5 ms·

Is it all just vapourware?

98 points by Lyngbakr 2mo ago

EA-3167 2mo ago
The tech is real, the use cases are increasingly forced and fabricated to justify a ludicrous valuation that will never come to pass. For research and military applications ML is great, but it isn’t going to print trillions for anyone.
- cyanydeez 2mo ago
  I agree, the fact that with an open model I can be modifying go and react code that I'd never consider touching as a human who values their eyesight and come up with real patches, fixes and extensions of almost any project on github is truely fascinating and, addictive. I can absolutely see where this technology works; but like EVERYTHING THAT THESE VC FUNDED FASCISTS IGNORE, just because it works in the lab does not mean it works in real life. I can see exactly where this technology fails: it lets you spool out so much thread into the abyss that you're just going to keep refactoring everything, all the time and when it blows a hole in your project, whelllp! you wanted to refactor that too. Imagine having 100 side projects grossly built and still, you just want to move on. Fiishing projects are still going to need work and the explosion of "this is _my_ engineering harness" is everyone twiddling their thumbs cause real projects of significant value are still about scope and "total addressable market" and not "I made an AI to diddle children, so you dont have to" crowd.
mariocesar 2mo ago
The product is being launched before the value is clear. We've seen similar waves with new technologies before: overexposing the pros, dismissing the cons, hyper-optimism, and people using a lot of jargon without saying much of substance. The difference this time is the scale of the impact and the volume around it.
- chrisjj 2mo ago
  > The product is being launched before the value is clear. May I fix that for you? The product is being launched before the value is there.
robertclaus 2mo ago
The trouble is that the loudest voices will dominate, so the little measurable wins adding up in most organizations don't get attention.
gwilikz 2mo ago
Was ready for some interesting music theory or analysis on genres of music that somehow map to the sound of vaporwave... but of course it's just about LLMs.
simonw 2mo ago
When this article talks about ONA it means https://ona.com/ https://ona.com/ - a cloud agent service that was acquired by OpenAI a couple of months ago. (I wouldn't suggest basing my evaluation of the entire field of coding agents around that particular product.)
- iLoveOncall 2mo ago
  [flagged]
  - simonw 2mo ago
    What the heck? What product was I advertising here?
    - iLoveOncall 2mo ago
      The one you link to?
      - simonw 2mo ago
        You mean in the comment where I suggested that I didn't think it was a very good product? I posted this comment because I didn't know what the author meant by ONA and had to look it up myself.
Multiplayer 2mo ago
YMMV but I think with the SOTA models building a token efficient engineering loop is absolutely doable with (imho) solid development and testing practices. I see no reason to buy a 3rd party system for this either. I'm not in enterprise so don't come at me here - I'm a small shop and I'm not trying to corral 100 devs or whatever. We've got linear boards getting cards pushed and pulled, debated over by multiple models, coded, debated, tested, accepted, etc etc. True software factories now exist and they don't screw up the login.
- copperx 2mo ago
  > True software factories now exist That statement somehow amazes me. Obviously, LLMs need plenty of steering, but I don't get how a company can be built on that.
  - Multiplayer 2mo ago
    Small companies doing consulting certainly could. My use of the term "software factory" really implies a lot of automation in turning out useful tools for internal and external customers.
wewewedxfgdf 2mo ago
"The hard part of software engineering was never writing the code." Again, are we still on this ridiculous concept. I stopped reading at that sentence. Is that going to be the revisionist future that the industry tells itself - ""one day, LLMs came along and suddenly computers could program themselves, and it was an absolute revolution, but it made no difference at all to anything because "The hard part of software engineering was never writing the code." so people stopped using LLMs because of that. And that's how LLM's came to an end after being a short trend.""
- fellowniusmonk 2mo ago
  The hard part was the rote memorization of leetcode challenges and then learning to pattern match to the particular problem in a 5 minute technical interview. The second part was that the test was being administered by a gatekeeper who was hired before those practices were put in place. The 3rd was what? Amazon or Netflix burning your ass out because they are anti-human companies?
- satvikpendem 2mo ago
  A great article yesterday about this very concept: https://news.ycombinator.com/item?id=49222189 https://news.ycombinator.com/item?id=49222189
- preg_match 2mo ago
  I think it's true. Writing code is the most fun part of my job, but it's also the least time consuming. For any given feature, everything around the code takes 10x as much time. Getting the requirements, writing the spec, refining the spec, doing the QA work, delivery. The actual "coding" part in the middle is quick, fun, and creative. Since it's quick I get to sit and think about abstractions and performance, which is great. But, it could be even quicker if I just give up and willingly write shitty code that works. I don't do that, but I could, and I doubt anyone outside of close developers on my team would ever notice.
zatkin 2mo ago
I find it hard to buy this generalization about _all_ "AI"/agent software when the author has only provided _one_ example. A couple alternatives could've been explored, like Cursor Cloud Agents or even just running Claude Code with remote control on another machine. I'd also personally never spend a dime on any product unless I've read _some_ positive sentiment from online commentary, like Hacker News. To my point, Ona appears to have a pretty low amount of feedback that makes it difficult to justify any $20 bills: https://hn.algolia.com/?q=ona.com https://hn.algolia.com/?q=ona.com
grebc 2mo ago
It’s starting to resemble a pyramid scheme with Nvidia at the top, OpenAI & Anthropic beneath. That Nvidia finances a lot of this should give anyone with a clue on finance pause, that it doesn’t tells you you’re in the middle of a bubble.
firasd 2mo ago
I wonder if there is cargo culting afoot There are definitely guys in some companies just pointing an agent swarm at 50 Github tickets and saying "go get 'em boys" and hence need a lot of orchestration tools but for the rest of us do we really need the AI to do all the build steps and the testing steps... or do we just need the new feature that runs when the button is clicked and then we can check it out in the browser ourselves. The code gen is what I need the AI for, not the 'smoke tests' and the tsc finagling. I'm willing to spend some mental calories myself in figuring this feature out step by step Actually this makes me wonder if some people are just not very into building step by step like "okay first let's check the JSON shape the endpoint returns", "okay now let's make a simple form", etc
- Traubenfuchs 2mo ago
