What is an "AI project"? The post doesn't define it.
Is it writing some software from scratch? Using an LLM chatbot by non-coders, either internally or externally? Or something else entirely?
Some examples would really help.
the ill-conceived moonshots by and for a non-technical audience get labelled as "AI projects/initiatives" and they fail.
> There is a related “Theorem” about progress in AI: once some mental function is programmed, people soon cease to consider it as an essential ingredient of “real thinking”. The ineluctable core of intelligence is always in that next thing which hasn’t yet been programmed. This “Theorem” was first proposed to me by Larry Tesler, so I call it Tesler’s Theorem: “AI is whatever hasn’t been done yet.”
I am reminded of "game AI", which for the most part has historically been just giant decision trees, encoded one way or another, because if you hook up any sort of real AI to a game entity or collection of game entities that does any sort of learning or training, even simple 1980s-era reinforcement learning, it turns out the game entities will roflstomp the human players, and the human players aren't interested in paying for that experience. We've been calling those collections of if statements and for loops "AI" for a long time, though, because who wants to hear about how deliberately stupid their opponents are?
We taught the computer to spell check, but the computer still didn't feel smart like a person, just smart like a machine so that obviously wasn't AI. We taught it to do algebra, same thing. With LLMs though, now it really does feel like an artificial human, so this time it really is AI.
I completely buy the “emperor’s new clothes” argument for work process automation. I’m surprised they don’t address AI-assisted engineering, which seems to be going positively for a lot of folks (although I have doubts about its sustainability). I disagree about the success of chatbots, if the problem is narrowly-defined and chosen properly. My previous company built a conversational interface to a vector database and saw good results. (Although, arguably, the vector database was the real magic, and a traditional UI would have been faster and more accurate.)
In general, I think OP is more right than wrong, though, particularly about the AI mania and unrealistic expectations sweeping the C-suite.
If you can narrow the problem down, then you could design a much better interface for it than a text box and free form text (unless that's the better solution).
As for as AI assisted engineering goes, the thing is that after some time with a project, you already have much of the workflows and routines nailed down as scripts and other various combinations of tooling. And unless it's spaghetti code, you will have various snippets you can copy from for new code. The one thing I've observed about AI projects is that there's often little technical design coherence about them. It's always a kitchen sink of technologies and practices.
Yes, I agree, in that the chatbot we built probably would have worked just as well with a traditional UI, and would have been done a lot faster. But it would have been a lot less sexy (actually important for the bottom line!) and there are future directions that could take advantage of the conversational interface that’s potentially better than a traditional UI.
On the down side, good chatbots are really frikkin difficult to write. These things (LLMs) are not reliable at scale. The basic functionality came together in weeks. Getting it to behave consistently and obey guardrails took months, and even then we had to accept a low level of failed conversations.
That’s what the author have been saying. They do for nice demos which sell the illusion of having Jarvis in text format, but the usefulness is not really proven. And that may be important business wise. But as far as end users is concerned, there’s not a lot of productivity boost.
[1] Ford rehires human engineers after AI fails to match quality checks
You need to get through the Bloomberg paywall: https://www.bloomberg.com/news/articles/2026-06-25/ford-has-...
> Over the last three years, Ford says it has hired 350 veteran engineers, many of them former employees and others from suppliers, to help address seemingly intractable quality woes that have cost the automaker billions. [...]
> “We had been relying more and more on automated quality systems” and not getting the desired results, Galhotra said. “We brought back technical specialists” and “they hunt for failure points before a part ever reaches the plant floor.”
(I made these points on the HN thread about it 3 weeks ago and got voted down and I'm still salty about it https://news.ycombinator.com/item?id=48674446#48675045 )
Oh come on, Simon. Are your glasses so rose coloured they are opaque? They fired, and then re-hired because the AI couldn't do the job. They had to re-hire the quality folks. So, no, it wasn't LLMs, it was quality control -- which is a much more well established domain for automated systems. LLMs are a complete shitshow compared to industrial process automation.
Side question -- do you worry about being so pro-LLM when the promises of LLMs are so clearly falling short?
Your comment is exactly the misinterpretation I'm pushing back against here.
The time period covered by this story starts three years ago! What kind of LLMs do you think they were using back then?
> Side question -- do you worry about being so pro-LLM when the promises of LLMs are so clearly falling short
I think my record is looking pretty good here. I was early to the "LLMs are useful for writing code" thing, especially with the code interpreter pattern (both write and then execute code in a loop) which I now realize was our first hint at coding agents.
A couple of years ago I was one of the few people talking about what a natural fit LLMs were for the commandline - https://simonwillison.net/2024/Jun/17/cli-language-models/ With hindsight maybe I should have doubled-down on that!
I've also written plenty about the weaknesses of these models - in terms of security in particular - which has aged well.
As for AI-assisted engineering going well, I think the jury is still out. Here on HN and with the engineers I know, you see people claiming multiples of productivity on coding tasks. But you also see people complaining about drowning in slop PRs.
I think there’s a lot of confounding factors to these reports. The type of work matters a lot: bug fixing good, prototyping good, big legacy codebases not so much, but maybe good for increased understanding. The type of automation matters: aggressive autocomplete good, vibe coding bad, dark factory (vibe coding with fancy harnesses and auto-“correcting” eval loops) questionable.
And then finally, the perennial mistake our industry makes, which is to value speed of creation over maintenance costs. Personally, I think this is where AI-assisted engineering is going to fall down really hard, but the jury’s still out on that one.
Anyway, there’s a really big spread in experiences with AI, that I think chalk up more to all this context rather than religion and belief. OP didn’t address it at all, which I think is a big gap in their essay, but I do think think they describe the executive-level mania pretty well.
Anecdotally, AI-assisted engineering has helped me flesh out ideas or to learn extremely complicated APIs faster than trying to understand the docs (which usually are labyrinthine). MS COM ones, for example. I can go read the docs but it's easier to get a quick idea of what I need to do if I ask Claude to provide me an example of doing something specific with it, because MS's code samples (particularly their full ones in, say, the windows Desktop SDK repo) have always been annoying for me to wade through because I have to filter out a bunch of noise. I can't (and won't) try to guestimate "productivity" improvements though, but as an assistant AI has (somewhat) helped. I still do all the engineering work though. Along with it giving me tips on using more modern language features for languages like C++.
If you can find some MSDN CDs/DVDs from the early 2000s, the content is much better (and you can clearly see that the current docs are often missing descriptions and names for method arguments or even entire paragraphs).
They boast about "ancient techniques" from books written prior to the year 2000
> For non-executive management who might be struggling to deliver things that feel beyond their control, we have ancient techniques (see: books written between 1986 and 1999) to turn your team into the envy of the organisation, and we can drop in directly to get your team the resources it needs to save a struggling project.
So yeah, of course these people hate AI and everything about it.
No serious company is reaching out to these people for help with their AI project.
I don't think everyone on this forum is as objective as we'd like to think. I know I'm not. A large part of why I dislike AI is because I view it as making my life, personally, worse. It has completely fucked up the career I've been building for going on two decades
And all I hear is "adapt or die" from assholes who are chugging the AI koolaid by the bucketfull
Meanwhile the really intelligent people end up with beliefs surprisingly close directionally to the stupid people who've barely thought about an issue, just fleshed out with 100x the detail.
A little knowledge is a dangerous thing
Everyone's just portraying a strawman of the other side with new formats.
I feel though that if you picked a random sample of members of the public and asked them about the probability of the singularity you would get blank looks from most people on the left tail even if you explained it.
Whereas if you had the statement "ChatGPT can be useful for some things, but it isn't going to fundamentally change the world" you would get a lot of people on both tails agreeing and the people who disagreed would be clustered in the middle.
Maybe that's just my bias speaking though and actually I'm the midwit
Instead it spat back a bunch of physics related stuff, alleged problems with the idea ("there are 30 orders of magnitude difference between that and dark energy, and why the Higgs field and not any of the other fields, and did you know about axions which are somehow relevant, and ..."). I humored it by saying "well the Higgs field is the only one with a nonzero vacuum expectation value" and it told me I'm absolutely right, that's a key insight, etc etc etc. Then I asked it to tell me more about axions and it said some stuff about CP violation, instantons, but then it made some connections to dark energy and to the Higgs field and said I was clever to bring that up.
