6 ms·

Three kinds of AI products work

• 8organicbits 11mo ago
  > It’s easy to verify changes by running tests or checking if the code compiles This is actually a low bar, when the agent wrote those tests.
• baxtr 11mo ago
  From the article: > Summary By my count, there are three successful types of language model product: - Chatbots like ChatGPT, which are used by hundreds of millions of people for a huge variety of tasks - Completions coding products like Copilot or Cursor Tab, which are very niche but easy to get immediate value from - Agentic products like Claude Code, Codex, Cursor, and Copilot Agent mode, which have only really started working in the last six months On top of that, there are two kinds of LLM-based product that don’t work yet but may soon: - LLM-generated feeds - Video games that are based on AI-generated content
• deleted 11mo ago
  [deleted]
• Shebanator 11mo ago
  Author forgot about image, video, and music creation. These have all been quite successfully commercially, though maybe not as much artistically.
  • carsoon 11mo ago
    Recent articles seem only to mean LLMs when they reference AI. There are tons of commercial usecases for other models. Image Classification models, Image Generation models (traditionally difusion models, although some do use llm for image now), TTS models, Speach Transcription, translation models, AI driving models(autopilot), AI risk assessment for fraud, 3D structural engineering enhancement models. With many of the good usecases of AI the end user doesn't know that ai exists and so it doesn't feel like there is AI present.
    • qayxc 11mo ago
      > With many of the good usecases of AI the end user doesn't know that ai exists and so it doesn't feel like there is AI present. This! The best technology is the one that you don't notice and that doesn't get in the way. A prominent example is the failure of the first generation of smart phones: they only took off once someone (Apple) managed to the hide OS and its details properly from the user. We need the same for AI - chat is simply not a good interface for every use case.
• wongarsu 11mo ago
  This seems to be biased heavily towards products that look like an LLM. And yes, only a small number of those work. But that's because if your product is a thing I chat with, it immediately is in competition with ChatGPT/Claude/Grok/etc, leading to everything the article expressed. But those are hardly the only use cases for LLMs, let alone AI (whatever people nowadays mean by AI) To name some of the obvious counter-examples, Grammarly and Deepl are both AI (and now partially LLM-based) products that don't fit any of the categories in the post, but seem pretty successful to me. Lots of successful applications of Vison-LLMs in document scanning too, whether you are deciphering handwritten text or just trying to get structured data out of pdfs.
  • themanmaran 11mo ago
    Perhaps I'm biased since we're in a document heavy industry, but I think the original post misses a lot of the non-tech company use cases. An insane percentage of human time is spent copy pasting things from documents.
    • dbreunig 11mo ago
      Agree. I bucket things into three piles: 1. Batch/Pipeline: Processing a ton of things, with no oversight. Document parsing, content moderation, etc. 2. AI Features: An app calls out to an AI-powered function. Grammarly might pass out a document for a summary, a CMS might want to generate tags for a post, etc. 3. Agents: AI manages the control flow. So much of discussion online is heavily focused towards agents so that skews the macro view, but these patterns are pretty distinct.
  • echelon 11mo ago
    > One other thing I haven’t mentioned is image generation. Is this part of a chatbot product, or a tool in itself? Frankly, I think AI image generation is still more of a toy than a product, but it’s certainly seeing a ton of use. There’s probably some fertile ground for products here, if they can successfully differentiate themselves from the built-in image generation in ChatGPT. This guy is so LLM-biased that he's missing the entire media gen ecosystem. I feel like image, video, music, voice, and 3D generation are a much bigger deal than text. Text and code are mundane compared to rich signals. These tools are production ready today and can accomplish design, marketing, previz, concept art, game assets, web design, film VFX. It's incredibly useful. As a tool. Today. Don't sleep on generative media.
• bix6 11mo ago
  On agents it’s interesting but not surprising coding has seen so much initial success. Personally I’m waiting for better O365 and SharePoint agents. I think there’s a lot of automation and helper potential there.
  • airstrike 11mo ago
    I'm building an opinionated take on this. It's shaping up nicely. If you're a Rust developer reading this, interested in AI + GUI + Enterprise SaaS, and wants to talk, I'm building a team as we speak. E-mail in profile.
