quoted on the call.
“Alex is a natural educator and he made the session fun and kept the team engaged. The session was organized, thoughtful and customized to our needs.”
Three weeks after any training, teams drift. New questions surface that nobody had in the room. Somebody gets hired and has no idea what you built. A workflow breaks and people quietly stop using it. This is the part that keeps the first two days true.
Starts the month after your sessions. Three-month minimum — the drift shows up around week three, so three months is the shortest window where you’d actually find out whether it stuck. Month to month after that.
The same thing for one person instead of a team — usually an owner or a leader who wants to get genuinely good at this themselves. A dedicated weekly slot, built around what you want to get good at and worked against your own day-to-day rather than a curriculum. Up to six hours a month.
Sometimes a workflow turns out to be worth building for real — a pipeline, a portal, an integration, a CRM untangled. I’ve shipped all of those and I still do, scoped individually rather than sold off a menu. But it is never a substitute for your team knowing how to think about this. If someone offers to automate your way out of an adoption problem, be suspicious. See what I’ve shipped →
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Take the two-minute readiness check, or just book a call — I’ll tell you straight if I’m not the right person for it.
The teaching is what I sell. The building is why the teaching is worth buying — I'm not explaining this from the documentation, I'm explaining it from having shipped it. It's also how I can look at one of your workflows and tell you it isn't worth automating. Client details are kept general on purpose.
Alex is a natural educator and he made the session fun and kept the team engaged. The session was organized, thoughtful and customized to our needs. We're excited to keep building on what we learned.
Independent contractors spanning a daily AI power user to a complete beginner — delivering a large project for a public-sector client with strict data-handling rules: every AI output human-reviewed, tools limited to an approved list.
One planning call, two two-hour sessions. Everyone left logged into Claude, writing in their own voice, working in one shared Claude project — each with a real workflow built or scoped. Compliance was designed into the setup, not bolted on after.
Worth being straight about: this was the pilot, run as two short sessions. The Team AI Adoption Intensive is what it grew into — two full days, and the follow-through that this engagement didn't have.
"A steady pace, great humor, thoughtful approach. Alex's teaching style is effortlessly comfortable, straddling the line between experienced and self-effacing."
An ongoing weekly engagement with a single client, working AI into the specific shape of her day-to-day — not a curriculum, her actual inbox and her actual decisions. Each week starts with what’s on her desk, not with a lesson plan.
This is what the 1:1 Adoption Coaching rung is: the same method as the Intensive, for one person instead of a room. Usually the owner getting good at this first.
— HER WORD FOR IT
Production work, not prototypes — each of these runs or ran for a real business. It isn’t a menu: builds get scoped one at a time, and only after we’re sure the process underneath deserves one. It’s here so you know what I’m drawing on when I tell you a workflow isn’t worth automating. Named clients available on request.
A searchable knowledge base built over a brokerage’s entire podcast archive, generating social posts and newsletters personalized per agent — every claim cited back to the episode it came from.
Unattended and weekly: finds 300+ page regulatory filings, scrapes and sanitizes them, and extracts the numbers that matter into structured, reviewable data.
Every client gets a live URL into their own data, replacing a hard platform limit — now run day to day by non-technical staff.
Reads inbound replies, sorts them by intent, drafts the right response. Shipped in draft mode first, then earned its way to auto-send. Saves 2–3 hours a week.
Twelve years of scattered event data resolved into a single CRM record per person, so staff can finally see someone’s full history — plus a live fundraising view the founder uses weekly.
My own meal-planning product: recipe import, pantry-aware shopping lists, grocery checkout handoff, with AI used inside the product itself. Deployed, with a full end-to-end test suite.
I'm a communicator by training — a Communication Studies degree from Colorado State, then almost two years at a premier marketing agency, then a startup that hired me for the marketing experience. What I found there became a passion: automation and AI.
It started with a workflow nobody wanted to do. I was updating a CRM by hand, so I automated it. The first build I was genuinely proud of was a data-entry process with eight separate manual touchpoints that took 24 to 48 hours to get through. I got it down to two or three minutes, start to finish, with nobody touching it.
That snowballed. Custom reports running on live CRM data. Then client portals stitching several systems together for a realty brokerage. Now I take everything I've learned and hand that proprietary knowledge to teams who are just dipping their toes in.
Then someone asked me, more or less on a whim, to teach their team how to use Claude.
I didn't expect that to be the thing — but it was. Workshopping real workflow ideas live with people, watching someone who was certain they were "not technical" build their first working automation inside a two-hour session. I'm a natural teacher, and I like beginners best.
So that's what clAIry is: teaching teams to think with AI in ways that are actually practical. No computer-science degree, no dev job before this — thousands of hours and dozens of shipped systems, learned the same way the people I teach will have to. That's exactly why it lands with people who are sure this isn't for them.
These days I work with owners and operations leaders of service businesses, roughly five to fifty people. Not tech companies — firms where everyone is already busy doing the actual work, the AI seats got bought months ago, and training everybody has quietly become the owner's job.