Dear founder,
I just had one of those realizations that makes you stop and think differently about everything we’ve been discussing around AI tools. You know, we talk a lot about AI helping us build things faster, about automation, about whether it’s going to replace developers. But there’s a side effect happening right now that I think is either completely undervalued or just not being observed at all.
And honestly? It might be more transformative than the automation piece we’re all focused on.
The Way We’ve Always Learned to Code
Let me paint you a picture of how learning to code has worked for, well, basically forever.
For the longest time, if you wanted to learn how to code, you had two main paths. The first was the intellectual approach - you’d dive into books, wade through documentation, try to absorb all this abstract knowledge and somehow transform it into working code. The second was the experiential route - what most of us self-taught developers know intimately. You’d run headfirst into every single issue, one by one.
You’d tap into Stack Overflow when you were lucky, maybe find someone else’s solution that kind of fit your problem. If you could handle it, you’d try to read more experienced developers’ code and reverse-engineer how that could apply to what you were building. But here’s the thing - it was always this process of consuming information that wasn’t really code to then produce code.
And it was asynchronous. Always.
You’d hit a wall, spend hours researching, maybe post a question somewhere and wait for an answer. If you were really fortunate, you were part of a team where you’d get feedback, but even then, the core experience was the same: you, alone, diving into a problem, running into a wall, then running into twenty more walls over the next few hours.
Then you’d either give up and ask someone else, or you’d figure it out through sheer persistence and take that hard-won learning forward. That’s how we’ve been learning to be better programmers, better infrastructure developers, better software architects for decades.
The Shift That’s Happening Now
But something fundamental is shifting with AI software development tools. And I want to be clear - this has very little to do with the admitted magical capacity of letting AI do the work for us. That’s a whole other conversation.
This is about something much more profound for people who are still willing to learn how to code. And there are still very many of those people, because here’s what I think we all understand deep down: coding is significantly more than telling a machine what to do.
To be able to judge good code, you still have to be able to write good code - or at least understand what the difference is between good code and bad code. You can’t delegate that judgment entirely.
So for people who want to learn this craft, something remarkable is happening. All of a sudden, they don’t have to do it all by themselves anymore.
The 24/7 Coding Mentor
Think about this: with AI tools, learners can actually look at what an experienced person would do and pair program with them. Not just occasionally, not just when schedules align, but 24/7. They can ask questions of that experienced developer 24/7, for effectively free.
Even if they’re paying $20 a month or $200 a month for an agentic system, it’s a 24/7 relationship. If someone’s trying to learn how to code, they can constantly have an AI system build code for them and - here’s the crucial part - teach them how they did it, why they did it, what they thought about, why they approached things a certain way, why they didn’t choose alternative approaches.
For people who learn by imitation, for people who learn by watching other people practice their craft, I think this is the first time that coding has become truly accessible to them at scale, and for almost zero marginal cost.
The YouTube Effect for Interactive Learning
This reminds me of what I call the YouTube effect - that phenomenon that’s been teaching people to do all kinds of things for decades now. And yes, coding has been on YouTube too, and it’s been a great way to learn. But YouTube still has that asynchronous limitation. You watch a video, you try to figure something out, you watch another hour of tutorials, then you attempt to implement it in your system.
With AI systems, both for coding and all other activities, something different is happening. Coaching - active, synchronous coaching - has become a way of getting into things.
I find this fascinating because coaching used to be something highly expensive, highly exclusive, and honestly, very hard to get right.
The Coaching Revolution
If you’ve ever worked with a coach or consultant before, you know the challenges. Most of them might not be the best fit for you. Most consultants might not have the exact experience you need for your specific situation. Most coaches might just have a different personality that doesn’t click with how you learn.
It’s like finding a therapist - it often takes a while to find someone who really works for you, because you need that compatibility. Same with coaches, same with consultants.
But AI systems? They can be all of these different types of mentors just by being prompted to be them. You can very quickly establish a connection with these tools that would have been impossible with real people - either because you were limited to a certain selection of available experts, or because those relationships were prohibitively expensive.
And this is really exciting to see, not just for coding, but for all kinds of learning activities.
Different Ways of Learning
Here’s something I think we don’t talk about enough: a guided, experiential approach that’s almost synchronous in nature is now available. And this is going to do a lot for people who learn in ways that our traditional education system hasn’t served well.
A lot of people are not the best readers. They’re not the best listeners or abstract thinkers when it comes to learning. A lot of people need to be shown precisely what and how, in an almost deductive way.
They don’t learn inductively - where you gather all the knowledge first and then synthesize the result. They learn deductively - they need to see the result first, then deduce their way into understanding the components. They disassemble the final product to understand the pieces they’ll need to reassemble it themselves in the future.
This is a completely valid way of learning, but it’s been incredibly hard to access in traditional coding education.
Reframing the Narrative
So if we look past all the shiny “AI is doing work for me” headlines, or the “AI is threatening my job” anxiety, and instead see these tools as always-on, extremely affordable empowerment tools - as personal coaches for everything - then all of a sudden, this technological shift becomes even more significant.
Yes, there’s definitely a hype cycle happening with AI companies building products that nobody wants or needs. But if we change our perspective and see AI as a learning vehicle first and foremost, we’re looking at something really interesting.
We’re looking at the democratization of mentorship.
The Bigger Picture
This isn’t just about coding, of course. This same principle applies to design, to marketing, to business strategy, to any skill where learning from experienced practitioners has traditionally been gate-kept by access and cost.
But coding is a particularly powerful example because it’s been such a clear illustration of the “lone wolf” learning path. The image of the programmer staying up all night, banging their head against incomprehensible error messages, finally having that breakthrough moment at 3 AM - that’s been our romantic notion of how this works.
And while there’s still value in that struggle, in building that persistence and problem-solving muscle, we don’t have to make the learning process unnecessarily isolating anymore.
What This Means for You
If you’re someone who’s been thinking about learning to code, or if you’re early in your journey and feeling overwhelmed by the traditional path, I want you to know that you have options now that simply didn’t exist before.
You can have conversations with your AI coding mentor. You can ask “why did you choose this approach over that one?” You can say “I don’t understand this concept - can you show me three different ways to implement it?” You can request “walk me through your thought process as you debug this.”
This isn’t about replacing the fundamentals or skipping the hard work. It’s about having a guide for that hard work.
And if you’re an experienced developer, I think there’s an opportunity here to reflect on how you learned and consider how you might help others learn more effectively. The AI tools are democratizing access to mentorship, but they’re modeling their guidance on the collective wisdom of experienced developers.
The Learning Revolution
We’re witnessing something that goes far beyond just coding tools. We’re seeing the emergence of accessible, personalized, always-available mentorship for any skill we want to develop.
The question isn’t whether this will change how people learn - it already is. The question is whether we’ll recognize this shift for what it really is: not just about making us more productive, but about making learning itself more accessible, more personalized, and more effective for different types of minds.
That’s the revolution hiding in plain sight while we’re all debating whether AI will replace developers.
And honestly? I think this learning revolution might be the more important story.
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