    • bix6 11mo ago
      So like an o365 ServiceNow?
      • airstrike 11mo ago
        Not quite. It's a desktop GUI
  • esseph 11mo ago
    At this point MS should probably sunset SharePoint and try again.
    • bix6 11mo ago
      How come?
• torlok 11mo ago
  So the only AI products that work is a chat bot you can talk to, or a chat bot that can perform tasks for you. Next thing you'll tell me is that the only businesses that work are ones where you can ask somebody to do something for you in exchange for money.
  • owenpalmer 11mo ago
    > Next thing you'll tell me is that the only businesses that work are ones where you can ask somebody to do something for you in exchange for money. What other type of business is there?
    • hobs 11mo ago
      That is the joke.
      • gordonhart 11mo ago
        The best kind of businesses are the ones I don’t have to ask; they’ve already built a better product than what I would have asked for. That’s kinda the point the OP is making about chat vs a [good] dedicated interface.
  • ohyoutravel 11mo ago
    Realistically there are only four types of businesses writ large: tourism, food service, railroads, and sales. People building AI-based products should focus on those verticals.
    • lelandbatey 11mo ago
      Really only two kinds: - Energy generation and - Expending energy to convince the folks generating energy to give you money for activating their neurons (food service, entertainment, tourism, transportation, sales). Any other fun ways to compartmentalize an economy?
    • tehjoker 11mo ago
• theptip 11mo ago
  I think this is kind of like saying “Only three kinds of internet products work, SaaS, webpages, and mobile apps” At the level of granularity selected, maybe true. But too coarse to make any interesting distinctions or predictions.
• Aldipower 11mo ago
  In my current project the agent (GPT-5) isn't helpful at all. Damn thing, lying all the time to me.
  • kevin_thibedeau 11mo ago
    They're idiot savants. Use them for their strengths. Know their weaknesses.
    • Aldipower 11mo ago
      So, what are their strengths then? I've fed it with a detailed, very well documented and typed API description. Asking to construct me some not too hard code snippets based on that. GPT-5 then pretend to do the right thing, but actually is creating meaningless nonsense out of it. Even after I tried to reiterate and refine my tasks. Every junior dev is waaay better.
      • ohyoutravel 11mo ago
        Parsing a thousand line stack trace and telling me what the problem was. Writing regexes. Spitting out ffmpeg commands.
      • gherkinnn 11mo ago
        I recently had something no longer compile. I got bored sniffing around after maybe an hour, set Claude in Zed on to it, got a snack, and by the time I was back it had found the problem. When I am unsure how to implement something, I give an LMM a rough description and then tell it to ask me five questions it needs to get a good solution. More often than not, that uncovers a blind spot. LLMs remain unhelpful at writing code beyond trivial tasks though.
• skerit 11mo ago
  The article claims Claude Sonnet 3.5 was released less than 9 months ago, but this is wrong. Claude 3.5 was released in june 2024. Maybe he has been writing this article for a while, maybe he meant Claude Code or Claude 4.0
  • simonw 11mo ago
    He meant Sonnet 3.7 which was released on the same day as Claude Code, Feb 24th 2025: https://www.anthropic.com/news/claude-3-7-sonnet https://www.anthropic.com/news/claude-3-7-sonnet With hindsight, given that Claude Code turned into a billion dollar precut category, it was a bit of a miss bundling those two announcements together like that!
• SirensOfTitan 11mo ago
  I’ve been working on a learning / incremental reading tool for a while, and I’ve found LLM and LLM adjacent tech useful, but as ways of resolving ambiguity within a product that doesn’t otherwise show any use of LLM. It’s like LLM-as-parser.
  • owenpalmer 11mo ago
    Is there somewhere I can try the tool out? I'm interested in that kind of thing.
• zkmon 11mo ago
  >> in five years time most internet users will spend a big part of their day scrolling an AI-generated feed. Yep. Looking forward to the future where you can eat plastic pop-corn while watching the AI-generated video feeds.
  • pixl97 11mo ago
    Why 5 years, I'm pretty sure we're there today.
    • jongjong 11mo ago
      Yeah the popcorn probably has microplastics in it.