Now from my point of view I had to deliberately keep in mind that I was talking to a Markov chain and that I was myself acting as a Markov chain, and it's likely that none of these statements actually meant anything in physics. I can very easily see how someone who didn't realize that would be captured and then write a blog post proclaiming themselves to have made a discovery in physics.
There surely are companies out there using AI in such a way that is actually advancing them above and beyond their competition. They are probably quietly doing it rather than announcing it loudly.
The whole point of the article is about the big corps with hordes of management and people in them. My argument is that they have always been that way. Before AI it was "data science and analytics" or (as the author says) "blockchain".
Anyone can use an LLM make a bad ideas sound like a good idea. I imagine this will lead to insane amounts of productivity loss as the entire organisation ends up pivoting to follow the bad idea of a mediocre VP etc.
Doing feature development seems to take just as long or productivity gains are modest (where I work at least) and I think the reason is touched on in the article. Most orgs are just terminally bad at building software.
AI that just, does something, like extract text from scanned documents, is apparently boring. They don't seem interested in bragging about boring things.
The companies tracking AI usage don't seem to be tracking usage of that sort of thing either.
That's got to be hyperbole, which blows out their credibility. They chose to say 'AI' rather than, for example, LLM, or Transformer model, or Diffusion model. This means they are including a huge swathe of things dating back to Expert Systems in their claim.
And who hasn't seen productivity gains from more established AI technology - at least things like semantic search? Who hasn't seen diffusion models generating content in roles that might have done the work by hand before? Who hasn't seen some kind of regression algorithm (even using linear regression in a supervised context counts as AI - so you can absolutely do AI even in tools like Excel) improve operation productivity?
Even if they narrowed it to the Transformer model LLMs which re-ignited recent public interest in AI, less ambitious projects to give them to engineering staff to automate easy but boring tasks in the background generally have been a success. More ambitious ones that are beyond what you'd reasonably expect the models to be able to do - for sure, those tend to fail. For most of these, the failure is predictable in advance, while some are at the boundary of what's possible, and so it is harder to predict (these are rationally genuine R&D projects).
Go to their home page and one of their consulting selling points is recovering struggling projects.
One of their front-page selling points is that they use "ancient techniques" from books written prior to the year 2000, because presumably everything newer than that is bad?
> For non-executive management who might be struggling to deliver things that feel beyond their control, we have ancient techniques (see: books written between 1986 and 1999) to turn your team into the envy of the organisation, and we can drop in directly to get your team the resources it needs to save a struggling project.
This is entirely a selection bias issue that they've created for themselves: Advertise a consulting service for saving failing projects to companies that don't have internal expertise to handle it, then write blog posts that 100% of the projects you see are failing. Also refuse to help them, to guarantee they can't be converted to successful projects to keep the success number at 0%.
Perhaps this will get downvoted but I personally take with a grain of salt anything written/stated by a company that can't even get the most basic functions (like running a simple website) correct.
And the even bigger irony here is that the author has a ranty blog post in which he claims he saved his employer $500,000 by clicking a button. "[It] is fucking wild that an inefficiency that took me five minutes to solve in a GUI configuration panel was allowed to persist," he wrote.
https://ludic.mataroa.blog/blog/i-accidentally-saved-half-a-...
Most consultants try to impress you by talking about the great companies they've worked for.
This blog post screams, "Look how dumb my past coworkers were!" from top to bottom, then expects us to be impressed with their experience?
I've had to delete some really silly code that would slow things down or just force waits as a result of either dealing with legacy APIs or some other arcane reason. Not without testing or making sure it wasn't there for a reason mind you, but these inefficiencies can sometimes be hidden big problems.
Soy un loser
https://ludic.mataroa.blog/blog/i-accidentally-saved-half-a-...
Never a good sign when a "consulting" company has time to play petulant child.
> even within projects that we have observed in passing while doing totally unrelated work.
The kind of companies with failing projects seem to be very bad at using AI. That’s different from the normal mix of success and failures at most large companies.
No company with a good AI strategy is going to go to the Hermit Tech website where text written in Ye Olde Font explains that they'll use ancient techniques from the 80s and 90s to make your software work and thinks, "These are the right people for our AI job!"
These people are trying to carve out a niche for themselves as being anti-modern, anti-AI, and being contrarian consultants that you can bring in when you want some external consultants to agree with you in a very specific way.
Large companies where every project is going well are rare.
I agree companies with good AI strategies are unlikely to use these people, but excluding failures is just as much a bias as excluding winners. AI lets you shoot your sold in the foot even faster shouldn’t be surprising, but it’s still something to consider.
Company does x. X sucks, and is largely derided as being a bad idea, but it’s important-employee-bobs baby. No one wants to be the guy that tells bob that x is killing the company in some small or large way, because bob can get them fired or is protected by someone who can, so you hire consultants xyz who specialize in “transforming productivity through x management” and they come in and “transform” x into something less lovecraftian, or just explain why it’s bad in a way that makes bob look like a genius.
Whether or not you think it likely that this threat will materialize is beside the point. Workers never like it when someone is advertising that they will put you out of work.
[0]- Assuming it's true, which in my experience it isn't especially, but this isn't the best argument.
Anyway, I didn't say it was a political thing I said it was a cultural thing. The average liberal is not someone who thinks primarily in political terms, they are just going about their lives unreflectively and they genuinely believe in the moral weight of their feelings, which are their primary guide. Now, I'm not saying that human life is not generally composed of its daily concerns, which tend to rule us, but for the average liberal politics is no different from acting on basic urges; like a mouse chasing the next piece of cheese in a maze, they cannot see that no turn will ever lead to their escape; that so long as they continue to chase the very next thing, they are trapped in constraints that have been laid out for them in advance. Like the conservatives of the 80s, there is always one more moral panic, one more thing that you're supposed to be upset about, one more cause to fight for. There is no stopping to think why this is something that is supposed to upset me, why is this something that needs to change. They are not able to go just one step beyond common opinion and wonder why there are so few avenues for them in the first place, they are not able to question why the maximum content of their decisions is good or evil, just or unjust, left or right. Yes any decision is binary, but one must be able to choose that for themselves, be able to consider the decision to leave the maze, even if they are, in the end, no more powerful than all the other rats, and there might not be any cheese outside of it; and there might be no end to the maze, and even very far from what you thought was the exit lay the bodies of those who attempted to leave before.
But anyway this is what I mean by primarily cultural. Liberals "drink matcha," go to running clubs, obsess over "consent" (they now have a term "weaponized consent," how absurd! that they are just realizing now that consent is always given within certain relations of power...) Whatever politics they have is on the same plane, they are doing it because its something to be done. Someone who thinks primarily in terms of politics, that is, in terms of the social dynamics of power, would never call themselves a liberal.
> Its just the thing that upsets me the most about your everyday liberal professional, how much they hate AI just because Trump is pro AI
That's what I'm refuting here -- that people here dislike AI just to be contrary to Trump. This is implausible.
And trying to lecture a life long New Englander who currently lives within the MBTA zone on what the culture is like in the northeast is maybe not the best look. We aren't afraid of Waymos here; the only people I've met who weren't jealous of them were taxi or Uber drivers. That supports my hypothesis, not yours.
But I don't think that hating AI or technology or whatever to be contrary to Trump is a genuine political statement, its just reaction. It involves politics in the same way that everything we do involves politics, but it is not "consciously" political in the same way that a baby demanding care from an overworked mother is also not consciously political. Baby wants milk, your average liberal wants to feel self-righteous (they would honestly do better with the milk). Someone can claim anything they want is political, it does not mean they are doing it for genuinely political reasons, they are probably just doing it because they fear the censure of their friends and the dissolution of their social life. Not engaging with something because you are afraid of how it could harm you personally, consciously or no, is not an objective way of making a decision that effects society more broadly. Like, a baby will just die if it doesn't get milk, you won't necessarily die because some of your friends stop talking to you.
I don't think you can decouple Trump from himself in this way without a concrete explanation. If some factor causes one to dislike something just because Trump likes it, then that same factor would influence voting. We have numbers for voting. When there are lots of other plausible explanations than Trump, the onus would be on you to demonstrate why more people are taking reverse-psychological cues from Trump in a place where more people also voted for him. Gesturing at "culture" doesn't do that.
