Instead of mandatory AI workshops simply cancel all meetings with more than 3 people and no written agenda. Instead block the meeting time for productive work. That’ll be 2000$ of advisory fees for the insane productivity gains I just unlocked you. You’re welcome

If the underlying workflow is noisy, ambiguous, or overloaded with coordination overhead, faster generation just produces more low-context output to review and reconcile.

It absolutely will make some things faster. Anyone that has ever churned out some boilerplate code with it knows that.

...but yeah most organizational processes & people aren't set up for leveraging it and roll out will be slow (same on learning where it does / doesn't work).

It makes small teams without organizational overhead go lightning fast.

It might be the ultimate tool of disruption.

On the one hand, this is a clean post that explains exactly what a lot of us have been thinking and seeing on the job at large organizations doing tech work. Dear Author, I agree with you 110% and want everybody else to come to understand what you have written.

On the other hand, it feels like we've been over this tens of times recently, on HN specifically and IRL at work. Another blog post isn't going to convince leaders that this is how the world works when they are socially and financially incentivized to pretend like AI really will speed things up. So now I just wait for their AI projects to fail or go as slowly as previous projects and hope they learn something.

> Yes, AI can generate code quickly (whether that’s a good thing is open for debate), but that doesn’t mean it’s generating the correct code.

No, the code is actually almost always correct. The way it’s added is probably not what you’re going to like, if you know your code base well enough. You know there’s some ceremony about where things are added, how they are named, how much comments you’d like to add and where exactly. Stuff like that seems to irritate people like me when not being done right by the agent, and it seems to fail even if it’s in the AGENTS.md.

> If you were to give human developers the same amount of feature/scope documentation you would also see your productivity skyrocket.

Almost 2 decades in IT and I absolutely do not believe this can ever happen. And if it does, it’s so rare, it’s not even worth talking about it.

> Every software developer knows that you can’t make projects go faster just by typing faster. If that were the case we would all be taking typing lessons.

So well said.

AI is unveiling how the bureaucracy is the slow part.

    > ...but that doesn’t mean it’s generating the correct code.

Something I'm observing is that now a lot of the pressure moves to the product team to actually figure out the correct thing to build. Some product teams are simply not used to this and are YOLO-ing prototypes now, iterating, finding out they built and shipped the wrong thing, and then unwinding.

Before, when there was the notion that "building is expensive", product teams would think things through, do user interviews up-front, actually do discovery around the customer + business context + underlying human process being facilitated with software.

This has shortened the cycle to first working prototype, but I'd guess that in the longer scale, it extends the time to final product because more time is wasted shifting the deliverable and experience on the user during this process of discovery versus nailing most of the product experience in big, stable chunks through design.

At the end of the day, there is a hidden cost to fast iterative shifts on the fundamental design of the software intended for humans to use and for which humans are responsible for operation. First is the cost on the end users who have to stop, provide feedback, and then retrain on each cycle. Second is that such compounding complexities in the underlying implementation as product learns requirements and vibe-codes the solution creates a system that becomes very challenging for humans to operationalize and maintain.

Ultimately, I think the bookends of the software development process are being neglected (as author points out) to the detriment of both the end users and the teams that end up supporting the software. I do wonder if we're entering an "Ikea era" of software where we should just treat everything as disposable artifacts instead.

I think when LLMs first came out people thought they could just say something like, "Make a Facebook clone". But now we're realizing we need to be more exact with our requirements and define things better. That has always been the bottle neck in software.

When I was working we used to get requirements that literally said things like, "Get data and give it to the user". No definition of what data is, where its stored, or in what format to return it. We would then spend a significant amount of time with the product person trying to figure out what they really wanted.

In order to get good results with LLMs we need to do something similar. Vague requirements get vague results.