  • vorticalbox 11mo ago
    By Ai generated feeds do you mean a feed that is just full of AI posts or an AI generating a feed to one can scroll?
• koliber 11mo ago
  A few more seem to work as well, because I've used them and found them valuable - human language translation - summarization - basic content generation - spoken language transcription
  • loloquwowndueo 11mo ago
    > basic content generation Dunno, man, I can spot ai-generated content a mile away, it tends to be incredibly useless so once I spot it, I’ll run in the opposite direction.
    • HelloUsername 11mo ago
      > once I spot it Exactly; pretty sure you've seen media or read text that you thought was human created..
    • carsoon 11mo ago
      You spot bad ai content. Since there is no button that will tell you if something was Ai generated you never know if what you read was/wasn't.
      • loloquwowndueo 11mo ago
        Wow didn’t take long for the machine fanbois to show up.
    • koliber 11mo ago
      I hate what LLM spit out and would never accept the whole output verbatim. I love how they occasionally come up with a turn of phrase, a thought path, or surprising perspective. I work with them iteratively to brainstorm, transform, and crate compose content that I incorporate into my own work. Regarding spotting AI-generate content, I was once accused of posting AI-generated content where I bona-fide typed every single letter myself without as much as glancing at an LLM. People's confidence in spotting AI content will vary and err on fake-positives and fake-negatives too. My kids now think all CG movies are AI generated, even the ones that pre-date image and video gen. They're pretty sure it's AI though.
• renewiltord 11mo ago
  The classic problem that online commenters face is that they only know products that are on Hacker News and Reddit. And I get why. Not being plugged into anything the only way to get information is social media so you only know social media. E.g. https://www.thomsonreuters.com/en/press-releases/2025/september/thomson-reuters-acquires-additive-a-specialist-in-ai-powered-tax-document-processing https://www.thomsonreuters.com/en/press-releases/2025/septem... B2B AI company, 2 years in sold for hundreds of millions, not an agent, chatbot, or completion. Do you know it exists? No. You only read Hacker News. How could you know?
  • Dilettante_ 11mo ago
    Additive’s GenAI-native platform streamlines the repetitive, time-consuming task of ingesting and parsing pass-through entity documents From TFA: There’s another kind of agent that isn’t about coding: the research agent. LLMs are particularly good at tasks like “skim through ten pages of search results” or “keyword search this giant dataset for any information on a particular topic”.
  • PopAlongKid 11mo ago
    >The company’s [Additive] technology automates complex tasks such as extracting footnotes from K-1s, K-3s, and related forms, so every staff member can become a reviewer and complete work that used to take weeks in a matter of hours. Any tax professional who takes weeks to enter footnote info from a K-1 form into their professional tax prep software is probably just as bad at other job-related tasks and either needs more training or to find another job.
• larodi 11mo ago
  More than three kinds are then actually listed in the article
  • shermantanktop 11mo ago
    Formatting did not help. Three kinds, but then subheadings in the same size font, and then here come two more kinds, plus a side journey into various topics.
• adammarples 11mo ago
  >I think there are serious ethical problems with this kind of product. Unless there are serious ethical problems with people generating arbitrary text ie. Writing - then no there isn't
• bob1029 11mo ago
  Chatbot is the only one I agree with (human in the loop). Agents are essentially the chatbot, but without the human in the loop. Chatbot without human in the loop is a slop factory. Things like "multi-agent systems" are a clever ploy to get you to burn tokens and ideally justify all this madness. Copilot/completion does not work in business terms for me. It looks like it works and it might feel like it's working in some localized technical sense, but it does not actually work on strategic timescales with complex domains in such a way that a customer would eventually be willing to pay you money for the results. The hypothesis that work/jobs will be created due to sloppy AI is proving itself out very quickly. I think "completion" tools like classic IntelliSense are still at the peak of efficiency.
  • mrweasel 11mo ago
    Chatbot in many environment simply doesn't work, because we won't let them and if we did, they'd be agents. Here I'm mostly thinking in terms of things like customer service chats. A chatbot that can't reach into other systems are essentially only useful for role playing. The copilot/completion thing also doesn't work for me. I have no doubt that a lot of developers are having a lot of benefits from the coding LLMs, but I can't make them work. I think one glaring obvious missing kind of AI is medical image recognition, which is already deployed and working in many scenarios.
