I'm a Senior Freelance Programmer, I can see many of my past and present clients moving towards the exact path you described. I keep warning them during meetings that Claude model isn't sustainable for long, eventually the VCs will come for their revenues and Claude will be forced to close their access to all but the most enterprisey ones with deep pockets. The mere electricity cost for that kind of high level reasoning and abstraction can't be subsidized forever. However, there are other forces which pull them towards Claude and AI workflows. Most of the clients are in a "wait and watch" mode right now, using LLM assistance for code generation but not fully depending on them.

Before LLMs came, there used to be the technical debt to deal with in a project, now there is also the added cognitive debt which is way more subtle and impactful long-term. If your source of truth isn't source code but a prompt (or even a series of prompts with branches) and the executor of prompts is a non-deterministic agent, I think you've already lost the battle there.

I have had some truly spectacular results that still kind of stagger me in the last few months using Claude in my hobby projects -- but even though Claude insists on trying to slip its name into the git history as credit it's not Claude -- it's me. Someone who has studied CS and software engineering for decades will craft different prompts from someone without that background. A suggested axiom: there is nothing I can build with Claude that I could not build myself with my current level of CS knowledge, assuming I had infinite focus and time. In my hands it can go as far I could anyway, and no further. (But it is faster!) My experience bears that out so far.

For the last 6 decades or so, a computer was a machine assumed to operate with high levels of precision and deterministic outputs. Such precision enabled spacecraft like Voyager 1 & 2 to travel billions of miles from Earth, staying on course, semi-operational and sending telemetry- 50 years after launch.

Now we have machines that, when asked to produce a paperclip, may instead produce a butter knife, or a banana, or maybe just a "try again later".

These modern "tools" are quite a different animal. They're more akin to roulette wheels that generate massive amounts of heat and CO2.

> ask claude to write, and ask claude to explain

This works, until it doesn’t. I’m continuously shocked by these stories, where so many people put the future of their job/company in the hands of these agents after only a few months of existing.

I still constantly run into bad output from LLMs, from code to basic questions. I don’t understand how anyone can hand things over to something that is laughably wrong on a pretty regular basis, often in subtle ways that won’t be noticed by someone who isn’t reading closely and thinking critically.

They’ve gotten better, but I still regularly give them the old Nick Burns treatment, push it out of the way, and do it myself.

We're still running the race, but it's just not on foot anymore. You can still run it into the wall if you're not careful where you're going.

Remember you had to quit social media to keep your sanity in check? Ok, now AI. Same thing.

I mean, literally the answer is that nobody knows. Maybe the robots replace us all. Maybe they shift those who remain into being some combination of Product Manager and QA. Maybe there's still a role for a technical overseer even in the medium-long run.

But it sounds like you're really asking about the state of the world today. If so, I don't think that ideal state is like your friend's company (or at least, as it appeared to be to you). It might be possible that you can make that "dark factory" pattern work (StrongDM seems to be doing it), but it would require infrastructure and discipline that I doubt they're mustering. Think about how CD didn't involve taking a sloppy build process with no testing or observability and just going straight to prod -- it required building up a lot of infra and discipline first.

But on the other hand, I don't think the ideal present involves artisan hand-crafting code either. I haven't written a line of code by hand in enough months that it would genuinely feel weird if I were to try to program that way despite decades of having done just that. That era's done with, and moderate normie practices right now today are more about supervising and guiding agents than about chiseling code into clay tablets.

I've posted a recent article about the future of software development https://saturnino.substack.com/p/out-of-the-loop?r=7eqhw&utm...

Basically, in a decade or so, we'll be completely out of the loop in software development; even this title won't exist anymore (like the 2000's webmaster). We'll still be around, but with different roles.

This has always been a very different profession depending on where you work and what you're working on.

I haven't worked at a startup in over a decade, but the stories I hear now sound the same as back then. There's lots of wasted effort for mediocre to poor code destined to be rewritten or thrown away until there's enough investment to justify more work. At which point, "more work" just means more sprawling slop instead of fixing the technical debt rotting at the foundation.

AI just put a spotlight on the futility of trying to run before you can walk. Whether so many founders are going to stay in denial about it is yet to be seen. Statistics about any line of business says yes. This is how most businesses fail and most of them have to fail.

From what you said: Not looking at code is bad, not because Claude can slip a few bugs (it can), but because LLMs tend to default to writing more code and features than needed, which isn't a good thing. I see a lot of people making 10+ PRs per day, but most of them are just going back to fix earlier PRs.

Claude always likes to "go big," for example, by choosing tools that can support millions of concurrent users or by adding unnecessary layers of abstraction that create more maintenance pain. I guess that's good for LLM companies, since more tokens are spent fixing the mess it caused.

Every time I enter plan mode for a huge feature, I end up cutting about 30-60% of the task scope before the LLM can actually start the work. I review the final code, and I still find things to cut. As said before "The best code is no code, or code you don’t have to maintain" [0]

0: https://www.simplethread.com/20-things-ive-learned-in-my-20-...

My personal experience: writing code has always been the easy part. AI does most of that now.

Understanding the problem and the existing system well enough to design the right solution, even with AI assistance, is a higher cognitive load. I’m doing a lot more of that lately.

I’m more productive, but also more tired. This may be due in part to the breadth of what my team owns, which makes my day a bit more context-switchy than other teams.

As others in this thread have noted, the situation is still evolving. However, I worry less each day about being replaced by AI. There has always been more work than available bandwidth in my experience.

What seems clear to me is that expectations around velocity and throughput will increase (are increasing). AI use will be required to meet those expectations. Learning to use this new tool effectively will be essential for career progression (and preservation).

For me in large tech:

- Humans still own the code

- All code reviewed by humans

- LLM adoption varies across the org. Some are heavy users and some less. Some suspicious some less.

Where are we heading? Depends on model/harness capabilities. Likely some sort of mix where some projects will still require expert humans and others will just be vibe coded. How much we lean in that direction - we'll see.

> First off, is this similar to what's going on at your company?

Everyone is trying to figure out how to do this.

My team writes all its code with agents/LLMs but for any meaningful PR we're pretty aggressive code reviewers. I'll easily spend half a day reading my own PR if it's important enough, and make sure I understand conceptually everything that's happening. This is partly because I know my peers will read the PR with the same intensity and will ask questions.

But I'm also not sure this is the right way long term. To address you're other, larger question: I keep thinking we (as a profession) are focusing too much on how to make software this way, rather than thinking bigger picture. I often wonder "why aren't some of our customers just building their own version of our product with AI?" Not the software itself, just the part that gives them the answer they need.

Honestly, I think the answer to that question is inertia. People, especially non-tech people, just aren't thinking this way about the software products they purchase. Likewise, all these managers at big corps aren't trying to automate their teams away (C-level might be) because those people represent the authority of that manager, it's how they show how important they are. So AI fumbles in these corporate environments where it's required because nobody has incentives to succeed.

But that will change. There will still be software, but how it looks and where its used I suspect will be radically different.

how is that company doing?

i think that is a more important question that you shouldn't ignore.

do they have growing revenue?