So apparently according to Axios this blog post has gone "mega viral" and their article concludes by stating affirmatively that the "AI" revolution is here now. It's been shared by a number of normally trusted sources; my sister linked it to me because she saw Medi Hassan share it with a note that it's the most important thing you'll read in like forever.
To me it reads exactly like every other blog post of it's genre. It substitutes subjective personal experience for any kind of externally verifiable fact, makes appeals to anonymous authorities that always seem to support the author's conclusion, uses language designed to induce a sense of fear if not outright panic in the reader, and at no point addresses the fundamental reality of "AI's" catastrophic unprofitability. Not to mention how gross it feels to read the author's slobbering all over Amodei as some kind of model for good corporate behavior.
Fundamentally my real problem with it is that the author believes that if we make LLMs good enough at coding, they will then become capable of doing all other knowledge work to a high enough standard that they will replace human knowledge workers. That is such a breathtaking example of a Leap to Conclusion that if we could harness it's energy we could start sending spaceships directly to other star systems.
It doesn't take much effort to find news about AI (LLMs) successfully being deployed with ROI in healthcare, legal, customer operations, retail, banking accounting/tax and more. I don't think the article needs to worry about Leaping a Conclusion as there is plenty of evidence outside.
PhD physicist (Stanford/SLAC), Research Software Engineer doing low-level systems work in C/C++ and LLM research. Not a founder or investor — just a practitioner.
One data point for this thread: the jump from Opus 4.5 to 4.6 is not linear. The minor version number is misleading. In my daily work the capability difference is the largest single-model jump I've experienced, and I don't say that casually — I spent my career making precision measurements.
I keep telling myself I should systematically evaluate GPT-5.3 Codex and the other frontier models. But Opus is so productive now that I can't justify the time. That velocity of entrenchment is itself a signal, and I think it quietly supports the author's thesis.
I'm not a doomer — I'm an optimist about what prepared individuals and communities can do with this. But I shared this article with family and walked them through it in detail before I ever saw it on HN. That should tell you something about where I think we are.
If you use Claude Code, it will take you half a day to learn to use Codex, and like 30 minutes to start being productive in it. The switching cost is almost zero. Just go test out GPT 5.3, there is no reason not to
It's a bit more than zero, because I have substantial tooling around Claude Code – subagents, skills, containerization, &c – that I'd have to (have Opus...) reimplement.
one feels the llm wow moment whenever what they do on an area has been surpassed by an llm. newer versions of llms are probably trained by the feedback from developer code agent sessions; so this is probably why pro developers started to feel "wow" recently.
the real challenge will be in the frontier of the human knowledge and whether llms will be able to advance things forward or not.
ps1; i'm using 5.3/o4.6/k2.5/m2.5/glm5 and others daily for development - so my work has 1.5x intensified - i tackle increasingly harder problems but llms still really fail big in brand new challenges like i fail too. so i'm more alert than ever.
ps2: syntactical autocomplete used to write 80% of my code; now llms replaced autocomplete but at a semanticlevel; i think and LLM implements most of my actions like a cerebellum for muscle coordination; but sometimes teaching me new info from the net.
The frontier-of-knowledge point is the right question. My own research is a case in point - I apply experimental physics methods to LLMs, measuring their equations of motion in search of a unified framework for how and why they work. Some of the answers I'm looking for may not exist in any training data.
That's where the 4.5->4.6 jump hit me hardest - not routine tasks but problems where I need the model to reason about stuff it hasn't seen. It still fails, but it went from confidently wrong to productively wrong, if that makes sense. I can actually steer it now.
The cerebellum analogy resonates. I'd go further - it's becoming something I think out loud with, which is changing how I approach problems, not just how fast I solve them.
I don't know enough to disprove Matt, but I don't know why anyone should listen to him. There are far smarter people who have come up with similar conclusions.
Well, I did read it, I did listen to him. Assuming he isn't lying about his anecdotal evidence, he did a very good job opening my eyes to just how fast the AI models are moving and how the disruption can and likely will hit the public before they realize it.
What’s the point in using these tools if they’re gonna replace us in a few years? It’s weird the author says that but then his conclusion is basically “go spend money on stuff I’m invested in”.
Covid comparison is apt. I remember being insanely scared in Jan 2020 when those videos of Chinese people dropping dead were coming out (and being shamed by most of my peers etc). Few months later it was starting to become obvious it was really only a major risk if you were old or infirm, but the rest of the world had took awhile to catch up.
AI’s big and gonna change stuff - and like COVID probably for the worse - but we’re in a poorly understood hype cycle right now.
> Few months later it was starting to become obvious it was really only a major risk if you were old or infirm, but the rest of the world had took awhile to catch up.
Only a risk in terms of dying sure, but plenty of people lost taste and smell for long periods before the vaccine (I wouldn't be surprised if some of them have yet to get it back). I'd rather be dead, to be honest. The food around my part of the world is too delicious.
