Summarizer

I watched a video of some (unemployed) programmer lamenting over the current job situation market. He had been coding for a good while, but had recently been laid off. The vid was mainly concerning the searching and interview process, but it also did highlight something I find somewhat true and important: Right now we're in a gold rush. Companies, that be established ones or startups, are in a frenzy to transform or launch AI-first products. You are not rewarded for building extremely robust and fast systems - the goal right now is to essentially build ETL and data piping systems as fast as humanly (or inhumanly) possible, and being able to add as many features as possible. The quality of the software is of less importance. And, yes, senior engineers with other priorities are being overshadowed - even left in the dust - if they don't use tools to enhance their speed. As the article states, there are novice coders, even non-coders that are pushing out features like you wouldn't believe it. As long as these yield the right output, and don't crash the systems, that's a gold star. Of course there are still many companies whose products do not fall under that, and very much rely on robust engineering - but at least in the startup space there's overwhelmingly many whose product is to gather data (external, internal), add agents, and do some action for the client. You need extremely competent, and critically thinking technical leaders on the top to tackle this problem. But we're also in the age where people with somewhat limited technical experience are becoming CTOs or highly-ranked technical workers in an org, for no other reason than that they know how to use modern AI systems, and likely have a recent history of being extremely productive.

I've simply not seen this at all. As someone with 10 YOE who was in the job market from November to early April going for senior software engineer roles, quality and architecture seemed to be the thing every org cared about. The bar not only to secure and interview, but to get hired was unbelievably high. Some of the interviews I were getting were at AI startups and all of them were either doing architectural questions or multiple rounds of architectural, behavioural and leetcode problems. Only one of the orgs was hiring junior engineers and the director of technology mentioned to me he didn't want to as they were "incapable", but it was a quota given to him by the board. I also got told by multiple recruitment agents that I wasn't experienced enough, and some hiring managers were demanding 15 YOE for a senior role.

If anything, the current era looks like how 1995-2015 was for me. Back then I was not in the “nitpicker’s radar” yet. I was working in small teams and shipping like crazy, sometimes fixing small bugs literally in seconds. Things worked, were stable, made money, teams were fun and code and product had quality. The post-Thoughtworks, post-Uncle-Bob world of 2015-2025 was absolute hell for a maker. It was 100% about performative quality. Everything was verbose and had to be by the book, even when it didn't make sense from an engineering or product point of view. Different opinions were simply not accepted. It was the age of bloat, of thousands of dependencies, of nitpicks, of infinite meetings, of quality in paper but not in practice, of doing overtime, of being on a fucking pager, of having CI/CD that took 10 hours to merge, and all the stress it comes with. I would be totally ok if all those “professional” engineers from that generation were to be replaced with hackers, both old and new.

Companies that don't fall under that rubric are established and have actual money on the line if their software shits the bed. Software that handles actual logistics and transactions can't be treated to lots of LLM updates without some serious problems arising. Startups and B2B ones especially have always been cheap, cut corners, screwed up and apologized later, and most importantly just created hype and fluff to get investment that's rarely spent on building solid foundations. There's not much crap AI is writing for them now, as code or marketing material, that wasn't already just as junky when it was written by humans. That's been the mutually agreed upon game that startups and VC have played since the 90s. LLMs just distill the douchery and the flawed logic, and it's pleasant to watch their artifacts go down in flames.

Most of the software engineering field ain't no startups, however distorted the most vocal representation on HN could be. Neither are they code sweat shops churing one quick templated eshop/company site after another (knew some people in that space, even 20 years ago 1 individual churned out easily 2-3 full sites in a week depending on complexity). Typical companies, this includes banks btw, see these llms as production boosters, to cut off expensive saas offerings and do more inhouse, rather than head count cutting tool par excellence. Not everybody is as dumb and pennypinching-greedy as ie amazon is. There, quality of output is still massively more important than volume of it or speed. CTOs are not all bunch of shortsighted idiots. But these dont make catchy headlines, do they.

Sounds like it was a prototype to validate an idea? I think at validation stage technical details like that shouldn’t matter. All that matters is there market demand for this. If yes, go and build it properly.