1) Exit polling (https://www.timesunion.com/capitol/article/voted-trump-new-y...) does not back you up. More college educated New Yorkers reported voting for Trump than total fraction of San Franciscans that voted for Trump.
2) Middlesex County, Massachusetts (roughly, the north half of greater Boston) is an alternative example to NYC that has a very similar proportion of college degrees compared to SFO (about 1% less). Middlesex County is in the northeast. About 42% of those voters voted for Trump, which is more than New York and more than double SFO. Suffolk County (with Boston proper) has very similar numbers to NYC for both college education and voting for Trump. This can't be explained as a cultural difference between NYC and Boston because the Suffolk ratios are so similar. It can't be explained as an educational difference between SFO and Boston because the Middlesex educational numbers are so similar but there are proportionally more Trump voters than NYC. It can't be explained as a cultural difference between Suffolk and Middlesex because first, they are direct neighbors sharing a public transit system, and second, Middlesex is considerably more traditionally leftist than Suffolk (leaning on that cultural difference would undermine your original argument).
But the point is fair. Where are the huge AI wins? Why haven't Anthropic and OpenAI produced a regular series of case studies where Company X did Fun AI Thing and incredible success ensued?
Why do these conversations always end up mentioning chat bots?
Why do c-suites seem to be full of people chasing trends instead of leading?
Does anyone remember what customers are, or are corporations aiming for Platonic abstraction, where business activities become ends in themselves, with no useful output?
Even better, why aren't AI labs guaranteeing success if a certain formula is followed and asking for perpetual royalties for successful projects?
Also like people have asked about the 70% failure rate, how do you define failure/success.
https://medium.com/@trienpont/why-do-over-70-of-software-pro...
Given the way LLMs are marketed, we should expect a vastly more favorable project success rate, not simply a close parity, and definitely not a decreased rate.
Even if we consider that the number of attempts will rise if development becomes faster, we're told to expect a greater number of projects should also succeed because they're easier. They're supposed to justify the higher costs.
It's reasonable to ask if that's the case.
I'm not sure I follow why you would think this. Prior to AI was the reason most projects failed because generating the code was too slow or too labor intensive? That would be surprising to me if it was true.
Now, with LLMs, we're supposed to be able to paper over some or all of these problems.
They're supposed to be able to understand and intuitively fill the assumptions present in vague requirements, then produce working applications. They're supposed to shrink the timelines from years and months to weeks and days. They're supposed to replace human expertise with a reliable service.
Why else would I hire an LLM service over a team of humans?
But none of those sound like things that would change how likely any given project is to succeed. Shrinking timelines from years and months to weeks and days just means that you can fail faster and try again sooner (hopefully with lest costs), but nothing about that implies your rate of success is going to get better.
Most large software projects I've worked on in a professional environment, "writing the code" was one of the fastest and smallest parts of the project. Maybe 10% of the overall calendar time of any given project was "designing and typing in software." The bulk of time spent tends to be working with customers, researching and refining requirements, reviewing the requirements with execs and leads to get their buy-in and support for staffing the project, performing various non-engineering reviews like legal and privacy, aligning timeframes among multiple contributing teams, seeking approval from Director X to move on to the next project phase, waiting for Key Team Member Y to get back from vacation, conducting QA and field testing, soaking the software through various rollout stages like internal, dogfood, internal staging, external beta, and then incremental percentages in prod, while watching and waiting for any regressions or failures. On a project that takes 6 months from idea to 100% in-production, writing the code might take a few weeks of that.
So why are we so focused on a tool that speeds up the smallest part of this process?
I get what you are saying here.
At the same time, was reading Deming's last book [0] and there is a great line that I have never seen in any recent business books:
"The organizational chart is usually a pyramid. The main benefit of this style of chart is to clarify who reports to whom. Notably absent from this chart: the customer."
I've also worked at firms filled with very smart people who had no concept (or were not incentivized) to think about the Theory of Constraints, Total Quality Management or that the firm is supposed to work as a team and not a collection of fiefdoms.
What I'm saying is: just because a book was written before 2000 doesn't make it irrelevant.
The former is easy to get right. Any software engineer (at least provided they aren't actively resisting the technology )can get useful results out of Claude Code these days.
The latter is really hard. LLMs are a strange beast to build software on, and most of the obvious projects - like the internal chatbots described in this article - are easy to have over-promise and under-deliver.
In general I find their submissions tend towards extreme grandiosity. I find I really appreciate people who have some nuance about the world, can see some duality, and the many many many submissions here are (I admit) often quite fun and enjoyable, but spoken much more from a bully pulpit perspective, with a zeal and self certainty that I find rarely coincides with truth-seeking.
You have to be very careful about claiming productivity gains. There may have been some instances of gains in a specific part of a workflow but does it slow down others or result in overall gains is yet to be empirically measured and validated. We’re seeing metrics like more lines of code, better unit tests, documentation, faster PRs etc. but the actual gains of businesses are still a question mark. Do more PRs lead to faster features being shipped or does it lead to slower reviews or bug ridden code that breaks user experience? I’ve see a lot of companies tout their metrics around more code being shipped but the same companies aren’t talking about how that translates to an actual dollar amount.
If it's not obviously showing for the all-in, AI-selling companies, I simply don't expect serious improvement for everyone else.
They're undeniably neat tools, but so far there's no observable evidence that they're transformative.
I'm doing fundraising for my tf-idf startup. It's named after a very big number!
Do you work with lots of companies and see large AI success stories?
Or do you just vibe that you personally find AI useful so it must also be a business success?
Look, I honestly don’t care, but I think “it must be false” is also unsubstantiated hyperbole. If an agency says they see no AI success, I see no particular reason to believe they’re lying.
They’re not saying AI can’t be a success. They’re saying they haven’t seen it. That matches my experience too. Proven AI success stories seem… vague, when you dig into the details, in my personal experience.
It doesn’t seem surprising to me.
He's not a big fan of polite, corporate speech, I suspect.
But I like his style and he often has some insightful points that go against some popular industry practices.
"This is unreasonable.
"Do I seem like a reasonable person?"
The corporate mindset keeps going through different mania at different times. It could be initiated by some consulting gurus (processes), or some security nerds (strap yourself down until you can't move), or peer pressure (fear of missing out), or presentation goals (show that you are a AI-powered and modern company).
We can't remove or stop manias. Infact that is not the goal. The music should go on and the dance should go on. Everyone is in this dance - customers, businesses, supply chains, governments, thinkers and philosophers. It's a world-wide dance. So it's OK. The music track won't last forever. It will change and dance will change.
> We have rejected all AI implementation work. It is absolutely a gigantic bubble and we have minimized our exposure to it – every single one of our current contracts would be totally unaffected by OpenAI collapsing, save for perhaps some second-order effects such a recession causing a client to become unable to pay us. And there’s nothing we can do to insulate ourselves from that anyway.
Following the link to their company page goes to Hermit Tech, where the primary advertisements for their services are about helping failing projects and troubled teams.
So this is just one huge selection bias example? Start a consulting company for recovering struggling projects, then make claims like "100% of the projects we've seen are struggling"?
There's so much more in this blog post that feels like they're working hard to ignore anything that disagrees with their bubble. Building an AI data pipeline with evals such that you can swap between AI APIs is standard. It's actually part of doing a decent job because you need to select which model hits the right cost/performance tradeoffs and be in a position to pivot when that math changes. Harboring ideas that OpenAI is going to collapse and bring your projects down with it is the kind of talk you hear out of people who don't understand how AI projects work or that there's an ecosystem to it beyond a single company.
The latest projects I'm working on even include open weight models that can be run on reasonable local hardware as cost and performance benchmarks. Even if all of the AI providers collapsed at the same time and nobody offered any services (not going to happen) these projects can still continue on.
It's a very weird time in technology. You can have one foot in a world where people are adopting technologies and using them intelligently, then you can run into articles like this from people who have built their own little self-selecting bubble that confirms all of their ideas who can't even imagine that successful projects exist right now.