I am not having the exact same experience as the author--Opus 4.6 and Codex 5.3 seem more incremental to me than what he is describing--but if we're on an exponential curve, the difference is a rounding error.
4 months ago, I tried to build an application mostly vibe-coded. I got impressively far for what I thought was possible, but it bogged down. This past weekend, my friend had OpenClaw build an application of similar complexity in a weekend. The difference is vast.
At work, I wouldn't say I'm one-shotting tasks, but the first shot is doing what used to be a week's work in about an hour, and then the next few hours are polish. Most of the delay in the polish phase is due to the speed of the tooling (e.g. feature branch environment spin up and CI) and the human review at the end of the process.
The side effects people report of lower quality code hitting review are real, but I think that is a matter of training, process and work harness. I see no reason that won't significantly improve.
As I said in another thread a couple days ago, AI is the first technology where everyone is literally having a different experience. Even within my company, there are divergent experiences. But I think we're in world where very soon, companies will be demanding their engineering departments converge to the lived experience of the people who are seeing something like the author. And if they can find people who can actuate that reality, the folks who can't are going to see their options contract precipitously.
> But I think we're in world where very soon, companies will be demanding their engineering departments converge to the lived experience of the people who are seeing something like the author.
I think this part is very real.
If you’re in this thread saying “I don’t get it” you are in danger much faster than your coworker who is using it every day and succeeding at getting around AI’s quirks to be productive.
My wife manages 70 software developers. Her boss, the CIO, who has no practical programming experiece, is demanding her and her peers cut 50% of their staff in the next year.
Yes, for me --moved past AI coding accelerating you to 80-90% then living in the valley of infinite tweaks. This past month with with right thinking working with say Opus 4.6 has moved past that blocker.
> But I think we're in world where very soon, companies will be demanding their engineering departments converge to the lived experience of the people who are seeing something like the author.
We already live in that world. It's called "Hey Siri", "Hey Google", and "Alexa". It seems that no amount of executive tantrum has caused any of these tools to give a convergent experience.
Jokes aside it should be noted that the author is a founder and ceo of an AI company, not to mention an active investor in the sector. (All disclosed in his "about" page)
It should be noted that the author doesn't shy away from that, and that his argument is convincing. He notes that while he is in the AI field, the actual cutting edge of AI development is done by a far smaller group of companies and researchers than the broader AI industry which includes his company.
Was there something specific in the article you found unconvincing, or that directly counters an experience you've had with AI?
I'm not making a statement on his arguments (well I dont agree with it, but that was not in my post).
I posted that because I consider blogging a fringe form of journalism, and basic journalism ethics require clear disclosure of conflict of interests.
His entire blog is very self serving. Which doesn't mean his opinion is wrong, but potentially not "cold" or impartial. More like a sales pitch probably. He is also very trasparent about his business but the article is posted here without that context, and I think it's important to point it out given the era of sensationalized and fake news we live in.
Every once in a while, I try LLMs just to see how improvement is going.
Yesterday I had to explain to Opus what the color white is and what "bottom right" means after it declared problems fixed, repeatedly, that a literal preschooler would have been able to tell were absolutely unchanged from the original problem description.
I am still waiting for this world of redundant programmers I've been hearing about for years.
I use FreeBSD. When talking to LLMs, they insist on giving me code in bash. Bash is not native to FreeBSD (though you can get it and use it). I correct them, and of course they apologize, but another day continue to use bash in other questions.
Considering the rate of improvement of these LLMs, wait for a month or two and then you may not even need an os, let alone some obsecure piece of software (shell).
Let's take that vibe coded product and iterate what it gave you 100 times, as you tweak it to fit your vision. When you do that 101st iteration, can you prevent it from breaking something else, or changing it in a way you don't like it?
What if it doesn't understand what you're asking it to do and keeps failing and you have to keep rolling back? Can you understand the 20,000 lines it's generated so you can make the change yourself without tearing your hair out? Can you fix bugs in it that it can't, without starting from zero and having to understand the whole codebase?
To guard against this, the best course of action is probably modularization and composition, right? The Unix philosophy, ie building small, focused tools out of small, focused tools.
yes - i've thought that could work. returning to a more protected object oriented programming model (with hard-defined interfaces) could be a way - "make these changes but restrict yourself to this object" etc.
If you take the author's arguments on face value, you just hit YOLO button and have one iteration and publish it to production fast so you are on the market before competition does the same.
To me, this is highlighting the fall of modern media - people have lost trust in MSM and have flocked to 'influencers' and 'thought leaders'. There is no checking for credibility, veracity of claims, or any relevant expertise. This is basically vibe news, sentiment peddling.
I could say AI is here - we don't even need to do research anymore. All I need to say is: "Claude, cure cancer", go away for 4 hours to drink my coffee, come back and boom - cancer cured. Perfect research ready for funding and trials.
