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GET mosaicsolutions.tech/learn/ai-enablement-session keynote · 45 minutes

Promoting AI Transformation at All Levels

Where You Are

How useful is AI in your work today? How much has it changed what you actually do? Hold up a hand and a number of fingers that reflect your level.

Maybe you have an account. Maybe you've tried it before. But it doesn't seem like it could help you at work.

Next Step:Try your own fun, little, dumb thing. Experiment without judgment.

Note

These are not rankings or measures of your quality - they are simply a way to communicate with one another and consider next steps.

What You'll Leave With

If you could only walk away with three things, this is my short list.

Access is not adoption
Buying licenses doesn't magically cause AI transformation.
Start little, start fun
Find the smallest value add to get motivated, and have fun with it.
Wring out simplicity
Our world is complex, and our expertise is the only way to simplify it.

We Bought the Licenses

the rollout — mosaic
what we assumeWe bought the licenses. Everyone has the tool. Productivity gains inevitably follow.what we missEveryone has a different mental model of how AI can help and what it can do. Licenses don't change that.what happens insteadSome use it, some don't, and the mission still goes the same way as before.what actually worksStart with an individual and their own needs. Pair them with an AI champion and talk about one way AI can help with that problem.

Permission Isn't Participation

If you don't go to each individual and focus on real people and their real problems, you might get usage, but you won't get change. Granting permission opens the door with technology. Does your culture open that door, too?

Permission
  • Access
  • AI Policies
  • Directives to Use AI

Result: Usage and compliance, with more direction and policies needed every step of the way.

Ownership
  • Problems worth solving
  • Room to experiment
  • Encouragement and incentives

Result: Participation, agency, and a culture that promotes change, not only with AI.

Giving 1 person the means to drive change is more valuable than crafting the perfect policy or directive.

Fun, Little, Dumb Things

We've all been reluctant to try something new. Ruth Paarman writes content for businesses. She was one of the first people to worry what AI would do to her livelihood. She resisted using AI for years — it wasn't as good at writing, it didn't know the context, and it destroyed the spirit of the work. who said the way in is to find a fun little dumb thing to work on. It stuck with the room harder than anything on my slides, and it's right for a reason: it moves the incentive from money or promotion to curiosity, which is the only motivation you can supply yourself.

Backing

Anne-Laure Le Cunff makes the same case at book length in Tiny Experiments (2025): small, bounded attempts turn every result into data instead of a verdict, which is what removes the fear of failing.

  1. One annoying task

    Something that irritates you personally. Not the company's top priority.

  2. Ten minutes

    Bound the risk before you bound the scope. Ten minutes cannot fail expensively.

  3. One question

    Follow the curiosity, not the roadmap. Let the result tell you what to try next.

A Stack of Ungraded Paper

a teacher, some evening in 2024
There's a huge pile of ungraded work on my desk. I feel like I'll never catch up.That's a rough place to be. Grading is the part of teaching that scales worst, and the part students need fastest.Can you help me grade it?Yes — send your rubric and a couple of essays you have already scored, so I match your standard instead of inventing one.Can I pump the feedback right into Canvas?Sure. One call per submission:POST /assignments/:id/submissions/:student{ "comment": { "text_comment": "<feedback>" } }Wow. Let's build it!Then that's the whole thing: export the essays, strip the names, score against your rubric, post the comments back. Feedback before the weekend.

How Long It Took

2011
Took one coding class. Other people were better at it, and that scared me, so I quit and majored in languages instead.
2022
A childhood friend described a language box you could talk to that talked back. Nobody was sure exactly why it worked. We started building LexiLift.
2023
LexiLift failed.
2024 · spring
The grading automation. The first thing I built that changed my own working life.
2024 · summer
Left teaching for a curriculum role. No AI in the job description, so I did it at night.
2024 · nov
Automation consultant for law firms. Finally it was the job.
2025 → now
Innovation Lead for AI transformation at a firm of about a hundred people. Then Mosaic.
It took 15 years to try coding again. It took 18 months to turn that into a career.

A Bag of Cans

Iowa has a bottle deposit: five cents on every container. For decades, getting that nickel back worked like this.

  1. Sort

    Separate every category at home.

