We're at a unique moment with AI. Companies want employees to use AI to work more efficiently, and a lot of employees are genuinely curious about new tools.

But there's a gap.

While the priority is clear, a lot of people don't know where to start. Companies are telling their teams to use these tools, but they aren't giving any guidance on how to actually learn them. According to a survey, nearly 47% of people don't know how to achieve the productivity gains their companies expect.

And this is especially hard with AI because unlike normal software it's harder to find books and courses to learn from because what's possible is getting redefined every day with new models, tools, and best practices.

So how do you learn something that feels unlearnable?

Why play?

Giving yourself the time to play with these tools and experiment is the best way to learn what they're capable of and how to use them.

When it comes to learning, hands-on practice has a 75% retention rate compared to just 5% for lectures and 10% for reading. Sitting down and getting practice is the easiest and most effective way to learn.

But it's not just about practicing, it's about experimenting in a safe space without feeling the need to perform. You're not worrying about learning how to do something brand new and delivering results, you're just learning. By letting yourself be wrong and test things out you'll build the skills you need to use AI in practice.

How to use play to learn AI

This isn't about following tutorials or getting everything right the first time, it's about giving yourself the breathing room to experiment and find our for yourself what works and what doesn't.

The framework is straightforward:

Pick an app: What's something you're genuinely curious about trying out? In order to be self driven it's got to be something you care about.

Set a budget: Decide how much money you're comfortable spending to learn. Just paying $20 to try out a tool for a month is a great place to start.

Set a time budget: How much time can you spend learning? 30 minutes at the start of your day, or even just 1 hour a week is enough to get started.

Pick a task: What's something specific you want to try doing with the app you've picked?

Picking a task

That last part (picking a task) is the most important part, it's the games we play. Games have goals and teams, winners and losers. And if you don't have something to aim at then you risk just clicking around aimlessly.

It doesn't have to be ambitious and it's perfectly fine if you're not able to accomplish it, but you at least need a direction to aim at to push you out of your comfort zone. Bonus points if it's related your day to day work, but it's not required.

For me my first task was trying to use Replit to make my own todo app. It took a lot of trial and error and it was pretty bad, but it taught me a lot about vibe coding and prompting. Here are some other ideas:

• Use Lovable to make a code prototype based on something you've designed

• Use Chatgpt train a custom GPT to give you design feedback

• Use Gemini to create a new desktop wallpaper

• Use NotebookLM to teach you front end development

• Use Claude to review the analytics from your portfolio site and suggest changes to make

Track what you learn

As you're learning, make sure to take notes. What prompts work, which ones don't? What tools are best for what tasks? Is something harder than you expected? Is there a prompt you want to use again in the future?

When I was learning Replit and v0 I recorded Loom devlogs, just to track progress. And I made a Figjam board to throw chat links and screenshots in to keep track of everything.

No matter how you journal, you want a record so it's always easy to jump back in and pick up where you left off.

Do your research

Play until you get stuck, and then get more info to fill in the gaps. Read prompting guides, documentation, listen to podcasts or watch tutorials. Or just ask AI itself to try to get more help.

You can subscribe to newsletters like Lenny's podcast, How AI, or Dive Club to hear from other people in tech about their workflows and tips. And Product Hunt or X/Twitter are great places to look out for new tools.

Being loud about it

A huge part of this is sharing what you learn. Whether it's in team meetings, design reviews, 1:1s, or just chatting with your coworkers, it has a lot of benefits:

It helps you formalize your insights and ideas by putting them into words and teaching other people.

It helps other people on your team on their own learning journey.

It helps you stand out on your team as someone leading the charge.

It helps make the case to execs of the ROI of these tools to get you more buy in and budget.

Send links and ideas in team Slack channels, or start a Slack channel for AI experiments. Find kindred spirits using AI and talk to them. Share ideas and ask questions. And be loud online too. You'll find people all over working on learning the same stuff that you can learn from.

The risk of not playing

So, what happens if I don't play? What's the risk?

Start now or catch up later: If you wait for someone else to tell you what to learn you risk falling behind and having to catch up later once AI becomes the bare minimum expectation at work.

Never seeing the full potential of the tools because you're just following step by step instructions. If you just follow other people's instruction you're barely going to scratch the surface of what the tools can do.

Waiting for instruction from your company that never comes, or being at the mercy of how they expect you to learn.

Having to learn and show results at the same time, instead of learning in a safe space.

I'm not trying to scare anyone, these are just the facts. This is a huge opportunity for you to take charge about what you're curious about, instead of delegating that decision to someone else.

So what's next?

For me, I just kept playing and regularly auditing what works and what doesn't. I still play with AI weekly, if not daily to try out new tools I hear about. But depending on your work environment and the company's stance on AI, next steps will look different:

• As a freelancer my priority was building my personal skills, so I slowly dedicated more money to learning new tools and slowly integrated them into my client projects.

• If your company is mandating AI usage then maybe you want to show your proficiency to your manager and talk to other people at your company to learn from them. Maybe you can even get ahead of the curve and be a trendsetter teaching everyone else new use cases and tools.

• If your company is recommending AI usage then maybe showing other people how AI can be used could help you advocate for a bigger budget and approval for the whole team to use the tools you're playing with. Being specific about what tools you want to use might make it easier to get budget approval.

• If your company is skeptical about AI then you can show the potential impact to leadership to get more buy in and dispel myths. If you can learn enough to explain AI and answer people's questions it's easier to be an advocate.

Conclusion

All in all, this is a huge opportunity for curious people because most companies have the same goal as you do, they're just waiting on you to decide where to start. Since companies don't know how to give direction for AI adoption, curious people like you can start to play with these tools and lead the charge.

All in all, the barrier to start playing is very low, and the potential upside is huge for you and your career. And you can have a lot of fun while doing it too.