I'm actively watching understanding slip away from developers, code review getting paired down to no comment checkmarks, and codebases go to bloated messes that nobody can read. Axioms like engineers must understand and take responsibility for the code they ship are getting torn down, and the products coming out are reflecting conway's law, becoming impenetrably obtuse and always "so complex there are no obvious deficiencies" (as opposed to "so simple there are no obvious deficiencies" which used to be the aim).
The one thing plan mode helped is for the humans to get an understanding of the strategy, and be able to poke around and look at the design and architecture. You can achieve this with some self discipline and keeping shorter leashes on agents, but it feels like a losing battle. The best devs still put out good code, but the poor devs are learning nothing while their metrics look great. I can't help but think we are racking up immense amounts of debt that will very soon become due.
Just like rushing made messes in the before times so too does rushing via LLM. The exact same outcome will happen, but at a far greater velocity and scale than anything we've seen in this industry before. Old Testament, Mr. Mayor, real wrath-of-God type stuff!
100% this. Some people are basically adding AI as a dependency for their projects. They no longer understand the code
"The one thing plan mode helped is for the humans to get an understanding of the strategy"
For me, this phase still happens, but a distinct "plan mode" is unnecessary: I just tell the model, "This is discussion; no code changes yet." and spend hours figuring out what will and will not be done.
It's truly bizarre to read about all these people who just give up on any understanding about what they are working on.
I very regularly use plan mode not to even make a plan of action itself, but to better understand what possible issues might come up when implementing some feature or fixing some bug. And it is quite common for me to fix or rewrite certain findings that AI comes up because its assumptions are not quite right or don't align with overall goal.
And yet so many seem to be perfectly fine leaving all the decisions to AI - even if it's going in the wrong direction. I suppose that's all the people who got into software purely for money or status - never really caring about the actual thing they are working on.
And what happens when it becomes due?
> The best devs still put out good code, but the poor devs are learning nothing while their metrics look great. I can't help but think we are racking up immense amounts of debt that will very soon become due.
I agree with this, but the reality is that it's only the result of models empowering devs, and power in good hands amplifies positive results while power in mediocre hands amplifies technical debt.
It's a good time to choose wisely who you work with.
I feel the same way but I have successfully refactored some of the early experiments. Our team has settled on targeting a double output from the before times but more ambitious product vision because AI can teach us things we don't know. We actually target 2 days of coding and 3 days of learning with Ai so the increased efficiency allows upskilling rather than just pushing more code