9 ms·

Product Strategy in the Age of AI

83 points by egman_ekki 3y ago

blitzar 3y ago
As with all Hype Cycles; stick the buzzword into your company name (see "dot com" for examples) work it into every sentence of every conversation that you have and benefit from the torrential flow of investment chasing said buzzword. Ignore all else and get the company name infront of the cheque books as quickly as humanly possible. Product-market fit, MVP, bootstrapping and stealth are naughty words that have no place in Hype Cycles. No further strategy required, however, for the advanced entrepreneur - be aware that all cycles have a bust phase - and this time it is not different. (unless you wrote blog posts and "content" - in which case copy the article you wrote about Product Strategy in the Age of NFTs a couple of years ago and swap the crypto for ai - you will get lots of clicks and nobody will notice)
- klysm 3y ago
  Picking a time when interest rates are zero doesn’t hurt either
  - blitzar 3y ago
    Blaming interest rates is for losers with blocks, chains, tokens and metas in their name. Interest rates were high in the "dot com" era and that didnt stop them. If you raise 100mil now you can make your payroll and your AWS bill from the interest alone.
- keiferski 3y ago
  Yes I find myself wishing that "AI" wasn't the term chosen for generative text and image tools, as this term has been pushed by culture/movies/games for the last half-century to mean something specific, not just (still very impressive) tools to generate images and text. Of course, this could have never happened, as the temptation of "AI" for marketing products is irresistible and the confusion between "real AI" and "new generative LLM tools" is actually beneficial for companies. I don't know what will happen to the term "AI" after this hype cycle dies down.
  - suoduandao2 3y ago
    Serious question, do you think the current generation of llm cannot pass the Turing test? If you think it can, did you not put much stock on the Turing test before they passed it?
    - keiferski 3y ago
      Yes I think they can pass the Turing test, yes I think this was a poor test to begin with if we are attempting to clarify what machine intelligence is and how it compares to human intelligence.
      - suoduandao2 3y ago
        I genuinely do not understand how this attitude is so common on a site with so many experts. Surely two things being indistinguishable is a step change if we’re trying to compare them?
        keiferski 3y ago
        The Turing Test is a test of mimicry, not of identity. It's based on a metaphysics that says appearance = reality, which has all sorts of issues. There are plenty of ways we can distinguish humans from machines and I expect this other "background information" (primarily biological in nature) will play an increasingly important role. Especially embedded cognition and the gradual realization that intelligence is embedded in its environment, not some kind of abstract, external entity. I wrote this comment a few weeks ago, maybe relevant here: https://news.ycombinator.com/item?id=37221294 https://news.ycombinator.com/item?id=37221294
  - komali2 3y ago
    "crypto means cryptography" is bouncing around in my head. I guess we'll enjoy adding "AI means artificial intelligence, not generative text" to that statement for the rest of our lives.
  - famouswaffles 3y ago
- romanovcode 3y ago
  Just out of curiosity I googled the title with AI replaced by Blockchain and viola - hundreds of similar type articles that have no meaning nowadays. I know it's a stupid comparison but still funny to me.
- naillo 3y ago
  This is all making me realize investors are just people with money (not these super intelligent market predictors that they're often portrayed). You'd do the same to market a product as you would to skim off the flood of money going into a hyped field I suppose.
  - eru 3y ago
    Yes, investors are just people. Some of them smart, some of them less so.
  - quickthrower2 3y ago
    Other People’s Money TM!
  - re-thc 3y ago
    > not these super intelligent market predictors that they're often portrayed If that was true there wouldn't be that many funded failed startups. In fact there might not even be startups at all. The investors can take the funds and just find someone to do their binding instead of randomly "investing".
- quickthrower2 3y ago
  Content will be flooded with chatgpt waffling on too
janalsncm 3y ago
Here is the problem. Every investor is going to ask what your moat is. What differentiates your Whisper -> Llama -> Midjourney Pipeline.ai from the next one? And the answer is, if you’re just making API calls, nothing. Sorry. There’s nothing stopping Jian Yang from creating newpipeline.ai in a weekend. Here’s a couple of things which could set you apart off the top of my head. Customers. Having customers is an advantage over the next guy who doesn’t, because now you can start customizing your product for unique needs rather than having a generic crud app. Custom models. A custom model means some kid can’t just replicate your app easily. Unique data. Data which is infeasible for another company to acquire or replicate. Special people. People who will give your startup an edge in creating all of the above.