People would call me crazy. But what if I say 'PHARMACEUTICAL CEO', 'PhD', 'MULTIPLE COMMERCIAL DRUG SUCCESSES' - people will eat it up.
Let's see what you can find out about Matt Shumer, the AI CEO, from his public profiles:
No technical background - looks like a business 'entrepreneurial' degree from what looks like a middle-of-the-road school
No experience working anywhere other than the companies he founded
No notable exits or commercial success from the companies he founded
And if you dig deeper, it appears that:
His latest startup is a scam https://news.ycombinator.com/item?id=41484981
He is the CEO of a startup
He's trend-hopping on the 'new thing' (all in with VR in 2019, now AI) - incredible that there is no crypto in there
The post offers no concrete evidence for its claims and is peddling fear and sentiment, yet somehow respected publications write opinion pieces about his article, credible people retweet it, and it goes MEGA viral.
The only credit I am willing to give here is that he managed to accurately reflect the vibes that resonate with people, which is really a shame because this is what people actually think.
What's worse is that now he probably has legitimate people seeking his views and opinions on technical matters because he's got it 'so right' and he is so 'knowledgeable' about it.
Hopefully someone can succeed in online reputation management for websites, content, and people, and help us separate credible from grift.
Absolutely agreed—seeing this post continue to circulate across all forms of media with seemingly zero critical thinking or evaluation of its author’s credibility reminds me of the Zoolander “I feel I’m taking crazy pills” meme.
I remembered this guy from his “Reflection 70b” scam in 2024. That should have basically put his credibility at zero, but clearly it has not.
I found this interaction in the HN comments from the time of that minor scandal to be prescient:
>> It's amazing what people will do for clout. His whole reputation is ruined. What was Schumer's endgame?
> But does reputation work? Will people google "Matt Shumer scam", "HyperWrite scam", "OthersideAI scam", "Sahil Chaudhary scam", "Glaive AI scam" before using their products? He wasted everyone's time, but what's the downside for him? Lots of influencers did fraud, and they do just fine.
I find these water-against-a-rock literary tones so tedious. Even the writer always seems to have to go back and put some of it in BOLD TEXT, supposedly highlighting the main ideas, but really optical affordances.
The truth of this seems much more banal. Computing has become a major drag. There have been tens of thousands of libraries that reinvent the wheel. Every operating system has become a toy. All major language systems have an absurd learning curve. Each important application is fortified by a giant corporation. Social media is self-important pop babble.
LLMs are surprisingly good at dealing with complex systems. I can fire one up and ask, for example, why this Swift code is not compiling. But why doesn’t my Swift editor explain that problem? Why is it a confusing question at all? The entire system was built from the ground up at enormous expense. Why do I seek outside help?
Our computing is full of whizzy animations and pointless Victorian ironmongery. All meaningless. AI is medicine, not the cure.
Because if we engineered these to work, then we'd be out of a job because the problems would be solved and we could not sell the same service or software 1000 times.
I noticed that in the article he includes a link to follow him on X. It made me wonder if the article exists to get him followers. Or get more investment into his company.
I'm not saying the article isn't worth reading. I just now wondered--and wouldn't be surprised--if it was written by AI.
with these posts I always wonder, what happens when this code runs into a customer? Or 1000 customers, or a million? All with their own divergent needs year over year.
I have just gotten off 3 years as a developer for that kind of project, and I used the best AI tools diligently every day. It often saved me time. Like from some small drudgery of half day of flailing about in config land. Or it could generate some nice rails controllers and a javascript front end from a well-written spec. writing tests was also a strong suit.
but just as often it failed to understand the depth of the product and its myriad concerns and led me down the garden path, reducing my efficiency.
Aside from that, a large part of my job was the parts that weren't coding - wrestling with specs that were far from ready for primetim, chaotic internal processes, deployment, internal coordination/communcation, talking to customers, etc.
In the end it seemed like it saved me maybe 20% of my time overall. Nothing to sneeze at.
I get that greenfield apps that have no customer contact can be created with a phrase now. That's pretty amazing. But I would love to see Opus 4.6 up against a real beast of a codebase that you're far from a master of.
You know, as a (prickly) analogy, whatever your take on covid was, half the population vehemently disagreed with your take. No matter which side was more "correct", either way, a huge percentage of the population can be, and often is, completely deluded on even fairly understandable topics.
When it comes to something as complex as AI, what are the odds that a random person is going to have any sort of good/informed take on it? Especially someone like this, who's a non-technical angel investor? Their entire job is hyping things up to raise money / get paydays. They actually list on their resume various "viral articles/tweets" that they made that got attention / raised money. Could this guy remotely explain, technically, how an LLM works under the hood? I highly doubt it. His credentials are not building AI, not technical knowledge, but hyping up companies that use AI.
