techtuition · ai enablement & organizational capability
The AI mandate landed. The tools showed up. The work didn't change.
Somewhere between the announcement and Monday morning, adoption stalled. If you lead a team — content, ops, support, product — the licenses are paid for, the pilot went fine, and the actual work looks the way it did last year. You're being asked to make AI real: measurable, governed, part of how work happens. Without new headcount, and without breaking what already works.
The tools were never the hard part. I build the organizational capability underneath adoption — redesigned workflows, working governance, and teams trained to run the system without me.
independent · remote · engagements begin with a conversation, not a pitch
why adoption stalls
Organizations don't fail to try AI. They fail to make it stick.
tools without systems
A license is not a workflow. When AI arrives without evaluation criteria, governance, or a defined place in the process, every team member is left to improvise — and improvisation quietly reverts to the old way of working.
training without practice
A workshop creates enthusiasm; it doesn't create capability. If nothing about the daily work changes by Friday, the training evaporates by the following Monday. Adoption is a teaching problem — and teaching is repetition inside real work, not a slide deck beside it.
pilots without operations
The pilot succeeded, then stayed a pilot. Moving from “it worked once” to “it's how we work” requires SOPs, standards, measurement, and an owner — the operational layer most AI initiatives never build.
the method
Diagnose → Redesign → Build → Enable → Leave.
I've run the same five-move arc for nearly two decades — through content systems, knowledge architecture, and now AI-enabled work. Diagnose the friction where it actually lives. Redesign the workflow around how work really happens. Build the system — governance, standards, evaluation criteria, and the technical infrastructure itself; I implement what I design, from agentic workflows to evaluation systems, so strategy doesn't die in the gap between the deck and the daily work. Enable the people who will run it, at every level. Then leave — because a system that still depends on the consultant is a system that failed.
the full method →proof
Measured in outcomes. Verified by what's still running.
~$3M
saved through one workflow redesign at Airbnbinternal analysis
1,500
people across one organization adopted one operating model at Coursera
100s
of practitioners trained, from Fortune 100/500 teams to four-person client crews
Still running
the systems I've built continue operating years after hand-off
selected clients
practitioners trained from
three ways in
diagnose
Know exactly where you stand
A fixed-fee diagnostic that maps your workflows, adoption barriers, and governance gaps — and hands you a prioritized roadmap with the first intervention scoped. From $7,500 · two to four weeks.
build
Turn one pilot into permanent practice
Workflow redesign, governance, and implementation — or a fractional enablement lead who stands up the whole function and then helps you hire her replacement. Scoped engagements to multi-quarter.
train
The curriculum, in-house
The capability-building curriculum I taught for four years at UX Content Collective and beyond — tailored to your stack, your governance reality, and your teams' actual work. Half-day to multi-week.
Not sure which door? That's normal — most real problems arrive unlabeled. Start with the conversation; I'll propose the smallest engagement that solves the real problem.
Facing the decision before the mandate — what to adopt, what to skip, what to tell the board? That's advisory, and it lives at rebelevolve.com. Same research, different chair.
the flagship engagement
When you need the whole function built — and then owned in-house.
fractional enablement lead
Someone accountable for AI adoption, until your team is.
Some organizations don't need a diagnostic or a single workshop — they need someone to own the whole thing: the strategy, the governance, the workflows, the training, and the uncomfortable job of making it all actually land. For a defined stretch, that's me. I embed with your team, stand up the enablement function end to end, and carry the accountability a stalled mandate has usually been missing.
what I own
The operating model and where AI fits it. Governance and evaluation standards that hold up. Redesigned workflows your team runs daily. The capability-building so people can actually work the new system — not just admire it. And the measurement that proves it's working.
how it ends
By design, with me gone. The whole engagement points toward a function your team runs without me — including helping you define, hire, and onboard the permanent owner who takes the seat. A fractional lead who makes herself unnecessary is the point, not a risk.
the research underneath
Alongside the client work, I publish research: LLM evaluation (Apart Research, 2026) and an ongoing taxonomy of how constructive conversations progress — 264 documented pathways, becoming an API at Quantum Magic. You don't need the research to hire me. It's just why my evaluation rubrics ask questions other people's don't.
Bring the real problem.
A stalled mandate, a pilot that won't scale, a team that needs to become capable of more than it was hired for — or the thing you can't quite name yet that's making this year harder than last year. Peer-to-peer from the first interaction.
One 30-minute discovery call. We talk about what's actually happening — thirty minutes, no deck. If the fit is right, we'll schedule a follow up with a proposal review. If it isn't, I'll say so and point you somewhere better.