My anxiety about falling behind with AI plummeted after I realized many of these tweets are overblown in this way. I use AI every day, how is everyone getting more spectacular results than me? Turns out: they exaggerate.
Here are several real stories I dug into:
"My brick-and-mortar business wouldn't even exist without AI" --> meant they used Claude to help them search for lawyers in their local area and summarize permits they needed
"I'm now doing the work of 10 product managers" --> actually meant they create draft PRD's. Did not mention firing 10 PMs
"I launched an entire product line this weekend" --> meant they created a website with a sign up, and it shows them a single javascript page, no customers
"I wrote a novel while I made coffee this morning" --> used a ChatGPT agent to make a messy mediocre PDF
Getting viral on X is the current replacement for selling courses for {daytrading,amazon FBA,crypto}.
The content of the tweets isn't the thing.. bull-posting or invoking Cunningham's Law is. X is the destination for formula posting and some of those blue checkmarks are getting "reach" rev share kickbacks.
Yeah, if you get enough impressions, you get some revenue, so you don't need to sell any courses, just viral content. Which is why some (not ALL) exaggerate as suggested.
It's a bit insane how much reach you need before you'd earn anything impactful, though.
I average 1-2M impressions/month, and have some video clips on X/Twitter that have gotten 100K+ views, and average earnings of around $42/month (over the past year).
I imagine you'd need hundreds of millions of impressions/views on Twitter to earn a living with their current rates.
Thanks a lot for your transparency Jeff! Much needed in this area. And your content is quality, much unlike what else being discussed here.
It is really hard to actually make anything substantial on social media exposure. Unfortunately this does not stop many from exaggerating claims in order to (maybe become) be internet famous, or seeing high number of clicks etc. So it is both bad business for creators, and poisoning the discourse for readers - the only real winners are the social media companies and the product companies that get hyped up.
> Unfortunately this does not stop many from exaggerating claims in order to (maybe become) be internet famous
I've been thinking about this a lot lately in another context -- vira priests being anti-vax and realized it's the other way around: their motivation doesn't matter, but the viewers don't want to see moderate content, they want to see highly polarized and controversial topics.
The same with the claims about AI. Nobody wants to hear AI boosts productivity in nuanced way, people either want to hear about 10X or -10X so the market dictates the content/meme.
I'm not as familiar with your content but how often do you post? I have a friend who posts 'meme' type of content (all original) and he makes a decent amount, but he has it all queued up.
I pretty much never even went there for technical topics at all, just funny memes and such, but one day recently I started seeing crazy AI hype stories getting posted, and sadly I made a huge mistake and I clicked on one once, and now it’s all I get.
Endless posts from subs like r/agi, r/singularity, as well as the various product specific subs (for Claude, OpenAI, etc). These aren’t even links to external articles, these are supposedly personal accounts of someone being blown away by what the latest release of this or that model or tool can do. Every single one of these posts boils down to some irritating “game over for software engineers” hype fest, sometimes with skeptical comments calling out the clearly AI-generated text and overblown claims, sometimes not. Usually comments pointing out flaws in whatever’s being hyped are just dismissed with a hand wave about how the flaw may have been true at one time, but the latest and greatest version has no such flaws and is truly miraculous, even if it’s just a minor update for that week. It’s always the same pattern.
I actually read through the logs and the code in the rare instances someone actually posts their prompts and the generated output. If I'm being overly cynical about the tech, I want to know.
The last one I did it on was breathlessly touted as "I used [LLM] to do some advanced digital forensics!"
Dawg. The LLM grepped for a single keyword you gave it and then faffed about putting it into json several times before throwing it away and generating some markdown instead. When you told it the result was bad, it grepped for a second word and did the process again.
It looks impressive with all these json files and bash scripts flying by, but what it actually did was turn a single word grep into blog post markdown and you still had to help it.
Some of you have never been on enterprise software sales calls and it shows.
> Some of you have never been on enterprise software sales calls and it shows.
Hah—I'm struggling to decide whether everyone experiencing it would be a good thing in terms of inoculating people's minds, or a terrible thing in terms of what it says about a society where it happens.
“I used AI to make a super profitable stock trading bot”
—-> using fake money with historical data
“I used AI to make an entire NES emulator in an afternoon!” —-> a project that has been done hundreds of times and posted all over github with plenty of references
> “I used AI to make a super profitable stock trading bot” —-> using fake money with historical data
Stocks are another matter. There were wonder "algorithms" even before "AI". I helped some friends tweak some. They had the enthusiasm and I had the programming expertise and I was curious.
That was a couple years ago. None of them is rich and retired now - which was what the test runs were showing - and I think most aren't even trading any more.
I feel the same.
I understand some of the excitement. Whenn I use it I feel more productive as it seems I get more code done.
But I never finish anything earlier because it never fails to introduce a bizarre bug or behaviour that no one in sane made doing the task would
> "I wrote a novel while I made coffee this morning" --> used a ChatGPT agent to make a messy mediocre PDF
There was a story years ago about someone who made hundreds of novels on Amazon, in aggregate they pulled in a decent penny. I wonder if someone's doing the same but with ChatGPT instead.
Pretty sure there was a whole era where people were doing this with public domain works, as well as works generated by Markov chains spitting out barely-plausible-at-first-glance spaghetti. I think that well started to dry up before LLMs even hit the scene.
It had happened in Japan. There was on author who were updating 30+ series simultaneously on Kakuyomi, the largest Japanese web novel site. A few of them got top ranked.
Afaik, I think the way people are making money in this space is selling courses that teach you how to sell mass produced AI slop on Amazon, rather than actually doing it
At the end of the day, it doesn't really get you that much if you get 70% of the way there on your initial prompt (which you probably spent some time discussing, thinking through, clarifying requirements on). Paid, deliverable work is expected to involve validation, accountability, security, reliability, etc.
Taking that 70% solution and adding these things is harder than if a human got you 70% there, because the mistakes LLMs make are designed to look right, while being wrong in ways a sane human would never be. This makes their mistakes easy to overlook, requiring more careful line-by-line review in any domain where people are paying you. They also duplicate code and are super verbose, so they produce a ton tech debt -> more tokens for future agents to clog their contexts with.
I like using them, they have real value when used correctly, but I'm skeptical that this value is going to translate to massive real business value in the next few years, especially when you weigh that with the risk and tech debt that comes along with it.
Since I don't code for money any more, my main daily LLM use is for some web searches, especially those where multiple semantic meanings would be difficult specify with a traditional search or even compound logical operators. It's good for this but the answers tend to be too verbose and in ways no reasonably competent human would be. There's a weird mismatch between the raw capability and the need to explicitly prompt "in one sentence" when it would be contextually obvious to a human.
Yep - no doubt that LLMs are useful. I use them every day, for lots of stuff. It's a lot better than Google search was in its prime. Will it translate to massively increased output for the typical engineer esp. senior/staff+)? I don't think it will without a radical change to the architecture. But that is an opinion.
I completely agree, I found it very funny that I have been transitioning from an "LLM sceptic" to a "LLM advocate", without changing my viewpoint. I have long said that LLM's won't be replacing swathes of the workforce any time soon and that LLM's are of course useful for specific tasks, especially prototyping and drafting.
I have gone from being challenged on the first point, to the second. The hype is not what it has been.
"I used AI to write a GPU-only MoE forward and backward pass to supplement the manual implementation in PyTorch that only supported a few specific GPUs" -> https://github.com/lostmsu/grouped_mm_bf16 100% vibe coded.
One of my favorite stories from the dotcom bust is when people, after the bust, said something along the lines of: "Take Pets.com. Who the hell would buy 40lb dogfood bags over the internet? And what business would offer that?? It doesn't make sense at all economically! No wonder they went out of business."
Yet here we are, 20 years later, routinely ordering FURNITURE on the internent and often delivered "free".
My point being, sure, there is a lot of hype around AI but that doesn't mean that there aren't nuggets of very useful projects happening.
There are two major reasons people don't show proof about the impact of agentic coding:
1) The prompts/pipelines portain to proprietary IP that may or may not be allowed to be shown publically.
2) The prompts/pipelines are boring and/or embarrassing and showing them will dispel the myth that agentic coding is this mysterious magical process and open the people up to dunking.
For example in the case of #2, I recently published the prompts I used to create a terminal MIDI mixer (https://github.com/minimaxir/miditui/blob/main/agent_notes/P...) in the interest of transparency, but those prompts correctly indicate that I barely had an idea how MIDI mixing works and in hindsight I was surprised I didn't get harrassed for it. Given the contentious climate, I'm uncertain how often I will be open-sourcing my prompts going forward.
You weren't harassed for it because (1) it is interesting and (2) you were not hiding the AI involvement and passing it off as your own.
The results (for me) are very much hit-and-miss and I still see it as a means of last resort rather than a reliable tool that I know the up and downsides of. There is a pretty good chance you'll be wasting your time and every now and then it really moves the needle. It is examples like yours that actually help to properly place the tool amongst the other options.
I'm fundamentally a hobbyist programmer, so I would have no problem sharing my process.
However, I'm not nearly organized enough to save all my prompts! I've tried to do it a few times for my own reference. The thing is, when I use Claude Code, I do a lot of:
- Going back and revising a part of the conversation and trying again—sometimes reverting the code changes, sometimes not.
- Stopping Claude partway through a change so I can make manual edits before I let Claude continue.
- Jumping between entirely different conversation histories with different context.
And so on. I could meticulously document every action, but it quickly gets in the way of experimentation. It's not entirely different from trying to write down every intermediate change you make in your code editor, between actual VCS commits.
I guess I could record my screen, but (A) I promise you don't actually want to watch me fiddle with Claude for hours and (B) it would make me too self-conscious.
It would be very cool to have a tool that goes through Claude's logs and exports some kind of timeline in a human-readable format, but I would need it to be automated.
---
Also, if you can't tell from the above, my use of Claude is very far from "type a prompt, get a finished program." I do a lot of work in order to get useful output. I happen to really enjoy coding this way, and I've gotten great results, but it's not like I'm entering a prompt and then taking a nap.
1) no one cares if it works. No one cared before how your code looked as long as you are not a known and well used opensource project.
2) there are plenty of services which do not require state or login and can't be hacked. So still plenty of use cases you can explore. But yes i do agree that Security for production live things are still the biggest worry. But lets be honest, if you do not have a real security person on your team, the shit outthere is not secure anyway. Small companies do not know how to build securely.
> 1) no one cares if it works. No one cared before how your code looked as long as you are not a known and well used opensource project.
Forgive me if this is overly blunt, but this is such a novice/junior mindset. There are many real world examples of things that "worked" but absolutely should not have, and when it blows up, can easily take out an entire company. Unprotected/unrestricted firebase keys living in the client are all the rage right now, yea they "work"until someone notices "hey, I technically have read/write god mode access to their entire prod DB", and then all of a sudden it definitely doesn't work and you've possibly opened yourself to a huge array of legal problems.
The more regulated the industry and the more sensitive the business data, the worse this is exacerbated. Even worse if you're completely oblivious to the possibility of these kinds of things.
> Forgive me if this is overly blunt, but this is such a novice/junior mindset.
Unfortunately the reality is there are far more applications written (not just today but for many years now) by developer teams that will include a dozen dependencies with zero code review because feature XYZ will get done in a few days instead of a few weeks.
And yes, that often comes back to bite the team (mostly in terms of maintenance burden down the road, leading to another full rebuild), but it usually doesn't affect the programmers who are making the decisions, or the project managers who ship the first version.
You seem to think I'm an AI coding hater or something. I'm not. I think these tools are incredibly useful and I use them daily. However, like described in the article, I do am skeptical about stories where AI writes whole applications, SaaS or game engines in a few hours and everything "just works". That is not my experience.
The Cloudflare OAuth lib is impressive, I will readily admit that. But they also clearly mention that of course everything was carefully reviewed, and that not everything was perfect but that the AI was mostly able to fix things when told to. This was surely still a lot of work, which makes this story also much more realistic in my opinion. It surely greatly sped up the process of writing an OAuth library - how much exactly is however hard to say. Especially in security-relevant code, the review process is often longer than the actual writing of the code.
I don't know why you're giving me two paragraphs of response. I'm not psychoanalyzing you. I had a simple suggestion: if agent code output is so bad nobody runs it because it would get people owned, go own up the code Kenton generated.
