For years, I've navigated two parallel universes: building software businesses and playing/making music. Both taught me important lessons—but in totally different ways.
The software world prized big strategic plans, detailed roadmaps, and ruthless execution. Predictability was our muse and agile was our way there. Music on the other hand, music laughs at neat little plans. It demands practice, creativity, and intuition. Sure, you can study theory—but to really play, you have to grab an instrument, mess around, make mistakes, and slowly find your voice.
And when you’re ready, you and the band can hit the stage and try to make the crowd happy.
Right now, the world of AI feels way more like music to me than software development.
And here's the catch: that's great news…
AI isn't something you neatly spec out, package up, and deploy. It’s dynamic, messy, and endlessly fascinating (just like the best music). The teams making real progress aren't those stuck in perpetual planning mode—they're the ones who pick up the AI instrument, practice daily, and slowly find their voice. And when they’re ready, they find their band and step out of the garage and onto the main stage.
Forget Roadmaps—Think Jam Sessions
If I’m totally honest, traditional software development had become a bit comfortable, almost too predictable: define, build, ship, iterate, repeat. You could set your two-week watch to it.
But AI doesn’t share that predictability. It thrives on improvisation, exploration, and rapid adaptation. You don’t “launch” AI once—you live with it, adapt with it, and grow with it. Models and experiences get stagnant and outdated rather quickly; but like music—practice (and improvement) is forever.
Great musicians don’t just rehearse scales—they jam, explore, collaborate, and discover their sound. The best AI teams work exactly the same way.
AI demands:
Less rigid rollouts, more daily experiments and refinement.
Less reliance on launch plans, more on learning paths.
If you're a leader used to classic enterprise tech cycles, this might feel strange—but anyone who’s ever picked up a guitar or keyboard knows exactly what I mean.
A Wake-Up Call from a Multibillion-Dollar Leader
A few days back, a senior executive from a multi-billion dollar company/client (that I can’t name, sadly) sent out an email to her team that is exemplary for what to do in Times Like These (what an incredible song)...
“If you’re resisting AI, please stop. Just take ten minutes a day and play around. Explore, experiment, get curious—because the future isn’t us versus machines, it's us with machines.”
That’s not marketing. That’s leadership. Real talk, real permission, real encouragement to dive in and start learning. She’s not waiting for the data and tech team to implement AI in her org, she’s setting the expectation that experimentation, fluency, and proficiency in AI is everyone’s accountability.
I love that. Kudos (you know who you are).
Why Practice Beats Perfection Every Time
Some companies love a good framework—they’ll buy expensive decks, strategies and change management plans from big consultancies. That’s all well and good, but the teams that I see that are really making progress are the ones just using AI daily:
Designers rapidly prototyping new features and experiences (and discovering radically new ways to do their work).
PMs using AI to capture conversations with users and simultaneously turning that into first drafts of user stories (freeing them up to make strategic decisions about what to do next and why).
Engineers building entirely new products (not proof of concepts) just to see if they're feasible (and if not, finding a real understanding of what their org needs to change to make it so)
Executives having “conversations” with the data being created by all of their teams, unlocking profound insights about what they could do to drive efficiencies or growth
The list goes on and on…
None of these use cases are perfect—they're messy, scrappy, and (often) a little self-serving.. But they’re all brilliant precisely because of one thing, people are getting better with these new AI instruments.
The ideas then improve because they’re actively used, refined, and shared. Like a great song, they get better the more they’re practiced, shared, and refined.
Leaders: It’s Time to Step Up
Here’s the truth from what we’re seeing across industry/level/etc: Your job isn’t to become the AI expert. Your job is to create an environment where teams feel empowered and supported to get good at a brand new instrument (AI).
What does that look like?
Make space: Protect time and space for exploration.
Celebrate messy: Praise early experiments—even the half-baked ones.
Clear the path: Reduce friction so teams can experiment without red tape.
Set smart guardrails: Align AI practice clearly with business goals, create the conditions for experimentation without risk.
Lead openly: Show your own experimentation; share what you learn (especially your mistakes).
Make curiosity a habit: Shift from occasional practice to consistent experimentation.
Culture change doesn’t come from mandates. It comes from sparks of curiosity, growing into rhythms of experimentation, eventually settling into a groove of continuous practice and improvement.
Keep the Band Playing
AI is changing stupidly fast. Models change, APIs shift, prompt techniques evolve, new capabilities roll out daily. "One-and-done training" with AI won't cut it. You and your teams need to be practicing with these tools every single day.
Think of how hard it would be to learn the guitar if the guitar was being completely reinvented/improved every other month – that’s what it’s like to get really good at AI right now…
The best teams we’re working with are building muscle memory by:
Running frequent demos and internal showcases.
Pairing business owners directly with AI builders.
Constantly swapping prompts and real-world insights.
Creating the conditions (and expectations) for continuous practice
Learning an instrument isn’t about nailing perfection from the start. It’s about regular, deliberate practice until the instrument feels natural. AI fluency is exactly the same.
Waiting for perfection means waiting forever. Dive in, practice daily, adapt in real-time, and watch what happens.
TL;DR
🎸 AI isn’t a product to launch—it’s an instrument you (and your org) master through daily play.
🧠 Real results aren’t born in boardrooms—they emerge from continuous curiosity.
🛠 Scaling AI from pilot to production demands daily practice, not endless planning.
🔄 Leaders don’t need AI expertise—they need to foster environments where curiosity thrives. 🚀 Momentum is your goal, not mastery.
So quit waiting around and start jamming.
Take it from our client – “The future of work isn’t humans versus machines—it’s humans with machines.”
 | A guest post by
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