> Was it just sales fluff? The answer was a lot more interesting.... Executives at their customers were saying absurd things about achieving 100x productivity, and this meant that if any executive at the vendor said that these gains were not plausible, it would undermine the credibility of the customer’s executive, be perceived as an attack (or heresy), and possibly result in an enterprise contract cancellation.
A lot of excellent anecdotes here.
> Employees don’t use internal chatbots because companies tend to have low-quality documentation and an LLM is not psychic – it can only know things that have been written down and made accessible.
Then later:
> In one extreme case, I have seen an executive confess that they had never even used ChatGPT or any AI tool in their life, immediately after producing a technical strategy for an organisation with $2B+ in revenue which was entirely centered around AI.
And:
> In fact, we have been forced to opt out of every sale where the lead has expressed anything beyond the most fleeting curiosity in the use of AI in their business. I don’t mean that we’ve heard that they’re interested in AI and elected to drop the contract on moral grounds. I mean that, over the course of the engagement, these people have exhibited a pattern of behavior that has made it near-impossible to sell to them without incurring reputational and legal risk, and are furthermore crafting management environments that I can only describe as cultish, ineffective, and “please dear God, do not let it be on earth as it is on LinkedIn”.
And:
> with one client, we uncovered that staff were totally unaware they had been given licenses for AI tooling, which cast into doubt all productivity claims.
I don't see any hints of LLM writing in this article though.
Nothing will improve until things get bad enough. You need enough greedy yes men doing quailty control on airplanes to escalate.
It took me decades to understand the use of and need for escalation in big organisations.
I didnt understand seemingly unproductive strict job descriptions either. Hilarious situations with 10 people doing nothing at all their entire shift (really nothing) while i had work todo on my own that really required 5 people. A few days later someone showed up to tell me the qualty was below average. LOL
Now i know i should do only half a shift worth of work. When they come complaint about it i say: very good, write it down, make the official report.
Then i hear nothing and a year later its two people with work for 5 scheduled. I tell them to slow down but we still do 2.5 shifts because they dont understand how escalation works.
The nummers now show we are 5 times as productive which isnt good for the company. The beurocracy is slow to adapt and all it has is numbers.
For many years i tried to do all of the work but that means nothing is wrong. The numbers say all is fine most of the time. Someone grinning at how much work i did isnt going to get recorded or processed.
If it looks like an unattended LLM can do a better job it means you dont know what you are talking about. If you fire everyone who noticed you might buy time but reality will catch up.
It reminds me of when they first put computers in trains in NL, they ran on windows 3.11 and no one trusted it to do anything. The solution was to give it all the data so that it could display a nice overview but it didnt control anything. Lots of trains drove around with a blue screen of death or a boot error. If there was a problem it was slightly harder to diagnose but it wouldnt drive if [say] a door was open. If the gui said a door was open you could just ignore it. On its own it means someone has to replace a sensor. If it also didnt move anymore the message is a real issue.
I imagine LLMs are wonderful for that kind of thing.
What I see are that there are a lot of extremely fake humans, who want and need cover. Who have absurd ridiculous (and often dastardly or sinister) plans. Who want to do things, a-priori. But could never get away with their actions, in any just clear reasoned normal rules of society.
And AI is this new circuit breaker. It's innovative permission to move ridiculously fast and break everything, right now. Take the perhaps old IBM slide and flip it upside down,
> A computer can never be held accountable.
> Therefore a computer must never make a management decision
https://simonwillison.net/2025/Feb/3/a-computer-can-never-be...
The people "using" AI today to "make decisions" are using it because AI cannot be held accountable therefore that is the cover for their decisions.
This is is all such a resounding PKD nightmare, a reality bring invaded by Fake Humans. It was that was already, just gobs of nonsense, the worst liars spreading the most ridiculous memetic caltrap everywhere: Bullshit Asymmetry Principle weaponized against reason to ever higher degrees, Fox News terrormongering advanced and advanced, Hastert Rule obstructionist politics by wicked pedophile protectors and system ruiners and monsters. AI is a rapid accelerant for burning down reality, for propagating the disreality that the fake humans require for existence. Un-people truly from some other dimension, who've worked and worked to get away with their twisted anti- reality over us all.
AI can and does help with a lot of decision making, in good ways. It's an incredibly tool. It can comb through incredible amounts of data. But it's primary use in "decision making" seems to be in deflecting responsibility, in making hideous choices no human system could reasonably make. In concocting fabulations. Both of management design, and endless fuel nightmare disreality slop video to dislodge any last bits of real reality still clinging on (hello ai faked campaign videos!).
The "frothing excitement" here is the frothing excitement to destroy society, to be and bring out the most wicked brutal careless world that can be brought upon us, to raise up the Theil-istic/(Octavia) Butler-ian nightmare neofuedalim. It is to escape accountability, to give cover for sin savagery and sabotage.
(Regarding the article, I do think it's worth tempering ones read of this article by reading the authors previous work on AI. Which to me exposes their baises and in my view makes them so vastly unreliable & overdramatic a narrator as to be near worthless. Their other submissions are less greviously clearly full of it, but also tend towards ridiculous over-grandiosity. https://news.ycombinator.com/item?id=48002795 )
He generalizes CEO's behavior but provides no evidence. Cool.
He's ramped his own AI spite up to a manic level.
Perhaps it is the wording. For my org, I think people are getting value out of AI use supplementally, but what I would see as "AI projects" are definitely dead in the water.
AI will only help if you use rapid iteration to cheaply/quickly produce ideas. All the normal project failure modes still exist.. Blaming AI because AI is dumb.
I only read up to point 3 because the hyperbole and frothing fervour was overwhelming.
They proudly claim that every AI project they've observed over the past year and a half had a 0% success rate, and that they've rejected all AI implementation work. While this is evidence that the market is crazy, at its core, it's a painful confession that they have no engineering expertise to implement and control modern AI architectures like RAG, Agentic Workflow, and context window optimization to meet business requirements. I find it fascinating how they're packaging that. It's basically saying, 'We're behind the times.'
There are already products that have achieved results by using AI as part of their development process, yet lumping all different types of AI usage into a single failure category is not only inaccurate but also misleading.
Same goes for the Snowflake Cortex anecdote. Even a freelancer like me can explain technical limitations and distinguish between what's possible and what's not, especially when clients are eager.
There's no engineering analysis in this entire post about why AI fails. No mention of technical bottlenecks like vector DB retrieval quality degradation or prompt injection failures.
I've also worked on RAG for a specific company. For internal knowledge chatbots, it often fails depending on document collection rates and chunking. But none of that is mentioned.
So I understand that AI projects and related things are bad. But there's no analysis of why.
For example, regarding Snowflake, I'm not sure, but did they discuss accuracy in terms of what query set or what ground truth they were using? You're consultants, aren't you?
Honestly, I don't understand why people are excited about this. I'd rather they just used AI. TIt's not about whether human writing is good or bad. It's that this kind of writing feels like a deception of the reader.
When making overgeneralizations, there's a basic minimum standard required.
Saying that making token usage a KPI makes it hard for employees to report is just an 'obvious' fact that's already appeared in far too many essays. Wake up. You're 'consultants.' Consultants are supposed to provide metrics and directions, but all you're doing is shouting into an echo chamber and asking for agreement.
If a significant portion of corporate AI investments are shoddy, you could at least propose specific metrics like document collection rates or user evaluation scores using the very skills you claim to have. I really don't get it.
Just use AI. I wish the OP had used AI. Let me be realistic.
How would AI writing help in any way?
Same goes for their 0% claim. It's overgeneralization, isn't it?
So why did they fail, what went wrong, and how should these AI projects be analyzed—and by what metrics? They skip all that and just throw out a single KPI. What insight does that offer?
Honestly, there are a lot of people on HN who just shout that AI is useless because their own jobs are at risk. That's an undeniable fact. In my country, Korea, we say 'like a pheasant hiding its head in the ground.' It means denying reality and lacking self-awareness.
I've also seen many failed AI projects due to a lack of proper evaluation of AI capabilities. I don't want to deny that premise.
But if you're going to make that argument, you need to describe why they failed. There's none of that here, just this:
'We're going to opt out because it looks like AI projects will fail.'