> The prompts/pipelines are boring and/or embarrassing and showing them will dispel the myth that agentic coding is this mysterious magical process
You nailed it. Prompting is dull and self evident. Sure, you need basic skills to formulate a request. But it’s not a science and has nothing to do with engineering.
Could you clarify that last paragraph for me? I’m not sure what ”contentious climate” is here. AI antihype? I don’t understand the connection to not being harassed for something, isn’t that a good thing rather than something that would make you uncertain if you want to share prompts in the future?
"AI tech bro creates slop X because they don't understand how X actually works" is a common trope among the anti-AI crowd even on Hacker News that has only been increasing in recent months, and sharing prompts/pipelines provides strong evidence that can be pointed at for dunks. Sharing AI workflows is more likely to illicit this snark if the project breaks out of the AI bubble, though in the case of the AI boosters on X described as in the HN submission that's a feature due to how monetization works that platform. It's not something I want to encourage for my own projects, though.
There's also the lessons on the recent shitstorms in the gaming industry, with Sandfall about Expedition 33's use of GenAI and Larian's comments on GenAI with concept art, where both received massive backlash because they were transparent in interviews about how GenAI was (inconsequentially) used. The most likely consequence of those incidents is that game developers are less likely on their development pipelines.
You'd think so, but with the recent extreme polarization of GenAI the common argument among the anti-AI crowd is the absolute "if AI touched it, it's slop". For example in the Expedition 33 case (which won Game of the Year), even though the GenAI asset was clearly a placeholder and replaced 2 days after launch, a surprisingly large number of players said sincerely "I enjoyed my time with E33 but after finding out they used GenAI I no longer enjoy it."
In a lesser example, a week ago a Rust developer on Bluesky tried to set up a "Tainted Slopware" list of OSS which used AI, but the criteria for inclusion was as simple as "they accepted an AI-generated PR" and "the software can set up a MCP server." It received some traction but eventually imploded, partially due to the fact that the Linux kernel would be considered slopware due to that criteria.
Sure, but I'm gonna push back and go "so what"? That sort of thing is what haters do, especially in the notoriously toxic world of gaming.
"Some people expressed disappointment about a thing I think is silly" is literally the center square on the gamer outrage bingo card lol. Same with "someone made a list that I think is kind of stupid".
And again, so what? Why should you care? Again, if you feel that insecure about it, it's you and your work that's the problem, not the haters who are always going to exist. Have the courage of your own convictions or maybe admit that it isn't that strong of a conviction lol.
My dude, that's not "victim blaming" lol. Nobody's forcing you, personally, to do anything. I don't care if you, personally, publish your work or not.
What I'm saying is that _feeling_ of insecurity doesn't come from haters, because haters gonna hate, it's a sign that _your_ work might not be as good as you think it is, and you don't feel that you can stand behind it.
Also, managing public expectations and messaging is a thing professionals in many industries do all the time. It's not even particularly difficult, you just hear about it when it's bungled.
EDIT: To clarify, as a SWE, my work is available to anyone at the company. Any engineer I work can see what I've done, and the public sees it too, they just don't know about it, because if I screw up, the company will take the blame for it. You get very very very very used to critique in this role and taking responsibility for what you make and making the case for your technical solution.
you can use however you like, no one cares. really, no one.
but, people in general are NOT inclined to pay for AI slop. that is the controversy.
why would I waste my time reading garbage words generated by an LLM? If people wanted this, they would go to the llm themselves.
the whole point of artistic expression is to present oneself, to share a perspective. llms do not have a singular point of view, they do not have a perspective, they do not have an cohesive aggregate of experiences. they just regurgitate the average form.
no one is interested in this. even when distributed for free, is disrespectful to others that put their time until they realized is just hot garbage yet again.
people are getting tired of low effort `content`, yet again another unity or unreal engine resking, asset flipping `game`...
you get the idea, lots of people will feel offended and disrespected when presented with no effort. got it? it is not exclusively about intellectual property theft also, i don't care about it, i just hate slop.
now whether you like it or not, the new meta is to not look professional. the more personal, the better.
AI is cool for a lot of things, searching, learning, natural language apropos, profiling, surveilling, compressing information...it is fantastic technology!
not a replacement for art, never will be.
Did you post them with commentary along the lines of "this is the second coming of $DEITY, AI will replace us all, click on this Claude referral link to sign up"?
No, don't think so.
However, 90% of "AI" articles either are full of bullshit about "AI" or are someone trying to pass as an "expert" in some domains with LLM generated bullshit.
Doesn't the existence of consumer products like ChatGPT indicate that LLMs aren't able to do human-level work? If OpenAI really had a digital workforce with the capabilities of ~100k programmers/scientists/writers/lawyers/doctors etc, wouldn't the most profitable move be to utilize those "workers" directly, rather that renting out their skills piecemeal?
If this stuff worked, then given that Microsoft has a huge share of it, shouldn't Microsoft's products be good? Or at least getting better. I use Bing most days [1], and it's consistently an absolute joke.
[1] to farm reward points to get cosmetic items in video games
That depends on what the real value is. The sure way to get rich selling pickaxes to gold miners. However you would be even richer if you figured out where the gold really was and mined in that exact location.'
To be more exact, the fact that everyone sells access to models they are continually "improving" is proof that any statement from the LLM peddlers about AGI is a lie.
LLMs are able to do human-level work. I think surely now that is unquestionable? They can't do all human-level work, in the same way that not all humans can do all human-level work, but a lot of criticism implicitly benchmarks it against all work. LLMs have this remarkable ability to be both the smartest thing in the room and the dumbest thing at the same time.
On the profitability point. Yes and no I guess. ChatGPT will likely go down as the most influential thing in the ai race (or early ai race) simply because it was the most visceral illustration of the art of the possible to the general public.
Technical people will correct me or have arguments to why this isn't the case but they'll be wrong simply because ChatGPT captured consumer attention, which ultimately led to supercharged financial attention, and everything that has happened since is due to that. Whether its pure marketing or futuregazing, the world of money bought into it, with the ultimate view that this is the worst it will ever be.
The ultimate profitable goal is unarguably replacing human labour (at a lesser all in cost) but if that is not possible, but you believe it could be possible, then showcasing and getting people to believe that you can achieve that goal, is pretty damn profitable too and it's proven to be for some people while giving them runway to continue to pursue the ultimate goal.
What we really need is an updated Turing test: "can a project manager tell the difference between a junior dev working remotely vs Claude Code hooked up to a Slack account?"
It's been a long time since I thought of the Segway, which exemplifies one possible trajectory: Recognizable to all, everyone interested in trying one out, but still fell short of the investor dream of replacing the car and changing urban travel forever.
Sure but my point isn't that ChatGPT will be dominant, it has already changed the world. Even if Openai fell over tomorrow, that doesnt change that it was the step change from a public consciousness in the potential of LLMs. And LLMs aren't falling by the wayside anytime soon
You know, there's a number of different competing propaganda battles going on:
1) There's the people and companies that stand to make money and build up companies by convincing people to buy their ai projects, hyping up ai, etc.
2) There's companies and nation states trying to destroy competitor's / other country's ai efforts, turn citizens against them, in order to gain an advantage/lead in the race.
3) There's, conversely, nation states that want to boost up and promote their ai industry in order to win the race rather than other countries winning (assuming there's a "win" at the end, like AGI, which I don't believe there is).
4) Normal citizens that have been ideologically brainwashed one way or the other, and so are going online to argue in a culture war for their beliefs / "side".
5) People posting crazy takes on ai, one way or the other, to get clicks / money on their articles.
The whole topic is awash in serious propaganda. Effectively the only path forward is believing what you yourself know for sure, from your direct experience / knowledge.
Fully featured LSP (take a look at the GIFs in the repo), step debugger, BDD-testing framework built into the language and runtime itself (novel!), asynchronous/join in pipelines (novel!), middleware for postgres, jq, javascript, lua, graphql (with data loaders), etc. It does quite a bit. Take a look at my GitHub timeline for an idea of how long this took to build.
It is 100% an experiment in language and framework design. Why would I otherwise spend years of my life handcrafting something where I just want to see how my harebrained ideas play out when actualized?
I would absolutely love to talk about the language itself rather than how it was made but here we are.
And I wrote my own blog in my own DSL. Tell me that's not just good old fashioned fun.
I saw this DSL on HN yesterday, and this syntax is total garbage. It’s some stupid mixture of different PLs. Are you seriously OK with this so that you keep posting it here? I don’t even want to look through source code knowing what garbage it is at the surface level.
describe "hello, world"
it "calls the route"
let world = "world"
when calling GET /hello/{{world}}
then status is 200
and selector `p` text equals "hello, {{world}}"
What don't you like about it? I think it's interesting
> Why would I otherwise spend years of my life handcrafting something where I just want to see how my harebrained ideas play out when actualized?
If you're sure that's all you wanted out of it. If this were more a path-vs-destination kind of project for you, you might have gotten deep insights about programming language design and implementation over those years which the efficient route deprives you of.
I did miss the sarcasm you pointed out in the separate mail to me (I should have paid more attention to the word "otherwise", I guess). I did not mean to lecture at you at all. I thought it was something you built very quickly with LLMs, but clearly this was a passion project, whether or not you used LLMs.
It's OK, I was being overly sensitive based on the other comment in this thread. In fact, I do value the journey over the destination and it is helpful to be reminded of this. I've updated the project's README to make this explicit!
I’ve taken to calling this (in my mind) the Age of the Sycophants. In politics, in corporate life, in technology and in social media, many people are building a public life around saying things that others want to hear, with demonstrably zero relationship to truth or even credibility.
It would certainly make an interesting anthropological case study.
Humans have always been performative with those outside of their immediate social circle. Politics is effectively the art of performance, and using it to gain influence and power. With legacy media the general public was still largely on the receiving end of it, but modern technology and social media have given that ability to anyone capable of building an audience. So now performative behavior is everywhere, since we're all competing to get our voice heard, to experience adoration, fame, power, fortune. We're in this weird state where this is all done in digital worlds, where it's easier than ever to fabricate an image, and yet it all ends up affecting the real world in one way or another. Our leaders are celebrities who are good at this game, and not necessarily people worthy of this position.
Honestly, I have little faith we can turn this around. It's going to get much worse before it gets better, if at all.
In the White House, you have to say what Trump wants to hear. If you are a foreign leader, you have to say you’ll share your peace prize with him, because that’s what he wants to hear. TACO is a thing because he wants to say things, but not do things.
In tech, you have to say you’re bullish on AI, because that’s what managers want to hear. They say it their CEO, because that’s what CEO wants to hear. And the CEO says it to the public because that’s what Wall Street wants to hear.
Turn around and ask ChatGPT a question and it tells you what you want to hear, along with a compliment about how smart you are.
I think this
"* The software is pretty specific to my requirements."
is the biggest part for me. I built something with Antigravity over the holidays that I can use for myself and it solves my use case.
I tried thinking about if this can be helpful for others and pushed it a bit further into a version that could be hosted. Which does not make that much sense because it is a computationally intense numerical solver for thermal bridges and just awfully slow on a free hosted platform.
But the project was a couple of evenings and would otherwise haven taken me half a year to complete (and thus never been done).
> Antigravity did the vast amount of work, it feels unworthy
I think this is true for me as well. I have two types of projects that I’ve been working on - small ones with a mix of code I wrote and AI. I have posted these, as I spent a lot of time guiding the AI, cleaning up the AI’s output, and I think the overall project has value that others can learn from and built on.
But I also have some that are almost 100% vibe-coded. First, those would take a lot of time to clean up and write documentation for to make them publishable/useful.
But also, I do think they feel “unworthy”. Even though I think they can be helpful, and I was looking for open-source versions of those things. But how valuable can it really be if I was able to vibe-code it in a few prompts? The next person looking for it will probably do the same thing I did and vibe-code their own version after a few minutes.
This is a strage phenomenon where people get excited by the mere fact that someone else is excited by something which is not directly visible to the spectator. It works well in horror movies and as it seems with AI hype.
Being respected inside big companies has little to do with engagement on social media. Most of the best engineers are working hands-down. Arguably shitposting on the internet may have a negative correlation with technical ability inside Google.