  > just pointing an agent swarm at 50 Github tickets and saying "go get 'em boys" I still don‘t know if this is real. If it works like that, where are the companies that only kept every tenth, 10x‘d AI enhanced dev? They should have significantly higher margins. The companies that keep all devs and 10x‘d them, finally bringing that backlog to 0 should have exploding revenue and profit. Where does AI create value? I can‘t see it. I use it every day, but nothing got faster.
  - makk 2mo ago
    The creation of downstream issues has gotten faster, in my experience. The rate at which shit is thrown against walls has also gotten faster.
    - msdz 2mo ago
      Exactly. If you can free engineering capacity from tedious busywork (fixing bugs), you have them available for implementing/delegating to implement experimental features into new revenue streams. Why fire anyone in this scenario? Growth is only going to keep coming.
  - deleted 2mo ago
    [deleted]
protimewaster 2mo ago
> I was optimistic, but once I had it wired up to one of my projects, instead of making magical hands-off progress on my todo list it spent nearly my entire $20 worth of “ona compute units”, whatever those are, thrashing and trying to get a hold of the todos from linear just so it could pick one to start. This is one of the reasons that I've simply not bothered with a lot of these types of AI products. It feels like gambling. Maybe I'll spend $20 on tokens and end up with something awesome. Or maybe I'll spend $20 on tokens and end up with nothing useful and then I'll be glad it was only $20 I lost.
trencedamp 2mo ago
> But so far most of what they do is make more annoying work for me. More integrations to debug, more auth tokens to refresh, more bills to keep track of, more meandering and drawn out descriptions of non-bugs with bogus fix suggestions and misinformed “root cause” analyses. It’s tiresome. God this times 1000. I'm so sick of having AI chase a bug and having to lead it by the hand like a toddler to try and help me solve bugs. The difference is, a toddler learns when you explain. An LLM holds your responses in context and uses them to generate more authentic sounding garbage, but next session, foomf, the lesson is unlearned again. I had a tiny problem with prerendering not working on a react site last night, I must have spent close to an hour running commands it asked me to run like a moron, verifying dumb things I had already checked like "did the file actually upload to ftp" or had I restarted Apache or was there some magic htaccess file somewhere. Eventually I just gave up on Claude and tried some different paths in Apache virtual host settings and it worked. Of course if I went back to Claude and reported that, as would be my instinct with a human, it would confidently explain why that was the bug, why it couldn't spot the issue, and how smart I am for finding it. And then it would forget everything tomorrow
- kristianc 2mo ago
  I suspect the issue there was Claude, especially Opus 5, which just hates the idea that it could ever be wrong about anything.
- wvenable 2mo ago
  > I'm so sick of having AI chase a bug and having to lead it by the hand like a toddler to try and help me solve bugs. This hasn't been my experience at all. I can give it a vague description of the problem and have it find it pretty easily without any more input from me. I do think there's a pretty big variation in tools and setups and what output people are getting. I'm now just using OpenAI Codex in VS Code and it churns through problems like they're nothing. Sometimes I have to get it to not over-engineer a solution; not because it's necessarily wrong but because I don't need that much correctness.
  - trencedamp 2mo ago
badlibrarian 2mo ago
It's August 9, 2026 and if you're a software engineer who hasn't had multiple "holy shit, I can't believe it just did that" moments, it's time to consider a new trade.
- uncivilized 2mo ago
  Not everyone is a web developer bub
  - badlibrarian 2mo ago
    Might I recommend HVAC or plumbing, it's honorable work and pays well. Trim trees if you've got the body for it. I don't recommend web work, the last ten years or the next ten. Wouldn't touch the stuff. I skipped the phone app era, too.
    - copperx 2mo ago
      Why is there honor in HVAC? Family honor?
      - esseph 2mo ago
        You're definitely doing something with a net good impact on people instead of making the next ad tracking software or camera image recognition loop.
  - wvenable 2mo ago
    https://news.ycombinator.com/item?id=49226923 https://news.ycombinator.com/item?id=49226923
  - pixelesque 2mo ago
    I had DeepSeek 4 Pro do a very good job yesterday of loop-unrolling and SIMD-ifying (both SSE/AVX and ARM Neon versions) some very old scalar Col3f image processing and resampling/resizing C++ code I hadn't touched in 12 years or so. It also wrote some unit tests that validated the kernel sampling weights, and wrote some Jupyter notebooks to go along with the kernel algorithms as comparisons. It's not just web dev... It helps (a lot in some cases) if you ask very specific things rather than just "make this vague thing", but I'm more and more coming round to the conclusion it is now a useful dev tool (until two months ago I was a sceptic).
solomonb 2mo ago
The churn in this space puts javascript to shame. As an example, its only been a few months and AFAICT no one is even talking about openclaw anymore.
- tripleee 2mo ago
  remember moltbook?
- copperx 2mo ago
  Maybe OpenClaw solved the problem it was designed to solve.
- hankbond 2mo ago
  I agree but how many developers did you know making heavy use of it? It always seemed like it was a poorly thought out experiment that gained a lot of traction and hype from the non-technical crowd. I don't say that to be elitist, I just think that non-technical users need a much more consistent and constrained product because they can't really fix and upstream things themselves (even with the use of agents). For all the hype it got, not a single person from my circle installed it to even check it out. I do agree that the current pace of abandonware creation is wild. I think a lot of projects are generated top down from an idea, and not bottom up through usage. If you have a new experimental project, and you don't have recent commits, I assume you are not using it and thus it has no value. I think agentic use is mostly only valuable as author extension (help you search, rubber duck, generate code but needs very heavy review). Over time with enough usage of a process I do think some of them can turn into author automation but not from simply writing down an idea. It takes lots and lots of executions, iterations, generalizations, specifications, basically lots of work to get any decently hands-off intelligent automation through agents.
- y1n0 2mo ago
  Did that get bought by openai? Lost its rogue cool factor.
  - Multiplayer 2mo ago
    Did not get bought by OpenAI. Creator was hired by OpenAI and they sponsor the project with tokens. OpenClaw is a non-profit now. The problem is really that the promise was so big but the management and implementation was so painful, coupled with non-stop updates, coupled with far too big of an implementation surface. A classic "lets solve 15 problems at once" situation, but none of them really well.
fhub 2mo ago
> Is it all just vapourware? No. Anyone making this claim is being disingenuous.
jeffreyrogers 2mo ago