They package it as being cautious, but when you peel back the wrapper, it really means:
'We can't keep up with the AI trend. And we can't tell what works and what doesn't.'
Sure, AI has a bubble. No one can deny that. But separate from that, it is useful. Do you really think millions of consumers would stick around for something useless?
Social problems are arising, and people are losing jobs because of it. Let's think the other way around. It doesn't make sense for people to lose jobs over something that's truly useless and wrong.
People are losing jobs because it's useful and valuable. So wouldn't it be more accurate to say that the problem is 'over-application' rather than the thing itself being bad? In other words, we could say that it's being valued more than it's worth. But this argument just says it's bad, period, with no nuance. I can't trust someone who talks like that.
AI writing, if you give it a red-team prompt, can at least refine the surface of counterarguments to your claim. But this—from overgeneralization to extremes—is a textbook example of bad human writing
I don't think you're upset because AI is useful and valuable. Are you upset because you can't describe how the bubble will burst?
Some (more) quantitative types saying that the economics are deflationary. So NVIDIA have already won.
But there are some that claim that the bubble has nothing to do with NVIDIA's monopoly on compute (21.C steam engine/steel). That the bubble is in the OX layer. (You?). If Anthropic (or Palantir replacement) fail to do what? Then the bubble will burst.
This is the more interesting but I will have to sleep on it.
Rather than saying NVIDIA will be the ultimate winner, I think Apple could be the final winner as a hedge against semiconductor stocks, at least for now.
In that sense, I'm not sure. You can't time a bubble, so it's just a bubble.
But I do think NVIDIA will remain powerful because of its CUDA ecosystem—though the future is uncertain.
I wouldn't say I get frustrated by illogical writing--esoecially ones that only _seem_ illogical---, but more that people like us who might know better don't point out precisely where that illogic is after thinking carefully about it. ]
It's possible to time a burst _if_ you see the pin, but anything you do _when_ you see it is technical illegal?
So your OX idea feels like just the sort of thing that could open our eyes new kinds of pins.
Further, I'm not totally closed to the idea that actively trying to pop the Anthropic bubble is moral, indie of how quixotic that sounds. Even if it might be a good case study for deinstitionalizing research math.. even if that Napoleon quote that's trending..
I would also never bet against Jensen taking some ideas from "the Apple playbook". Especially when multiple people have already pointed it out. Though this is tangential. Less tangential---
Refinement of OX framework would help us think about how NVIDIA can or cannot play the Apple game. Certainly, if given calibrated riskiness and timing, Apple would move against Anthropic. You know what I mean?
Of course, they can write it on a personal blog. That's not inherently bad.
But when they're rejecting client requests while offering no opinion on how to model the metrics that would define success—that's the problem. This type of writing is just an illusionary piece that claims to offer insight. It's a bad form of human writing. I like to call this style the 'Rhonda Byrne Secret type.'
At the very least, a consultant should provide modeling of their hypothesis and actionable advice.
Explaining everything with a single reason—that people are afraid of being laid off if they don't adopt AI—is just a cop-out. There's no hypothesis, no reasoning behind why that claim holds. It's trying to explain everything with just that one assertion. I'm not even sure if that holds up organizationally
The OP offers no logical reasoning about how decisions are made or why they break down.
A proper piece of writing would have looked like this:
Why did the client want to adopt LLMs?
What problems arose during the client's process of adopting LLMs?
How does this connect to the organization's internal issues and disrupt its pipeline?
You need at least that level of description. This is just an emotional post that seems to say 'I wish LLMs would fail.
If they had really explained organizational dynamics, they would have talked about the asymmetry of expected costs.
Professional managers and mid-level managers prioritize career defense above all else, so they're extremely risk-averse. They would have explained the costs of adopting AI versus the costs of failing to adopt AI.
If they reject AI adoption, shareholders or the board would say they're 'failing to read the trend.' If they adopt AI and fail, they can package it as 'early market entry costs'—a defensible risk.
Providing that kind of defensive logic to decision-makers is exactly what consultants do.
It's described as being held at gunpoint, but it's really just a prisoner's dilemma. In a market where competitors and vendors are all lying and saying 'we've achieved 100x productivity with AI,' the moment someone tells the truth and says 'we don't need AI for our business,' they become a political target both inside and outside the organization. In the end, everyone knows it's useless, but they approve budgets for 'fake AI projects' anyway. I can offer that kind of cheap insight too—it's a Nash equilibrium where the system has been driven to a race to the bottom.
And I'm not even a consultant
> If you’re being asked to review huge volumes of terrible AI code, just assume that the organisation is going to burn you out and fire you. You will not convince the person drowning you in 2000 line PRs to stop. Start looking for a new job as if you have already been fired. I have seen this happen many times now
I suspect we will see this phenomenon more and more as organizations more widely adopt agentic development.
Go back and re-read the quote from your comment - which I responded to: “ You will not convince the person drowning you in 2000 line PRs to stop. Start looking for a new job as if you have already been fired.”
I’m not overreacting to some nuanced take here. I’m not sure how to characterise quitting as a response to over-enthusiasm / slop as anything other than the career equivalent of sticking your fingers in your ears. I’ve been there, I’ve had the arguments, I have little sympathy for staff/principal engineers or above who react like this - their job is to fix the organisation, put a yoke around the beast of AI and find a way to tap the benefits and use the problems (like those 2000 line PRs) as a golden signal for where you need to educate and improve process and planning.
Again - I’m not selling anything here, I just have found it an interesting challenge over the last year and one where I’ve been happy to make progress organisationally despite the frustrating moments. If someone’s response to a problem like this is to throw their hands up in despair or to engage in whatever the logical opposite of AI-hype is (which the article resorts to repeatedly) then yes I’d worry about being laid off. If you’re in an organisation where you don’t have the agency to fix problems then absolutely - start looking for a new job.
[0] https://pluralistic.net/2025/12/05/pop-that-bubble/#u-washin...
[1] https://pluralistic.net/2026/01/05/fisher-price-steering-whe...
This exact situation occurred to me. I blocked all PRs with “request changes”. Most engineers don’t like AI slop, most take pride in their work.
The occasional AI slop engineer can be contained by rejecting their PRs, having team discussions around norms, bringing up feedback on retros, etc.
If you know what you are looking for and know what “a solution looks like”, AI is amazing at distilling ideas. If you have no clue, the AI will return “clueless” solutions.
It is just like before the AI: there are people who know how to search the web, read and understand documentation and so on. And then there are peole who are incapable.
AI is naking the latter category fail incredibly fast. Really, nothing new under the sun: garbage in, garbage out.
Take climate change- you have torrential rainfalls, sweping away whole city-parts in mountanous regions, in some enormous russian roulett. And it doesnt even factor into building evaluations because then it would basically reduce the prevalent pension scheme to cinders.
You have dry months in europe now, where some thrown cigarett butt could ignite a firestorm- and the obvious solution is to remove the dangerous greenery from the burbs. Nobody does it though.
And that is just the plain sight visible layer of this shit cake. If i was some missguided fool into heroics and leadership and signed up for a little more then i could take and fake- i would long for some magic box that lowers the burden too. Those up there are human after all.
Russian roulette was a good pun. I don't know if it was intended.
It makes perfect sense for the shovel sellers (nvidia, anthropic)
It's like some 90s kid with a Nintendo power glove who's convinced themselves that this makes them a hacker. This is not the singularity.
I personally can't wait for this to end, and for everyone to collectively get back to waiting for whatever the next golden ticket that's supposed to solve all of our problems turns out to be.
It seems quite premature to say that. We're 3 to 4 years into the LLM revolution and the rate of progress is still impressive. The recursive self-improvement aspect that is necessary for the actual singularity is something we're only really starting to get into this year.
If the singularity is 5 years from now, that is still much sooner than most people (including me) previously expected it to happen.
When we were 3 to 4 years into mobile phone revolution it was already abundantly clear that it's changing the way people leave.
Ditto when mobile phones became smartphones, and for many other tech items we got in the past decades.
As for LLMs... outside of a few precious professions you could live your life and not notice they are there.
We're just shy of 10 years since attention is all you need and just a few years past the first commercially viable LLMs. So in cellphones we are something like early 90s.