One of the times I think the draconian approach Apple has towards employee speaking as an associate of the firm without explicit authorization is the correct one.
LLMs are amazing and I do seriously wonder if the singularity could happen in my lifetime ... but there definitely are people over-hyping present capabilities too much right now. If present models were fully human-level proper-extended-Turing-test-passing AGI, then the results on the economy and the software ecosystem would be as immediately obvious and world-changing as a comet impact.
I don't think Rakyll or Andrej are claiming these things; I think they're assuming their readers share more context with them and that it's not necessary to re-tread that every time they post about their surprise at AI currently being better than they expected. I've had the experience multiple times now of reading posts from people like them, nodding along, and then reading breathless quote-tweets of those very same posts exclaiming about how it means that AGI is here right now.
If you don't get the results you don't get the results. If someone else can use this tool to get the results, they'll out-compete you. If they can't, then they've wasted time and you'll out-compete them. I see these influencer guys as idea-generators. It's super-cheap to test out some of these theories: e.g. how well Claude can do 3D modeling was an idea I wanted to test and I did and it's pretty good; I wanted to test Claude as a debugging aid and it's a huge help for me.
But I would never sit down to convince a person who is not a friend. If someone wanted me to do that, I'd expect to charge them for it. So the guys who are doing it for free are either peddling bullshit or they have some other unspecified objective and no one likes that.
Yes! And like … “out-compete” assumes a zero sum game. There are massive industries where the tools used to serve different market segments only barely overlap decades after the “game changing” tool was made available.
Like, screw the whole “artisanal small-batch software” argument—there are massive new systems being written in C every day despite decades of claims that it is an obsolete language doomed to be replaced by better alternatives. Those alternatives caught on in some segments and not in others. Electric cars caught on in some segments and not in others. Steel-and-concrete building construction caught on in some segments and not in others. It’ll be fine.
Anecdotally, I’m finding that, at least in the Spark ecosystem, AI-generated ideas and code are far from optimal. Some of this comes from misinterpreting the (sometimes poor) documentation, and some of it comes from, probably, there not being as many open source examples as CRUD apps, which AI “influentists” (to borrow from TFA) appear to often be hyping up.
This matters a lot to us because the difference in performance of our workflows can be the difference in $10/day in costs and $1000/day in costs.
Just like TFA stresses, it’s the expertise in the team that pushes back against poor AI-generated ideas and code that is keeping our business within reach of cash flow positive. ~”Surely this isn’t the right way to do this?”
Let's not put humans on too much of a pedestal, there are plenty of us who are not that reliable either. That's why we have tests, linting, types and various other validation systems. Incidentally, LLMs can utilize these as well.
Humans are unreliable in predictable ways. This makes review relatively painless since you know what to look for, and you can skim through the boilerplate and be pretty confident that it's right and isn't redundant/insecure, etc.
LLMs can use linters and type checkers, but getting past them often times leads it down a path of mayhem and destruction, doing pretty dumb things to get them to pass.
I never read the tweet as anything other than that an expert with deep knowledge of their domain was able to produce a PoC. Which I still find to be very exciting and worthy of being promoted. This article didn't really debunk much.
these are the kinds of people that can use generative AI best IMO. Deep domain knowledge is needed to spot when the model output is wrong even though it sounds 100% correct. I've seen people take a model's output as correct to a shocking degree like placing large bets at a horse track after uploading a pic of the schedule to ChatGPT. Many people believe whatever a computer tells them but, in their defense, no one has had to question a large calculation done by a calculator until now.
Totally agree. The more you know about software development the better you can use the tools. A noob trying to write a kernel driver would quickly hit a brick wall and give up. It's kind of self correcting.
Writing code is the easiest thing to do at Google. Getting past layers of hierarchy and nailing down what the code will actually do and who gets credit for it will take years for a major project.
Perhaps nobody wants to have the uncomfortable conversation that AI is making the competent more competent and the incompetent less competent, because it would imply that AI provides brutally unequal benefits. The AI haters don't want this discussion because it would imply AI has any benefits, and the AI lovers don't want to have this discussion because it would imply the benefits of AI aren't universal and will increase inequality.
I want to see an example of this. Any real example. So far what I’ve seen, I wouldn’t give my name to any of those barely usable code, and most of the time they were even slower, especially when they pretended that they reviewed their code. And even with reviews they happily accepted bad code. This was true even with my friends, not just random examples on the internet.
I still need to understand every single line of the code to be responsible for it, and that takes the majority of time anyway, and quite often I need to rewrite most of it, because average code is not particularly good, because most code wasn’t produced by senior professionals, but random people making a random python script with only Hello World under their belt. So at the end doesn’t really matter whether I copy paste from a source, or an LLM does the same.
I understand that many coder are happy with the “John made his first script in his life” level of code, but I’m paid well because I can do better, way better. Especially because I need to be responsible for my code, because the companies to whom I work are forced to be responsible.
But of course, when there is no responsibility, I don’t care either. For those home projects where there is exactly zero risks. Even big names seem to use these only to those kind of projects. When they don’t really care.
I'll start by saying that in my past life I was a PM, and from that angle I can very much see how people writing code for large-scale, production systems take real issue with the quality of what LLMs produce.
But these days I run a one-man business, and LLMs (currently Claude Code, previously GPT) have written me a ton of great code. To be clear, when I say "great" I don't mean up to your standards of code quality; rather, I mean that it does what I need it to do and saves me a bunch of time.
I've got a great internal dashboard that pulls in data from a few places, and right now CC is adding some functionality to a script that does my end of month financial spreadsheet update. I have a script that filters inbound leads (I buy e-commerce brands, generally from marketplaces that send me an inordinate amount of emails that I previously had to wade through myself in order to find the rare gem). On the non-code front, I have a very long prompt that basically does the first pass of analysis of prospective acquisitions, and I use Shortcut.ai to clean up some of the P&Ls I get (I buy small e-commerce brands, so the finances are frequently bad).
So while I can't speak to using LLMs to write code if you're working in any sort of real SaaS business, I can definitely say that there's real, valid code to be had from these things for other uses.
One of my friends did a job for a government. He generated the code for it with some LLM. It provided a result which was about what he thought should be. He - or anybody - never checked the code whether it really calculated what it should have. “It did what [he] needed it to do”. Now the said government started to make decisions based on a result which proved by nobody. In other words, lottery.
What you mentioned doesn’t mean anything until there is no hard proof that it really works. I understand that it seems to you that it works, but I’ve seen enough to know that that means absolutely nothing.
Thanks, I can relate to the parent poster, and this is a really profound comment for me. I appreciate the way you framed this. I’ve felt compelled to fact check my own LLM outputs but I can’t possibly keep up with the quantity. And it’s tempting (but seems irrational) to hand the results to a different LLM. My struggle is remembering there needs to be input/query/calculation/logic validation (without getting distracted by all the other shiny new tokens in the result)
"Not only were the colours and patterns unusually fine, but the clothes that were made of the stuffs had the peculiar quality of becoming invisible to every person who was not fit for the office he held, or if he was impossibly dull."
The article nails the pattern but I think it's fundamnetally an incentives problem.
We're drowning in tweets, posts, news... (way more than anyone can reasonably consume). So what rises to the top? The most dramatic, attention-grabbing claims. "I built in 1 hour what took a team months" gets 10k retweets. "I used AI to speed up a well-scoped prototype after weeks of architectural thinking" gets...crickets
Social platforms are optimized for engagement, not accuracy. The clarification thread will always get a fraction of the reach of the original hype. And the people posting know this.
The frustrating part is there's no easy fix. Calling it out (like this article does) get almost no attention. And the nuanced followup never catches up with the viral tweet.
Good article. "hype first and context later". Loads of online content has become highly sentational. I notice this on Youtube (especially thumnails and titles) Seems to be a trend. I wonder if -- collectively -- we'll develop a "shield" for this: (more critical thinking?)
Its a strange phenomenon. You want to call out the bs but then you are just giving them engagement and boost. You want to stay away but there is a sort of confluence where these guys tend to ride on each others' post and boosts those posts anyway. If you ask questions, very rarely they answer, and if they do, it takes one question to unearth that it was the prompt or the skill. Eg: huggingface people post about claude finetuning models. how? when they gave everything in a skill file, and claude knew what scripts to write. Tinker is trying the same strategy. (yes, its impressive that claude could finetune, but not as impressive as the original claim that made me pay attention to the post)
It does not matter if they get the details wrong, its just that it needs to be vague enough, and exciting enough. Infact vagueness and not sharing the code part signals they are doing something important or they are 'in the know' which they cannot share. The incentives are totally inverted.
Great post! Indeed, it s deeply disappointing to see how both the tech industry and scientific community have fallen into the same attention-seeking trap: hyping their work with vague, sensational claims, only to later "clarify" with far more grounded—and often mundane—statements.
This tactic mirrors the strategies of tabloids, demagogues, and social media’s for-profit engagement playbook (think Zuckerberg, Musk, and the like). It’s a race to the bottom, eroding public trust and undermining the foundations of our society - all for short-term personal gain.
What’s even more disheartening is how this dynamic rewards self-promotion over substance. Today’s "experts" are often those who excel at marketing themselves, while the most knowledgeable and honest voices remain in the shadows. Their "flaw"? Refusing to sacrifice integrity for attention.
Almost every aspect of public life on social media nowadays is guided by sensationalism. It's simply a numbers game, and the "number" is engagement. Why would you do anything that's not completely geared towards engagement?
The original post by Jaana made 8.4 million impressions, while the follow-up that included the previously/deliberately omitted context and some important information, such as "what I built is a toy version", has 277K impressions as of right now.
I respect Jaana and have been following her for years. I'd expect she ought to know how that claim would have been understood. But I guess that's the only way to go viral nowadays.
Also, this incident goes to show how the self-proclaimed AI influencer, Rohan Paul, puts a lot of thought and importance into sharing "news" about AI. As if it were not enough to share Jaana's bold claim without hesitation, he also emphasized it with an illustrious commentary: "Dario Amodei was so right about AI taking over coding."
Like everything in LLM land it's all about the prompt and agent pipeline. As others say below, these people are experts in their domain. Their prompts are essentially a form of codifying their own knowledge, as in Rakyll and Galen's examples, to achieve specific outcomes based on years and maybe even decades of work in the problem domain. It's no surprise their outputs when ingested by an LLM are useful, but it might not tell us much about the true native capability of a given AI system.
Off topic, but AI hype is appearing in hardware and consumer electronics. I just bought a rechargeable hand warmer that claims to have an "... Have Intelligent AI Temperature Control Chips That Can Accurately Control the Temperature,"
At least in the early days the Transistor, radios did have them.
Influentists: LLM or get left behind! Also Influentists: surprisingly, not suggesting some friendly bioterrorism for the upper hand... or is this the real motivation for RTO? I wouldn't know.
Anyway, I'll worry when the dead weight disappears and ceases to be replaced. Shields and energy reserves are critical, etc.
This is very well said - it is much nicer and more professional than the sentiments I could express on the matter.
The age of niche tech microcelebrities is on us. It existed a bit in the past (ESR, Uncle Bob, etc), but is much more of a thing now. Some of them make great content and don't say ridiculous things. Others not so much.
AI is like flossing. You waste more time listening to other people's opinions on whether it's helpful, than just trying it out yourself for a few days.
I'm still waiting for all these remarkable achievements produced with this new technology to provide tangible value to the world. Surely we should be seeing groundbreaking products and innovations in all industries by now, improving the lives of millions of people.
Instead all we get is anecdata from influencers and entrepreneurs, and the technology being shoved into every brand and product. It's exhausting.
At least it seems that the tide is starting to turn. Perhaps we are at the downward slope of the Peak of Inflated Expectations.
It's quite likely that the answer to the worlds problems isn't more apps/products. AI may have arrived at a moment to bring the cost down of creating software there isn't much demand for in the first place.
Sure, that's one part of it, but this technology is also used by highly intelligent people in tech and other industries, some of whom are singing its praises. I would expect to see amazing products and innovations from them, and yet progress has largely maintained the same momentum. Am I expecting too much, too soon?