I was fairly skeptical of agentic coding before I used it for a real product. Although I still have to be heavily involved in planning the code that LLMs write for me, they can write code much faster than I can, and they know more about edge cases than I do, so they can handle edge cases/subtle bugs that I would have missed. I have been paid to write code at every level of the stack from assembly to frontend javascript, but I'm not equally good at all those areas. In some areas I can still outperform LLMs, but for areas I'm weak they do a much better job than I would have. I still think of what I'm doing as software engineering, and I'm glad that I had many years of professional and hobby development before using agents since I think that's given me the ability to make good architectural decisions (and helps me resteer the LLMs when they want to do something suboptimal), but my involvement in actually writing code is quickly going to zero. That said, they aren't perfect and they still introduce bugs, but I believe the quality of my current product is higher than what I would have created pre-agentic coding. Things I've found helpful in keeping quality high: - Visual regression tests (detect UI bugs before you commit them) - Fuzz testing of interfaces and app behavior - Automatically add regression tests for any bug that I/the LLM fixes - Logging/alerting that tracks an errors/invariant violations triggered in the app - Performance metrics that are surfaced in a dashboard. All of these are very easy to add since the LLM can create this infrastructure for you. The fuzz testing in particular is something very few products I've previously worked on have since most people don't know how to implement it. I ran the fuzzers for a few minutes and they quickly caught multiple subtle bugs that I was not aware of. This is a real product that helps a real, non-VC funded service business, and although I could have made something similar myself it would have taken me a lot longer, be harder to use, and probably be less reliable. Edit: while it's true that you can quickly blow through the $20/month plan, the $200/month plan allows you to get a lot done and is basically sufficient for my needs. It's also very cheap when you consider what it would cost to pay someone to do similar work.
- IsTom 2mo ago
  Adding too many tests was a real issue before LLMs. You end up in situations where you when you add a feature there's 200 (out of e.g. 10k) tests that fail and you have to figure out which of them should fail and you need to fix them and which are actual bugs.
lordnacho 2mo ago
I don't know how you can claim it's all vapour ware. Two years ago, I couldn't just roughly describe my backlog and then have the code fixed. I had to type it out myself, run it, look at logs, fix toolchain issues, and so on. It was tedious. Or I could get a junior to do it. Now can get these things done quite fast, without concentrating nearly as hard. Clearly, it isn't vapour. It delivers something. That something we have yet to figure out the best way to use, but there's definitely something there that works. I get the feeling a lot of people are frustrated because the little gains are lost in organisational chaos, rather than the tools not working.
- mihaelm 2mo ago
  On your last point, I think it has a lot to do with how it's introduced in organizations. If everyone just goes hog wild with it, enamored with their newfound productivity, not only will the little gains be lost, I'd argue all the generated noise will be a net negative. And people will hate that. That's the result of AI adoption in a company being people just getting a subscription and doing their own thing, instead of systematically introducing and finding a common ground; a trivial example of that would be open source projects increasingly adopting LLM policies to get everyone on the same page.
20k 2mo ago
>If agentic development actually worked the way any of them say it does I think its fascinating just how much of a gap there is between what's being claimed, and the verifiable observable data of the open source world. Major open source projects are by and large starting to ban LLMs now, because the contributions made by LLM users have been universally terrible and unhelpful. There doesn't appear to be a single major project that's found generating code to lead to major productivity speedups, and the consensus appears to be that its just lead to a lot of crappy contributions that are harder to spot immediately as being obvious crap I regularly see people claim that they are now 10x more productive with LLM code generation, and I just wonder where all the code is. Is it somehow true that these gains are only being realised in proprietary projects, and not a single one of them has put even a small fraction of their new found engineering powers into eg Godot? Why do only the poor quality LLM code generation users make PRs to open source projects, and never the engineers that know how to really use it correctly? If you look in the open source major project space, you can find almost no evidence that AI code generation exists at all. Go browse your favourite critical tool and look for AI generated PRs that have landed in the codebase, its probably a tiny handful of them in comparison to the human written PRs prior to an LLM ban. It turns out that once you have a verifiable, open quality review bar, for some reason almost no LLM commits really meet the level of quality necessary I strongly suspect that what we're seeing is that much of the tech code-writing economy had already become completely performative prior to AI turning up. It no longer matters in the current age if your code is good, or works, because your job is to give the illusion of product development while the stock market price gets pumped, until you all cash out your share value, get bought, or hop jobs in 2 years. For many companies it literally does not matter if you produce anything that generates value (or works), because the illusion of progress is all that matters. AI is absolutely incredible at creating the illusion of progress, because it looks a whole lot like real code, it just appears to have failed the bar of making actual projects that work. If that was never the goal in the first place, it probably really is a 10x productivity boost
- xendo 2mo ago
  @antirez is a very prominent open source contributor that gets lot of shit done with LLMs. Mitchel Hashimoto is also open about using LLMs to speed up his work. There are some caveats attached: neither of them is doing crazy loops or graphs producing thousands of lines of code, they are both amazing software engineers and they know what they are doing.
storus 2mo ago
Writing meaningful and correct code was always difficult. That we know how to generate pointless CRUD or half-baked apps using agents doesn't mean we can do them well. It's probably sufficient for selling them as a business but far from being great.
gryfft 2mo ago
It's strange to me that the voices naysaying agentic coding capabilities seem to be getting louder in recent weeks. I almost wonder if there's a campaign to start suppressing public awareness of where SOTA capabilities really are.
- gmueckl 2mo ago
  The discontent is real. The deficiencies these people mention are real. And it's not actually getting better. Sure, web devs and CRUD app devs may be screwed over a bit harder now, but when it gets into really deep complex stuff, the usability of the output goes way, way down. This cliff is real. I assure you. And it's not getting better.
- weakfish 2mo ago
  Why is that strange? To me, it’s evidence of growing dissatisfaction with the direction of the field and frustration with being made to deal with the consequences of others bad work
