A billion-dollar company was just built by one person using AI.
And yet, many Fortune 500 teams are still only using AI for basic tasks.
Summarize meetings
Draft emails
Write slides
Do basic analysis
Your fast track to AI fluency.
So how do we actually start building AI fluency with our team?
We created an experience called The Counter — we guide a cohort of 8–16 from your team through hands-on work on real problems they’re already focused on, over four to six weeks.
Throughout the process, working and thinking with AI becomes fluid, instinctual, eventually second nature.
Wait — we already have AI tools and guidelines.
And we’ve rolled out training plans.
That’s not a problem.
We provide a safe sandbox environment alongside everything you have, so your team can practice AI fluency without you getting a heated email from IT or HR.
What’s in it.
- Instinct how to think + work with AI
- Curriculum your cohort’s real problems
- Coaching through iteration
- Prototypes one per person
- Cohort your future advocates
What is the Counter Experience?
We partner with you to shape the right cohort and set the experience up for a strong start.
To kick off, each person learns how to define and frame a real problem or project from their own day to day work clearly enough to begin working on it with AI through the experience.
One by one, we coach them to think and work with AI to build a working prototype that solves their problem in hours.
They take the prototype into their real work — test, learn, and iterate until it works in practice.
By the end, they have real solutions in hand — and the confidence to keep thinking and working with AI more fluently on their own.
And you have the PROOF you need to scale it further.
Outcomes we deliver
The Counter produces outcomes traditional corporate programs rarely can because it is built around applied practice, curiosity, playfulness, and safe experimentation.
AI fluent
The cohort builds the skills, mindsets, and confidence to think and work with AI more instinctively in their day-to-day work.
Real solutions
The cohort leaves with prototypes and solutions that solve the problems they were working on.
New possibilities
The organization begins to uncover opportunities, solutions, and forms of value they would not have reached through traditional ways of working.
Proof to scale
You come away with the proof points needed to bring other leaders along and make the case to scale AI fluency more broadly.
Let’s start a conversation.
Thanks for your message!
We’ll be in touch in less than 72 hours.
AI fluency in practice.
When a customer disputes a charge as fraud, it’s my job to figure out what happened. But the evidence is scattered everywhere, transaction records, account history, notes from other teams, so I’d spend half my day pulling it together before I could even start reviewing the dispute.
— Maya, Fraud Dispute AnalystMaya tested new ways to bring the relevant information together. Her prototype flags contradictions, separates confirmed facts from unsupported claims, and gives her a clearer starting point for each decision. It’s working in her day-to-day — and she now has the proof points to bring back to the business and partner on what scaling it could look like.
- EMV chip-read + first-attempt PIN at Orlando terminal
- Billing address Minneapolis; transaction geo Orlando
- Long tenure, no prior disputes on record
- Whether CH was in Orlando on transaction date
- Whether camera footage identifies this CH
I usually know where a campaign needs to go pretty fast. The slow part is everything after. In life sciences, every claim has to trace back to real efficacy and safety data, so turning my instinct into something my agency can run with takes way more time than I’d like.
— Rachel, Brand Marketing LeadRachel tested new ways to shorten the path from data to direction. Working with her team, and inside the regulatory, compliance, and data standards life sciences marketing requires, she built a prototype that pulls her brand’s efficacy, safety, and outcomes data into one place, shapes it into concept territories (each traceable back to its source), and lets her mock up early ideas to bring to her agency with a sharper point of view more quickly.
There’s probably twenty years of formulation data sitting across the company, but none of it’s easy to search. So when I’ve got a question, it’s usually faster to re-run the experiment from scratch than to find out whether someone already answered it.
— Sarah, R&D ScientistSarah tested new ways to unlock the formulation work already sitting in the company’s files. Working with her team, she built a prototype that indexes historical test data across lab notebooks, ELNs, and project archives, and lets her run digital scenarios against that body of work before committing to a lab cycle. Now she walks into each cycle testing the most promising hypotheses, not just the ones she had time to get to.
AI Literacy
- ✓ Knows what AI can do
- ✓ Uses AI for simple tasks
- ✓ Accepts what AI gives
- ✓ Applies generic use cases
- ✓ Speeds up existing work
- ✓ Reduces costs
AI Fluency
- ✓ Knows how to work with AI
- ✓ Uses AI on real problems
- ✓ Shapes what AI produces
- ✓ Builds context-specific solutions
- ✓ Expands what teams can take on
- ✓ Reduces costs and unlocks growth
Why We Founded The Counter
We founded The Counter because we felt this discomfort ourselves. We spent years at one of the world's largest innovation and technology consultancies, teaching ourselves to think and work with AI until it was instinctive.
Once we got there, we could see what fluency actually makes possible — not just faster work, but work we couldn't do before. And we could see how far most organizations are from giving their people that chance. Most are still teaching AI literacy and leaving AI fluency to chance, and the talking points have been hammered home to the point people are tuning out.
The window to change that is open now, but it won't stay open. It takes honesty about what people are feeling, patience with a process that moves one person, one problem, one solution at a time — and brave leaders who know the current approach isn't enough.
Fred Sham
Co-founderI’ve spent the last two decades helping organizations turn growth ambition into something real. That has meant shaping new offerings and ventures, launching them into the world, and helping teams build the mindsets, behaviors, and skills to work in more innovative and entrepreneurial ways.
For most of my career, I was an executive leader at ?What If! Innovation, which was acquired by Accenture in 2019. There, I worked with Fortune 500 companies on the messy, human side of growth, from understanding customers and shaping new opportunities to building internal capability and helping teams make decisions with more creativity, speed, and confidence. After that, I went independent, advising Fortune 500s, nonprofits, and new ventures on similar questions in moments of change.
The same pattern kept showing up in all that work. Smart people with deep expertise were learning more about AI, but not necessarily becoming more confident using it in the work that matters. For many people, that makes AI feel like a threat to their judgment rather than a way to extend it. For organizations, it means AI stays trapped in tool adoption instead of becoming a real capability for thinking, deciding, building, and growing differently. Helping organizations and people tackle this challenge head-on is what got me excited about starting The Counter.
Drew Castellaw
Co-founderI’m a specialist and leader in Innovation and AI transformation where I’ve spent the past few years continuously building, prototyping, and teaching teams how to work with AI in their day-to-day.
For most of that time I was at ?What If! Innovation, where I was nicknamed “Drewbot” (you don’t always get to pick your nicknames). I authored most of the firm’s perspective on how AI would change the way in which we work, developed patents for agentic systems, and led the application and upskilling of AI throughout multiple engagements and within the firm itself.
I’ve seen firsthand that everyone has the tools, most have had the trainings, but what they lack is how you show up for a change this big. AI doesn’t just change the work, it changes the people doing it. That’s what we’ve come to call fluency.
I like to think of working with AI like working with pixels. When video games first arrived, they introduced an entirely new language — a new way of working, and most importantly, a new way of making. We tend to think analog. AI lets us think in pixels.
Tell me and I forget.
Teach me and I remember.
Involve me and I learn.
Often attributed to Benjamin Franklin. Probably not actually him. Nonetheless — the principle behind our approach.
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