A recent favorite of mine is simonw who usually is unable to stop hyping LLMs suddenly forgetting they exist in order to rhetorically "win" an argument:
> If you're confident that you know how to securely configure and use Wireguard across multiple devices then great
Great article. This needs to be framed. The whole trust me bro, and shock and awe of social medias is a non-stop assault these days. You can't open a wall without seeing those promoted up front and centre and without any proof.
If AI was so good today, why isn't there an explosion of successful products? All we see is these half baked "zomg so good bro!" examples that are technically impressive, but decisively incomplete or really, proof of concepts.
I'm not saying LLMs aren't useful, but they're currently completely misrepresented.
Hype sells clicks, not value. But, whatever floats the investors' boat...
Thank you for calling this out, we are being gaslit by attention seeking influencers. The algorithmic brAInrot is propagated by those we thought we can trust, just like the instagram and youtube stars we cared about who turned out to be monsters. I sincerely hope those people become better or wane into meaninglessness. Rakyll seems to spend more time on X than working on advancing good software these days, a shame given her past accomplishments.
Idk man, all AI discussion feels like a waste of effort.
“yes it will”, “no it won’t” - nobody really knows, it's just a bunch of extremely opinionated people rehashing the same tired arguments across 800 comments per thread.
There’s no point in talking about it anymore, just wait to see how it all turns out.
The cool thing is you can just try it. The barrier to entry is incredibly low right now. If it works for you, great. If it doesn't work for you, great. At least you know.
That's the real reason the conversation seems pointless. Every thread is full of comments from one group saying how useful AI is, and from another group saying how useless it is. The first group is convinced the second group just hasn't figured out how to use it right, and the second group is convinced the first group is deluded or outright lying.
Yes, I'm in the second group and I have that conviction about the first group based on personal experience with LLMs.
But most hype is not delusion. It's people trying to present themselves as "AI" experts in order to land those well paid "AI" positions. I don't think they even believe what they're saying.
It's not "yes it is" vs "no it won't" though. The discussion is "Yes it does" vs "no it doesn't" (present tense.) There's nothing wrong with guessing about the future, but lying about a present that is testable and unwillingness to submit to the testing is wrong.
Even then nothing is learned. Every HN thread there is on AI coding: "I am using $model for writing software and its great." "I am using $model for writing software and it sucks and will never do it." 800 comments of that tit for tat in present tense. Still nothing learned.
Doesn't help that no one talks about exactly what they are doing and exactly how they are doing it, because capitalism vs open technology discussions meant to uplift the species.
> Doesn't help that no one talks about exactly what they are doing and exactly how they are doing it
Let me try a translation:
> I am using $model for writing software and its great.
I have generated an extremely simple javascript application that could have been mostly done by copy/paste from StackOverflow or even Geeks4Geeks and it runs.
This is true. I have a PWA that I generated with a LLM on my phone right now. It works. Pretty sure even w3schools would be ashamed to post that code.
> I am using $model for writing software and it sucks and will never do it.
This is also true. At work I have a 15 year old codebase where everything is custom.
You can't get a LLM to use it all as a context because you simply don't have ram for it so you can't even test the quality of advice given on it.
You can't train a LLM on it because you don't have the budget for it.
You maybe could get a LLM to generate code by prompting it "this is the custom object allocation function, these are the basic GUI classes, now generate me the boilerplate for this new dialog I'm supposed to do". Unfortunately it takes as long or longer than doing it yourself, and you can't trust the output to boot.
There is proof that AI isn't what they all make it to be, in the acquisitions of these companies. Why would Anthropic need Bun or OpenAI need windsurf for billions, if agents are all knowing and ready to replace devs?
This is a modern marketing, based on FUD and sensationalism
Its still not a Hype, its still crazy what is possible today and we still have no clear at all if this progress continues as it does or not with the implication, that if it continues, it has major implications.
My wife, who has no clue about coding at all, chatgpted a very basic android app only with guidance of chatgpt. She would never ever been able to do this in 5 hours or so without my guidance. I DID NOT HELP HER at all.
I'm 'vibecoding' stuff small stuff for sure, non critical things for sure but lets be honest, i'm transforming a handfull of sentences and requirements into real working code, today.
Gemini 3 and Claude Opus 4.5 def feel better than their prevous versions.
Do they still fail? Yeah for sure but thats not the point.
The industry continues to progress on every single aspect of this: Tooling like claude CLI, Gemini CLI, Intellij integration, etc., Context length, compute, inferencing time, quality, depth of thinking etc. there is no current plateau visible at all.
And its not just LLMs, its the whole ecosystem of Machine Learning stuff: Highhly efficient weather model from google, Alpha fold, AlphaZero, Roboticsmovement, Environment detection, Image segmentation, ...
And the power of claude for example, you will only get with learning how to use it. Like telling it your coding style, your expectations regarding tests etc. We often assume, that an LLM should just be the magic work collegue 10x programmer but its everything an dnothing. If you don't communicate well enough it is not helpful.
And LLMs are not just good in coding, its great in reformulating emails, analysing error messages, writing basic SVG files, explaining kubernetes cluster status, being a friend for some people (see character.ai), explaining research paper, finding research, summarizing text, the list is way to long.
Alone 2026 there will go so many new datacenters live which will add so much more compute again, that the research will continue to be faster and more efficient.
There is also no current bubble to burst, Google fights against Microsoft, Antrophic and co. while on a global level USA competets with China and the EU on this technology. The richest companies on the planet are investing in this tech and they did not do this with bitcoins because they understod that bitcoin is stupid. But AI is not stupid.
Or Machine learing is not stupid.
Do not underestimate the current status of AI tools we have, do not underestimate the speed, continues progress and potential exponential growth of this.
My timespan expecation for obvious advancments in AI is 5-15 years. Experts in this field predict already 2027/2030.
But to iterate over this: a few years ago no one would have had a good idea how we could transform basic text into complex code in such a robust way, which such diverse input (different language, missing specs, ...) . No one. Even 'just generating a website'.
> My wife, who has no clue about coding at all, chatgpted a very basic android app only with guidance of chatgpt. She would never ever been able to do this in 5 hours or so without my guidance. I DID NOT HELP HER at all.
I know what app builders are but she talked to a computer system, told it what she wanted and it WALKED HER through all the steps and i think she used android studio.
She did all of this in a few hours and doesn't work with computers.
Literally all much of the business world needed was a slightly more capable VB but now we have a bunch of crappy, web browser based SaaS platforms instead.
I think it really depends how a person judges the progress from chatgpt 3.5, 3 years ago to Opus 4.5.
In one light it is super impressive and amazing progress, in another light it is not impressive at all and totally over hyped.
Using the Hubert Dreyfus analogy. It is impressive if the goal is to climb as high as we can up giant tree. The height we have reached isn't impressive at all though if we are trying to climb the tree to get to the moon.
Even if we assume for a moment everything you are saying is true and/or reasonable, can't you see how comments like these paint your position here in a bad light? It just reads a little desperate!
It might be just different viewpoints people don't understand?
I'm advocating for spending time with AI because it works already good enough and it continues to progress surprisingly fast. Unexperienced fast for me tbh.
If i say "AI is great" i also know when AI is also stupid but i'm already/stil so impressed that i can transform basic text into working go/java whatever code, that i accept that its not perfect just because I highly appreciate how fast we got this.
And it feels weird too tbh. It doesn't feel special to talk to an LLM and get code back somehow while this was unthinkable just a few years back.
Somethimes it likes you just forget about all these facts and have to remind yourself that this is something new.
Just because it’s “new” doesn’t mean it’s going to fulfill all our wildest fantasies. It’s becoming clear that these things are just… tools. Useful in certain situations, but ultimately not the game-changer they’re sold as.
For me its getting clear that there is so much broad ways of continues improvement, and constant speed, that if this continues like this, even a basic LLM can do a lot of jobs.
Just today cursor released a blog were they run an agent for a week and it build a browser.
Claude Code with subagents and hooks are really good too.
And it takes time to just get it and roll it out to everyone, it takes time to do research, experiments, it takes time to install GPUs and make them etc.
We are currently only limited by things we can progress on.
My anxiety about falling behind with AI plummeted after I realized many of these tweets are overblown in this way. I use AI every day, how is everyone getting more spectacular results than me? Turns out: they exaggerate.
Here are several real stories I dug into:
"My brick-and-mortar business wouldn't even exist without AI" --> meant they used Claude to help them search for lawyers in their local area and summarize permits they needed
"I'm now doing the work of 10 product managers" --> actually meant they create draft PRD's. Did not mention firing 10 PMs
"I launched an entire product line this weekend" --> meant they created a website with a sign up, and it shows them a single javascript page, no customers
"I wrote a novel while I made coffee this morning" --> used a ChatGPT agent to make a messy mediocre PDF
Getting viral on X is the current replacement for selling courses for {daytrading,amazon FBA,crypto}.
The content of the tweets isn't the thing.. bull-posting or invoking Cunningham's Law is. X is the destination for formula posting and some of those blue checkmarks are getting "reach" rev share kickbacks.
Same with Linkedin. Ive seen a lot of posts telling u to comment something to get a secret guide on how to do Y.
If it was successful, they wouldnt be telling everyone about it
Yeah, if you get enough impressions, you get some revenue, so you don't need to sell any courses, just viral content. Which is why some (not ALL) exaggerate as suggested.
It's a bit insane how much reach you need before you'd earn anything impactful, though.
I average 1-2M impressions/month, and have some video clips on X/Twitter that have gotten 100K+ views, and average earnings of around $42/month (over the past year).
I imagine you'd need hundreds of millions of impressions/views on Twitter to earn a living with their current rates.
Thanks a lot for your transparency Jeff! Much needed in this area. And your content is quality, much unlike what else being discussed here.
It is really hard to actually make anything substantial on social media exposure. Unfortunately this does not stop many from exaggerating claims in order to (maybe become) be internet famous, or seeing high number of clicks etc. So it is both bad business for creators, and poisoning the discourse for readers - the only real winners are the social media companies and the product companies that get hyped up.
> Unfortunately this does not stop many from exaggerating claims in order to (maybe become) be internet famous
I've been thinking about this a lot lately in another context -- vira priests being anti-vax and realized it's the other way around: their motivation doesn't matter, but the viewers don't want to see moderate content, they want to see highly polarized and controversial topics.
The same with the claims about AI. Nobody wants to hear AI boosts productivity in nuanced way, people either want to hear about 10X or -10X so the market dictates the content/meme.
I'm not as familiar with your content but how often do you post? I have a friend who posts 'meme' type of content (all original) and he makes a decent amount, but he has it all queued up.
The worst is Reddit these days.
I pretty much never even went there for technical topics at all, just funny memes and such, but one day recently I started seeing crazy AI hype stories getting posted, and sadly I made a huge mistake and I clicked on one once, and now it’s all I get.
Endless posts from subs like r/agi, r/singularity, as well as the various product specific subs (for Claude, OpenAI, etc). These aren’t even links to external articles, these are supposedly personal accounts of someone being blown away by what the latest release of this or that model or tool can do. Every single one of these posts boils down to some irritating “game over for software engineers” hype fest, sometimes with skeptical comments calling out the clearly AI-generated text and overblown claims, sometimes not. Usually comments pointing out flaws in whatever’s being hyped are just dismissed with a hand wave about how the flaw may have been true at one time, but the latest and greatest version has no such flaws and is truly miraculous, even if it’s just a minor update for that week. It’s always the same pattern.
There’s clearly a lot of astroturfing going on.
> There’s clearly a lot of astroturfing going on.
Yeah I think so too. I even see it here on HN
I'm just tuning it all out. The big test is just installing the damn thing and seeing what it can do. There's 0 barrier to trying it
Lo and behold, here’s a concrete example I stumbled across just a few seconds after opening Reddit again (really gotta stop doing that):
https://www.reddit.com/r/codex/s/Y52yB6Fg3A
Completely in the same boat as you, the constant bombardment on Reddit is getting really detrimental to my wellbeing at this point lol
>There’s clearly a lot of astroturfing going on.
Reddit is like 90% astroturfing, trolls, and bots.
[dead]
I actually read through the logs and the code in the rare instances someone actually posts their prompts and the generated output. If I'm being overly cynical about the tech, I want to know.
The last one I did it on was breathlessly touted as "I used [LLM] to do some advanced digital forensics!"