• happyopossum 11mo ago
  Very myopic view here - agents are turning out useful output in many fields outside of coding..
  • Xiol 11mo ago
    Such as?
    • carsoon 11mo ago
      Legal seems to be a big usecase for AI. I think more for simplification and classification versus generation though.
• ZeroConcerns 11mo ago
  Well, the elephant in the room here is that the generic AI product that is being promised, i.e. "you get into your car in the morning, and on your drive to the office dictate your requirements for one of the apps that is going to guarantee your retirement, in order to find it completely done, rolled out to all the app stores and making money already once you arrive" isn't happening anytime soon, if ever, yet everyone pretty much is acting like it's already there. Can "AI" in its current form deliver value? Sure, and it absolutely does but it's more in the form of "several hours saved per FTE per week" than "several FTEs saved per week". The way I currently frame it: I have a Claude 1/2-way-to-the-Max subscription that costs me 90 Euros a month. And it's absolutely worth it! Just today, it helped me debug and enhance my iSCSI target in new and novel ways. But is it worth double the price? Not sure yet...
  • madeofpalk 11mo ago
    The other part to this is that LLMs as a technology definitely has some value as a foundation to build features/products on other than chat bots. But unclear to be whether that value can sustain current valuations. Is a better de-noisier algorithm in Adobe Lightroom worth $500 billion?
    • ansgri 11mo ago
      A bit off-topic, but denoise in LR is like 3 years behind the purpose-built products like Topaz, so a bad example. They've added any ML-based denoise to it when, like a year ago?
    • ZeroConcerns 11mo ago
      > Is a better de-noisier algorithm in Adobe Lightroom worth $500 billion? No. But: a tool that allows me to de-noise some images, just by uploading a few samples and describing what I want to change, just might be? Even more so, possibly, if I can also upload a desired result and let the "AI" work on things until it matches that? But also: cool, that saves me several hours per week! Not: oh, wow, that means I can get rid of this entire department...
  • pixl97 11mo ago
• websap 11mo ago
  > Users simply do not want to type out “hey, can you increase the font size for me” when they could simply hit “ctrl-plus” or click a single button3. I would def challenge this. “Turn off private relay”, “send this photo to X”, “Add a pit stop at a coffee shop along the way” are all voice commands I would love to use
  • chrisweekly 11mo ago
    Yes, this! esp the last one. Finding coffee shop / restaurant options ALONG THE WAY seems like it should've been solved years ago. Scenario: while driving, "want to eat in about an hour, must have vegetarian options, don't add more than 10m extra drive time" and get a shortlist to pick from.
    • hencq 11mo ago
      Yeah that one is surprisingly difficult even with a Human Intelligence in the passenger seat.
  • Mikhail_Edoshin 11mo ago
    Old Apple Newton had a feature, I don't remember how they called it, but on any screen you could write "please", and then describe what to do, e. g. using one of their examples: "please fax this to Bob". And it worked. Internally it was a rather simple keyword match plus access to data, such as the system address book. New applications could register their own names for actions and relevant dictionaries.
• levocardia 11mo ago
  Very obviously missing the mundane agentic work. I think the following things are basically already solved, and are just waiting for the right harness: - Call this government service center, wait on hold for 45 minutes, then when they finally answer, tell them to reactivate my insurance marketplace account that got wrongly deleted. - Find a good dentist within 2mi from my house, call them to make sure they take my insurance, and book an appointment sometime in the next two weeks no earlier than 11am - Figure out how I'm going to get from Baltimore to Boston next Thursday, here's $100 and if you need more, ask me. - I want to apply a posterizing filter in photoshop, take control of my mouse for the next 10sec and show me where it is in the menu - Call that gym I never go to and cancel my membership
  • input_sh 11mo ago
    Basically already solved = you've never used it for any of those purposes and have no idea if or how well would they work?