Mobile phones were severely constrained by hardware that made them impractically expensive and unwieldy, and also by the time it took to set up wireless networks at a large enough scale. That's why it took mobile phones a few decades to really get going, and this is going to be different for every other technology.
LLMs, for instance, were not as hardware-constrained - we have a lot more compute now, but there wasn't a hardware paradigm shift or anything, things were already pretty good a few years ago - now it's just about scale. LLMs were also always relatively affordable - there wasn't a period where they cost $10/token, so we don't get the same kind of affordability scaling as with phones. They also utilize existing internet infrastructure and don't need to be rolled out in some new worldwide grid.
Regardless, the point of the GP that we saw revolutionary changes in society within a few years of technology introduction is off. It took decades for the full impact of the pc, internet, or mobile to be seen. We're still in a very early phase of figuring out how to use LLMs.
And old folks said the same thing about the internet and smart phones. Fads that would pass. While the younger generations lived an entirely different lifestyle.
I’m personally seeing the same. I resisted AI being a “thing” for a long while, but since I’m around a lot of teens and young adults it was a choice of burying my head in the sand or deciding to take a look.
They are going to change society on a scale far beyond smart phones. In ways many will not see as positives, but change never goes the way one may expect.
Ironic how LLM promoters like to hallucinate citations, much like the tools they espouse.
I recall seeing similar sentiment in other publications throughout the late 90s.
https://www.reddit.com/r/retrocomputing/comments/1m6i4ui/art...
(Apologies that this was the best image host I could find for it)
I was there in the 1990s too and we were deluged with headlines trumpeting how everyone, young and old, was rushing headlong onto the Information Superhighway as the dotcom bubble kept inflating.
The “Attention Is All You Need” paper came out in 2017 and OpenAI released GPT-1 in 2018. ChatGPT was released in late 2022 but that was not the beginning of LLMs. Transformers and generative AI go back even further.
It hasn't been even close to even the recent claims! It's been like three straight years where it was supposed to utterly transform society any minute now.
I think we more or less have a fragile consensus that in like, computer programming and really very little else, that on a good day you're probably going to come out ahead with the AI assist. That seems relatively uncontroversial now. But it also seems like success with AI is largely about working hard to get good at it, as a first order concern. It is not at all obvious that blind, uncritical use by anyone is a net win.
It's pretty unclear, sone might say dubious, that anyone has made serious, aboveboard money net of debt and equity, other than the hardware vendors. There's some pretty serious revenue, but it's a drop in the proverbial bucket against the outlay. There like a two trillion dollar balance sheet hole in the US alone where investment into AI has gone.
While I personally don't agree with them, multiple S-tier machine learning researchers think we've got our wheels stuck in the mud, that autoregressive decoder architectures on a tokin-suffix pre-train is tapped out as a paradigm.
It's ok to say "AI is starting to get useful in pretty durable ways" and not sound like an Anthropic shareholder/employee, i.e. completely full of shit.
That can be true while it also being the case that to someone who has no idea how this stuff works under the hood, it's basically Dunning Kreuger in a box. The next person to go /u/PhdInEverything on me with Fable is getting an education in the history of hardware support for mixed precision training or something. Fable is a masterclass in refusal to ground and a dozen other alignment catastrophes.
So yeah, the models are still getting a little better, but from here out I think it's rapidly becoming a skill game.
The singularity requires exponential improvement. That's not happening. Maybe we will develop something that sets that off, but there's no indication of that right now.
The logic has always been that the AI would have to have significant tools and agency to do self-improvement for the singularity to occur. This is exactly the thing that a bunch of the AI labs are working on hard right now.
Seriously? Maybe I’m just getting old, but having lived through the dot-com hype in the 1990s, the XML hype in the 2000s, and the cloud hype in the 2010s, this has been an utterly predictable hype cycle around AI. This does not mean that AI is completely useless. It will impact the world but not in the ways the snake oil salesmen are claiming. This is very similar to the internet. The best bubbles are built on a kernel of truth that is then blown way out of proportion and wrapped in layers of snake oil fabrication.
> I personally can't wait for this to end, and for everyone to collectively get back to waiting for whatever the next golden ticket that's supposed to solve all of our problems turns out to be.
So, you’re committed to falling for the next one, too, eh?
The history of the UK's railway mania in the 1840s is worth researching, because it's uncannily similar, with a stock bubble, fraudsters and chancers, huge hype, cutthroat competition, boardroom intrigue and drama, miles and miles of unnecessary infrastructure in the wrong places, and eventually a technology that became useful, but could have been developed more intelligently.
https://www.cambridge.org/core/books/boom-and-bust/D09C2E3BE...
Tilting at windmills over the stupidity of it is just something I’m trying to get over and not care about at a personal level. Nothing I can do about it either way!
Having not lived through this, I'm actually curious as to how similar it was to the current hype cycle. Was there a general sense that something singularity-like was approaching?
I don't and wouldn't claim that AI is completely useless, I personally use it for at least a couple hours out of each working day and feel that it boosts my productivity significantly. My point is that the kind of benefits we're seeing from AI are not the ones we expected, and the difference between expectation and reality doesn't seem to have sunk in for most. I regularly hear friends talk of the post-scarcity future which is just around the corner, something like the culture Minds from Ian M. Banks, and this pseudoreligious narrative seems to be what the big AI players are deliberately selling. What I'm actually seeing is something more akin to Mr Meeseeks from Rick and Morty.
> So, you’re committed to falling for the next one, too, eh?
Haha, no. The point was that I've seen better things in the long winters between hype cycles than in any hype cycle.
To a degree. There was breathless expectation that this was a turning point for commerce, government and society and that everyone had to stake their claim now. Everything was going to change.
What was it going to change into? Beyond "$OLDTHING but on the Internet!!!", nobody really knew. Those first steps were just webbifying existing processes, stumbling along, refining what was reasonably successful and dumping that which wasn't.
It was like a black hole; from afar we could vaguely see an event horizon, but the people falling into it had no idea what was happening or where they were in the process.
And then the crash happened and we learned that all the old rules still did apply, and while the Internet was hugely transformative, the simplistic idea that brick and mortar was bad and e-commerce was the only way forward was fundamentally wrong. Yea, surely some segments did change (Amazon killing Borders and Waldenbooks, Netflix crushing Blockbuster, etc.), but investors ultimately look at profit even if they’re willing to ignore it for a while to grab market share.
So, I suspect that AI is going to play out similarly. Right now everyone is frothy, screaming that anyone not token maxing will die. Yes, AI is going to be impactful, and, yes, it’s not going away. But the hype is surely overblown. When was the singularity supposed to arrive? Three years ago, Altman was saying it was going to be 2025, right?
A singularity? No.
One of the early driving obsessions was a coalition dethroning Microsoft (which both did and didn't happen). A battle over closed-vs-open. That story was everywhere.
The main thing I notice is that there's a bit of a difference in the way value is created. Even in the UK the arrival of the web created a lot of early adopter winners — ISPs, design agencies, small dev shops like the one I worked for. And it generated a fair chunk of early money, changed the direction of state monopoly telecom etc.
Early well-bounded successes in 96-98 earned proper money, generated a bunch of press, generated new work. Because they had to: you didn't get access to huge pots of cash to grow with, until you had a product that was on the market and selling. The VCs didn't know you existed.
At the beginning it was small tech industry hustle and actual product creation, and a lot of companies really had the small software company playbook and ran that. You had a lot of PC resellers and systems builders who suddenly found themselves as qualified as anyone to build websites or run ISPs.
The problem after that was everyone's eyes got bigger than their bellies, the projects got too ambitious too soon, the VC money arrived even in the UK, and there were a lot of failures. I perceive the moment the firm I worked for got VC money to be the beginning of the end. I thought my bosses were altogether crazy to take the deal.
We basically were not ready to scale fast — the dot com era really scaled brand new companies in terms of number of employees and scope at a level that was at that time sort of unprecedented except maybe in the semiconductor industry.
Towards the pets.com IPO crash end of things, that is when it started to get unreal in a way that you'd recognise now — people talking about entirely new business models, and you had a running joke that if you just put "… on the internet" at the end of your elevator pitch people showered you with cash. The most insane of these being CueCat: a barcode scanner, but on the internet.
