Rely On AI And Get Left Behind

LLM-based code generation comes with multiple potential gotchas for a business.

More code hitting process bottlenecks like testing, review and integration makes most teams slower.

More problems being generated by text prediction engines that simply don’t understand what the requirements or the code means makes releases less stable.

These are effects we’re seeing today. Most dev teams are shipping less reliable software, and shipping it later thanks to “AI”. Good work, everyone!

But I suspect the biggest risk is creeping up on us without us necessarily realising.

The more teams offload their thinking to these tools, the less they understand the code your business relies on. And the less they understand it, the less able they are to fix problems that “AI” can’t fix. Outages last longer, and fixes are less sticky.

Mean Time To Failure goes down, and Mean Time To Recovery gets longer. More fires, taking longer to put out. Just ask the folks at AWS!

“AI”-assisted programming’s a bit like pedal-assist on electric bicycles. It makes progress feel easy, but we might not realise the impact that’s having on our coding “muscles” – our ability to comprehend and reason about code.

That is, until we run out of juice and have to pedal unaided. That’s when it becomes obvious just how much of our Code Fu we’ve lost as we’ve come to rely on that assistance more and more. Increasingly, I hear developers say “I’ve hit my token limit, so I’m blocked.”

Working in the low-gravity environment of “AI” coding, we may not notice the decline in our own abilities. And the more they decline, the less able we are to notice – until we find ourselves back in 1g and suddenly are unable to walk.

I’m seeing teams where most of the developers now have a hard time working on their code unaided by “AI”. It’s taking them much longer to wrap their heads around it, and they’re missing more and more problems.

Shipping code faster than we can understand it creates comprehension debt – extra time needed to build that understanding when the tool can’t do what we need it to do (and the need for that is very probably never going away).

Relying on LLMs to write the code for us erodes our ability to understand code, full stop. It’s a double-whammy.

There’s little doubting now that the devs who are most effective using “AI” are the ones who can work just fine without it.

Some say “Use AI or get left behind”. The reality is more probably “Rely on AI and get left behind”. Developers need to maintain their cognitive edge, which means keeping their hand in with regular unaided working.

There’s every chance that, in the future, these developers will be most in-demand.

If they don’t, then this is going to add a lot of risk for businesses – not least because the vendors will have them over a barrel. Price plans are heavily subsidised today. That can’t last, and if you’re not able to walk away, then you have no negotiating position.

That more businesses don’t see becoming completely reliant on a third-party as a strategic risk is baffling, especially in such a volatile market as “AI”. It could all implode at any moment.

But the real risk is that, one day, your core product or system will break, and there’ll be nobody capable of fixing it.

Well, nobody you could afford.