  • irq-1 11mo ago
    > - Find a good dentist within 2mi from my house, call them to make sure they take my insurance, and book an appointment sometime in the next two weeks no earlier than 11am The web caused dentists to make websites, but they don't post their appointment calendar; they don't have to. Will AI looking for appointments cause businesses to post live, structured data (like calendars)? The complexity of scheduling and multiple calendars is perfect for an AI solution. What other AI uses and interactive systems will come soon? - Accounting: generate balance sheets, audit in real-time, and have human accountants double check it (rather than doing) - Correspondence: create and send notifications of all sorts, and consume them - Purchase selection: shifting the lack of knowledge about products in the customers favor - Forms: doing taxes or applying for a visa
    • qayxc 11mo ago
      The problem is that we're reverting back to the stone age by throwing unnecessary resources at problems that have a simple and effective solution: open, standardised, and accessible APIs. We wouldn't need to use an expensive (compute-wise) AI agent to do things like making appointments. Especially if in the end you'd end up with bots talking to bots anyway. The digital equivalent of always up-to-date yellow pages would solve many of these issues. Super simple and "dumb" but reliable programs could perform such tasks. Scheduling multiple calendars doesn't require "AI" - it's a comparatively simple optimisation problem that can be solved using computationally cheap existing algorithms. It seems more and more to me that AI - and LLMs in particular - are the hammer and now literally everything looks like a nail...
• Mikhail_Edoshin 11mo ago
  AI would make a very good librarian. It doesn't understand, only comprehends, but in this case it is enough. Thing is, there is no library for it to work in.
• theonething 11mo ago
  seem like data analysis would be a good one. Company ingests massive amounts of disparate business data. Ask AI to clean and normalize it, visualize it and give recommendations.
  • jongjong 11mo ago
    I think this is not a sure bet because of the relatively high cost of inference. It is likely not suitable for large amounts of data. We don't actually know yet because current prices are so heavily subsidized, we don't know if it would actually be viable in a normal financial environment without subsidies. We know it's not viable to hire humans to do this, but we don't know if it's viable for LLMs to do it.
• kken 11mo ago
  Well, considering that the long term idea is to have AGI, general intelligence, it seems that the goal as also to only have a single product in the end. There may be different ways to access it, but the product is always the same.
• EagnaIonat 11mo ago
  > This doesn’t work well because savvy users can manipulate the chatbot into calling tools. So you can never give a support chatbot real support powers like “refund this customer”, ... I would disagree with this. Part of how security is handled in current agentic systems is to not let the LLM have any access to how the underlying tools work. At best it's like hitting "inspect" in your browser and changing the web page. Of course, that assumes that the agentic chatbot has been built correctly.
• samuelknight 11mo ago
  I look at LLMs with an engineering mindset. It is an intelligence black box that goes in a tool box with the old classical algorithms and frameworks. In order to use it in a solution I need to figure out: 1) Whether I can give it information in a compatible and cost effective way 2) Whether the model is likely to to produce useful output I have use language models for years before LLMs such as part of speech classifiers in the Python NLTK framework.
• sgt101 11mo ago
  The product is the LLM, the wrap has marginal value atm. You can write an agent, it's cool. I can copy it. I cannot build my own LLM (although I can run open source ones).
• YesBox 11mo ago
  Regarding games: > A third reason could be that generated content is just not a good fit for gaming. This is my current opinion as a game developer. IMO this isn't going to be fun for most once the novelty wears off. Games are goal oriented at the end of the day and the great games are masterfully curated multi-disciplinary experiences. I'd argue throwing a game wrapper around an LLM is a new LLM experience, not a new game experience.
• leksak 11mo ago
  I would consider profitable to be a requirement to qualify as a product working and none of these fit the bill I believe?
• deleted 11mo ago
  [deleted]
• throwawaymaths 11mo ago
  I think there's a space for something that wraps an llm (especially multimodal) to do something that's halfway to agentic. Yes you could do it yourself but it's not worth it to you to figure out prompts etc, especially when someone has already optimized it. Plus, it could go from 100 clicks and 10 minutes in front of chatgpt to zero clicks, automated ingest, and get an email when the results is baked. A good example I saw recently was stripping ads from podcasts.
