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Most leaders get AI adoption backwards. They see how powerful these tools are and think the path forward is pushing everyone to training on their own, making them learn to prompt, and hoping they figure it out on their own time.
This doesn't work.
Your ops people aren’t going to suddenly become developers and your marketers aren’t going to start writing Python scripts, unless you equip them with the AI tools that make it stupid simple.
Here's what actually works.
Take your most technical people and have them build packaged tools that everyone else can put on.. like a suit. One click, instant superpowers.
1. The Iron Man suit model
Tony Stark doesn't train everyone to be Iron Man. He builds suits.
This is exactly how we've been approaching AI adoption internally. Instead of saying "everyone needs to learn to prompt better," we've been building what we call suits. Pre-packaged systems with everything wired up and ready to go.
Our technical folks (myself included) are spending time/energy building tools that multiply everyone else.
When someone joins our team now, they won’t have to spend weeks figuring out how to configure Claude Code or connect their data sources. They grab the pack, run one command, and suddenly they have access to the same capabilities our most technical people have.
The time to productivity dropped from weeks to hours.
2. What a suit really looks like
A suit isn't just a prompt template. It's an entire system that's been pre-configured, tested, and packaged for reuse.
For us, that means meeting transcripts automatically synced, client context loaded, skills for common workflows like generating status reports, analyzing feedback, or drafting comms. All the boring setup work already done.
When someone new joins our team, our goal is to make it so they don’t need to understand how everything works under the hood. They just need to put the suit on and within a few hours they’re pulling insights from transcripts, generating drafts, and moving faster than ever before. Not because they became technical, but because someone built them a suit.
Our shared repo at StealthX (aka “The Suit”), which contains everything someone needs to supercharge their workflow using Claude Code.
3. Your technical folks have a new job
This changes what technical roles are for.
The most valuable thing your developers and engineers can do right now isn't necessarily building more features. It's building internal tools that multiply your team's output.
Every hour spent building a repeatable skill or automation that 10+ people can use is worth more than an hour of individual contribution.
We've started thinking about it like this.. instead of having engineers in customer meetings translating requirements, have them building systems that let the non-technical folks handle those conversations with AI backup.
Technical folks are toolmakers so that others use those tools to become capable of things they couldn't do before.
4. The "crack the code" test
Here's how you know if your suits are working. Can you take someone who has the right soft skills and attitude but zero technical ability, and make them 100x more effective with AI tools?
If your AI adoption strategy requires people to become technical to benefit, it won't scale. Most of your team isn't going to become technical. That's not an insult, it's just reality.
But if you can take someone with great communication, sharp thinking, and solid work ethic, hand them a suit, and watch them produce at a level that surprises even you.. that's the unlock.
That's when AI stops being a nice-to-have experiment and becomes your competitive advantage.
Putting this into action
Stop running AI training sessions, start building suits.
Identify the 3-5 workflows your team does repeatedly. These are your suit candidates. Meeting prep, reports, research synthesis, draft generation, whatever shows up every week.
Pick your most technical person and give them explicit time to package these into reusable tools. Not side projects, real prioritized work.
Test the suits with your least technical team members first. If they can't use it without help, it's not done yet.
Once a suit works, document nothing. The whole point is that it should be obvious. If it needs a manual, rebuild it.
Wrapping up
AI adoption is as much a mindset and education problem as it is a tooling problem.
Your job as a leader isn't to turn everyone into prompt engineers. It's to build systems that let people do their actual jobs better, faster, and with capabilities they didn't have before.
Build the suits, let people put them on, and watch what happens.
Onward & upward
Drew
P.s. If we haven’t met yet, hello! I’m Drew Burdick, Founder and Managing Partner at StealthX. We work with brands to design & build great customer experiences that win. I share ideas weekly through this newsletter & over on the Building Great Experiences podcast. Have a question? Feel free to contact us, I’d love to hear from you.