Well, at least he gives 1-5 year time frames for all his grand claims, so when they don't actually happen he'll be quickly proven wrong. But of course, it's the internet, and nothing will ever come from somebody making grand claims and then being completely proven wrong, there will be no follow up, no self reflection, no retraction, no long-term credibility hit, just on to hyping up the next thing after getting his payday.
Management is going to quickly start bisecting human engineers along lines of maximalists and minimalists. The minimalists will all be let go. A few bad things will happen. A few systems will strain under the pressure but itll be “worth it” in the same way that its cheaper to pay lawsuits than do a recall of a plane.
We arent innovating in other areas that might soften the blow. We dont have good support systems, social security, healthcare, or even demands in other areas. How many engineers are going to be plumbers and construction workers?
Think IBM training manual had a quote about not being able to hold a computer accountable, so you cant let them make management decisions. Basically management will stick around so somebody can be held to blame if AI slop breaks
So long as perceived LLM skill is still "spiky" - e.g. within a domain, still showing relatively high variation in ability (often depending on the task or user, to be fair), people will continue to dismiss it
I think the author should put his money where his mouth is, to prove his point. He should install OpenClaw, switch it to whatever he wants and give it access to his brokerage account. If he is right, he should become rich in almost no time.
>Making AI great at coding was the strategy that unlocks everything else. That's why they did it first.
That will happen in an universe where infinite acceleration and infinite speed is possible. The laws of our universe are still bounded by the speed of light. Nothing grows exponentially forever.
This is a solid assessment of whats here and what is in front of us. Broad brush stroke dismissals aside, we are here. Evolve or Perish. AI is like unchecked fire, but make no mistake fire is very powerful once it was harnessed. AI leans more supplemental vs incremental than prior major tech shifts and that's worth noting. It will be the same for other sectors and verticals over time. The markets view software eats the world is being eaten by new software.
yep, and for the finances to make sense, these AIs need to make a significant impact on employment rolls, ie., they need to replace humans. Personally I think its the wrong tech at the wrong time, but I don't think me and this timeline is a very good match so ymmv
Protect the human culture while you can. His advice to embrace AI in order to survive what's coming is naive. When Europeans came to native Americans, they brought their technology, their way of thinking and erased the native culture in a matter of years. The weak were poisoned with alcohol, the strong were killed and the few survivors were sent to reservations. Would it be possible to survive by embracing the alien culture? Don't fool yourself.
> You can describe an app to AI and have a working version in an hour. I'm not exaggerating. I do this regularly. If you've always wanted to write a book but couldn't find the time or struggled with the writing, you can work with AI to get it done.
Interesting. So you regularly make new apps in 1 hour each.
How is that the same as...writing a book? Did you mean write several short stories? Or are we talking non-fiction?
Yep! They still remain stupid (in the intelligence sense, not the pejorative sense) tools which have no practical value to anyone with decent skills. But the people who have a financial interest in hype are still trying to convince everyone "it's totally different now bro, use the latest model bro". It's so tiresome.
So apparently according to Axios this blog post has gone "mega viral" and their article concludes by stating affirmatively that the "AI" revolution is here now. It's been shared by a number of normally trusted sources; my sister linked it to me because she saw Medi Hassan share it with a note that it's the most important thing you'll read in like forever.
To me it reads exactly like every other blog post of it's genre. It substitutes subjective personal experience for any kind of externally verifiable fact, makes appeals to anonymous authorities that always seem to support the author's conclusion, uses language designed to induce a sense of fear if not outright panic in the reader, and at no point addresses the fundamental reality of "AI's" catastrophic unprofitability. Not to mention how gross it feels to read the author's slobbering all over Amodei as some kind of model for good corporate behavior.
Fundamentally my real problem with it is that the author believes that if we make LLMs good enough at coding, they will then become capable of doing all other knowledge work to a high enough standard that they will replace human knowledge workers. That is such a breathtaking example of a Leap to Conclusion that if we could harness it's energy we could start sending spaceships directly to other star systems.
It doesn't take much effort to find news about AI (LLMs) successfully being deployed with ROI in healthcare, legal, customer operations, retail, banking accounting/tax and more. I don't think the article needs to worry about Leaping a Conclusion as there is plenty of evidence outside.
Mind sharing some of this supposedly easy to find evidence? I'm having a real hard time digging any up.
PhD physicist (Stanford/SLAC), Research Software Engineer doing low-level systems work in C/C++ and LLM research. Not a founder or investor — just a practitioner.
One data point for this thread: the jump from Opus 4.5 to 4.6 is not linear. The minor version number is misleading. In my daily work the capability difference is the largest single-model jump I've experienced, and I don't say that casually — I spent my career making precision measurements.
I keep telling myself I should systematically evaluate GPT-5.3 Codex and the other frontier models. But Opus is so productive now that I can't justify the time. That velocity of entrenchment is itself a signal, and I think it quietly supports the author's thesis.