Dawg. The LLM grepped for a single keyword you gave it and then faffed about putting it into json several times before throwing it away and generating some markdown instead. When you told it the result was bad, it grepped for a second word and did the process again.
It looks impressive with all these json files and bash scripts flying by, but what it actually did was turn a single word grep into blog post markdown and you still had to help it.
Some of you have never been on enterprise software sales calls and it shows.
> Some of you have never been on enterprise software sales calls and it shows.
Hah—I'm struggling to decide whether everyone experiencing it would be a good thing in terms of inoculating people's minds, or a terrible thing in terms of what it says about a society where it happens.
“I used AI to make a super profitable stock trading bot” —-> using fake money with historical data
“I used AI to make an entire NES emulator in an afternoon!” —-> a project that has been done hundreds of times and posted all over github with plenty of references
> “I used AI to make a super profitable stock trading bot” —-> using fake money with historical data
Stocks are another matter. There were wonder "algorithms" even before "AI". I helped some friends tweak some. They had the enthusiasm and I had the programming expertise and I was curious.
That was a couple years ago. None of them is rich and retired now - which was what the test runs were showing - and I think most aren't even trading any more.
I vibe coded a few ideas i had in my mind for a while. My basic stack is html, single page, local storage and lightweight js.
It is really good in doing this.
those ideas are like UI experiments or small tools helping me doing stuff.
Its also super great in ELI5'ing anything
Same result if you copied and pasted from a couple passionate blogs.
Not in the same timeframe. My experiments take an hour.
I feel the same. I understand some of the excitement. Whenn I use it I feel more productive as it seems I get more code done. But I never finish anything earlier because it never fails to introduce a bizarre bug or behaviour that no one in sane made doing the task would
> "I wrote a novel while I made coffee this morning" --> used a ChatGPT agent to make a messy mediocre PDF
There was a story years ago about someone who made hundreds of novels on Amazon, in aggregate they pulled in a decent penny. I wonder if someone's doing the same but with ChatGPT instead.
Pretty sure there was a whole era where people were doing this with public domain works, as well as works generated by Markov chains spitting out barely-plausible-at-first-glance spaghetti. I think that well started to dry up before LLMs even hit the scene.
"AI helped me make money by evading anti-spam controls" doesn't have quite the same ring to it. :p
"Adding the abbreviation 'AI' to my marketing for online courses for making millions making marketing for online courses made me millions!"
It had happened in Japan. There was on author who were updating 30+ series simultaneously on Kakuyomi, the largest Japanese web novel site. A few of them got top ranked.
Afaik, I think the way people are making money in this space is selling courses that teach you how to sell mass produced AI slop on Amazon, rather than actually doing it
People say outrageous things when they’re follower farming.
At the end of the day, it doesn't really get you that much if you get 70% of the way there on your initial prompt (which you probably spent some time discussing, thinking through, clarifying requirements on). Paid, deliverable work is expected to involve validation, accountability, security, reliability, etc.
Taking that 70% solution and adding these things is harder than if a human got you 70% there, because the mistakes LLMs make are designed to look right, while being wrong in ways a sane human would never be. This makes their mistakes easy to overlook, requiring more careful line-by-line review in any domain where people are paying you. They also duplicate code and are super verbose, so they produce a ton tech debt -> more tokens for future agents to clog their contexts with.
I like using them, they have real value when used correctly, but I'm skeptical that this value is going to translate to massive real business value in the next few years, especially when you weigh that with the risk and tech debt that comes along with it.
> and are super verbose...
Since I don't code for money any more, my main daily LLM use is for some web searches, especially those where multiple semantic meanings would be difficult specify with a traditional search or even compound logical operators. It's good for this but the answers tend to be too verbose and in ways no reasonably competent human would be. There's a weird mismatch between the raw capability and the need to explicitly prompt "in one sentence" when it would be contextually obvious to a human.
Imo getting 70% of the way is very valuable for quickly creating throwaway prototypes, exploring approaches and learning new stuff.
However getting the AI to build production quality code is sometimes quite frustrating, and requires a very hands-on approach.
Yep - no doubt that LLMs are useful. I use them every day, for lots of stuff. It's a lot better than Google search was in its prime. Will it translate to massively increased output for the typical engineer esp. senior/staff+)? I don't think it will without a radical change to the architecture. But that is an opinion.
I completely agree, I found it very funny that I have been transitioning from an "LLM sceptic" to a "LLM advocate", without changing my viewpoint. I have long said that LLM's won't be replacing swathes of the workforce any time soon and that LLM's are of course useful for specific tasks, especially prototyping and drafting.
I have gone from being challenged on the first point, to the second. The hype is not what it has been.
"I used AI to write a GPU-only MoE forward and backward pass to supplement the manual implementation in PyTorch that only supported a few specific GPUs" -> https://github.com/lostmsu/grouped_mm_bf16 100% vibe coded.
Pretty much every x non-political/celeb account with 5K followers+ is a paid influencer shill lol.
Welcome to the internet
One of my favorite stories from the dotcom bust is when people, after the bust, said something along the lines of: "Take Pets.com. Who the hell would buy 40lb dogfood bags over the internet? And what business would offer that?? It doesn't make sense at all economically! No wonder they went out of business."
Yet here we are, 20 years later, routinely ordering FURNITURE on the internent and often delivered "free".
My point being, sure, there is a lot of hype around AI but that doesn't mean that there aren't nuggets of very useful projects happening.
True, but I think the point of that story is it’s really hard to predict what’s crap and what’s just too early.
It doesn’t guarantee the skeptics are wrong all the time.
"Look at what happened with the internet!" also doesn't mean the same will happen with AI
Neither argument works
There's 0 requirement that [new technology] must follow the path of the internet though. So it's kind of an irrelevant non sequitur.
Pets.com was both selling everything at a loss and spending millions on advertising. It wasn't the concept that was the issue.
There are two major reasons people don't show proof about the impact of agentic coding:
1) The prompts/pipelines portain to proprietary IP that may or may not be allowed to be shown publically.
2) The prompts/pipelines are boring and/or embarrassing and showing them will dispel the myth that agentic coding is this mysterious magical process and open the people up to dunking.
For example in the case of #2, I recently published the prompts I used to create a terminal MIDI mixer (https://github.com/minimaxir/miditui/blob/main/agent_notes/P...) in the interest of transparency, but those prompts correctly indicate that I barely had an idea how MIDI mixing works and in hindsight I was surprised I didn't get harrassed for it. Given the contentious climate, I'm uncertain how often I will be open-sourcing my prompts going forward.
You weren't harassed for it because (1) it is interesting and (2) you were not hiding the AI involvement and passing it off as your own.
The results (for me) are very much hit-and-miss and I still see it as a means of last resort rather than a reliable tool that I know the up and downsides of. There is a pretty good chance you'll be wasting your time and every now and then it really moves the needle. It is examples like yours that actually help to properly place the tool amongst the other options.
I've seen people harassed for their personal projects because they used AI.
I'm fundamentally a hobbyist programmer, so I would have no problem sharing my process.
However, I'm not nearly organized enough to save all my prompts! I've tried to do it a few times for my own reference. The thing is, when I use Claude Code, I do a lot of:
- Going back and revising a part of the conversation and trying again—sometimes reverting the code changes, sometimes not.
- Stopping Claude partway through a change so I can make manual edits before I let Claude continue.
- Jumping between entirely different conversation histories with different context.
And so on. I could meticulously document every action, but it quickly gets in the way of experimentation. It's not entirely different from trying to write down every intermediate change you make in your code editor, between actual VCS commits.
I guess I could record my screen, but (A) I promise you don't actually want to watch me fiddle with Claude for hours and (B) it would make me too self-conscious.
It would be very cool to have a tool that goes through Claude's logs and exports some kind of timeline in a human-readable format, but I would need it to be automated.
---
Also, if you can't tell from the above, my use of Claude is very far from "type a prompt, get a finished program." I do a lot of work in order to get useful output. I happen to really enjoy coding this way, and I've gotten great results, but it's not like I'm entering a prompt and then taking a nap.
All your conversations are living as json files inside `~/.claude/`.
But that includes a ton of dead ends and stuff.
No. The main reasons are that
1) the code AI produces is full of problems, and if you show it, people will make fun of you, or
2) if you actually run the code as a service people can use, you'll immediately get hacked by people to prove that the code is full of problems.
1) no one cares if it works. No one cared before how your code looked as long as you are not a known and well used opensource project.
2) there are plenty of services which do not require state or login and can't be hacked. So still plenty of use cases you can explore. But yes i do agree that Security for production live things are still the biggest worry. But lets be honest, if you do not have a real security person on your team, the shit outthere is not secure anyway. Small companies do not know how to build securely.
> 1) no one cares if it works. No one cared before how your code looked as long as you are not a known and well used opensource project.
Forgive me if this is overly blunt, but this is such a novice/junior mindset. There are many real world examples of things that "worked" but absolutely should not have, and when it blows up, can easily take out an entire company. Unprotected/unrestricted firebase keys living in the client are all the rage right now, yea they "work"until someone notices "hey, I technically have read/write god mode access to their entire prod DB", and then all of a sudden it definitely doesn't work and you've possibly opened yourself to a huge array of legal problems.
The more regulated the industry and the more sensitive the business data, the worse this is exacerbated. Even worse if you're completely oblivious to the possibility of these kinds of things.
> Forgive me if this is overly blunt, but this is such a novice/junior mindset.
Unfortunately the reality is there are far more applications written (not just today but for many years now) by developer teams that will include a dozen dependencies with zero code review because feature XYZ will get done in a few days instead of a few weeks.
And yes, that often comes back to bite the team (mostly in terms of maintenance burden down the road, leading to another full rebuild), but it usually doesn't affect the programmers who are making the decisions, or the project managers who ship the first version.
I'm an architect and have 20 years of experience.
I have seen production databases reachable from the internet with 8 character password and plenty others.
But my particular point is only about the readability of code from others.
You should go hack the Cloudflare Workers OAuth stuff then, right?
You seem to think I'm an AI coding hater or something. I'm not. I think these tools are incredibly useful and I use them daily. However, like described in the article, I do am skeptical about stories where AI writes whole applications, SaaS or game engines in a few hours and everything "just works". That is not my experience.
The Cloudflare OAuth lib is impressive, I will readily admit that. But they also clearly mention that of course everything was carefully reviewed, and that not everything was perfect but that the AI was mostly able to fix things when told to. This was surely still a lot of work, which makes this story also much more realistic in my opinion. It surely greatly sped up the process of writing an OAuth library - how much exactly is however hard to say. Especially in security-relevant code, the review process is often longer than the actual writing of the code.
I don't know why you're giving me two paragraphs of response. I'm not psychoanalyzing you. I had a simple suggestion: if agent code output is so bad nobody runs it because it would get people owned, go own up the code Kenton generated.
How are both of these not simply the second case they provided?
> The prompts/pipelines are boring and/or embarrassing and showing them will dispel the myth that agentic coding is this mysterious magical process
You nailed it. Prompting is dull and self evident. Sure, you need basic skills to formulate a request. But it’s not a science and has nothing to do with engineering.
Could you clarify that last paragraph for me? I’m not sure what ”contentious climate” is here. AI antihype? I don’t understand the connection to not being harassed for something, isn’t that a good thing rather than something that would make you uncertain if you want to share prompts in the future?
"AI tech bro creates slop X because they don't understand how X actually works" is a common trope among the anti-AI crowd even on Hacker News that has only been increasing in recent months, and sharing prompts/pipelines provides strong evidence that can be pointed at for dunks. Sharing AI workflows is more likely to illicit this snark if the project breaks out of the AI bubble, though in the case of the AI boosters on X described as in the HN submission that's a feature due to how monetization works that platform. It's not something I want to encourage for my own projects, though.
There's also the lessons on the recent shitstorms in the gaming industry, with Sandfall about Expedition 33's use of GenAI and Larian's comments on GenAI with concept art, where both received massive backlash because they were transparent in interviews about how GenAI was (inconsequentially) used. The most likely consequence of those incidents is that game developers are less likely on their development pipelines.
Counterpoint: If the tech was actually that good, nobody could dunk on it and anyone who tried would be mocked back.
