Last week, I read that while nearly half of organizations are now deploying AI (up from just a year ago), 95% of generative AI pilots at companies are failing and they’re not seeing meaningful productivity gains. I’m not surprised.

While I strongly disagree with yesterday’s New Yorker claim that AI may not be living up to the hype (trust me, AI has changed my life, saved my life, and leveled me up 10x this past year), I do agree with the counterpoint, that system-wide change takes time.

Over the past year, I’ve been building reflexively with AI. Last summer, I was just at the very start of my learning journey, one I rapidly accelerated while creating a curriculum with the team at Decoded Futures to help others learn how to use AI. This summer, I’m building a new app every week. (That’s not an exaggeration.)

I’ve said this many times before, but it bears repeating: Using AI isn’t like picking up a tool, it’s like learning a language. And learning a language requires practice, fluency, and intentionality.For leaders, that means creating a new normal for the AI age.

Many of us grew up in a professional world where the unspoken rule was, “only share once it’s ready.” But true creative building requires the opposite approach, whether you’re launching software on the internet or reinventing internal tools.

In building software (or building anything), the process starts the second you get that first draft in front of someone else. That means leaders need to reward creativity, experimentation, and play. In fact, the less perfect, the better. (It also means that you get a better feel for how people on your team think, which is an added bonus.)

Consider this reframe: First drafts are the play doh that makes creativity possible. If you are expecting your team to invent new processes or systems for themselves, their colleagues, or your users, you need to start somewhere. This means normalizing a culture of experimentation, tinkering, and exploration.

When people realize they can build apps with AI, they get excited and start to share ideas for things they’ve always wanted to build (often, ideas they’ve held onto for years). But what comes next is hard: You need to learn how to shrink those ideas down to the bite-sized bits or an MVP (the minimum viable product).

As a highly creative person without an engineering background, this has been one of my biggest struggles this year. I carry really big ideas, then try to leap from step one straight to step ten. But that’s not how things actually get built.

Building requires order of operations, taking the next right step, one at a time. This so-called “messy middle,” with all its creative frustration, is the new normal for anyone who wants to build. If you’re new to it (like I am), you may need a little help.

As it turns out, there are people around us who think in systems and processes all the time: Engineers, developers, and product managers. Now it’s time for them to become our tutors and coaches. One of the smartest moves a company can make right now is to have engineering teams teach colleagues how to build, turning experts into engineers.

This year I’ve learned firsthand: It’s one thing to hack together an app for my own kids, and another to share that messy, iterative process with collaborators. But this is a crucial step toward developing organization-wide AI fluency.

After all, if we can’t collaborate, we can’t create. Leaders should create spaces where teams can co-build, test, and tinker openly because fluency grows fastest in conversation, not isolation.

This summer, I’ve been exploring what this looks like in my own work, and I’m excited to see how teams will unlock their collective creative momentum in this new builder era.

Over the past year, I’ve spent thousands of hours experimenting to rewire my own problem-oriented mindset for the AI age. If you’re leading a company (big or small), it’s time to move AI fluency from a solo sidequest to an organization-wide framework.

AI isn’t just another tool; it touches every part of an organization. That’s why we have to think differently, and why team-level fluency is critical. Now that I’ve done it for myself, that’s exactly what I help organizations unlock.

So if you’re ready to upskill your team or executives for the AI age, let’s talk about what we can Build First.

Last week, I read that while nearly half of organizations are now deploying AI (up from just a year ago), 95% of generative AI pilots at companies are failing and they’re not seeing meaningful productivity gains. I’m not surprised.

While I strongly disagree with yesterday’s New Yorker claim that AI may not be living up to the hype (trust me, AI has changed my life, saved my life, and leveled me up 10x this past year), I do agree with the counterpoint, that system-wide change takes time.

Over the past year, I’ve been building reflexively with AI. Last summer, I was just at the very start of my learning journey, one I rapidly accelerated while creating a curriculum with the team at Decoded Futures to help others learn how to use AI. This summer, I’m building a new app every week. (That’s not an exaggeration.)

I’ve said this many times before, but it bears repeating: Using AI isn’t like picking up a tool, it’s like learning a language. And learning a language requires practice, fluency, and intentionality.For leaders, that means creating a new normal for the AI age.

Many of us grew up in a professional world where the unspoken rule was, “only share once it’s ready.” But true creative building requires the opposite approach, whether you’re launching software on the internet or reinventing internal tools.

In building software (or building anything), the process starts the second you get that first draft in front of someone else. That means leaders need to reward creativity, experimentation, and play. In fact, the less perfect, the better. (It also means that you get a better feel for how people on your team think, which is an added bonus.)

Consider this reframe: First drafts are the play doh that makes creativity possible. If you are expecting your team to invent new processes or systems for themselves, their colleagues, or your users, you need to start somewhere. This means normalizing a culture of experimentation, tinkering, and exploration.

When people realize they can build apps with AI, they get excited and start to share ideas for things they’ve always wanted to build (often, ideas they’ve held onto for years). But what comes next is hard: You need to learn how to shrink those ideas down to the bite-sized bits or an MVP (the minimum viable product).

As a highly creative person without an engineering background, this has been one of my biggest struggles this year. I carry really big ideas, then try to leap from step one straight to step ten. But that’s not how things actually get built.

Building requires order of operations, taking the next right step, one at a time. This so-called “messy middle,” with all its creative frustration, is the new normal for anyone who wants to build. If you’re new to it (like I am), you may need a little help.

As it turns out, there are people around us who think in systems and processes all the time: Engineers, developers, and product managers. Now it’s time for them to become our tutors and coaches. One of the smartest moves a company can make right now is to have engineering teams teach colleagues how to build, turning experts into engineers.

This year I’ve learned firsthand: It’s one thing to hack together an app for my own kids, and another to share that messy, iterative process with collaborators. But this is a crucial step toward developing organization-wide AI fluency.

After all, if we can’t collaborate, we can’t create. Leaders should create spaces where teams can co-build, test, and tinker openly because fluency grows fastest in conversation, not isolation.

This summer, I’ve been exploring what this looks like in my own work, and I’m excited to see how teams will unlock their collective creative momentum in this new builder era.

Over the past year, I’ve spent thousands of hours experimenting to rewire my own problem-oriented mindset for the AI age. If you’re leading a company (big or small), it’s time to move AI fluency from a solo sidequest to an organization-wide framework.

AI isn’t just another tool; it touches every part of an organization. That’s why we have to think differently, and why team-level fluency is critical. Now that I’ve done it for myself, that’s exactly what I help organizations unlock.

So if you’re ready to upskill your team or executives for the AI age, let’s talk about what we can Build First.