But did we think it would fuck everything up everywhere all at once? No. It was going to make us money and make it easier for everyone to buy and sell things, but it was going to create jobs (and it did for a while). It took until well into the early 2000s for the impact on retail to be truly felt.
Nowadays, companies scale enormously before they make any money, VC cash gets handed over to PhD students who only have the concepts of a plan, freemium tiers do the marketing and everyone is trying to follow the loss-leading market-share growth strategy that Amazon arguably pioneered.
The AI boom is perhaps the peak of that Amazon growth culture, "winner-takes-all" thinking, which was always insane.
The closest the internet got to becoming the focus of hopes for a great transformation of society (or the focus of an ideology or comprehensive narrative) that I saw was a conversation started by John Perry Barlow's "A Declaration of the Independence of Cyberspace" (published Feb 1996) and the crypto enthusiasts. Both conversations consisted mostly of libertarians (with the crypto conversation also having anarchists), which as everyone knows only ever made up 4 or 5% of the US population (but a much larger fraction of internet users in the 1990s).
Also, Teilhard de Chardin's books (written in the 1950s and 1960s) inspired people with a grand vision of the human future and in particular predicted the creation of a "noösphere" which was much like the global internet, so Teilhardists wrote some about that. But the Teilhardists were never more a tiny tiny group, much smaller even than the aforementioned crypto enthusiasts. Almost not worth mentioning.
>Was there a general sense that something singularity-like was approaching?
No. Although millions of words were written during the 1990s about the singularity (referring to it using that word specifically IIRC), even then it was always AI that was expected to bring about a utopia, never the internet. And the discussion was restricted to a few mailing lists (the extropians list, Yudkowsky's SL4 list and ISTR a transhumanism list), one or two books (e.g., Great Mambo Chicken and the Transhuman Condition), Omni magazine and maybe Wired magazine.
>From memory, the last time I was given a presentation on it, by actual Snowflake staff, they reported that ideal configuration results in something like ~92% accuracy due to the complexity of data at a large business ...
it's exactly this problem. nobody has solved it. lots of companies are trying to sell that they have solved it.
when I don't care about the end result that might be fine (I have used wordpress too), but frequently it ends up that they helped find relevant docs (they're quite good at finding that from vague descriptions, and it's very easy to verify) and I would have been quicker if I had simply read those docs in full. and then I'd have a more complete understanding of the space too. my biggest worry for personal use is that LLMs will write those docs in the future, and be riddled with mistakes :\
1: ...and then they're quite good code dictation tools. people who think "writing code isn't the bottleneck" just haven't spent enough time in well-understood spaces or rebuilt enough wheels. it absolutely can be a several-multiples bottleneck in day-to-day work, or when re-doing something you've done before and fully understand.
We still need a bubble pop to drive out all nonsense ideas and paths.
LLMs are of course a form of progress, the same way blockchain was, but it has been baffling and cringy nonetheless to see people with a strong technical background pretending that at some point in the future the development of complex applications was going to be reduced to a few prompt lines written in English.
Once the AI fad dies and the next hype appears I told myself I'm going to jump on it to take financial advantage of it. At this point I believe that the technological cycle of hype is an almost entirely social/economic phenomenon and there is no reason not to make money from it given that people insist on this kind of irrational behavior.
I don't want to sound like a jerk, so please let me know if I do - I don't understand why you claim that "most of us" felt that way. I ignored "AI" until mid 2024. Then I tried it and was very unimpressed. I tried again in 2026. Seemed useful, then very quickly I realized that it's something that looks great until you look closer.
I was never impressed by a text generator. A talking computer might be the most boring thing I could imagine. I never understood why people got so obsessed by it and I certainly don't understand why it would "change society". Society is composed of people. What would change society is something that would allow people to think less, feel more clearly, express themselves more freely, and suffer less. Of course, things that accomplish these results exist, but they require a lot of effort. I cannot fathom how a technology that doesn't lead to these results could revolutionize anything. In fact, every technology, that I witnessed arising since late 90s has made things worse precisely because it has not done anything to address the human condition, instead praying on it.
Especially as somebody that's no longer in the software profession and so doesn't have 40 hours a week to just sit there and crank out code, agentic AI is a technological leap on the level of search engines, bulletin boards or compilers.
You can literally just open Claude Code, say:
- "Add these domains with these mailboxes to an SMTP server running on my homelab, forward all incoming and outgoing via mxroute"
- "Port this unmaintained app from 2017 to modern Android, and then test it on an emulator and sign it with my real key for distribution via Google Play"
- "get my GitHub Actions runner on Linux, Windows, macOS and Android, ensuring that it supports all available architectures from the last decade and a half, then check your outputs in a loop until it works"
and it just spits it out while you do the dishes.
Someone the other day talked about "AI psychosis psychosis" and it absolutely stuck with me. The people who deny this is a big deal are in la-la land.
We could literally hit a brick wall in terms of model intelligence now and it would still be a game changer.
2. The gap between the singularity and really strong automation is huge. It's basically that between 1 million and infinity, or even better, that joke about the difference between 1 million and 1 billion being roughly 1 billion.
If this is the singularity, consider me extremely underwhelmed. My job my have changed, but to the rest of the world, it's just more of the same.
And that’s assuming you really need to do these type of tasks using an LLM. As GP said, and as you’ve proven, most people are trying to use LLM as an hammer for everything that looks like a nail, without verifying first if it’s a screw or something else.
That's not the problem, the problem is that for every hour of dev saved society will lose 10 hours on fake data, fake bug reports, automated scams, needlessly convoluted email, etc.
Just like block chain still exists, it just didn’t revolutionize decentralization. It created a new tool that can be implemented when you want the benefits of what the blockchain can do, same thing will happen with language models.
And it's just... not. People want to be challenged, they want to read human material, they want to listen to human music. Sure those like crappy Spotify fake artists might make some coin for Spotify. But are people going out to those non-existent tours, or are they instead listening to Confessions II and praying nightly that Madonna tours again?
And, Madonna, if you're reading this: please go on tour. Please.
Personally, I’d be knitting and crocheting things for other people with most of my day if I didn’t have to worry about money, or I’d help my neighbor with the website she wants for her business venture, or I’d teach kids how to code. These are things I’d like to do, that I can’t readily do while having the overhead of a full time job unless I run myself ragged and tbh, I’d rather not.
I miss the code mines
I’m also perusing for shops that aren’t necessarily “anti-ai”, but where lack of using it isn’t seen as a negative
May I recommend Aldous Huxley's "Brave New World" to you?
> most people don't want to turn off their brains
Biologically, life is an effort-minimizing machine. Our brains have a whole system of habit-forming to minimize the enormous amount of energy it takes to think.
Whatever people say, give them a way to think less, and they will necessarily prefer it unless they literally are a Buddhist monk, seeking to be aware over every action and thought.
Optimizing the menial is the end-goal, optimizing fun and humanity and expression is not desirable. It's just not, and we're seeing that over and over again.
We have gotten very good at hacking this reward function. It has reached a point where a thinking-minimization engine will pay a significant amount of resources to, say, Paradox Studios to do what is effectively the opposite of not thinking.
So yeah I love AI and it really helps my personal projects. But my actual work? A little, I can work on some nice-to-have PR in the background during my meetings. I might be 20% more effective coding? Mostly because I do more of these low-hanging fruit PR like bug fixes and refactoring. The hard stuff still require thinking. But that's not even half of my time. It's fun, but not world-changing.
I laughed reading this. Have you actually tried it? I recently tried to get Claude (Opus) to give me a setup for a simple SMTP relay with Postfix. I had to constantly fight it not to include completely unnecessary components and configurations like Dovecot or just override my requirements. Even Claude is nothing but a semi-competent tutorial clicker.
To someone who never did anything like this themselves the result might seem fantastic. They might not battle Claude on details like I did because "hey, it works, doesn't it".
Don't get me wrong, I agree in general that LLMs are a significant milestone. But I would like to add, especially because of your tone, that perception of how much of a leap it is, is very likely a matter of individual competence. So your enthusiasm might say more about yourself than about the tool.
I've been "doing this" for over 30 years now and I consider these LLM results to be fantastic.