If your hand is good, throw it down and let the haters weep. If you scared to show your cards, you don't have a good hand and you're bluffing.
You'd think so, but with the recent extreme polarization of GenAI the common argument among the anti-AI crowd is the absolute "if AI touched it, it's slop". For example in the Expedition 33 case (which won Game of the Year), even though the GenAI asset was clearly a placeholder and replaced 2 days after launch, a surprisingly large number of players said sincerely "I enjoyed my time with E33 but after finding out they used GenAI I no longer enjoy it."
In a lesser example, a week ago a Rust developer on Bluesky tried to set up a "Tainted Slopware" list of OSS which used AI, but the criteria for inclusion was as simple as "they accepted an AI-generated PR" and "the software can set up a MCP server." It received some traction but eventually imploded, partially due to the fact that the Linux kernel would be considered slopware due to that criteria.
Sure, but I'm gonna push back and go "so what"? That sort of thing is what haters do, especially in the notoriously toxic world of gaming.
"Some people expressed disappointment about a thing I think is silly" is literally the center square on the gamer outrage bingo card lol. Same with "someone made a list that I think is kind of stupid".
And again, so what? Why should you care? Again, if you feel that insecure about it, it's you and your work that's the problem, not the haters who are always going to exist. Have the courage of your own convictions or maybe admit that it isn't that strong of a conviction lol.
> if you feel that insecure about it, it's you that's the problem, not the haters who are always going to exist
Pulling this victim-blaming sentence out of context to show how ridiculous it is.
Given this stance, I think GPs reasoning for not publicly bragging about using AI makes perfect sense.
Why paint a target on your back? Why acquiesce to "show us your AI" just to be mobbed by haters?
Fuck that, let them express their frustrations elsewhere.
My dude, that's not "victim blaming" lol. Nobody's forcing you, personally, to do anything. I don't care if you, personally, publish your work or not.
What I'm saying is that _feeling_ of insecurity doesn't come from haters, because haters gonna hate, it's a sign that _your_ work might not be as good as you think it is, and you don't feel that you can stand behind it.
Also, managing public expectations and messaging is a thing professionals in many industries do all the time. It's not even particularly difficult, you just hear about it when it's bungled.
EDIT: To clarify, as a SWE, my work is available to anyone at the company. Any engineer I work can see what I've done, and the public sees it too, they just don't know about it, because if I screw up, the company will take the blame for it. You get very very very very used to critique in this role and taking responsibility for what you make and making the case for your technical solution.
oh yeah, most of us would agree those remarks are unreasonable
you can use however you like, no one cares. really, no one.
but, people in general are NOT inclined to pay for AI slop. that is the controversy.
why would I waste my time reading garbage words generated by an LLM? If people wanted this, they would go to the llm themselves. the whole point of artistic expression is to present oneself, to share a perspective. llms do not have a singular point of view, they do not have a perspective, they do not have an cohesive aggregate of experiences. they just regurgitate the average form. no one is interested in this. even when distributed for free, is disrespectful to others that put their time until they realized is just hot garbage yet again.
people are getting tired of low effort `content`, yet again another unity or unreal engine resking, asset flipping `game`...
you get the idea, lots of people will feel offended and disrespected when presented with no effort. got it? it is not exclusively about intellectual property theft also, i don't care about it, i just hate slop.
now whether you like it or not, the new meta is to not look professional. the more personal, the better.
AI is cool for a lot of things, searching, learning, natural language apropos, profiling, surveilling, compressing information...it is fantastic technology! not a replacement for art, never will be.
Or 3 it’s my competitive advantage to keep my successes close to my chest.
That's 1, just reworded.
Did you post them with commentary along the lines of "this is the second coming of $DEITY, AI will replace us all, click on this Claude referral link to sign up"?
No, don't think so.
However, 90% of "AI" articles either are full of bullshit about "AI" or are someone trying to pass as an "expert" in some domains with LLM generated bullshit.
Stuff like yours is rare.
Doesn't the existence of consumer products like ChatGPT indicate that LLMs aren't able to do human-level work? If OpenAI really had a digital workforce with the capabilities of ~100k programmers/scientists/writers/lawyers/doctors etc, wouldn't the most profitable move be to utilize those "workers" directly, rather that renting out their skills piecemeal?
If this stuff worked, then given that Microsoft has a huge share of it, shouldn't Microsoft's products be good? Or at least getting better. I use Bing most days [1], and it's consistently an absolute joke.
[1] to farm reward points to get cosmetic items in video games
That depends on what the real value is. The sure way to get rich selling pickaxes to gold miners. However you would be even richer if you figured out where the gold really was and mined in that exact location.'
Of course you can also get rich selling scams.
All the truer when there is more miners than gold, one can't help but note.
For now it's better and easier to do this with our money and our feedback.
But yes, someone else said that as soon as any of these get to AGI you will not be able to use it.
To be more exact, the fact that everyone sells access to models they are continually "improving" is proof that any statement from the LLM peddlers about AGI is a lie.
Why?
It funds the initial cost and reduces risks
It also provides additional training data and feedback
A run can cost 100 Million $
LLMs are able to do human-level work. I think surely now that is unquestionable? They can't do all human-level work, in the same way that not all humans can do all human-level work, but a lot of criticism implicitly benchmarks it against all work. LLMs have this remarkable ability to be both the smartest thing in the room and the dumbest thing at the same time.
On the profitability point. Yes and no I guess. ChatGPT will likely go down as the most influential thing in the ai race (or early ai race) simply because it was the most visceral illustration of the art of the possible to the general public.
Technical people will correct me or have arguments to why this isn't the case but they'll be wrong simply because ChatGPT captured consumer attention, which ultimately led to supercharged financial attention, and everything that has happened since is due to that. Whether its pure marketing or futuregazing, the world of money bought into it, with the ultimate view that this is the worst it will ever be.
The ultimate profitable goal is unarguably replacing human labour (at a lesser all in cost) but if that is not possible, but you believe it could be possible, then showcasing and getting people to believe that you can achieve that goal, is pretty damn profitable too and it's proven to be for some people while giving them runway to continue to pursue the ultimate goal.
What we really need is an updated Turing test: "can a project manager tell the difference between a junior dev working remotely vs Claude Code hooked up to a Slack account?"
Or "can a junior dev tell from an email or Jira ticket whether it was written by Claude Code hooked up to email/Jira or an actual PM" =)
> ChatGPT will likely go down as
It's been a long time since I thought of the Segway, which exemplifies one possible trajectory: Recognizable to all, everyone interested in trying one out, but still fell short of the investor dream of replacing the car and changing urban travel forever.
Sure but my point isn't that ChatGPT will be dominant, it has already changed the world. Even if Openai fell over tomorrow, that doesnt change that it was the step change from a public consciousness in the potential of LLMs. And LLMs aren't falling by the wayside anytime soon
You know, there's a number of different competing propaganda battles going on:
1) There's the people and companies that stand to make money and build up companies by convincing people to buy their ai projects, hyping up ai, etc.
2) There's companies and nation states trying to destroy competitor's / other country's ai efforts, turn citizens against them, in order to gain an advantage/lead in the race.
3) There's, conversely, nation states that want to boost up and promote their ai industry in order to win the race rather than other countries winning (assuming there's a "win" at the end, like AGI, which I don't believe there is).
4) Normal citizens that have been ideologically brainwashed one way or the other, and so are going online to argue in a culture war for their beliefs / "side".
5) People posting crazy takes on ai, one way or the other, to get clicks / money on their articles.
The whole topic is awash in serious propaganda. Effectively the only path forward is believing what you yourself know for sure, from your direct experience / knowledge.
Can someone please explain to me how I was able to construct this DSL in as short a time as I did?
https://github.com/williamcotton/webpipe
https://github.com/williamcotton/webpipe-lsp
Fully featured LSP (take a look at the GIFs in the repo), step debugger, BDD-testing framework built into the language and runtime itself (novel!), asynchronous/join in pipelines (novel!), middleware for postgres, jq, javascript, lua, graphql (with data loaders), etc. It does quite a bit. Take a look at my GitHub timeline for an idea of how long this took to build.
It is 100% an experiment in language and framework design. Why would I otherwise spend years of my life handcrafting something where I just want to see how my harebrained ideas play out when actualized?
I would absolutely love to talk about the language itself rather than how it was made but here we are.
And I wrote my own blog in my own DSL. Tell me that's not just good old fashioned fun.
I saw this DSL on HN yesterday, and this syntax is total garbage. It’s some stupid mixture of different PLs. Are you seriously OK with this so that you keep posting it here? I don’t even want to look through source code knowing what garbage it is at the surface level.
Well hey, at least some feedback!
I hope you have a better day tomorrow than whatever was going on with you when you wrote your comment.
> Why would I otherwise spend years of my life handcrafting something where I just want to see how my harebrained ideas play out when actualized?
If you're sure that's all you wanted out of it. If this were more a path-vs-destination kind of project for you, you might have gotten deep insights about programming language design and implementation over those years which the efficient route deprives you of.
Thanks for your perspective and taking the time to lecture me!
I did miss the sarcasm you pointed out in the separate mail to me (I should have paid more attention to the word "otherwise", I guess). I did not mean to lecture at you at all. I thought it was something you built very quickly with LLMs, but clearly this was a passion project, whether or not you used LLMs.
My apologies.
It's OK, I was being overly sensitive based on the other comment in this thread. In fact, I do value the journey over the destination and it is helpful to be reminded of this. I've updated the project's README to make this explicit!
I’ve taken to calling this (in my mind) the Age of the Sycophants. In politics, in corporate life, in technology and in social media, many people are building a public life around saying things that others want to hear, with demonstrably zero relationship to truth or even credibility.
It would certainly make an interesting anthropological case study.
Humans have always been performative with those outside of their immediate social circle. Politics is effectively the art of performance, and using it to gain influence and power. With legacy media the general public was still largely on the receiving end of it, but modern technology and social media have given that ability to anyone capable of building an audience. So now performative behavior is everywhere, since we're all competing to get our voice heard, to experience adoration, fame, power, fortune. We're in this weird state where this is all done in digital worlds, where it's easier than ever to fabricate an image, and yet it all ends up affecting the real world in one way or another. Our leaders are celebrities who are good at this game, and not necessarily people worthy of this position.
Honestly, I have little faith we can turn this around. It's going to get much worse before it gets better, if at all.
In the White House, you have to say what Trump wants to hear. If you are a foreign leader, you have to say you’ll share your peace prize with him, because that’s what he wants to hear. TACO is a thing because he wants to say things, but not do things.
In tech, you have to say you’re bullish on AI, because that’s what managers want to hear. They say it their CEO, because that’s what CEO wants to hear. And the CEO says it to the public because that’s what Wall Street wants to hear.
Turn around and ask ChatGPT a question and it tells you what you want to hear, along with a compliment about how smart you are.
I agree, if the benefits are so large, there should be clearer evidence (that isn't, "trust me, just use it").
That said, I use Antigravity with great success for self hosted software. I should publish it.
Why haven't I?
* The software is pretty specific to my requirements.
* Antigravity did the vast amount of work, it feels unworthy?
* I don't really want a project, but that shouldn't really stop me pushing to a public repo.
* I'm a bit hesitant to "out" myself?
Nonetheless, even though I'm not the person, I'm surprised there isn't more evidence out there.
I think this "* The software is pretty specific to my requirements." is the biggest part for me. I built something with Antigravity over the holidays that I can use for myself and it solves my use case. I tried thinking about if this can be helpful for others and pushed it a bit further into a version that could be hosted. Which does not make that much sense because it is a computationally intense numerical solver for thermal bridges and just awfully slow on a free hosted platform. But the project was a couple of evenings and would otherwise haven taken me half a year to complete (and thus never been done).
https://github.com/schoenenbach/thermal-bridge https://thermal-bridge.streamlit.app/
> Antigravity did the vast amount of work, it feels unworthy
I think this is true for me as well. I have two types of projects that I’ve been working on - small ones with a mix of code I wrote and AI. I have posted these, as I spent a lot of time guiding the AI, cleaning up the AI’s output, and I think the overall project has value that others can learn from and built on.
But I also have some that are almost 100% vibe-coded. First, those would take a lot of time to clean up and write documentation for to make them publishable/useful.