I'm not a doomer — I'm an optimist about what prepared individuals and communities can do with this. But I shared this article with family and walked them through it in detail before I ever saw it on HN. That should tell you something about where I think we are.
If you use Claude Code, it will take you half a day to learn to use Codex, and like 30 minutes to start being productive in it. The switching cost is almost zero. Just go test out GPT 5.3, there is no reason not to
It's a bit more than zero, because I have substantial tooling around Claude Code – subagents, skills, containerization, &c – that I'd have to (have Opus...) reimplement.
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one feels the llm wow moment whenever what they do on an area has been surpassed by an llm. newer versions of llms are probably trained by the feedback from developer code agent sessions; so this is probably why pro developers started to feel "wow" recently.
the real challenge will be in the frontier of the human knowledge and whether llms will be able to advance things forward or not.
ps1; i'm using 5.3/o4.6/k2.5/m2.5/glm5 and others daily for development - so my work has 1.5x intensified - i tackle increasingly harder problems but llms still really fail big in brand new challenges like i fail too. so i'm more alert than ever.
ps2: syntactical autocomplete used to write 80% of my code; now llms replaced autocomplete but at a semanticlevel; i think and LLM implements most of my actions like a cerebellum for muscle coordination; but sometimes teaching me new info from the net.
The frontier-of-knowledge point is the right question. My own research is a case in point - I apply experimental physics methods to LLMs, measuring their equations of motion in search of a unified framework for how and why they work. Some of the answers I'm looking for may not exist in any training data.
That's where the 4.5->4.6 jump hit me hardest - not routine tasks but problems where I need the model to reason about stuff it hasn't seen. It still fails, but it went from confidently wrong to productively wrong, if that makes sense. I can actually steer it now.
The cerebellum analogy resonates. I'd go further - it's becoming something I think out loud with, which is changing how I approach problems, not just how fast I solve them.
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For reference the author's (Matt Shumer) AI business (hyperwrite ai) is a hundred small LLM wrappers that do things like:
- "transform complex topics into easy-to-understand explanations."
- "edit and transform images using simple text descriptions."
- "summarizes a research article, and answers specific questions about it."
You can see all of them here: https://www.hyperwriteai.com/aitools.
Hyperwrite does also have a markdown editor with an ai copilot sidebar that seems a little more substantial: https://www.hyperwriteai.com/ai-document-editor.
I don't know enough to disprove Matt, but I don't know why anyone should listen to him. There are far smarter people who have come up with similar conclusions.
Well, I did read it, I did listen to him. Assuming he isn't lying about his anecdotal evidence, he did a very good job opening my eyes to just how fast the AI models are moving and how the disruption can and likely will hit the public before they realize it.
What’s the point in using these tools if they’re gonna replace us in a few years? It’s weird the author says that but then his conclusion is basically “go spend money on stuff I’m invested in”.
Covid comparison is apt. I remember being insanely scared in Jan 2020 when those videos of Chinese people dropping dead were coming out (and being shamed by most of my peers etc). Few months later it was starting to become obvious it was really only a major risk if you were old or infirm, but the rest of the world had took awhile to catch up.
AI’s big and gonna change stuff - and like COVID probably for the worse - but we’re in a poorly understood hype cycle right now.
> What’s the point in using these tools if they’re gonna replace us in a few years?
Increase shareholder value in the short term.
> > What’s the point in using these tools if they’re gonna replace us in a few years?
> Increase shareholder value in the short term.
everytime I see this as the ultimate conclusion for all of these kind of hype posts
> Few months later it was starting to become obvious it was really only a major risk if you were old or infirm, but the rest of the world had took awhile to catch up.
Only a risk in terms of dying sure, but plenty of people lost taste and smell for long periods before the vaccine (I wouldn't be surprised if some of them have yet to get it back). I'd rather be dead, to be honest. The food around my part of the world is too delicious.
also people developed debilitating brain fog, chronic fatigue, and increased risk of heart trouble.
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I am not having the exact same experience as the author--Opus 4.6 and Codex 5.3 seem more incremental to me than what he is describing--but if we're on an exponential curve, the difference is a rounding error.
4 months ago, I tried to build an application mostly vibe-coded. I got impressively far for what I thought was possible, but it bogged down. This past weekend, my friend had OpenClaw build an application of similar complexity in a weekend. The difference is vast.
At work, I wouldn't say I'm one-shotting tasks, but the first shot is doing what used to be a week's work in about an hour, and then the next few hours are polish. Most of the delay in the polish phase is due to the speed of the tooling (e.g. feature branch environment spin up and CI) and the human review at the end of the process.
The side effects people report of lower quality code hitting review are real, but I think that is a matter of training, process and work harness. I see no reason that won't significantly improve.