  2. Transport

    Fill a car with loose containers.

  3. Count

    Feed or hand over every single item.

  4. Wait

    Get a receipt. Redeem the receipt.

can shed
{
  "What are we actually paying for": "the deposit back. not a receipt, not a count.",
  "Who verifies, and why": "both sides, twice, because the unit is one can",
  "What has to be true": "the count has to be trusted. it does not have to be watched.",
  "What could stand in for counting": "anything with a known, standard quantity"
}
Nobody automated counting. They changed what had to be counted.

What Must Be True

Can Shed is what the move looks like when somebody gets there by instinct. Here is how to get there on purpose. Four questions, in this order, and the order is the whole technique.

AskThe questionIf you skip it
PurposefirstWhat outcome actually matters?You automate a step nobody needed, perfectly.
RequirementsWho needs that outcome, when, and why?You remove something load-bearing and find out from the person it was bearing.
SystemWhat arrangement would satisfy that need?You rebuild today's process in code and call it transformation.
TechnologylastWhere do AI and automation actually help?You start from the tool and reason backwards to a problem that fits it.

The most common failure isn't refusing to automate. It's automating precisely what the person does today — align, trace, cut — and shipping a faster version of a process nobody ever designed.

Chesterton's Fence

Every one of those questions costs you something. Somebody at Can Shed had to understand deposit law, container types, transport costs and fraud before any of it could be made that simple. There is no version of this where you get the simple answer without doing that work first.

Chesterton's fence

Don't take a fence down until you know why it was put up. A good share of the steps that look pointless are load-bearing and undocumented, and the person who knows why is rarely in the room where it gets cut.

That is the guardrail. It is slower, it is less satisfying, and it is the only thing standing between a redesign and a very confident mistake.

Sixty-Three Elements

Here is what that work buys, from somebody who did it in 1869.

This story was told to me by Juan Aranda.

principles of chemistry — 1869
the problemSixty-three known elements. Each with its own weight, its own habits, and no reason to come before or after any other.first attemptList them by atomic weight. It is correct, and it is useless — a list tells you nothing you did not already know.the patternEvery eighth one behaves like the one before it. Lithium, sodium, potassium. The list wants to be a grid.the trouble with the gridSome squares come out empty. Either the pattern is wrong, or there are elements nobody has found yet.the decisionLeave the gaps. Say what belongs in them. Let somebody go and look.

Make Your Own

Three squares he left empty, and described anyway

Within seventeen years all three had been found, each close to the weight and the behavior he wrote down for a square that was, at the time, blank.

It's on the wall of every chemistry room on earth and nobody looks at it. Almost nobody asks the only question about it that matters: how would I make one of these for my own work?

You don't find simplicity. You wring it out of the complicated thing.

What This Asks of You

Enablement isn't a program you run. It's a condition you create, and each seat in the room creates a different part of it.

If you are anyone
Pick one fun, little, dumb thing this month. You don't need approval to spend ten minutes on something that annoys you.
If you lead
Protect small experiments. Your job isn't to approve the roadmap — it's to make it safe to have a bad idea in public, and to notice out loud when one of them works.
If you are on a team
Ask what the work must accomplish before anyone asks what tool to use. You're the only people who know which fences are load-bearing.
Own your transformation, then go help somebody own theirs. That is the whole of leading it.

Systems, Not Heroics

Here is the part that gets left out. Experimenting constantly is tiring. Learning something new every week, on top of the job you already have, at night, with nobody asking you to — that is a real cost, and it comes out of the rest of your life. If the transformation runs on you being heroic, it ends when you do.

Are you running on systems or heroics? Only one of those can work without you. Debbie Foster

I have been on every rung of that. I was the hero who could fix anything. Then I was the leader of heroes, teaching people to be smarter about their heroics. Then I worked out that a system which lifts your colleagues gives time back to all of you at once — including you. That last step is the only one that scaled, and it is the reason Mosaic exists.

Three Things

Access is not adoption
Give people a reason, not a directive.
Start little, start dumb
Practice making your own life better, then build from there.
Wring out simplicity
The simple version only exists once somebody has understood the complicated one. Be that somebody.
Take one question home

Where are we using heroics to compensate for a bad unit of work?