  - y1n0 2mo ago
    It's really just evidence of what group of people are doing submissions at any given time.
satvikpendem 2mo ago
[flagged]
- y1n0 2mo ago
  I don't think you really deserved downvotes. Some people are more geared toward evangelizing technology (or evangelizing anything really), and some are not. I'm pretty much in the 'not' camp. I'll share my experiences and how I do things, but I'm not about to engage in arguments about it. If you don't want to use it, then don't. What I do I care?
  - satvikpendem 2mo ago
    Exactly. So I find the sort of blog posts as TFA here quite strange, like who are they arguing against? I just follow ones that talk about how they use the tools rather than meta debates on their usage.
MangoCoffee 2mo ago
agentic coding is real. If AI labs can take over the coding tool market, that's a billion+ market. LLMs work in coding, and AI labs can slowly expand into other white collar work. Vaporware? Hardly.
jamestimmins 2mo ago
Its reasonable to dislike a bad product experience, but its strange to draw a conclusion of AI altogether based on a tool with limited usage (I've never heard of it). That's like saying smart watches are useless based on trying out the smart watch made by will.i.am's tech company rather than Apple's.
nowcomeonnow 2mo ago
It seems nobody is user testing/pentesting their projects anymore. The notion of an MVP being good enough has been pushed a lot recently but it seems that the user experience of these MVPs has not been taken into consideration.
neuralkoi 2mo ago
AI is good at building "disposable" software. I think this category will grow specially for regular joes. There's no such thing as a free lunch, and anyone trying to build software without significant guardrails and insights into the process will have to give up control of their codebase. Ray Myers does a good job of exploring this topic in a recent Software Should Work talk, trying to answer: "Is code for people or AI?" [0] [0] https://www.youtube.com/watch?v=mZgglPK8Rg0 https://www.youtube.com/watch?v=mZgglPK8Rg0
vekntksijdhric 2mo ago
I stopped at "The hard part of software engineering was never writing the code." Better read https://blog.senko.net/code-was-never-the-hard-part-is-an-insult-to-all-programmers https://blog.senko.net/code-was-never-the-hard-part-is-an-in...
aogaili 2mo ago
I'm honestly not sure if the people writing those articles are in a different field or something. I have been coding for 20 years and there goes no day that doesn't leave me impressed. It's nothing short of magic. And in terms of productivity, features that took months are now being done in days. I'm not even sure what the author is talking about frankly. Am I missing something?
burnto 2mo ago
No, but a lot is. You see a version of this in every tech boom cycle, but this one is way more reflexive. Mature technical software projects are slow moving because they have real users building other real software and businesses with them. Their engineering involves navigating the ecosystem and dep and compatibility constraints. Any project moving super fast pumping out PRs either isn’t burdened/blessed with real usage OR doesn’t care about (reap real value from) the users it has. Related theory is that the LLM “labs” are actually not particularly incentivized to prioritize stable API surfaces. They want machine interfaces to constantly rapidly change so that we must depend on model based natural language surfaces to navigate the complexity.
RealWed5 2mo ago
Kira is probably too young (good for her! I am not cynical here) to remember how the software development worked when PHP just came out. We are at that point of time now, again. Next stop will be Perl: write only language. And then we will hit the "Java EE" wall. Again. And our LinkedIn will get red hot from recruiters looking for "experienced crisis devlopers".
mattboyle 2mo ago
Hey Kira! I'm Matt, I run Product & Engineering at Ona. First, thank you for trying the product and for taking the time to write this up. I shared the post with our product engineering team. There are several things in your experience that simply aren't good enough, and we're working on them. I've also credited $200 to your account in case you do want to explore further. To be concrete: > My very first encounter with the app was that I was unable to login on their desktop version at all. Auth is hard, so I can empathize and forgive this. Whilst I appreciate the forgiveness, we hold ourselves to a higher bar than this. We've done extensive testing of the desktop authentication flow and haven't yet been able to reproduce the failure you experienced. If you're willing, could you email me at matt at ona dot com? I'd like to grab some logs and work out what went wrong. > it spent nearly my entire $20 worth of “ona compute units”, whatever those are, thrashing and trying to get a hold of the todos from linear just so it could pick one to start. Looking through what happened, there were a few different things going on here. - Roughly a quarter of the OCUs were spent by our devcontainer setup agent. That agent created a PR which standardises the development environment and adds install, build and CI tasks so that future agents can operate in a reproducible environment. There is real value in doing that setup once, but we did a poor job of making it obvious that it was happening, why it was happening, and what you were paying for. We'll fix this. We've also switched that setup agent from Sol to Luna as of today after tuning it against our evals. This should make that setup substantially cheaper going forward. - The Linear flow also involved far too much friction. You went through multiple authentication and setup steps before the agent could actually get to the work you wanted it to do. That's not the experience we want. We have shipped a fix that lowers this friction already, and have a couple more planned (that will take a little longer). - OCUs themselves are our attempt to combine model and compute consumption into a single unit. If someone has paid us money and still can't tell what they're spending it on, that's a problem. We're actively revisiting how we explain and expose this. > This only adds more friction between me and my projects, which is literally the opposite of what I want when I pay for developer tooling. I agree completely. Today, Ona asks a lot of a new user before it has earned the right to ask for that investment: connect this integration, authenticate that service, let us configure the environment, understand what an OCU is. The thing we need to get better at is making the initial experience more boring: sign in, point Ona at something useful, and see it accomplish something valuable before you have to think about any of the machinery underneath. > The thing is I think ONA is a good idea. I am evidently willing to pay for this kind of tooling. But I want a version that works without lighting twenty dollar bills on fire. Based on your experience, I can see why you reached this conclusion. If you're open to it, I'd love to spend an hour with you to help you get Ona working on something useful and show we can achieve what we outline in our marketing. No expectation that it changes your opinion but I'd like the opportunity to learn from what went wrong and show you what the product should have felt like the first time. Email is as above. I look forward to hopefully connecting soon. - Matt
deleted 2mo ago
[deleted]