• Animats 11mo ago
  > So you can never give a support chatbot real support powers like “refund this customer”, because the moment you do, thousands of people will immediately find the right way to jailbreak your chatbot into giving them money. And that's the elephant in the room. AI "agents" can't do much until someone solves that problem. Most AI "agents" work for and favor the business operating the agent, but impose the costs of their errors on the customer. Errors are an externality, like pollution. This is no good.
• PunchyHamster 11mo ago
  Probably want to add "scamming clueless out of their savings" by combination of LLMs and voice generation.
  • aunty_helen 11mo ago
    And the other side, detecting in real time as phishing is happening and intervening.
• rckt 11mo ago
  > The third real AI product is the coding agent. People have been talking about this for years, but it was only really in 2025 that the technology behind coding agents became feasible No, they didn’t. > LLMs are particularly good at tasks like “skim through ten pages of search results” or “keyword search this giant dataset for any information on a particular topic”. No. They are not. Amazing article without any support of the statements made. Just, “because I think so”. Cool.
  • Kiro 11mo ago
    I don't think any of those statements are controversial. Do you mind elaborating?
    • rckt 11mo ago
      There's nothing to elaborate actually. The state of the AI currently does not allow to use seriously. If we mean "then spend N amount of time reviewing and trying to make a better output", then yes, I can agree that AI is usable. But the time wasted on the reviews can be simply put into doing the task yourself. And it will be faster and less frustrating.
      • Kiro 11mo ago
        You not being able to use it successfully is no basis for such a conclusion. One verified observation is stronger than infinite lack of observation.
        • rckt 11mo ago
          It's not my personal observation. It's a general observation. I witnessed only one person in real life who said that they use AI in their job and they are completely satisfied with it. The rest point out the poor quality of the output and how technically savvy one should be to successfully (to some extent) use the AI in their jobs.
          • 11mo ago
• AndrewKemendo 11mo ago
  This is ridiculous Shazam is almost perfect song recognition and is built into iOS Every Google/Apple Maps route is based on an AI system I have at least a dozen apps that use almost perfect visual recognition based on images for search (plant identification, stochastic object identification etc…)
• joshribakoff 11mo ago
  I think this is a pretty narrow take. Without going into too much detail I can imagine many use cases. For example, there is a whole class of predictive algorithms and one limitation is that data has to be cleaned, ingested, and feature engineered. For example, clustering is only as good as your vectorization. With an LLM, it is easy to imagine predictive use cases that skip entire etl pipelines and just directly operate on less structured inputs, not just summarizing those inputs, but actually making decisions or predictions. You’re already seeing frameworks like BERT-topic integrating LLMs (for labeling topics), that is already far removed from the “3 use cases” listed here. By fine tuning llm based predictive systems we might unlock entirely new use cases, and prediction is just one thing i imagine, there are many other use cases. And then it’s not just the fact that frameworks like bert-topic are integrating LLMs. It’s also the fact that if you zoom out the architecture looks a lot like the architecture of an LLM… text -> embedding -> text An LLM could and is already being used to generate recommendations systems, like the ones used at Youtube and Netflix, it captures more semantics than older techniques.
• cpill 11mo ago
  This guy is full of horse manure.
• sota_pop 11mo ago
  I could be aging myself, but what about the back-office software that’s been driving business operations for at least two decades that utilize SVMs and other techniques unrelated to the transformer architecture or even deep learning?? I have always felt chat bots, although the most accessible, are the worst application of AI. Why would any business WANT to put layers of abstraction (sic ai chatbots) in between them and people who are potentially interested in paying them money? The famous book series got it right: “Automate the boring stuff” best use-cases for AI are embedded deeply within operational tasks, abstracted away completely, and used in applications where limiting scope/context of information makes traditional software methods overly cumbersome or intractable.
• KurSix 11mo ago
  To me, this classification overlooks the largest and arguably most profitable class of AI products: models that aren't the interface but are embedded deep within existing systems as infrastructure components, for example: - Anti-fraud systems in fintech - Supply chain optimization - Predictive maintenance for equipment - Models for medical image analysis They don't have a "chat," and they aren't "agents", they are just APIs that solve one highly specialized task, but do so with extreme precision and reliability. They don't compete with ChatGPT because they solve completely different problems, and they're the ones that have been bringing in real money for years