Experience vs Innovation: Breaking Down the AI Coding Divide
AI hype is very much in effect in the business world, but ironically any time a new technology comes along it’s often developers that harbor the most cynicism.
And this isn’t new, it’s actually the learned response of most engineers, especially the experienced ones. The old guard questioned Linux and open source, spent countless hours harping on how the cloud was an overpriced joke, and thought JavaScript on the server would never take off. This cynicism can now be found in AI as a developer tool.
Hacker News, whose crowd is usually quick to embrace new technology, isn’t immune to this tech cynicism. Nor is this entirely new - its precursor, Slashdot, was notorious for bad takes on the latest tech (The iPod? - “No wireless? Less space than a Nomad? Lame”, “I don’t see many sales”). It’s actually endemic in many of the established developer spaces. And, frankly, part of that cynicism is well earned; the tech industry is quite famous for over-promising and under-delivering, especially when paired with a grandiose vision for changing the world (“The Net interprets censorship as damage and routes around it” - a quote most developers, including myself, actually bought into).
AI is no different, but the divide seems particularly sharp. Less experienced (and largely younger) engineers are rapidly embracing AI coding tools, while older more established developers are, at best, dabbling. But that tide is starting to turn.
Recently, an article written by a developer using Large Language Models (LLMs) made it to the front page of Hacker News. This wasn’t just another AI hot take, but a deeper dive from someone actively using AI coding tools daily and speculating on how it will transform our industry’s coding practices. Normally, this would have been mercilessly roasted on Hacker News for a variety of reasons. Instead, the top comment read:
“One interesting bit of context is that the author of this post is a legit world-class software engineer already (though probably too modest to admit it). Former staff engineer at Google and co-founder / CTO of Tailscale. He doesn’t need LLMs. That he says LLMs make him more productive at all as a hands-on developer, especially around first drafts on a new idea, means a lot to me personally.” - dewitt
“Dumb engineers” and the parallels to Crypto
The cryptocurrency realm experienced a similar pattern of initial developer skepticism, much of it justified. Early Bitcoin discussions were rife with technical cynicism from established engineers who saw both Bitcoin and, more notably its users, as less sophisticated - **“The people that seem to be most involved in Bitcoin discussions seem to be…well, kinda dumb”**
Now, I’m not here to argue that cryptocurrency wasn’t over-hyped or that it’s lived up to its promises, although it’s hard to ignore that in 2010 when that comment was written, Bitcoin was close to 30 cents, and now is circling 6 figures. But the parallels are still striking. Just like AI today, Bitcoin wasn’t simply dismissed by the technical establishment because of its many very real issues - it was also largely dismissed because of its perceived users.
Until recently there’s been a similar perception of AI coding tools as a crutch for “dumb engineers”. You’ll find these “dumb engineers” in places like Reddit and Youtube, where the enthusiasm for AI feels similar to Bitcoin in the early days. And just like Crypto in 2010, the newcomers are seen as technically unsophisticated rubes, more interested in hype and quick wins than rigorous engineering.
Again, to be clear, there were a lot of people in Crypto that had no idea what they were doing, maybe even the majority. But just like with Crypto, while the people using and extolling AI coding tools may not be working a prestigious software engineering job, this doesn’t mean these tools won’t eventually come to have a huge impact on the entire software development world. Let’s not forget that the #1 IDE in use today (by far) is entirely based on a programming language for “Bad Developers”
It’s time to jump in with both feet
My point is this: if you’re a developer, don’t let this cynicism from the establishment keep you from diving into the AI developer ecosystem. This isn’t Copilot. It’s not some marginally improved autocomplete. This is turning into a junior engineer that handles all your busy work and leaves you with the fun stuff.
The tech world has always been about pushing boundaries, challenging assumptions, and embracing the next big thing. AI has, in many ways, been over-hyped — but it’s also turning into a fundamental shift in how we approach problem-solving and code creation. Those who hesitate will be left behind, watching from the sidelines as the industry moves forward without them - but this time without the enterprise Java job to fall back on (because this too will be filled with developers using AI).
It’s easy to play the cynical developer, and it’s a skill we’ve all learned through years of listening to the marketers, pundits, and tech gurus pitch the next big thing. But if you’re old enough to remember the beginnings of the consumer internet, this holds the same level of excitement and wonder, for me at least. Be the developer who sees the potential, who jumps in with both feet, and who recognizes AI for what it is - the biggest shift in software development since the move from mainframes to the personal computer.