98 points by Lyngbakr 2mo ago

The tech is real, the use cases are increasingly forced and fabricated to justify a ludicrous valuation that will never come to pass. For research and military applications ML is great, but it isn’t going to print trillions for anyone.

cyanydeez 2mo ago
I agree, the fact that with an open model I can be modifying go and react code that I'd never consider touching as a human who values their eyesight and come up with real patches, fixes and extensions of almost any project on github is truely fascinating and, addictive. I can absolutely see where this technology works; but like EVERYTHING THAT THESE VC FUNDED FASCISTS IGNORE, just because it works in the lab does not mean it works in real life. I can see exactly where this technology fails: it lets you spool out so much thread into the abyss that you're just going to keep refactoring everything, all the time and when it blows a hole in your project, whelllp! you wanted to refactor that too. Imagine having 100 side projects grossly built and still, you just want to move on. Fiishing projects are still going to need work and the explosion of "this is _my_ engineering harness" is everyone twiddling their thumbs cause real projects of significant value are still about scope and "total addressable market" and not "I made an AI to diddle children, so you dont have to" crowd.

mariocesar 2mo ago

The product is being launched before the value is clear. We've seen similar waves with new technologies before: overexposing the pros, dismissing the cons, hyper-optimism, and people using a lot of jargon without saying much of substance. The difference this time is the scale of the impact and the volume around it.

chrisjj 2mo ago
> The product is being launched before the value is clear. May I fix that for you? The product is being launched before the value is there.

robertclaus 2mo ago

The trouble is that the loudest voices will dominate, so the little measurable wins adding up in most organizations don't get attention.

gwilikz 2mo ago

Was ready for some interesting music theory or analysis on genres of music that somehow map to the sound of vaporwave... but of course it's just about LLMs.

simonw 2mo ago

When this article talks about ONA it means https://ona.com/ https://ona.com/ - a cloud agent service that was acquired by OpenAI a couple of months ago. (I wouldn't suggest basing my evaluation of the entire field of coding agents around that particular product.)

iLoveOncall 2mo ago
[flagged]
- simonw 2mo ago
  What the heck? What product was I advertising here?
  - iLoveOncall 2mo ago
    The one you link to?
    - simonw 2mo ago
      You mean in the comment where I suggested that I didn't think it was a very good product? I posted this comment because I didn't know what the author meant by ONA and had to look it up myself.

Multiplayer 2mo ago

YMMV but I think with the SOTA models building a token efficient engineering loop is absolutely doable with (imho) solid development and testing practices. I see no reason to buy a 3rd party system for this either. I'm not in enterprise so don't come at me here - I'm a small shop and I'm not trying to corral 100 devs or whatever. We've got linear boards getting cards pushed and pulled, debated over by multiple models, coded, debated, tested, accepted, etc etc. True software factories now exist and they don't screw up the login.

copperx 2mo ago
> True software factories now exist That statement somehow amazes me. Obviously, LLMs need plenty of steering, but I don't get how a company can be built on that.
- Multiplayer 2mo ago
  Small companies doing consulting certainly could. My use of the term "software factory" really implies a lot of automation in turning out useful tools for internal and external customers.

wewewedxfgdf 2mo ago

"The hard part of software engineering was never writing the code." Again, are we still on this ridiculous concept. I stopped reading at that sentence. Is that going to be the revisionist future that the industry tells itself - ""one day, LLMs came along and suddenly computers could program themselves, and it was an absolute revolution, but it made no difference at all to anything because "The hard part of software engineering was never writing the code." so people stopped using LLMs because of that. And that's how LLM's came to an end after being a short trend.""

fellowniusmonk 2mo ago
The hard part was the rote memorization of leetcode challenges and then learning to pattern match to the particular problem in a 5 minute technical interview. The second part was that the test was being administered by a gatekeeper who was hired before those practices were put in place. The 3rd was what? Amazon or Netflix burning your ass out because they are anti-human companies?
satvikpendem 2mo ago
A great article yesterday about this very concept: https://news.ycombinator.com/item?id=49222189 https://news.ycombinator.com/item?id=49222189
preg_match 2mo ago
I think it's true. Writing code is the most fun part of my job, but it's also the least time consuming. For any given feature, everything around the code takes 10x as much time. Getting the requirements, writing the spec, refining the spec, doing the QA work, delivery. The actual "coding" part in the middle is quick, fun, and creative. Since it's quick I get to sit and think about abstractions and performance, which is great. But, it could be even quicker if I just give up and willingly write shitty code that works. I don't do that, but I could, and I doubt anyone outside of close developers on my team would ever notice.

zatkin 2mo ago

I find it hard to buy this generalization about _all_ "AI"/agent software when the author has only provided _one_ example. A couple alternatives could've been explored, like Cursor Cloud Agents or even just running Claude Code with remote control on another machine. I'd also personally never spend a dime on any product unless I've read _some_ positive sentiment from online commentary, like Hacker News. To my point, Ona appears to have a pretty low amount of feedback that makes it difficult to justify any $20 bills: https://hn.algolia.com/?q=ona.com https://hn.algolia.com/?q=ona.com

grebc 2mo ago

It’s starting to resemble a pyramid scheme with Nvidia at the top, OpenAI & Anthropic beneath. That Nvidia finances a lot of this should give anyone with a clue on finance pause, that it doesn’t tells you you’re in the middle of a bubble.

firasd 2mo ago

I wonder if there is cargo culting afoot There are definitely guys in some companies just pointing an agent swarm at 50 Github tickets and saying "go get 'em boys" and hence need a lot of orchestration tools but for the rest of us do we really need the AI to do all the build steps and the testing steps... or do we just need the new feature that runs when the button is clicked and then we can check it out in the browser ourselves. The code gen is what I need the AI for, not the 'smoke tests' and the tsc finagling. I'm willing to spend some mental calories myself in figuring this feature out step by step Actually this makes me wonder if some people are just not very into building step by step like "okay first let's check the JSON shape the endpoint returns", "okay now let's make a simple form", etc