As I said in another thread a couple days ago, AI is the first technology where everyone is literally having a different experience. Even within my company, there are divergent experiences. But I think we're in world where very soon, companies will be demanding their engineering departments converge to the lived experience of the people who are seeing something like the author. And if they can find people who can actuate that reality, the folks who can't are going to see their options contract precipitously.
> But I think we're in world where very soon, companies will be demanding their engineering departments converge to the lived experience of the people who are seeing something like the author.
I think this part is very real.
If you’re in this thread saying “I don’t get it” you are in danger much faster than your coworker who is using it every day and succeeding at getting around AI’s quirks to be productive.
We’ve got repos full of 90% complete vibe code.
They’re all 90% there.
The thing is the last 10% is 90% of the effort. The last 1% is 99% of the effort.
For those of us who can consistently finish projects the future is bright.
The sheer amount of vibe code is simply going to overwhelm us (see current state of open source)
My wife manages 70 software developers. Her boss, the CIO, who has no practical programming experiece, is demanding her and her peers cut 50% of their staff in the next year.
Be careful here. I have more coworkers contributing slop and causing production issues than 10x’ing themselves.
The real danger is if management sees this as acceptable. If so best of luck to everyone.
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Yes, for me --moved past AI coding accelerating you to 80-90% then living in the valley of infinite tweaks. This past month with with right thinking working with say Opus 4.6 has moved past that blocker.
> But I think we're in world where very soon, companies will be demanding their engineering departments converge to the lived experience of the people who are seeing something like the author.
We already live in that world. It's called "Hey Siri", "Hey Google", and "Alexa". It seems that no amount of executive tantrum has caused any of these tools to give a convergent experience.
Voice assistants, which I've used less than 10 times in my life, are hardly related to what I'm talking about.
I asked ai to summarise this blog post.
Jokes aside it should be noted that the author is a founder and ceo of an AI company, not to mention an active investor in the sector. (All disclosed in his "about" page)
It should be noted that the author doesn't shy away from that, and that his argument is convincing. He notes that while he is in the AI field, the actual cutting edge of AI development is done by a far smaller group of companies and researchers than the broader AI industry which includes his company.
Was there something specific in the article you found unconvincing, or that directly counters an experience you've had with AI?
I'm not making a statement on his arguments (well I dont agree with it, but that was not in my post).
I posted that because I consider blogging a fringe form of journalism, and basic journalism ethics require clear disclosure of conflict of interests.
His entire blog is very self serving. Which doesn't mean his opinion is wrong, but potentially not "cold" or impartial. More like a sales pitch probably. He is also very trasparent about his business but the article is posted here without that context, and I think it's important to point it out given the era of sensationalized and fake news we live in.
How convenient that the AI apocalypse is happening RIGHT NOW, as the investors are more and more worried about an AI bubble. Good timing, I suppose.
Every once in a while, I try LLMs just to see how improvement is going.
Yesterday I had to explain to Opus what the color white is and what "bottom right" means after it declared problems fixed, repeatedly, that a literal preschooler would have been able to tell were absolutely unchanged from the original problem description.
I am still waiting for this world of redundant programmers I've been hearing about for years.
I use FreeBSD. When talking to LLMs, they insist on giving me code in bash. Bash is not native to FreeBSD (though you can get it and use it). I correct them, and of course they apologize, but another day continue to use bash in other questions.
Considering the rate of improvement of these LLMs, wait for a month or two and then you may not even need an os, let alone some obsecure piece of software (shell).
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I thought the article was going to delve into this.
"The future is being shaped by a remarkably small number of people".
That is a lot of power in the hands of a few people. Probably nothing to worry about. Power is hardly ever abused...
> Making AI great at coding was the strategy that unlocks everything else. That's why they did it first.
They did it first because doing it first was easier. There are tons of examples around and code can be verified to work.
Let's take that vibe coded product and iterate what it gave you 100 times, as you tweak it to fit your vision. When you do that 101st iteration, can you prevent it from breaking something else, or changing it in a way you don't like it?
What if it doesn't understand what you're asking it to do and keeps failing and you have to keep rolling back? Can you understand the 20,000 lines it's generated so you can make the change yourself without tearing your hair out? Can you fix bugs in it that it can't, without starting from zero and having to understand the whole codebase?
To guard against this, the best course of action is probably modularization and composition, right? The Unix philosophy, ie building small, focused tools out of small, focused tools.
yes - i've thought that could work. returning to a more protected object oriented programming model (with hard-defined interfaces) could be a way - "make these changes but restrict yourself to this object" etc.
Just run it a 102nd time to fix the error from the 101st time, obviously /j
If you take the author's arguments on face value, you just hit YOLO button and have one iteration and publish it to production fast so you are on the market before competition does the same.
To me, this is highlighting the fall of modern media - people have lost trust in MSM and have flocked to 'influencers' and 'thought leaders'. There is no checking for credibility, veracity of claims, or any relevant expertise. This is basically vibe news, sentiment peddling.
