I am on vacation, so posts will resume properly next week. In the meantime, please enjoy this round up of Friday’s live - with thanks to , and others for joining!
This week I explored what might be the most critical question for the future of software engineering: how do we learn—and teach—in the age of AI?
AI Summary
This talk examines the paradox at the heart of AI’s impact on software engineering: it simultaneously creates the greatest learning crisis and the greatest learning opportunity we’ve ever faced. The crisis is economic—junior engineers traditionally learned by doing small tasks repeatedly, but AI can now do those tasks for pennies and instantly, making the old apprenticeship model economically unviable. The crisis is also psychological: when you’re struggling to learn something and AI can just “do it for you” at the touch of a button, the temptation to take shortcuts is overwhelming.
But the opportunity is equally profound. We now have what might be the most powerful learning tool humanity has ever created—an interactive tutor available 24/7 that can explain concepts at any level, answer follow-up questions, and adapt to your learning style. The key question isn’t whether AI helps us learn, but what we should be learning. The answer lies in what makes us uniquely human: our ability to envision futures that don’t exist yet and navigate toward them. AI deals with the art of the probable (statistically likely outcomes); humans deal with the art of the possible (envisioning and creating what has never existed before).
This fundamental difference—between remixing existing patterns and genuinely envisioning new futures—is what will define valuable engineering work going forward. And getting there requires learning, which remains distinctly, powerfully human.
Chapters
(00:00:01) - Introduction: Learning in the Age of AI
(00:01:22) - Why Software Engineering Always Required Learning
(00:02:17) - My Journey: WordPress to React to AI
(00:05:16) - AI: The Biggest Shift in Software Engineering History
(00:06:38) - The Crisis: How Junior Engineers Traditionally Learned
(00:08:48) - The Economics Have Collapsed
(00:09:22) - The Temptation Crisis for Learners
(00:10:43) - Staying Sharp: The Discipline Required
(00:13:29) - The Opportunity: The Greatest Learning Tool Ever
(00:16:08) - The Economic Opportunity: Junior Engineers + AI
(00:19:13) - AI Forces Us to Do What Only Humans Can Do
(00:20:44) - What Should We Be Learning?
(00:21:55) - The Art of the Probable vs. The Art of the Possible
(00:23:11) - Envisioning: The Uniquely Human Skill
(00:26:28) - The Best of Times, The Worst of Times
(00:28:06) - The Core Trade-Off: $1 Today vs. $10 Tomorrow
(00:29:12) - What Is Software Engineering Really About?
Key Moments
The Economic Collapse (08:36) - “Now the economics of that completely tanked because now rewriting that component, changing the colour of that button, whatever those low-level tasks those first few years you would give to a junior engineer, now AI can do it for pennies on the dollar and incredibly quickly. So now it’s not twice as expensive to get a junior engineer to do it. It’s like 10,000 times more expensive, and it just doesn’t make economic sense.”
The Temptation (12:01) - “Learning is not always easy but now alongside us at the touch of a button we have this thing that could just do it, it just at least ostensibly at least in terms of feedback we could get something we could just seemingly get it just done magically and this is a real crisis right, it makes learning far more... it’s much more of a discipline.”
The Greatest Learning Tool (14:07) - “You have potentially the greatest learning resource known to man thus far at your fingertips... Not only can I ask it specifically the exact problem I’m having, exact problem I need support with, if it gives me an answer that I’m not sure about, or it doesn’t quite make sense or references other concepts I’m unaware of, I can have a conversation with it... We have essentially an interactive tutor, if we treat it like that, in our pockets alongside us.”
The Economic Opportunity (17:26) - “That junior engineer can do a lot more for a lot cheaper than would have been possible, and it really expands the market... I’m providing a junior engineer, layering over my fractional sort of support... They’ve got the energy. They’ve got the time. They’ve got the drive. They’re in that stage in their career where they need to be shipping and writing production code.”
The Uniquely Human (19:13) - “AI is going to force us and or encourage us, empower us to do what only humans can do. And I think that learning is… fundamental to what it means to be human.”
Art of the Probable vs. Possible (21:02) - “AI deals with the art of the probable and humans deal with the art of the possible. AI by the technology is always going to be statistically geared towards the mean, towards the average... The really unique thing that humans can do is this envisioning. I can see something in my mind’s eye that doesn’t exist and may have some relation to the existing world, but maybe like is really out there and would statistically be really unlikely.”
The Core of Engineering (29:40) - “The core of the craft is understanding what, how do you make software easy to change. That’s what I categorise as good software... easier to change software is more valuable software. It’s as simple as that. It generates more value for the company or whoever the person is you’re writing that software for.”
Sharing is caring!
If this exploration of learning in the AI age resonated with you, please consider sharing it with two friends navigating similar questions—especially if they’re early in their engineering careers.
Also, I’d love to hear your thoughts in the comments: How are you approaching learning with AI? What are you finding works (and doesn’t work)?