- inductive_magic 3y ago
  >There’s nothing stopping Jian Yang from creating newpipeline.ai As someone leading a product team which "only calls apis" in this context: this is a very premature take. Hear me out :-) Robust LLM-powered software requires * very thoughtful design of prompt templates * understanding of top_p and temperature in the context of said templates and their parameter space * very thoughtful design of representative test cases for a given combination of prompt template and api params. without these, you're not even able to reason about the value range of the function you're developing * execution and evaluation of those tests * maintenance of all above ...and that's just talking about ensuring the desired output types in one closed context. I won't go into the creativity required to solve more complex problems (content injections, for one). Let me just say this: I won't lose sleep because anyone could just replicate our applications. The opposite is the case: I invite anyone to try and catch up. Good luck with that. What you wrote might apply for prototypes of zero-shot applications, but not for production-ready software, letalone production-ready software that solves problems which involve more than one isolated LLM-call.
  - benob 3y ago
    I think the point of the parent was that you can build expertise in all of those in a relatively short time frame (esp. when more developers will start building up experience), compared to acquiring a large customer base or a large dataset.
infixed 3y ago
In their conversation, they bring up mobile as a recent platform shift that caused a lot of disruption. But I think it's interesting to remember how slow that took. The iPhone was released in 2007, but the real winners of mobile were launched years later -- Uber (2010), Snapchat (2011), and TikTok (2016) -- and those winners took several more years to even start to gain true traction in the market. I don't think a lot of people back in 2007 could have predicted that the biggest thing to come from mobile would be an app that let teens remix music videos and share with their friends. This is why I think it is a little pointless to try and create mental models for what products and features to build to capitalize on AI (though it can be fun). It's so early that we're not capable of understanding what's possible yet. If anything, we're probably at the viral "fart app" stage that mobile was in for its first few years.
- disgruntledphd2 3y ago
  >I don't think a lot of people back in 2007 could have predicted that the biggest thing to come from mobile would be an app that let teens remix music videos and share with their friends. I think that the biggest thing to come from mobile was always available location, exemplified by Google Maps which already existed before mobile happened. Many of the most successful apps relied on this. TikTok is different, in that it could have existed on desktop (but would have looked very different) whereas Uber (for example) definitely couldn't.
  - eru 3y ago
    Something like Uber could have been built on top of SMS, though. It didn't necessarily need Smartphones. (Perhaps SMS plus some feature-phone-level of GPS integration.)
    - varjag 3y ago
      Not really. The hard thing here is not the network transport but user interface.
      - 3y ago
gpt5 3y ago
One realization I had is that tech advantage might in fact become a disadvantage. Consider companies that have invested heavily in building a technological edge. Google Translate, for instance, faces challenges as a simple prompt can overshadow its billion-dollar product. Similarly, Grammarly's competitive edge may now rely more on its momentum and user interface than on its underlying tech. As ChatGPT introduces new capabilities, countless products see their technological edge vanish. To illustrate, the introduction of the image input feature means that, with a single prompt, it could serve as a top-tier school homework assistant, a photo-based calorie counter, and a plant identifier all at once. This dynamic raised into question the viability of ML research as a core business strategy. Take Midjourney, for example. They've made significant strides and achieved dominance with their advanced text-to-image generation technology. But if a product like DALL-E 3, or its successors, could render their entire offering redundant in a few short years, than it's a tricky path for a company to take. To me, this suggests that the actual "new strategy in the age of AI" is that tech companies need to transition from relying on their tech edge as their competitive advantages, to relying more on more stable moats. For example, the network effects rooted in two-sided marketplaces. It also hints that tech giants like Google, who above all relied on their tech advantage, could face existential challenges in the coming decade. A sort of a win-or-die situation. While companies like Amazon might be in a more stable ground for now.
- DrScientist 3y ago
  Does Google rely soley on it's tech edge? I'm not so sure. Don't they have a huge data moat that's hard to compete with in a data driven age? I'm thinking the data that optimises advertising rather than the data that feeds google translate etc.
  - flagrant_taco 3y ago
    I'm not so sure that Google's data is even their moat, their monopoly on everything related to ads might be the main thing keeping that so afloat.
