When I first started programming, some thirty-five years ago, it was a somewhat quiet, if not shy, profession. It had already been around for a while, but wasn’t visible to the public. Most people had never even seen a serious computer, just the overly expensive toys sold at department stores.

Back then, to get to an intermediate position took about 5 yrs. That would enable someone to build components on their own. They’d get to senior around 10 yrs, where they might be expected to create a medium-sized system by themselves, from scratch. 20 yrs would open up lead developer positions for large or huge projects, but only if they had the actual experience to back it up. Even then, a single programmer might spend years to get their code size up to medium, so building larger systems required a team.

Not only did the dot-com era rip programming from the shadows, but the job positions also exploded. Suddenly, everyone used computers, everyone needed programmers, and they needed lots of them. That disrupted the old order, but never really replaced it with anything sane.

So, we’d see odd things like someone getting promoted to a senior position after just 2 or 3 years of working; small teams of newbie programmers getting tasked with building big, complex systems with zero guidance; various people with no significant coding experience hypothesising about how to properly build stuff. It’s been a real mess.

For most computer systems, to build them from scratch takes an unreasonably large amount of knowledge and skill, not only about the technical aspects, but also the domain problems and the operational setups, too.

The fastest and best way to gain that knowledge is from mentoring. Courses are good for the basics, but the practice of keeping a big system moving forward is often quite non-intuitive, and once you mix in politics and bureaucracy, it is downright crazy.

If you spend years in the trenches with people who really get what they are doing, you come up to speed a whole lot faster.

We have a lot of stuff documented in books and articles, and some loose notions of best practices, but that knowledge is often polluted with trendy advice, so people bend it incorrectly to help them monetize stuff.

There has always been a big difference between what people say should be done and what they actually do successfully.

Not surprisingly, after a couple of decades of struggling to put stuff together, the process knowledge is nearly muscle memory and somewhat ugly. It’s hard to communicate, but you’ve learned what has really worked versus what just sounds good. That knowledge is passed mouth to mouth, and it’s that knowledge that you really want to learn from a mentor. It ain’t pretty, but you need it.

As a consequence, it is no surprise that the strongest software development shops have always had a good mix of experience. It is important. Kids and hardened vets, with lots of people in the middle. It builds up a good environment and follows loosely from the notion that ‘birds of a feather flock together’. That type of experience diversity is critical, and when it comes together, the shop can smoothly build any type of software it needs to build. Talent attracts talent.

That’s why when we see it crack, and there is a staffing landslide, where a bunch of experienced devs all leave at the same time, it often takes years or decades to recover. Without a strong culture of learning and engineering, it’s hard to attract and keep good people; it’s understaffed, and the turnover is crazy high.

There are always more programming jobs than qualified programmers; it seems that never really changes.

Given that has been an ongoing problem in the industry for half a century, we can see how AI may make it far worse. If companies stop hiring juniors because their intermediates are using AI to whack out that junior-level code, that handoff of knowledge will die. As the older generations leave without passing on any process knowledge, it will eventually be the same as only hiring a bunch of kids with no guidance. AI won’t help prevent that, and its output will be degraded from training on those fast-declining standards.

We’ve seen that before. One of the effects of the dot-com era was that the lifespan of code shrank noticeably. The older code was meant to run for decades; the new stuff is often just replaced within a few years after it was written. That’s part of why we suddenly needed more programmers, but also why the cost of programming got worse. It was offset somewhat by having more libraries and frameworks available, but because they kept changing so fast, they also helped shorten the lifespan. Coding went from being slowly engineered to far more of a performance art. The costs went way up; the quality declined.

If we were sane, we’d actually see the industry go the other way.

If we assume that AI is here to stay for coders, then the most rational thing to do would be to hire way more juniors, and let them spend lots of time experimenting and building up good ways to utilize these new AI tools, while also getting a chance to learn and integrate that messy process knowledge from the other generations. So instead of junior positions shrinking, we’d see an explosion of new junior positions. And we’d see vets get even more expensive.

That we are not see this indicates either a myopic management effect or that AI itself really isn’t that useful right now. What seems to be happening is that management is cutting back on payroll long before the intermediates have successfully discovered how to reliably leverage this new toolset. They are jumping the gun, so to speak, and wiping out their own dev shops as an accidental consequence. It will be a while before they notice.

This has happened before; software development often has a serious case of amnesia and tends to forget its own checkered history. If it follows the older patterns, there will be a few years of decreasing jobs and lower salaries, followed by an explosion of jobs and huge salary increases. They’ll be desperate to undo the damage.

People incorrectly tend to think of software development as one-off projects instead of continually running IT shops. They’ll do all sorts of short-term damage to squeeze value, while losing big overall.

Having lived through the end of programming as we know it a few dozen times already, I am usually very wary of any of these hype cycles. AI will eventually find its usefulness in a few limited areas of development, but it won’t happen until it has become far more deterministic. Essentially, random tools are useless tools. Software development is never a one-off project, even if that delusion keeps persisting. If you can’t reliably move forward, then you are not moving forward. At some point, the ground just drops out below you, sending you back to square one.

The important point at the high level is that you set up and run a shop to produce and maintain the software you need to support your organization’s goals. The health of that shop is vital, since if it is broken, you can’t really keep anything working properly. When the toolset changes, it would be good if the shop can leverage it, but it is up to the people working there to figure it out, not management.