I could say AI is here - we don't even need to do research anymore. All I need to say is: "Claude, cure cancer", go away for 4 hours to drink my coffee, come back and boom - cancer cured. Perfect research ready for funding and trials.
People would call me crazy. But what if I say 'PHARMACEUTICAL CEO', 'PhD', 'MULTIPLE COMMERCIAL DRUG SUCCESSES' - people will eat it up.
Let's see what you can find out about Matt Shumer, the AI CEO, from his public profiles:
No technical background - looks like a business 'entrepreneurial' degree from what looks like a middle-of-the-road school No experience working anywhere other than the companies he founded No notable exits or commercial success from the companies he founded And if you dig deeper, it appears that:
His latest startup is a scam https://news.ycombinator.com/item?id=41484981 He is the CEO of a startup He's trend-hopping on the 'new thing' (all in with VR in 2019, now AI) - incredible that there is no crypto in there The post offers no concrete evidence for its claims and is peddling fear and sentiment, yet somehow respected publications write opinion pieces about his article, credible people retweet it, and it goes MEGA viral.
The only credit I am willing to give here is that he managed to accurately reflect the vibes that resonate with people, which is really a shame because this is what people actually think.
What's worse is that now he probably has legitimate people seeking his views and opinions on technical matters because he's got it 'so right' and he is so 'knowledgeable' about it.
Hopefully someone can succeed in online reputation management for websites, content, and people, and help us separate credible from grift.
Absolutely agreed—seeing this post continue to circulate across all forms of media with seemingly zero critical thinking or evaluation of its author’s credibility reminds me of the Zoolander “I feel I’m taking crazy pills” meme.
I remembered this guy from his “Reflection 70b” scam in 2024. That should have basically put his credibility at zero, but clearly it has not.
I found this interaction in the HN comments from the time of that minor scandal to be prescient:
>> It's amazing what people will do for clout. His whole reputation is ruined. What was Schumer's endgame?
> But does reputation work? Will people google "Matt Shumer scam", "HyperWrite scam", "OthersideAI scam", "Sahil Chaudhary scam", "Glaive AI scam" before using their products? He wasted everyone's time, but what's the downside for him? Lots of influencers did fraud, and they do just fine.
https://news.ycombinator.com/item?id=41485180
I find these water-against-a-rock literary tones so tedious. Even the writer always seems to have to go back and put some of it in BOLD TEXT, supposedly highlighting the main ideas, but really optical affordances.
The truth of this seems much more banal. Computing has become a major drag. There have been tens of thousands of libraries that reinvent the wheel. Every operating system has become a toy. All major language systems have an absurd learning curve. Each important application is fortified by a giant corporation. Social media is self-important pop babble.
LLMs are surprisingly good at dealing with complex systems. I can fire one up and ask, for example, why this Swift code is not compiling. But why doesn’t my Swift editor explain that problem? Why is it a confusing question at all? The entire system was built from the ground up at enormous expense. Why do I seek outside help?
Our computing is full of whizzy animations and pointless Victorian ironmongery. All meaningless. AI is medicine, not the cure.
Because if we engineered these to work, then we'd be out of a job because the problems would be solved and we could not sell the same service or software 1000 times.
Why is this flagged? It's a relevant essay from someone in the field with very convincing arguments.
Does using "@dang" work to get attention to this?
I noticed that in the article he includes a link to follow him on X. It made me wonder if the article exists to get him followers. Or get more investment into his company.
I'm not saying the article isn't worth reading. I just now wondered--and wouldn't be surprised--if it was written by AI.
It was. He says as much in the replies to his tweet - https://x.com/mattshumer_/status/2021256989876109403
> They focused on making AI great at writing code first... because building AI requires a lot of code.
I'm not convinced this person knows what they're talking about.
with these posts I always wonder, what happens when this code runs into a customer? Or 1000 customers, or a million? All with their own divergent needs year over year.
I have just gotten off 3 years as a developer for that kind of project, and I used the best AI tools diligently every day. It often saved me time. Like from some small drudgery of half day of flailing about in config land. Or it could generate some nice rails controllers and a javascript front end from a well-written spec. writing tests was also a strong suit.
but just as often it failed to understand the depth of the product and its myriad concerns and led me down the garden path, reducing my efficiency.
Aside from that, a large part of my job was the parts that weren't coding - wrestling with specs that were far from ready for primetim, chaotic internal processes, deployment, internal coordination/communcation, talking to customers, etc.
In the end it seemed like it saved me maybe 20% of my time overall. Nothing to sneeze at.
I get that greenfield apps that have no customer contact can be created with a phrase now. That's pretty amazing. But I would love to see Opus 4.6 up against a real beast of a codebase that you're far from a master of.