But also, I do think they feel “unworthy”. Even though I think they can be helpful, and I was looking for open-source versions of those things. But how valuable can it really be if I was able to vibe-code it in a few prompts? The next person looking for it will probably do the same thing I did and vibe-code their own version after a few minutes.
This is a strage phenomenon where people get excited by the mere fact that someone else is excited by something which is not directly visible to the spectator. It works well in horror movies and as it seems with AI hype.
Being respected inside big companies has little to do with engagement on social media. Most of the best engineers are working hands-down. Arguably shitposting on the internet may have a negative correlation with technical ability inside Google.
One of the times I think the draconian approach Apple has towards employee speaking as an associate of the firm without explicit authorization is the correct one.
LLMs are amazing and I do seriously wonder if the singularity could happen in my lifetime ... but there definitely are people over-hyping present capabilities too much right now. If present models were fully human-level proper-extended-Turing-test-passing AGI, then the results on the economy and the software ecosystem would be as immediately obvious and world-changing as a comet impact.
I don't think Rakyll or Andrej are claiming these things; I think they're assuming their readers share more context with them and that it's not necessary to re-tread that every time they post about their surprise at AI currently being better than they expected. I've had the experience multiple times now of reading posts from people like them, nodding along, and then reading breathless quote-tweets of those very same posts exclaiming about how it means that AGI is here right now.
If you don't get the results you don't get the results. If someone else can use this tool to get the results, they'll out-compete you. If they can't, then they've wasted time and you'll out-compete them. I see these influencer guys as idea-generators. It's super-cheap to test out some of these theories: e.g. how well Claude can do 3D modeling was an idea I wanted to test and I did and it's pretty good; I wanted to test Claude as a debugging aid and it's a huge help for me.
But I would never sit down to convince a person who is not a friend. If someone wanted me to do that, I'd expect to charge them for it. So the guys who are doing it for free are either peddling bullshit or they have some other unspecified objective and no one likes that.
Yes! And like … “out-compete” assumes a zero sum game. There are massive industries where the tools used to serve different market segments only barely overlap decades after the “game changing” tool was made available.
Like, screw the whole “artisanal small-batch software” argument—there are massive new systems being written in C every day despite decades of claims that it is an obsolete language doomed to be replaced by better alternatives. Those alternatives caught on in some segments and not in others. Electric cars caught on in some segments and not in others. Steel-and-concrete building construction caught on in some segments and not in others. It’ll be fine.
Anecdotally, I’m finding that, at least in the Spark ecosystem, AI-generated ideas and code are far from optimal. Some of this comes from misinterpreting the (sometimes poor) documentation, and some of it comes from, probably, there not being as many open source examples as CRUD apps, which AI “influentists” (to borrow from TFA) appear to often be hyping up.
This matters a lot to us because the difference in performance of our workflows can be the difference in $10/day in costs and $1000/day in costs.
Just like TFA stresses, it’s the expertise in the team that pushes back against poor AI-generated ideas and code that is keeping our business within reach of cash flow positive. ~”Surely this isn’t the right way to do this?”
Most text worth paying for (code, contracts, research) requires:
- accountability
- reliability
- validation
- security
- liability
Humans can reliably produce text with all of these features. LLMs can reliably produce text with none of them.
If it doesn't have all of these, it could still be worth paying for if it's novel and entertaining. IMO, LLMs can't really do that either.
Let's not put humans on too much of a pedestal, there are plenty of us who are not that reliable either. That's why we have tests, linting, types and various other validation systems. Incidentally, LLMs can utilize these as well.
Humans are unreliable in predictable ways. This makes review relatively painless since you know what to look for, and you can skim through the boilerplate and be pretty confident that it's right and isn't redundant/insecure, etc.
LLMs can use linters and type checkers, but getting past them often times leads it down a path of mayhem and destruction, doing pretty dumb things to get them to pass.
I never read the tweet as anything other than that an expert with deep knowledge of their domain was able to produce a PoC. Which I still find to be very exciting and worthy of being promoted. This article didn't really debunk much.
> expert with deep knowledge of their domain
these are the kinds of people that can use generative AI best IMO. Deep domain knowledge is needed to spot when the model output is wrong even though it sounds 100% correct. I've seen people take a model's output as correct to a shocking degree like placing large bets at a horse track after uploading a pic of the schedule to ChatGPT. Many people believe whatever a computer tells them but, in their defense, no one has had to question a large calculation done by a calculator until now.
Totally agree. The more you know about software development the better you can use the tools. A noob trying to write a kernel driver would quickly hit a brick wall and give up. It's kind of self correcting.
Writing code is the easiest thing to do at Google. Getting past layers of hierarchy and nailing down what the code will actually do and who gets credit for it will take years for a major project.
Perhaps nobody wants to have the uncomfortable conversation that AI is making the competent more competent and the incompetent less competent, because it would imply that AI provides brutally unequal benefits. The AI haters don't want this discussion because it would imply AI has any benefits, and the AI lovers don't want to have this discussion because it would imply the benefits of AI aren't universal and will increase inequality.
I want to see an example of this. Any real example. So far what I’ve seen, I wouldn’t give my name to any of those barely usable code, and most of the time they were even slower, especially when they pretended that they reviewed their code. And even with reviews they happily accepted bad code. This was true even with my friends, not just random examples on the internet.
I still need to understand every single line of the code to be responsible for it, and that takes the majority of time anyway, and quite often I need to rewrite most of it, because average code is not particularly good, because most code wasn’t produced by senior professionals, but random people making a random python script with only Hello World under their belt. So at the end doesn’t really matter whether I copy paste from a source, or an LLM does the same.
I understand that many coder are happy with the “John made his first script in his life” level of code, but I’m paid well because I can do better, way better. Especially because I need to be responsible for my code, because the companies to whom I work are forced to be responsible.
But of course, when there is no responsibility, I don’t care either. For those home projects where there is exactly zero risks. Even big names seem to use these only to those kind of projects. When they don’t really care.
I'll start by saying that in my past life I was a PM, and from that angle I can very much see how people writing code for large-scale, production systems take real issue with the quality of what LLMs produce.
But these days I run a one-man business, and LLMs (currently Claude Code, previously GPT) have written me a ton of great code. To be clear, when I say "great" I don't mean up to your standards of code quality; rather, I mean that it does what I need it to do and saves me a bunch of time.
I've got a great internal dashboard that pulls in data from a few places, and right now CC is adding some functionality to a script that does my end of month financial spreadsheet update. I have a script that filters inbound leads (I buy e-commerce brands, generally from marketplaces that send me an inordinate amount of emails that I previously had to wade through myself in order to find the rare gem). On the non-code front, I have a very long prompt that basically does the first pass of analysis of prospective acquisitions, and I use Shortcut.ai to clean up some of the P&Ls I get (I buy small e-commerce brands, so the finances are frequently bad).
So while I can't speak to using LLMs to write code if you're working in any sort of real SaaS business, I can definitely say that there's real, valid code to be had from these things for other uses.
One of my friends did a job for a government. He generated the code for it with some LLM. It provided a result which was about what he thought should be. He - or anybody - never checked the code whether it really calculated what it should have. “It did what [he] needed it to do”. Now the said government started to make decisions based on a result which proved by nobody. In other words, lottery.
What you mentioned doesn’t mean anything until there is no hard proof that it really works. I understand that it seems to you that it works, but I’ve seen enough to know that that means absolutely nothing.
Thanks, I can relate to the parent poster, and this is a really profound comment for me. I appreciate the way you framed this. I’ve felt compelled to fact check my own LLM outputs but I can’t possibly keep up with the quantity. And it’s tempting (but seems irrational) to hand the results to a different LLM. My struggle is remembering there needs to be input/query/calculation/logic validation (without getting distracted by all the other shiny new tokens in the result)
I don't know if it's as nuanced as this.
Just seems like it's dependent on what you're working on and what training data is available for it.
AI definitely just spews out python and JavaScript for me to do all sorts of things quickly.
But it can't translate my XNA game to JavaScript worth a damn. It's terrible with visual work as well.
"Not only were the colours and patterns unusually fine, but the clothes that were made of the stuffs had the peculiar quality of becoming invisible to every person who was not fit for the office he held, or if he was impossibly dull."
The article nails the pattern but I think it's fundamnetally an incentives problem.
We're drowning in tweets, posts, news... (way more than anyone can reasonably consume). So what rises to the top? The most dramatic, attention-grabbing claims. "I built in 1 hour what took a team months" gets 10k retweets. "I used AI to speed up a well-scoped prototype after weeks of architectural thinking" gets...crickets
Social platforms are optimized for engagement, not accuracy. The clarification thread will always get a fraction of the reach of the original hype. And the people posting know this.
The frustrating part is there's no easy fix. Calling it out (like this article does) get almost no attention. And the nuanced followup never catches up with the viral tweet.
Good article. "hype first and context later". Loads of online content has become highly sentational. I notice this on Youtube (especially thumnails and titles) Seems to be a trend. I wonder if -- collectively -- we'll develop a "shield" for this: (more critical thinking?)
Its a strange phenomenon. You want to call out the bs but then you are just giving them engagement and boost. You want to stay away but there is a sort of confluence where these guys tend to ride on each others' post and boosts those posts anyway. If you ask questions, very rarely they answer, and if they do, it takes one question to unearth that it was the prompt or the skill. Eg: huggingface people post about claude finetuning models. how? when they gave everything in a skill file, and claude knew what scripts to write. Tinker is trying the same strategy. (yes, its impressive that claude could finetune, but not as impressive as the original claim that made me pay attention to the post)
It does not matter if they get the details wrong, its just that it needs to be vague enough, and exciting enough. Infact vagueness and not sharing the code part signals they are doing something important or they are 'in the know' which they cannot share. The incentives are totally inverted.
I think humans are proxying their value through what they can do with AI. It's like a domestication flex.
Great post! Indeed, it s deeply disappointing to see how both the tech industry and scientific community have fallen into the same attention-seeking trap: hyping their work with vague, sensational claims, only to later "clarify" with far more grounded—and often mundane—statements.
This tactic mirrors the strategies of tabloids, demagogues, and social media’s for-profit engagement playbook (think Zuckerberg, Musk, and the like). It’s a race to the bottom, eroding public trust and undermining the foundations of our society - all for short-term personal gain.
What’s even more disheartening is how this dynamic rewards self-promotion over substance. Today’s "experts" are often those who excel at marketing themselves, while the most knowledgeable and honest voices remain in the shadows. Their "flaw"? Refusing to sacrifice integrity for attention.
Almost every aspect of public life on social media nowadays is guided by sensationalism. It's simply a numbers game, and the "number" is engagement. Why would you do anything that's not completely geared towards engagement?
The original post by Jaana made 8.4 million impressions, while the follow-up that included the previously/deliberately omitted context and some important information, such as "what I built is a toy version", has 277K impressions as of right now.
I respect Jaana and have been following her for years. I'd expect she ought to know how that claim would have been understood. But I guess that's the only way to go viral nowadays.
Also, this incident goes to show how the self-proclaimed AI influencer, Rohan Paul, puts a lot of thought and importance into sharing "news" about AI. As if it were not enough to share Jaana's bold claim without hesitation, he also emphasized it with an illustrious commentary: "Dario Amodei was so right about AI taking over coding."
Slop, indeed.
Like everything in LLM land it's all about the prompt and agent pipeline. As others say below, these people are experts in their domain. Their prompts are essentially a form of codifying their own knowledge, as in Rakyll and Galen's examples, to achieve specific outcomes based on years and maybe even decades of work in the problem domain. It's no surprise their outputs when ingested by an LLM are useful, but it might not tell us much about the true native capability of a given AI system.
Off topic, but AI hype is appearing in hardware and consumer electronics. I just bought a rechargeable hand warmer that claims to have an "... Have Intelligent AI Temperature Control Chips That Can Accurately Control the Temperature," At least in the early days the Transistor, radios did have them.
Influentists: LLM or get left behind! Also Influentists: surprisingly, not suggesting some friendly bioterrorism for the upper hand... or is this the real motivation for RTO? I wouldn't know.
Anyway, I'll worry when the dead weight disappears and ceases to be replaced. Shields and energy reserves are critical, etc.
This is very well said - it is much nicer and more professional than the sentiments I could express on the matter.
