My eldest daughter is in her mid-teens, and I honestly don’t envy her, she’s trying to tackle the big question of what to do for the rest of her life, which is a question most adults still wrestle with! She is very strong in STEM but also super creative. She’s bouncing back and forth between multiple ideas including biology and music, but she says her ideal role would probably be a developer. If this was 20 years ago, I would have said AWESOME [#prouddad]! Now, I’m sadly not so sure…
In my 20+ years of being an IT greybeard, I’ve watched whole job categories appear, mature, and then blur into something else (albeit often just a rebrand!). So when my daughter says developer, I don’t hear a stable destination, I hear a role changing at a such high speed it’s making the current generation of devs heads spin!
Skills that survive change
The most interesting part of my career hasn’t been any specific technology (despite what some might think!), it’s been architectural thinking. The ability to take something vague and fuzzy, break it apart, work out how the pieces connect, and describe what “done” looks like clearly enough that someone can actually go and build it. I’ve done that for “human” teams for years, but it turns out AI needs exactly the same thing, just faster and with even less patience for ambiguity [which, if you’ve ever worked with developers, is really saying something 😁].
The numbers are genuinely becoming bonkers… Cursor generates around $16 million in revenue per employee, Midjourney hit $200 million with 40 people, and tonnes of organisations now have three engineers shipping what would’ve taken a team of ten, eighteen months ago. I won’t even guess how much Peter Steinberger got paid by OpenAI!
I think the interesting bit here is that the cost of writing code is collapsing, but the cost of being unclear about what you want built is going up! It’s the age old saying about kak in, kak out… AI speeds up code generation, even with vague requirements (unless of course, you’re reverse prompting!). As any developer who’s ever sat through an unclear brief will tell you, without that clarity of requirements, we will just build wrong code faster. Indeed, AWS seems to have invented KIRO to solve this exact problem…
Crystal balls…
Nate B Jones says there’s an uncomfortable split emerging. One group is learning to work with AI as a legit force multiplier, holding entire systems in their heads, defining outcomes clearly enough that agents can execute them, and actually checking whether what came back solved the right problem (and didn’t introduce a massive security hole in the process!). The other group is using AI as a faster version of what they were already doing, which he says sounds fine until you realise that’s also the work AI handles first when companies start “optimising” their teams. Entry-level developer postings are down, depending on who you ask this may be as much as two-thirds, and the junior pipeline that most people assumed would always exist is visibly narrowing. It’s worth noting that Matt Garman says the opposite!
His video on the topic was the other trigger for this post and is worthwhile taking the time to watch.
So what should we tell someone starting out? I would still encourage young people to go into tech, but think carefully about which skills they’re building. Understanding how systems work, how to define requirements precisely enough to actually be useful, how to translate from IT to human, how to ask the right questions before anyone opens an IDE… you don’t need the architect job title to think like one!
Part of me really wants to tell my daughter to go for it, because she’d be brilliant at it! But I can’t tell her in good conscience that aiming for a “traditional” developer role is a safe long-term bet. I’d rather she trained in the kind of thinking that travels well regardless of where the IT industry ends up (or indeed whichever industry she ends up working in). I know she’ll be fine whatever she picks… I just wish I could give her a better answer than “it depends”.







RSS – Posts