Traubenfuchs 2mo ago
> just pointing an agent swarm at 50 Github tickets and saying "go get 'em boys" I still don‘t know if this is real. If it works like that, where are the companies that only kept every tenth, 10x‘d AI enhanced dev? They should have significantly higher margins. The companies that keep all devs and 10x‘d them, finally bringing that backlog to 0 should have exploding revenue and profit. Where does AI create value? I can‘t see it. I use it every day, but nothing got faster.
- makk 2mo ago
  The creation of downstream issues has gotten faster, in my experience. The rate at which shit is thrown against walls has also gotten faster.
  - msdz 2mo ago
    Exactly. If you can free engineering capacity from tedious busywork (fixing bugs), you have them available for implementing/delegating to implement experimental features into new revenue streams. Why fire anyone in this scenario? Growth is only going to keep coming.
- deleted 2mo ago
  [deleted]

protimewaster 2mo ago

> I was optimistic, but once I had it wired up to one of my projects, instead of making magical hands-off progress on my todo list it spent nearly my entire $20 worth of “ona compute units”, whatever those are, thrashing and trying to get a hold of the todos from linear just so it could pick one to start. This is one of the reasons that I've simply not bothered with a lot of these types of AI products. It feels like gambling. Maybe I'll spend $20 on tokens and end up with something awesome. Or maybe I'll spend $20 on tokens and end up with nothing useful and then I'll be glad it was only $20 I lost.

trencedamp 2mo ago

> But so far most of what they do is make more annoying work for me. More integrations to debug, more auth tokens to refresh, more bills to keep track of, more meandering and drawn out descriptions of non-bugs with bogus fix suggestions and misinformed “root cause” analyses. It’s tiresome. God this times 1000. I'm so sick of having AI chase a bug and having to lead it by the hand like a toddler to try and help me solve bugs. The difference is, a toddler learns when you explain. An LLM holds your responses in context and uses them to generate more authentic sounding garbage, but next session, foomf, the lesson is unlearned again. I had a tiny problem with prerendering not working on a react site last night, I must have spent close to an hour running commands it asked me to run like a moron, verifying dumb things I had already checked like "did the file actually upload to ftp" or had I restarted Apache or was there some magic htaccess file somewhere. Eventually I just gave up on Claude and tried some different paths in Apache virtual host settings and it worked. Of course if I went back to Claude and reported that, as would be my instinct with a human, it would confidently explain why that was the bug, why it couldn't spot the issue, and how smart I am for finding it. And then it would forget everything tomorrow

kristianc 2mo ago
I suspect the issue there was Claude, especially Opus 5, which just hates the idea that it could ever be wrong about anything.
wvenable 2mo ago
> I'm so sick of having AI chase a bug and having to lead it by the hand like a toddler to try and help me solve bugs. This hasn't been my experience at all. I can give it a vague description of the problem and have it find it pretty easily without any more input from me. I do think there's a pretty big variation in tools and setups and what output people are getting. I'm now just using OpenAI Codex in VS Code and it churns through problems like they're nothing. Sometimes I have to get it to not over-engineer a solution; not because it's necessarily wrong but because I don't need that much correctness.
- trencedamp 2mo ago

badlibrarian 2mo ago

It's August 9, 2026 and if you're a software engineer who hasn't had multiple "holy shit, I can't believe it just did that" moments, it's time to consider a new trade.

uncivilized 2mo ago
Not everyone is a web developer bub
- badlibrarian 2mo ago
  Might I recommend HVAC or plumbing, it's honorable work and pays well. Trim trees if you've got the body for it. I don't recommend web work, the last ten years or the next ten. Wouldn't touch the stuff. I skipped the phone app era, too.
  - copperx 2mo ago
    Why is there honor in HVAC? Family honor?
    - esseph 2mo ago
      You're definitely doing something with a net good impact on people instead of making the next ad tracking software or camera image recognition loop.
- wvenable 2mo ago
  https://news.ycombinator.com/item?id=49226923 https://news.ycombinator.com/item?id=49226923
- pixelesque 2mo ago
  I had DeepSeek 4 Pro do a very good job yesterday of loop-unrolling and SIMD-ifying (both SSE/AVX and ARM Neon versions) some very old scalar Col3f image processing and resampling/resizing C++ code I hadn't touched in 12 years or so. It also wrote some unit tests that validated the kernel sampling weights, and wrote some Jupyter notebooks to go along with the kernel algorithms as comparisons. It's not just web dev... It helps (a lot in some cases) if you ask very specific things rather than just "make this vague thing", but I'm more and more coming round to the conclusion it is now a useful dev tool (until two months ago I was a sceptic).

solomonb 2mo ago

The churn in this space puts javascript to shame. As an example, its only been a few months and AFAICT no one is even talking about openclaw anymore.

tripleee 2mo ago
remember moltbook?
copperx 2mo ago
Maybe OpenClaw solved the problem it was designed to solve.
hankbond 2mo ago
I agree but how many developers did you know making heavy use of it? It always seemed like it was a poorly thought out experiment that gained a lot of traction and hype from the non-technical crowd. I don't say that to be elitist, I just think that non-technical users need a much more consistent and constrained product because they can't really fix and upstream things themselves (even with the use of agents). For all the hype it got, not a single person from my circle installed it to even check it out. I do agree that the current pace of abandonware creation is wild. I think a lot of projects are generated top down from an idea, and not bottom up through usage. If you have a new experimental project, and you don't have recent commits, I assume you are not using it and thus it has no value. I think agentic use is mostly only valuable as author extension (help you search, rubber duck, generate code but needs very heavy review). Over time with enough usage of a process I do think some of them can turn into author automation but not from simply writing down an idea. It takes lots and lots of executions, iterations, generalizations, specifications, basically lots of work to get any decently hands-off intelligent automation through agents.
y1n0 2mo ago
Did that get bought by openai? Lost its rogue cool factor.
- Multiplayer 2mo ago
  Did not get bought by OpenAI. Creator was hired by OpenAI and they sponsor the project with tokens. OpenClaw is a non-profit now. The problem is really that the promise was so big but the management and implementation was so painful, coupled with non-stop updates, coupled with far too big of an implementation surface. A classic "lets solve 15 problems at once" situation, but none of them really well.