- CuriouslyC 3y ago
  Midjourney basically used RLHF on their model, so they have a bit of a data moat in terms of human aesthetic preference, but DALL-E 3 isn't bad in terms of aesthetics and its prompt adherence is vastly superior so that preference moat might not save them. They'll need to improve prompt adherence quite a bit to stay relevant. Data is the new oil in the age of AI. The companies that do well will have products that siphon context enriched user behavior, build a strong brand with user loyalty, and effectively capitalize on the collected data to automate some expensive task. These data collection apps will be designed to break down and gamify tasks in such a way as to maximize the training value of the resulting data stream. For example, imagine an IDE with an integrated stack overflow type service, where people could do collaborative coding or request help and get answers inside the application. That would give edit-by-edit updates, console output, problems with solutions and user solution preference. The company that owned that data would have a huge leg up on the competition in terms of creating AI software generation tools.
loondri 3y ago
This article praises AI for improving products, but what about the jobs it might take over, like customer service roles? And can AI truly understand human emotions to handle sensitive customer issues or create artwork that resonates with people on a deeper level? There might be more to consider than just the cool tech.
jakeeee 3y ago
[flagged]
keiferski 3y ago
To me, these brainstorming sessions theorizing the future of AI tools always miss a key thing, which is that human beings are still human beings. They don't follow logical rules of adoption and they often rebel against the things you force them to do. For example, they talk about AI-generated copies of your voice becoming the way people communicate with each other. But who wants to listen to a computer copy of someone else's voice? No one. Maybe it will replace the pizza shop guy answering the phone, but it certainly isn't going to replace real conversations between friends and family members. I saw another app that uses a small number of family photos to generate the surrounding scene where the photos were taken. Again, it's just a gimmick – family photos have value because they are memories of real events, not because of the intrinsic nature of the photographic paper. If I were a betting man, I would bet on a major backlash to this sort of "automate everything" approach and a serious counter-culture to arise in the next decade or two.
- sensanaty 3y ago
  I think most of the people hyping it up are just thinking about the pure money-saving/generating side of it. You can automate away entire teams of people, imagine all the savings! You can generate infinite content with 2 clicks for basically free, think of the money to be made there! They of course ignore the fact that most people don't want to be talking to a robot and would take the human any day of the week. And most people create things as an outlet for their creativity or whatever else, not (solely) as a way to make oodles of money. The company I work for provides tools for Support teams, and there's been talks from the higher ups about "automating away 90% of conversations", which basically translates to us auto-closing 90% of all incoming messages for our customers based on some "AI" decisions. The only people who buy into it are the CEO/CTO and their direct underlings, everyone else in the company realizes how fucking stupid and shortsighted that is, but they don't care. It's the big hype thing, all the competitors do it regardless of how idiotic it is, and our customers want to get rid of as much human labor as possible.
  - wildrhythms 3y ago
    It's pretty clear the implementation of these 'AI's is not solving a user problem. At my workplace we have mountains of user requests for maybe ~5 key features from years ago that no staffing has been assigned to; instead, the PMs and VPs and Directors are focused on shiny new features (yes, like 'AI') that they can put into marketing materials and get promoted. It's all hype. I have never seen a single customer request for the 'AI' features that these multi million dollar engineering teams are working on now.
padjo 3y ago
They mention that “mobile-first companies killed companies that weren’t mobile-first”, can anyone point to a good example? My memory is that “mobile first” was a big hype cycle. A few years later everyone fired their native mobile teams because they realised most businesses don’t actually need a mobile app.
- infixed 3y ago
  Agreed with this sentiment. I personally find it funny that Craigslist is still very much alive and kicking, and is my go-to for apartment hunting amongst other things, despite an underwhelming mobile experience and a design that hasn't been updated in literally decades.
