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
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.
If it was successful, they wouldnt be telling everyone about it
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.
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
Reddit is like 90% astroturfing, trolls, and bots.
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.
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 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
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.
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
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.
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.
However getting the AI to build production quality code is sometimes quite frustrating, and requires a very hands-on approach.
Welcome to the internet
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.
It doesn’t guarantee the skeptics are wrong all the time.
Neither argument works
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.
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.
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) 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.
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.
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.
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.
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.
[1] to farm reward points to get cosmetic items in video games
Of course you can also get rich selling scams.
But yes, someone else said that as soon as any of these get to AGI you will not be able to use it.
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.
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.
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.
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 hope you have a better day tomorrow than whatever was going on with you when you wrote your comment.
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}}"
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.
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 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.
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.
https://github.com/schoenenbach/thermal-bridge https://thermal-bridge.streamlit.app/
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.
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.
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.
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.
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.
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?”
- 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.
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.
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.
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.
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.
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.
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.
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.
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.
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...
Anyway, I'll worry when the dead weight disappears and ceases to be replaced. Shields and energy reserves are critical, etc.
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)
Sitting 2 hours with an Ai agent developing end to end products does.
> The tech community must shift its admiration back toward reproducible results and away from this “trust-me-bro” culture.
Well said, in my opinion.
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.
> 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?
Claiming the steroids they’re taking are doing all the work and they don’t need to put in work anymore.
Masks during Covid and LLMs, used as political pawns. It’s kind of sad.
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...
“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.
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.
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
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
Someone mentioned to me they're like the historical paper boys who used to yell Extra Extra and announcing something trying to sell newspapers.
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'.
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
She did all of this in a few hours and doesn't work with computers.
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 also add interpolation to this.
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.
> 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.
This is truly impressive and not only hype.
Things have been impressive at least since April 2025.