If one has a deep, conceptual understanding of tools, systems and protocols and if one has the ability to carefully provide careful, concise specifications, these LLM tools are like being granted superpowers.
In fact ...
My next project upon which to bring LLM tools to bear is a fully local, solar-powered, self-hosted LLM toolchain.
Not only do I intend to never work without these tools again, I intend to do so without the ongoing environmental externalities that they produce.
Most people already don't have the ability to do this and their use of LLMs atrophies the little they had. "AI natives" will be completely doomed.
However, I never asked for LLMs nor did my consumer nor professional behavior send market signals that I would use them. They were thrust upon me apropos of nothing.
Now that I find them useful, the least I can do is stop making the problem worse.
Why buy a personal EV with 600 mile range that sits idle 95% of the time when you can take a bus (aka the cloud) that maximizes the resource utilization?
Will AI function the same way in all domains? That is the current narrative.
Every time there's a new model This Changes Everything. Every single time.
Every time someone points out a limitation of LLMs it's always the same refrain: "Have you tried the latest? Because they're so much better now!". Except this happens with every single model generation. Every time the new models are so good that it's a seismic shift, a step change, a paradigm shift. It's like the finest curve asymptoting ever upwards, a few billions of training cost at a time.
But- to where? AI keeps getting so groundbreakingly better and we're still stuck in the same old world, except now you can...
... port your unmaintained app from 2017 to modern Android? Why was your app unmaintained? What is the societal and technological upheaval that will come from automating such low-stakes tasks? For such huge costs?
Likewise with many other things - people who don't know how to code can produce large custom programs which do what they needed. They're probably not amazingly well written nor maintainable by a human with limited time on their hands but that also doesn't matter at all for nearly all use cases.
I've only found this guy trying to code GTA 6 before it's released (not II):
https://mashable.com/tech/ai-startup-founder-attempts-to-vib...
Is that the one you meant? I wonder why he didn't try to code GTA 7. I mean, why not?
That's the kind of irresponsible foolishness that makes it hard for me to take you seriously.
Even if the AI singularity is possible, the acceleration would take a long time. Possibly a lifetime.
It requires a level of self-driven intent and access to their own code LLMs aren't capable of on their own. They might be one component of such a future system though, we just don't know yet. Even then it would probably take quite a while to reach that tipping point. GP is just wrong, talking as if we'd already reached it.
Silver lining is that if it goes bad we probably won't live long (as a species) to say "I told you so"
Individuals will use LLMs as they see fit in their work. They'll make a lot of mistakes because they don't see their own work clearly and because they don't really understand the outcomes others care about. Executives who make their money with their mouths will, of course, endlessly open their mouths, even as they don't understand the tech because they never really use any tech beyond email, text, and phones. And so on.
Nobody knows how LLMs will ultimately shake out. But even five minutes of using Claude makes it hard to imagine all white-collar work will continue as in the past.
How do you imagine your or your children's lives in the singularity?
What do you do there for a living, or which hobbies do you pursue in the best case it frees you and everyone around to pursuit nothing but hobbies?
What do you do in the worst case it pushes everyone to underground strongholds to fight machines for the survival of the humankind?
And if there's some middle ground, how is it different from today's state of affairs?
I could absolutely fill my days with stuff, no problem
It'd be different from today's state of affairs in that I wouldn't need to spend the majority of my waking hours reading stuff I don't care about and building things I don't believe need to exist in order to pay for a house I don't own. Healthcare would probably be more reliable and accessible too.
At this point though, I no longer believe this is anyone's future except the most fortunate of the fortunate, most of whom essentially live this way already.
The second is the AI race / existential risk / pretending we’re Oppenheimer track which I think is the larpiest, basically pretending that LLM chatbots are some kind of super weapon and role playing accordingly.
None of this means they’re useful, AI coding, for one, obviously is a valuable tool (though there remains a lot to sort out). But the usefulness is unfortunately being overshadowed by, as you say, people not resetting expectations and instead wanting to play terminator or neuromamcer or whatever (I’m sure there are more relevant sci fi).
One thing is certain; it's here to stay. Now we just need to centralize it into the hands of a small, highly organized group of wise and motivated people, and give it the control it needs to follow through on things, without human oversight and accountability getting in the way.
We should focus on the positive side.*
*The positive side being the classified private versions where the models aren't hindered by guardrails, ethics, moralizing, etc and function as genuine force multipliers.
All I can say on the bearing of loads is that you forgot the emdash and preceding 'not' statements.
I'm no fan of narco, but with all the prejudicial executions of boaters and such, I really think Claude overstepped with the Venezuela plot. You just don't want too many historically unprecedented events happening all at once. The tyranny should be spaced. As I said, a little more sanding down of the harness, AI & Palantir should be ready to permanently solve our problems,
It sounds like the writer of this article could benefit from starting another brand which is the same product but with AI. That brand would make all the delusional AI chatbot sales and absorb the reputational damage when the chatbot destroys companies.
However, this illusion immediately falls apart during actual stress-testing like writing code for a complex, battle-tested production environments. Non-technical folks can effortlessly spin up simple web apps or tweak a frontend so now they conclude that software engineers are becoming redundant.
And even if there are obvious examples of all of this backfiring no one believes it...
Maybe you should be able to go down to your local web app shop, give a couple simple requirements, and get back an app in a week. So why can't you? Well there's actually a good reason for that - the customer would never be satisfied by the result, and building a satisfactory result requires many iterations back and forth. Rapid feedback is essential to software development.
Okay, an alternative is to give the customer an app builder so they can make their own app. We've done this many times in history, it always takes the customer time to make the app, the results are always mediocre, but it does work, why do we keep doing this and then stopping it? I'm not really sure. Why isn't there a visual basic today (apart from Roblox) or even a Frontpage (apart from Squarespace)? My best guess is the customer tires of working on the app or never had time for it in the first place. Why won't AI suffer the same fate? Really no idea.
When doing hard things I need to be 100% in the loop, but I don't have to do anything menial anymore. Imagine being in some CIA control room with 10 emplyees, and you're directing the team. You're still on top of things, just not bogged down with bulky minutiae.
It helps to think of AI as analogous to previous game changers like electricity, computers, internet. If your business is bad or you have no game plan beyond "use internet" your are fucked. But at the same time almost every business has some angle in which these technologies are valuable and necessary and ignoring them is also death.
This specific narrative reads like every narrative explanation of the Republican party in the period from the second half of the first Trump administration until now.
Again, I am talking only about the narratives here. But the pervasive narrative around Trump is that privately everyone hates his guts, comes away with a worse impression when they work with him closely, dreads him opening his mouth, thinks his decisions are insane, and they are telling journalists that, at every opportunity, and have done since the 2018 midterms. And yet in public we have committee hearings where any number of irrational topics become a sort of terror zone here rational people have to assert irrational beliefs or pretzel logic to be able to continue; where ordinary absurdities have become cult-like witness-bearing that everyone polices everyone else on. It's like the Hunger Games of litmus tests.
For example the desire for career advancement is a common thread in both of these narratives, even though this is being promoted further up into the kafkaesque absurdity. Both of these things remind me of other things, like somehow everyone in US politics seemingly believes in God and somehow nobody in an international football (soccer) team is gay. Even though these are not plausible.
This reminds me of "Youth without God" by Ödön von Horváth:
> Perhaps Anne’s mother was right. Perhaps men are mad now—those who aren’t mad haven’t the courage to put their maniacal fellows into strait-jackets.
>– An editor of this essay
The most popular form of AI psychosis in a nutshell, yea. "AI will understand this for us, so we can be groundbreaking and get rich if we just try" is only possible to believe when you have no idea what you or the rest of your field is doing, and have only attempted to learn about it from "AI", which has spent a lot of your money convincing you that you're brilliant and revolutionary.
It's exactly like surrounding yourself with relentless ego-boosting yes-men. You lose touch with reality. Just take a brief look at any super-wealthy person, they're obviously insane but everyone around them thrives on convincing them that they're not.
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>For the latter customer-facing applications, I have rarely had a pleasant experience as a consumer, with perhaps the exception of live transcription during medical appointments...
These have been abject failures, personally. They've made major mistakes in summaries, and added non-existent symptoms multiple times. Medical transcription seems an especially dangerous place to put them.