fhub 2mo ago

> Is it all just vapourware? No. Anyone making this claim is being disingenuous.

jeffreyrogers 2mo ago

I was fairly skeptical of agentic coding before I used it for a real product. Although I still have to be heavily involved in planning the code that LLMs write for me, they can write code much faster than I can, and they know more about edge cases than I do, so they can handle edge cases/subtle bugs that I would have missed. I have been paid to write code at every level of the stack from assembly to frontend javascript, but I'm not equally good at all those areas. In some areas I can still outperform LLMs, but for areas I'm weak they do a much better job than I would have. I still think of what I'm doing as software engineering, and I'm glad that I had many years of professional and hobby development before using agents since I think that's given me the ability to make good architectural decisions (and helps me resteer the LLMs when they want to do something suboptimal), but my involvement in actually writing code is quickly going to zero. That said, they aren't perfect and they still introduce bugs, but I believe the quality of my current product is higher than what I would have created pre-agentic coding. Things I've found helpful in keeping quality high: - Visual regression tests (detect UI bugs before you commit them) - Fuzz testing of interfaces and app behavior - Automatically add regression tests for any bug that I/the LLM fixes - Logging/alerting that tracks an errors/invariant violations triggered in the app - Performance metrics that are surfaced in a dashboard. All of these are very easy to add since the LLM can create this infrastructure for you. The fuzz testing in particular is something very few products I've previously worked on have since most people don't know how to implement it. I ran the fuzzers for a few minutes and they quickly caught multiple subtle bugs that I was not aware of. This is a real product that helps a real, non-VC funded service business, and although I could have made something similar myself it would have taken me a lot longer, be harder to use, and probably be less reliable. Edit: while it's true that you can quickly blow through the $20/month plan, the $200/month plan allows you to get a lot done and is basically sufficient for my needs. It's also very cheap when you consider what it would cost to pay someone to do similar work.

IsTom 2mo ago
Adding too many tests was a real issue before LLMs. You end up in situations where you when you add a feature there's 200 (out of e.g. 10k) tests that fail and you have to figure out which of them should fail and you need to fix them and which are actual bugs.

lordnacho 2mo ago

I don't know how you can claim it's all vapour ware. Two years ago, I couldn't just roughly describe my backlog and then have the code fixed. I had to type it out myself, run it, look at logs, fix toolchain issues, and so on. It was tedious. Or I could get a junior to do it. Now can get these things done quite fast, without concentrating nearly as hard. Clearly, it isn't vapour. It delivers something. That something we have yet to figure out the best way to use, but there's definitely something there that works. I get the feeling a lot of people are frustrated because the little gains are lost in organisational chaos, rather than the tools not working.

mihaelm 2mo ago
On your last point, I think it has a lot to do with how it's introduced in organizations. If everyone just goes hog wild with it, enamored with their newfound productivity, not only will the little gains be lost, I'd argue all the generated noise will be a net negative. And people will hate that. That's the result of AI adoption in a company being people just getting a subscription and doing their own thing, instead of systematically introducing and finding a common ground; a trivial example of that would be open source projects increasingly adopting LLM policies to get everyone on the same page.

20k 2mo ago

>If agentic development actually worked the way any of them say it does I think its fascinating just how much of a gap there is between what's being claimed, and the verifiable observable data of the open source world. Major open source projects are by and large starting to ban LLMs now, because the contributions made by LLM users have been universally terrible and unhelpful. There doesn't appear to be a single major project that's found generating code to lead to major productivity speedups, and the consensus appears to be that its just lead to a lot of crappy contributions that are harder to spot immediately as being obvious crap I regularly see people claim that they are now 10x more productive with LLM code generation, and I just wonder where all the code is. Is it somehow true that these gains are only being realised in proprietary projects, and not a single one of them has put even a small fraction of their new found engineering powers into eg Godot? Why do only the poor quality LLM code generation users make PRs to open source projects, and never the engineers that know how to really use it correctly? If you look in the open source major project space, you can find almost no evidence that AI code generation exists at all. Go browse your favourite critical tool and look for AI generated PRs that have landed in the codebase, its probably a tiny handful of them in comparison to the human written PRs prior to an LLM ban. It turns out that once you have a verifiable, open quality review bar, for some reason almost no LLM commits really meet the level of quality necessary I strongly suspect that what we're seeing is that much of the tech code-writing economy had already become completely performative prior to AI turning up. It no longer matters in the current age if your code is good, or works, because your job is to give the illusion of product development while the stock market price gets pumped, until you all cash out your share value, get bought, or hop jobs in 2 years. For many companies it literally does not matter if you produce anything that generates value (or works), because the illusion of progress is all that matters. AI is absolutely incredible at creating the illusion of progress, because it looks a whole lot like real code, it just appears to have failed the bar of making actual projects that work. If that was never the goal in the first place, it probably really is a 10x productivity boost

xendo 2mo ago
@antirez is a very prominent open source contributor that gets lot of shit done with LLMs. Mitchel Hashimoto is also open about using LLMs to speed up his work. There are some caveats attached: neither of them is doing crazy loops or graphs producing thousands of lines of code, they are both amazing software engineers and they know what they are doing.

storus 2mo ago

Writing meaningful and correct code was always difficult. That we know how to generate pointless CRUD or half-baked apps using agents doesn't mean we can do them well. It's probably sufficient for selling them as a business but far from being great.

gryfft 2mo ago

It's strange to me that the voices naysaying agentic coding capabilities seem to be getting louder in recent weeks. I almost wonder if there's a campaign to start suppressing public awareness of where SOTA capabilities really are.

gmueckl 2mo ago
The discontent is real. The deficiencies these people mention are real. And it's not actually getting better. Sure, web devs and CRUD app devs may be screwed over a bit harder now, but when it gets into really deep complex stuff, the usability of the output goes way, way down. This cliff is real. I assure you. And it's not getting better.
weakfish 2mo ago
Why is that strange? To me, it’s evidence of growing dissatisfaction with the direction of the field and frustration with being made to deal with the consequences of others bad work
- y1n0 2mo ago
  It's really just evidence of what group of people are doing submissions at any given time.

satvikpendem 2mo ago

[flagged]

y1n0 2mo ago
I don't think you really deserved downvotes. Some people are more geared toward evangelizing technology (or evangelizing anything really), and some are not. I'm pretty much in the 'not' camp. I'll share my experiences and how I do things, but I'm not about to engage in arguments about it. If you don't want to use it, then don't. What I do I care?
- satvikpendem 2mo ago
  Exactly. So I find the sort of blog posts as TFA here quite strange, like who are they arguing against? I just follow ones that talk about how they use the tools rather than meta debates on their usage.