You know, as a (prickly) analogy, whatever your take on covid was, half the population vehemently disagreed with your take. No matter which side was more "correct", either way, a huge percentage of the population can be, and often is, completely deluded on even fairly understandable topics.
When it comes to something as complex as AI, what are the odds that a random person is going to have any sort of good/informed take on it? Especially someone like this, who's a non-technical angel investor? Their entire job is hyping things up to raise money / get paydays. They actually list on their resume various "viral articles/tweets" that they made that got attention / raised money. Could this guy remotely explain, technically, how an LLM works under the hood? I highly doubt it. His credentials are not building AI, not technical knowledge, but hyping up companies that use AI.
Well, at least he gives 1-5 year time frames for all his grand claims, so when they don't actually happen he'll be quickly proven wrong. But of course, it's the internet, and nothing will ever come from somebody making grand claims and then being completely proven wrong, there will be no follow up, no self reflection, no retraction, no long-term credibility hit, just on to hyping up the next thing after getting his payday.
The problem with current technology is that it can't feed from what it produces. And the more it produces the less it has to feed from.
I wonder what will happen.
Management is going to quickly start bisecting human engineers along lines of maximalists and minimalists. The minimalists will all be let go. A few bad things will happen. A few systems will strain under the pressure but itll be “worth it” in the same way that its cheaper to pay lawsuits than do a recall of a plane.
We arent innovating in other areas that might soften the blow. We dont have good support systems, social security, healthcare, or even demands in other areas. How many engineers are going to be plumbers and construction workers?
If what the author says is true, there’s no point in management either.
Think IBM training manual had a quote about not being able to hold a computer accountable, so you cant let them make management decisions. Basically management will stick around so somebody can be held to blame if AI slop breaks
Here’s a counterpoint that attempts to argue an alternative view:
https://xeiaso.net/blog/2026/markdownlang/
StrongDM is shipping software in "markdownlang": https://github.com/strongdm/attractor
This link is now on the top level of DrudgeReport.
I hope he has a good hosting plan.
So long as perceived LLM skill is still "spiky" - e.g. within a domain, still showing relatively high variation in ability (often depending on the task or user, to be fair), people will continue to dismiss it
I think the author should put his money where his mouth is, to prove his point. He should install OpenClaw, switch it to whatever he wants and give it access to his brokerage account. If he is right, he should become rich in almost no time.
>Making AI great at coding was the strategy that unlocks everything else. That's why they did it first.
That will happen in an universe where infinite acceleration and infinite speed is possible. The laws of our universe are still bounded by the speed of light. Nothing grows exponentially forever.
If we cover our eyes, it definitely won't happen
> AI can already read contracts, summarize case law, draft briefs, and do legal research at a level that rivals junior associates.
And best of all, when it messes up, it doesn't get sued!
You do.
It doesn’t mess up. Not any more.
Claude, ChatGPT, and Gemini still make mistakes IME. What are you using?
Mostly speculative
This is a solid assessment of whats here and what is in front of us. Broad brush stroke dismissals aside, we are here. Evolve or Perish. AI is like unchecked fire, but make no mistake fire is very powerful once it was harnessed. AI leans more supplemental vs incremental than prior major tech shifts and that's worth noting. It will be the same for other sectors and verticals over time. The markets view software eats the world is being eaten by new software.
yep, and for the finances to make sense, these AIs need to make a significant impact on employment rolls, ie., they need to replace humans. Personally I think its the wrong tech at the wrong time, but I don't think me and this timeline is a very good match so ymmv
On their heads be it
Protect the human culture while you can. His advice to embrace AI in order to survive what's coming is naive. When Europeans came to native Americans, they brought their technology, their way of thinking and erased the native culture in a matter of years. The weak were poisoned with alcohol, the strong were killed and the few survivors were sent to reservations. Would it be possible to survive by embracing the alien culture? Don't fool yourself.
we need a cage match between “something big is coming” tribe and “ai bubble” tribe - I’d pay serious money to watch that
> You can describe an app to AI and have a working version in an hour. I'm not exaggerating. I do this regularly. If you've always wanted to write a book but couldn't find the time or struggled with the writing, you can work with AI to get it done.
Interesting. So you regularly make new apps in 1 hour each.
How is that the same as...writing a book? Did you mean write several short stories? Or are we talking non-fiction?
Also if a person always wanted to write a book I don’t think prompting an AI will scratch that itch.
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As you've proven it, some people really are holding it wrong:
https://chatgpt.com/share/698c97bb-0d04-8006-9418-8f299c6bd0...
I mean, you both used the exact same prompt, how is OP 'holding it worng'?
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> AI models are as shitty as they were in 2023.
Yep! They still remain stupid (in the intelligence sense, not the pejorative sense) tools which have no practical value to anyone with decent skills. But the people who have a financial interest in hype are still trying to convince everyone "it's totally different now bro, use the latest model bro". It's so tiresome.
All about AI taking over the world.