AI has made my work about 5-8x quicker, just because I'm able to have it cover a lot of the grunt work (update 42 if statements in 32 different files) that took time, but no particular skill. I think the use cases where AI makes an economic improvement to the status quo for a business are rare, but they do exist, and they can be a significant improvement. It's like the early days of the dotcom boom and bust - people thought the internet was good for every use case under the sun, including shipping people a single candy bar at a loss. After the dotcom bust, a lot of that went by the wayside, but there was a tremendous economic advantage to the businesses that were more useful when available on the internet.

Yes and this is why small startups can often beat them .

The CTO got fired last month, presumably for poor performance. And the director that has taken is place is now all in on AI because he's desperate to turn things around but has no idea how.

Finally someone who nailed this problem. In the age of AI you need smart people who are aligned with the organization more than ever. If people aren't aligned with the organization then bad, BAD things happen when the political people get access to AI and there's basically nothing you can do about it. They can use AI to fake things for a very extended time, then always find the most optimal way to cover up the problem before the consequences surface and at that point they've already moved so far up the ladder that the consequences don't matter to them anymore. IMO I think it's actively unsolvable in any org that is already deeply infested with politics. On the other hand, having really smart people has massively increased in value. The only way to surface them is through naturally selecting on actual merit which only an entrepreneurship environment can reliably provide. All of this means that I think startups with star teams are going to absolutely dominate for a few years (as in not just executing faster but with less bandwidth, but literally outright winning in everything) until near-full AI automation starts making the big firms win again simply by virtue of throwing tokens at the problem.

> related, i feel it's likely teams that go "all in" on agentic coding are going to inadvertently sabotage their product and their teams in the long run. They are trying to get warm by pissing their pants.

When I worked for a crypto startup early in my career, we were once chastised because no one was in the office at 6:30pm. Some engineers (including me) did mostly work from home but most people, engineers and non engineers alike, mostly worked from the office. And a couple years ago I did a short consulting stint for an AI startup (I know how to pick the bubbles huh?) where I shipped something at around 6pm my time, got a call at 9pm their time to talk about it, and then he asked me "what are you working on tonight?" I quit the next day. Anyway, this advice confuses me because many companies see staying late as a badge of commitment. Maybe it doesn't apply to startups.

"AI speedtracks bullshit shops into bullshit factories" is the other side of "AI enables efficiency gains beyond immagination". As a freelancer I get to see both in action. No surprise! Do you rememeber agile? Sometimes it was pragmatically applied towards efficiency, sometimes it became a bullshit religion full of priest and ceremonies. And on i could go, with more examples, the gist stays the same : new tools, speed increase, faster crash or faster travel depends on the trajectory the company/team/project/thing was already on. A special note on "People who cannot write code are building software." "Fuck yeah" to that! Devs has shipped bad software to people in other departements/domains, for ages. They would never build something better if what they had was good in the first place. When we (coders/startups) were doing it it was "innovation", now is "elephants in the china shop"? And this is not a rethorical snappy question: that IS innovation, instead of critizing the "wrong schema" ... understand the idea, help build it and do the job: ship code that works and is safe. Also, grey-beard here, pls, don't think you can ever have a stable job especially when code is around. It keeps changing, it always has, it always will. AI bringing unprecedented changes is hype. The world always changed fast. If "you" picked software development because of salary, you are in danger. If you did it because you love it, then tell me with a straight face this is not one of the best moments to be alive.

Dismissing this as just another anti-AI blog could appear a shallow dismissal, but in reality, it 8s mostly the pain of adapting to the change. The writer has certain framework of norms or world where good and bad are well defined, and that he knows what's desirable and what's not. This is not new. This happened with every new technology or paradigm change. The old norms take a while to adapt to the new world and it involves some pain, emitting writings like this one. Impersonation by using abilities that are not biologically their own, has been the strategy of dominance for human race. Horse-riding knights with bows and arrows dominated other humans that didn't have horse or arrows. What are you complaining about? Quality of the software produced? Quality of objectives? Here is the truth. None of that is the root goal. You need to change your assumptions and norms and root goals.