I recently got an email from a CRO I’ve worked with for years. Someone I deeply respect. The email was almost panicked: “I need to learn AI, right? I’ll do anything. I’ll intern for you. I’ll hang out in Amelia’s office. I’ll do whatever.”
I hear this constantly. “I need to learn AI. It’s important for my job.”
And here’s the thing: You’re asking the wrong question.
The Real Answer: Don’t Learn It. DO It.
The simplest advice I can give: You don’t need to learn AI. You need to DO AI.
Here’s exactly what you need to do:
- Pick an agentic AI product
- Pick the simplest possible one use case
- Deploy it yourself
- Train it yourself
- QA it yourself
- Test it yourself
If you deploy an agent yourself—actually hands-on keyboard—you’ll understand this technology in a way that matters.
Not your team. You. Yourself.
Why Delegating This One Doesn’t Work
We do Workshop Wednesdays with CMOs who tell me: “Oh, we encourage our team to use any AI tool they want. We allow them to try Perplexity. We encourage them to learn recipes online.”
You will never truly understand the go-to-market implications if you don’t do it hands-on keyboard.
This isn’t about being a control freak. It’s about the nature of this technology. AI agents don’t work like traditional software. You can’t just watch a demo and understand them. You have to train them, see where they break, iterate on prompts, and feel the difference between a 70% accurate agent and a 95% accurate one.
That only comes from doing it yourself.
A Real Example
Another CMO I’ve worked with—I’ve gotten her her last two jobs—just reached out after many years. She’s ready for her third role.
And I had to be direct with her: “Can I be honest with you? I don’t have anything for you right now.”
Why?
She doesn’t have hands-on experience with this stuff yet. She’s got great traditional marketing experience, but she hasn’t deployed an agent herself. I told her: “Go deploy an agent. Tell me how it worked. Tell me how the training went. Tell me the issues you ran into. Come back to me, and I’ll have opportunities for you.” Right now? I don’t have the right roles to recommend her for.
What Actually Happens When You Deploy It Yourself
When you personally deploy an AI agent, you learn things you can’t learn any other way:
- You learn what “training” actually means. It’s not uploading a document. It’s iterating on examples, testing edge cases, and understanding where the model gets confused.
- You learn where it breaks. And more importantly, you develop intuition for why it breaks and how to fix it.
- You learn the difference between a use case that works and one that doesn’t. Some things that sound great in theory fall apart in practice. You only discover this hands-on.
- You learn how to QA AI outputs. This is a genuinely new skill. It’s not like QA-ing traditional software.
- You understand the economics. When you see the actual performance, you can model out real ROI, not theoretical ROI.
This knowledge changes how you think about your function—sales, marketing, customer success, whatever it is.
The New Executive Skillset
In 2025, the executives who are getting the best opportunities can talk credibly about:
- The specific agent they deployed
- The use case they chose and why
- How they trained it
- What problems they encountered
- How they solved those problems
- The actual results they achieved
This isn’t about having “AI on your resume.” It’s about having real, hands-on experience that changes how you think about your work.
What “Deploy It Yourself” Actually Looks Like
Pick something simple. Here are real examples:
For CROs:
- Deploy a lead qualification agent
- Train it on 50 examples of good-fit vs. bad-fit leads
- Run it on inbound for one week
- Compare its outputs to your reps’ qualification
For CMOs:
- Deploy a content repurposing agent
- Train it on your last 10 blog posts
- Have it generate LinkedIn posts from one new article
- Edit and QA the outputs yourself
For VPs of Customer Success:
- Deploy a tier-1 support agent
- Train it on your top 20 support tickets
- Test it on 10 new incoming questions
- Measure accuracy and response quality
The point isn’t perfection. The point is hands-on experience with training, deploying, and improving an AI agent so you understand how this technology actually works.
Why This Is Different
With previous technology waves—cloud, mobile, social—you could learn by observation. You could have your team pilot it and report back. You could understand it conceptually and that was enough.
AI agents are different because they require training and iteration. The deployment itself is just the beginning. The value comes from the cycle of training, testing, learning, and improving. You can’t understand that cycle without doing it yourself.
- If you’re a CRO who hasn’t personally trained an AI SDR, you don’t have intuition for what works and what doesn’t. When your team proposes an AI strategy, you can’t separate the realistic from the aspirational.
- If you’re a CMO who hasn’t personally QA’d AI content outputs at scale, you can’t set the right quality bar or build the right workflow.
- If you’re a VP of Customer Success who hasn’t personally tested edge cases with a support agent, you don’t know where the landmines are.
You need the hands-on experience to develop judgment.
The Bottom Line
If you’re a senior executive asking “How do I learn AI?”—here’s the answer:
Stop trying to learn it conceptually. Pick the simplest possible agent deployment, and do it yourself this week. Then do another one. And another one.
That’s how you build the understanding that actually matters. Not courses. Not certifications. Not encouraging your team.
Hands-on keyboard. Yourself.
That’s the path forward.