MangoCoffee 2mo ago

agentic coding is real. If AI labs can take over the coding tool market, that's a billion+ market. LLMs work in coding, and AI labs can slowly expand into other white collar work. Vaporware? Hardly.

jamestimmins 2mo ago

Its reasonable to dislike a bad product experience, but its strange to draw a conclusion of AI altogether based on a tool with limited usage (I've never heard of it). That's like saying smart watches are useless based on trying out the smart watch made by will.i.am's tech company rather than Apple's.

nowcomeonnow 2mo ago

It seems nobody is user testing/pentesting their projects anymore. The notion of an MVP being good enough has been pushed a lot recently but it seems that the user experience of these MVPs has not been taken into consideration.

neuralkoi 2mo ago

AI is good at building "disposable" software. I think this category will grow specially for regular joes. There's no such thing as a free lunch, and anyone trying to build software without significant guardrails and insights into the process will have to give up control of their codebase. Ray Myers does a good job of exploring this topic in a recent Software Should Work talk, trying to answer: "Is code for people or AI?" [0] [0] https://www.youtube.com/watch?v=mZgglPK8Rg0 https://www.youtube.com/watch?v=mZgglPK8Rg0

vekntksijdhric 2mo ago

I stopped at "The hard part of software engineering was never writing the code." Better read https://blog.senko.net/code-was-never-the-hard-part-is-an-insult-to-all-programmers https://blog.senko.net/code-was-never-the-hard-part-is-an-in...

aogaili 2mo ago

I'm honestly not sure if the people writing those articles are in a different field or something. I have been coding for 20 years and there goes no day that doesn't leave me impressed. It's nothing short of magic. And in terms of productivity, features that took months are now being done in days. I'm not even sure what the author is talking about frankly. Am I missing something?

burnto 2mo ago

No, but a lot is. You see a version of this in every tech boom cycle, but this one is way more reflexive. Mature technical software projects are slow moving because they have real users building other real software and businesses with them. Their engineering involves navigating the ecosystem and dep and compatibility constraints. Any project moving super fast pumping out PRs either isn’t burdened/blessed with real usage OR doesn’t care about (reap real value from) the users it has. Related theory is that the LLM “labs” are actually not particularly incentivized to prioritize stable API surfaces. They want machine interfaces to constantly rapidly change so that we must depend on model based natural language surfaces to navigate the complexity.

RealWed5 2mo ago

Kira is probably too young (good for her! I am not cynical here) to remember how the software development worked when PHP just came out. We are at that point of time now, again. Next stop will be Perl: write only language. And then we will hit the "Java EE" wall. Again. And our LinkedIn will get red hot from recruiters looking for "experienced crisis devlopers".

mattboyle 2mo ago

Hey Kira! I'm Matt, I run Product & Engineering at Ona. First, thank you for trying the product and for taking the time to write this up. I shared the post with our product engineering team. There are several things in your experience that simply aren't good enough, and we're working on them. I've also credited $200 to your account in case you do want to explore further. To be concrete: > My very first encounter with the app was that I was unable to login on their desktop version at all. Auth is hard, so I can empathize and forgive this. Whilst I appreciate the forgiveness, we hold ourselves to a higher bar than this. We've done extensive testing of the desktop authentication flow and haven't yet been able to reproduce the failure you experienced. If you're willing, could you email me at matt at ona dot com? I'd like to grab some logs and work out what went wrong. > it spent nearly my entire $20 worth of “ona compute units”, whatever those are, thrashing and trying to get a hold of the todos from linear just so it could pick one to start. Looking through what happened, there were a few different things going on here. - Roughly a quarter of the OCUs were spent by our devcontainer setup agent. That agent created a PR which standardises the development environment and adds install, build and CI tasks so that future agents can operate in a reproducible environment. There is real value in doing that setup once, but we did a poor job of making it obvious that it was happening, why it was happening, and what you were paying for. We'll fix this. We've also switched that setup agent from Sol to Luna as of today after tuning it against our evals. This should make that setup substantially cheaper going forward. - The Linear flow also involved far too much friction. You went through multiple authentication and setup steps before the agent could actually get to the work you wanted it to do. That's not the experience we want. We have shipped a fix that lowers this friction already, and have a couple more planned (that will take a little longer). - OCUs themselves are our attempt to combine model and compute consumption into a single unit. If someone has paid us money and still can't tell what they're spending it on, that's a problem. We're actively revisiting how we explain and expose this. > This only adds more friction between me and my projects, which is literally the opposite of what I want when I pay for developer tooling. I agree completely. Today, Ona asks a lot of a new user before it has earned the right to ask for that investment: connect this integration, authenticate that service, let us configure the environment, understand what an OCU is. The thing we need to get better at is making the initial experience more boring: sign in, point Ona at something useful, and see it accomplish something valuable before you have to think about any of the machinery underneath. > The thing is I think ONA is a good idea. I am evidently willing to pay for this kind of tooling. But I want a version that works without lighting twenty dollar bills on fire. Based on your experience, I can see why you reached this conclusion. If you're open to it, I'd love to spend an hour with you to help you get Ona working on something useful and show we can achieve what we outline in our marketing. No expectation that it changes your opinion but I'd like the opportunity to learn from what went wrong and show you what the product should have felt like the first time. Email is as above. I look forward to hopefully connecting soon. - Matt

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