The age of niche tech microcelebrities is on us. It existed a bit in the past (ESR, Uncle Bob, etc), but is much more of a thing now. Some of them make great content and don't say ridiculous things. Others not so much.
Even tech executives are aping it...
Recent and related (were there others?):
Google engineer says Claude Code built in one hour what her team spent a year on - https://news.ycombinator.com/item?id=46477966 - Jan 2026 (81 comments)
Influences generally don't get to me.
Sitting 2 hours with an Ai agent developing end to end products does.
> We must stop granting automatic authority to those who rely on hype, or vibes, rather than evidence.
> The tech community must shift its admiration back toward reproducible results and away from this “trust-me-bro” culture.
Well said, in my opinion.
AI is like flossing. You waste more time listening to other people's opinions on whether it's helpful, than just trying it out yourself for a few days.
I'm still waiting for all these remarkable achievements produced with this new technology to provide tangible value to the world. Surely we should be seeing groundbreaking products and innovations in all industries by now, improving the lives of millions of people.
Instead all we get is anecdata from influencers and entrepreneurs, and the technology being shoved into every brand and product. It's exhausting.
At least it seems that the tide is starting to turn. Perhaps we are at the downward slope of the Peak of Inflated Expectations.
It's quite likely that the answer to the worlds problems isn't more apps/products. AI may have arrived at a moment to bring the cost down of creating software there isn't much demand for in the first place.
Sure, that's one part of it, but this technology is also used by highly intelligent people in tech and other industries, some of whom are singing its praises. I would expect to see amazing products and innovations from them, and yet progress has largely maintained the same momentum. Am I expecting too much, too soon?
Hey, why doesn't the pricing for google workspace go DOWN if it's become so cheap to maintain it because of "AI" "agents" ?
A recent favorite of mine is simonw who usually is unable to stop hyping LLMs suddenly forgetting they exist in order to rhetorically "win" an argument:
> If you're confident that you know how to securely configure and use Wireguard across multiple devices then great
https://news.ycombinator.com/item?id=46581183
What happened to your overconfidence in LLMs ability to help people without previous experience do something they were unable to before?
This is an inverse fitness influencer.
Claiming the steroids they’re taking are doing all the work and they don’t need to put in work anymore.
I think this "trend" is due to AI companies paying (in some form) the influencers to promote AI. Simple as that.
To me, debunking hype has always felt like arguing with an advertisement. A good read about that: https://www.liberalcurrents.com/deflating-hype-wont-save-us/
Hard to take that seriously. It’s a political hit-piece. Which I guess is most things today, but I don’t take those seriously either.
Masks during Covid and LLMs, used as political pawns. It’s kind of sad.
Are we talking about the same article?
Great article. This needs to be framed. The whole trust me bro, and shock and awe of social medias is a non-stop assault these days. You can't open a wall without seeing those promoted up front and centre and without any proof.
If AI was so good today, why isn't there an explosion of successful products? All we see is these half baked "zomg so good bro!" examples that are technically impressive, but decisively incomplete or really, proof of concepts.
I'm not saying LLMs aren't useful, but they're currently completely misrepresented.
Hype sells clicks, not value. But, whatever floats the investors' boat...
Thank you for calling this out, we are being gaslit by attention seeking influencers. The algorithmic brAInrot is propagated by those we thought we can trust, just like the instagram and youtube stars we cared about who turned out to be monsters. I sincerely hope those people become better or wane into meaninglessness. Rakyll seems to spend more time on X than working on advancing good software these days, a shame given her past accomplishments.
Idk man, all AI discussion feels like a waste of effort.
“yes it will”, “no it won’t” - nobody really knows, it's just a bunch of extremely opinionated people rehashing the same tired arguments across 800 comments per thread.
There’s no point in talking about it anymore, just wait to see how it all turns out.
The cool thing is you can just try it. The barrier to entry is incredibly low right now. If it works for you, great. If it doesn't work for you, great. At least you know.
That's the real reason the conversation seems pointless. Every thread is full of comments from one group saying how useful AI is, and from another group saying how useless it is. The first group is convinced the second group just hasn't figured out how to use it right, and the second group is convinced the first group is deluded or outright lying.
Yes, I'm in the second group and I have that conviction about the first group based on personal experience with LLMs.
But most hype is not delusion. It's people trying to present themselves as "AI" experts in order to land those well paid "AI" positions. I don't think they even believe what they're saying.
[flagged]
Talking about AI instead of just leveraging it (or not) is the new “talking about note-taking software” instead of just writing.
Organizing notes is the next problem to always solve after solving todo lists.
It's not "yes it is" vs "no it won't" though. The discussion is "Yes it does" vs "no it doesn't" (present tense.) There's nothing wrong with guessing about the future, but lying about a present that is testable and unwillingness to submit to the testing is wrong.
Even then nothing is learned. Every HN thread there is on AI coding: "I am using $model for writing software and its great." "I am using $model for writing software and it sucks and will never do it." 800 comments of that tit for tat in present tense. Still nothing learned.
Doesn't help that no one talks about exactly what they are doing and exactly how they are doing it, because capitalism vs open technology discussions meant to uplift the species.
> Doesn't help that no one talks about exactly what they are doing and exactly how they are doing it
Let me try a translation:
> I am using $model for writing software and its great.
I have generated an extremely simple javascript application that could have been mostly done by copy/paste from StackOverflow or even Geeks4Geeks and it runs.
This is true. I have a PWA that I generated with a LLM on my phone right now. It works. Pretty sure even w3schools would be ashamed to post that code.
> I am using $model for writing software and it sucks and will never do it.
This is also true. At work I have a 15 year old codebase where everything is custom.
You can't get a LLM to use it all as a context because you simply don't have ram for it so you can't even test the quality of advice given on it.
You can't train a LLM on it because you don't have the budget for it.
You maybe could get a LLM to generate code by prompting it "this is the custom object allocation function, these are the basic GUI classes, now generate me the boilerplate for this new dialog I'm supposed to do". Unfortunately it takes as long or longer than doing it yourself, and you can't trust the output to boot.
I mean this is just how social media works these days for anything
Our social hypemeter is broken beyond exaggeration
The single karpathy tweet launched hundreds of linkedin, youtube, substack thinkpieces, business articles- sometimes more than actual model releases
These days anything that gets our social attention is driven to 11
This is well written.
There is proof that AI isn't what they all make it to be, in the acquisitions of these companies. Why would Anthropic need Bun or OpenAI need windsurf for billions, if agents are all knowing and ready to replace devs?
This is a modern marketing, based on FUD and sensationalism
The more expressive AI talkers are the less they usually come from a tech background that can understand what the technology actually could do.
Someone mentioned to me they're like the historical paper boys who used to yell Extra Extra and announcing something trying to sell newspapers.
Its still not a Hype, its still crazy what is possible today and we still have no clear at all if this progress continues as it does or not with the implication, that if it continues, it has major implications.
My wife, who has no clue about coding at all, chatgpted a very basic android app only with guidance of chatgpt. She would never ever been able to do this in 5 hours or so without my guidance. I DID NOT HELP HER at all.
I'm 'vibecoding' stuff small stuff for sure, non critical things for sure but lets be honest, i'm transforming a handfull of sentences and requirements into real working code, today.
Gemini 3 and Claude Opus 4.5 def feel better than their prevous versions.
Do they still fail? Yeah for sure but thats not the point.
The industry continues to progress on every single aspect of this: Tooling like claude CLI, Gemini CLI, Intellij integration, etc., Context length, compute, inferencing time, quality, depth of thinking etc. there is no current plateau visible at all.
And its not just LLMs, its the whole ecosystem of Machine Learning stuff: Highhly efficient weather model from google, Alpha fold, AlphaZero, Roboticsmovement, Environment detection, Image segmentation, ...
And the power of claude for example, you will only get with learning how to use it. Like telling it your coding style, your expectations regarding tests etc. We often assume, that an LLM should just be the magic work collegue 10x programmer but its everything an dnothing. If you don't communicate well enough it is not helpful.
And LLMs are not just good in coding, its great in reformulating emails, analysing error messages, writing basic SVG files, explaining kubernetes cluster status, being a friend for some people (see character.ai), explaining research paper, finding research, summarizing text, the list is way to long.
Alone 2026 there will go so many new datacenters live which will add so much more compute again, that the research will continue to be faster and more efficient.
There is also no current bubble to burst, Google fights against Microsoft, Antrophic and co. while on a global level USA competets with China and the EU on this technology. The richest companies on the planet are investing in this tech and they did not do this with bitcoins because they understod that bitcoin is stupid. But AI is not stupid.
Or Machine learing is not stupid.
Do not underestimate the current status of AI tools we have, do not underestimate the speed, continues progress and potential exponential growth of this.
My timespan expecation for obvious advancments in AI is 5-15 years. Experts in this field predict already 2027/2030.
But to iterate over this: a few years ago no one would have had a good idea how we could transform basic text into complex code in such a robust way, which such diverse input (different language, missing specs, ...) . No one. Even 'just generating a website'.
> My wife, who has no clue about coding at all, chatgpted a very basic android app only with guidance of chatgpt. She would never ever been able to do this in 5 hours or so without my guidance. I DID NOT HELP HER at all.
you know Google used to have a app for this
https://www.youtube.com/watch?v=8ADwPLSFeY8
I swear people have forgotten how productive native programming 30 years ago was (Delphi, even VB)
compared to the disaster that is the web today
I know what app builders are but she talked to a computer system, told it what she wanted and it WALKED HER through all the steps and i think she used android studio.
She did all of this in a few hours and doesn't work with computers.
Literally all much of the business world needed was a slightly more capable VB but now we have a bunch of crappy, web browser based SaaS platforms instead.
There has been a legitimate hole after Excel, where Access, VB or other tools sat to help businesses grow.
When that hole wasn't as big, it seemed fewer software projects failed.
I think it really depends how a person judges the progress from chatgpt 3.5, 3 years ago to Opus 4.5.
In one light it is super impressive and amazing progress, in another light it is not impressive at all and totally over hyped.
Using the Hubert Dreyfus analogy. It is impressive if the goal is to climb as high as we can up giant tree. The height we have reached isn't impressive at all though if we are trying to climb the tree to get to the moon.
I keep in mind that even ChatGPT was unthinkable a few years ago and made a massive jump on human to computer communication and generic tasks resolve.
I also add interpolation to this.
Even if we assume for a moment everything you are saying is true and/or reasonable, can't you see how comments like these paint your position here in a bad light? It just reads a little desperate!
It might be just different viewpoints people don't understand?
I'm advocating for spending time with AI because it works already good enough and it continues to progress surprisingly fast. Unexperienced fast for me tbh.
If i say "AI is great" i also know when AI is also stupid but i'm already/stil so impressed that i can transform basic text into working go/java whatever code, that i accept that its not perfect just because I highly appreciate how fast we got this.
And it feels weird too tbh. It doesn't feel special to talk to an LLM and get code back somehow while this was unthinkable just a few years back.
Somethimes it likes you just forget about all these facts and have to remind yourself that this is something new.
Just because it’s “new” doesn’t mean it’s going to fulfill all our wildest fantasies. It’s becoming clear that these things are just… tools. Useful in certain situations, but ultimately not the game-changer they’re sold as.
For me its getting clear that there is so much broad ways of continues improvement, and constant speed, that if this continues like this, even a basic LLM can do a lot of jobs.
Just today cursor released a blog were they run an agent for a week and it build a browser.
Claude Code with subagents and hooks are really good too.
And it takes time to just get it and roll it out to everyone, it takes time to do research, experiments, it takes time to install GPUs and make them etc.
We are currently only limited by things we can progress on.
[dead]
[dead]
> X trackers and content blocked
> Your Firefox settings blocked this content from tracking you across sites or being used for ads.
Why is this website serving such crap?
For God's sake, if there is anything absolutely worth showing on X, just include a screenshot of it instead of subjecting us all to that malware.
I'm really surprised how much pushback and denial there is still from a lot of engineers.
This is truly impressive and not only hype.
Things have been impressive at least since April 2025.
Is this satire? This comment could not be a better example of what the linked article is talking about.
Not satire. The author is in denial of what's happening.
What is happening?
Not much. They can still parrot their training data. AGI is still 5-20 years away.