dasil003

This tension is why I refer to myself as a product engineer. Teams where non-technical product managers (ie. your "product team") become feature factories that eventually drown in their own tech debt. Teams where navel-gazing engineering managers (ie. your "engineering team") have too much power end up with premature platformization, and beautiful architecture diagrams while user needs go unmet.

The key is to understand that computers exist to serve human needs, and the less code / UI / hoops to solve a problem the better, and to think end-to-end. If you are able to do that, most systems built by committee have a lot of low-hanging fruit that can be improved without much sacrifice. In practice, political realities and operational concerns may come in the way, but I firmly believe this is the only way to successfully operate as an engineer, and it will only become more important in the age of AI.

Agreed. The law works pretty well for murder/manslaughter because it's a low frequency event that everyone viscerally understands and generally has evolutionarily-ingrained shared values about.

It works less well for other things, like, for example, white collar crime, even when it is low frequency, and even when it is built on financial concepts and norms that have existed at least for decades if not centuries, there's still plenty of gray area for reasonable doubt and spin.

It has pretty much not worked at all for computer and internet regulation except where it could be directly tied back to pre-internet crime definitions (eg. theft of funds). But data privacy, encryption, intellectual property, "hacking", etc, has all been a dumpster fire. And now we pour agentic gasoline on the whole thing? Our legal system is not equipped, least of all not with the current gerontocracy that is beyond clueless about any of this stuff.

This analysis is too one-dimensional, and doesn't factor in social and political factors. As a fellow introverted tech nerd, I understand the perspective, but things don't play out to their logical extremes the way this is projecting. Human factors and social upheaval will come long before any of this becomes a reality as stark as described.

Not that I disagree with the point the author is trying to make vis-a-vis Brooks' Law, but there's another narrative at play here that I find more interesting.

> But someone nudged me: can't you have a look at it?

Clearly this person has some combination of thinking the people already looking don't know what they're doing, and the author being a technical person will be better at it.

From the author's side there is little interest in engaging, perhaps because of a desire not to feed the help vampires, or maybe the meeting is low enough value that an unintentional filibuster is not such a bad thing, or any number of other situational reasons that I can imagine but are not discernible from the context given. Human psychology is fascinating.

It's a strange critique to personify a structural problem in this way. It neither holds any individual accountable for their actions, nor points towards a better structure.

There's a time and a place for both?

Certainly natural language prose can articulate human-level concepts and priorities that code cannot. The fact that LLMs can interpret and apply these things is novel and useful. I agree with the author there is a lot of juice that can be squeezed out of this.

But on the other hand, whenever I start writing code (with or without LLM assistance), there is always a huge amount of learning and iteration that happens. No matter how thoroughly I thought through everything, or how perfect the idea seemed in my head, it always evolved once the implementation was concrete. And furthermore, once you have code running and people depend on it, the code is the reality, and any other documentation or vision statements have a tendency to go stale. Obviously AI makes it easier to keep documentation up-to-date, but the disconnect between the idea of the system and what the system actually does remains.

For this reason I don't see any huge value in deliberately moving to a higher layer. All the same modalities can still be applied with AI: comments, commit messages, PR messages, literate programming, READMEs, AGENT.mds, tech specs, tech 1-pagers, vision statements, etc. I write a doc when it's useful to communicate to one or more parties, otherwise I try to keep everything as minimal and possible, often that means just live in the code.

Yes, let's just get over it.

The system is already broken, so turning over control to AI companies where no human ever sees the patient is a no brainer. There's no tradeoff to consider here, after all the our entire economy is riding on the success of AI, so any concern about human factors that can't be measured by economists is just a distraction from what really matters.

Is it surprising there’s a gap between their vision and reality? Obviously if all that comes to pass they’re hoping the societal implications get figured out to keep the pitchforks at bay.

FWIW no I don’t believe models can replace intellectual work because intelligence is not purpose, and no other entity can tell us what we want. While AI has made building cheap and cutting through the noise even harder, it hasn’t made deciding what to be build any easier, and personally I felt that was already the bottleneck a decade ago (think bullshit jobs, App Store saturation, etc).

Of course that’s just one perspective and I could be totally wrong. But given the situation it makes perfect sense for the big labs to stay focused on building the most valuable shovels in the world and leave the business risk and finding the money for the cash furnaces to others.

Is this always true? I'm honestly not sure. For unit tests I completely agree with you, for integration tests I'm not so sure—validating permutations does not necessarily couple you to code, and may in fact be good discipline for user expectations.

I'm really not worried about this scenario at all. I mean yes, it will be possible for bad programmers to build 173 million line monstrosities held together with duct tape and bailing wire, and certainly these things will exist. And it's also possible that good programmers will be paid by idiots to maintain said monstrosities with no agency to actually fix the root cause. Both of those things will happen.

But a good programmer given agency to solve the higher order problem will always have a path to rewrite, because any "simple CRUD app" exists to serve human purposes, and in order to meet those needs the human interface need to be legible, and to be legible there have to be tight enough inputs and outputs that you can create a parallel implementation without the incidental complexity.

Now you might say this won't be the case for large multi-party distributed systems, and that is true, but that is also true today where all manner of insane cruft and non-sensical logic and workflows exist. But even where things appear totally intractable due to legacy requirements and conflicting logic, there still is a human backstop where if the pain is big enough, any process can be fixed. In practice competing interests may prevent such fixes for a long time, but that is political problem not a technical problem, and it's not inevitable as things can flip very quickly due to the dynamics of human attention and power.

Your first sentence makes sense, but not following your second. Who needs to pick and what are the sides they are choosing between?

They may ask why you don’t have a stamp from the foreign country you were just in though, no? (At least for the ones that still do stamps)

Maybe so, but what I have found in my career long before AI is that a significant of percentage of biz people lack the capability to think holistically or end-to-end. Product people are a little better on average. But at the end of the day it is senior technical folks with product and UX sensibilities who are able to determine what most stakeholders actually want. I find the infantilisation to be going the other way.

Having worked continuously this decade on one massively complex consumer facing app that interacts heavily with real-world scenarios, I can say that the problems of cohesion existed well before the agentic revolution. Tons of features built by myopic teams simply because they couldn't understand enough of the system (both online and offline, meat-space interactions) to make good design decisions. AI actually helps here by being able to perform deeper reading and analysis than any human can do. But then the risk is that it can also produce way more random non-cohesive features.

So far I kind of feel like it nets out to the same bottleneck being good judgment from decision makers. And you might say, no, leadership will just put more and more pressure to add more complexity just because we can and it makes it appear that we are moving fast. But when it comes to real-world apps, there is a backstop which is that things that are too complex and illegible end up not being fit-for-purpose for human problems.

Claude Code and other general purpose AI tools are not like this, because they are literally trying to optimize it for every single kind of knowledge work with zero constraints on use case or target audience other than chasing the next juiciest one they can with essentially unlimited resource. 99% of software is not like this, and when the dust settles I suspect software won't be anywhere near as different as the doomers or the maxxers are predicting right now.

Certainly the level of detachment and alienation has been growing for a long time and is now at quite an extreme. I’m not sure that I would characterize that by saying there is less societal pressure overall though. People feel pressure for lots of reasons and it doesn’t necessarily require the judgment of another individual observing them.