- altdataseller 3y ago
  MyFitnessPal > SparkPeople iPhone games > Yahoo Games
- destraynor 3y ago
  every b2c app needed a native app (two actually) every web only consumer product basically died what is true is that b2b products didn't need them, or needed them as "companion apps", not full replacements.
epups 3y ago
It's interesting, I feel excited as I haven't felt in a long time because wherever I look, there is a possible side project where I can explore AI and LLM's. On the other hand, I would feel very scared to try to transform any of them into a business due to some of the issues discussed in the article.
msoad 3y ago
Honestly the way the models are improving I don’t see a ton of “product” work needed anymore. Any UI is worse than a good AI assistant that I can chat/talk to. Why do I need your forms and data rendering if the AI assistant is smart enough to figure it out on its own? I am a lot more pessimistic about the startup scene in this area. Look how ChatGPT can teach languages[1], good luck building an AI powered language learning app… It gets worse for startups because Google and OpenAI have a ton more context about me. For example in the language learning conversation Google can refer to my spoken samples from other places to improve the experience. And yet, no PM at Google needs to think of this, they only need to hook up the data and throw more compute at their models. [1] https://twitter.com/dmvaldman/status/1707881743892746381 https://twitter.com/dmvaldman/status/1707881743892746381
- deleted 3y ago
  [deleted]
- aurareturn 3y ago
  Hence why Bill Gates said the biggest winner in AI will be the first company who can build a true AI assistant. I thought the same and agreed with him. Everything we do now is just working towards that super assistant. I think in the future, your "phone" is just an interface between you and your assistant. Not much else. As an Apple shareholder, this is my biggest worry. iOS is suddenly a lot less necessary.
- jclulow 3y ago
  > Any UI is worse than a good AI assistant that I can chat/talk to Speak for yourself. I have zero interest in having a conversation with the computer, whether typing or (especially) speaking out loud. Product and UI and UX work will continue to be valuable; if anything, good quality work will stand out even more amongst the oncoming tidal wave of low quality AI/LLM stuff.
- sensanaty 3y ago
  > Any UI is worse than a good AI assistant that I can chat/talk to. Good lord no. Never. Not in a trillion years will I be okay with interacting with these data hoovering blackboxes rather than just fucking clicking on the button with my mouse.
danielovichdk 3y ago
I am headed in the other direction. Making something AI or a computer can't do. Times are changing and I can't handle another hype cycle. My CTO is already running around the halls talking to people about "have you done anything with ChatGPT in our projects...you should".
- wildrhythms 3y ago
  I have experienced this as well, also from higherups. They demand I interact with AI. What's the user problem it's solving for me? That's never actually defined.
xmcqdpt2 3y ago
> While AI can streamline tasks in SaaS categories like sales and customer service, offering relief from repetitive work, the impact on project management is more nuanced. Every single AI hype article includes some version of this sentence! "While AI can be helpful for the repetitive boring work that other people do, the impact on MY work is more nuanced." It's basically the face eating leopard meme. "AI wouldn't automate MY job" says president of AI job automation company.
- destraynor 3y ago
  I think we addressed this specifically when I spoke about Bloom's taxonomy.
robviren 3y ago
My personal take as a PM is to find narrow opportunities for the tech where it makes most sense and poses the least risk. One project we are looking at it to tune a model against our website with URL links to make a more natural search function given the utter labyrinth of a website we currently have. Not insane given the two search giants are applying the same idea. We can reduce hallucination by validating URLs it produces before hitting the user. Also build up a list of questions and not just search queiries. Other avenues are more human accelerators than replacement. I have been around long enough that I if a tool presents a risk to someones job the tool often gets thrown down the stairs "accidentally". GE bought in hard to Google glass back in the day and tried having it walk through procedures for complex repair processes. A great idea if literally anyone in the field asked for it. I'm with many that the hype train hit hard for "AI" and block chain, but LLMs for me do have real value and real application for some excellent use cases. I also find it an excellent sounding board for my own ideas, though the models tend to not want to disappoint you.
- chasd00 3y ago
  i work for a large consulting firm that is cheerleading LLMs very hard. I've yet to see a use case beyond a better chat bot and knowledge base search. I've also yet to hear about a large client putting an LLM in production, it's all been experimental and the total sum earned on generative AI projects in our firm last year was < $500M I'm not saying the hype isn't real but i'm definitely skeptical. edit: for context my firm screamed to high heaven how the whole metaverse thing was a game changer too. I called that one BS right out of the gate.
intended 3y ago
ctrl-F "eval" = no hits in article. The reason there is so much debate on Gen AI is due to the emergence of unpredicted abilities. Yes GenAI is insanely impressive - this is not a luddite argument. I have personally spent months on it, and continue to do so. ITS AWESOME. However it really isnt going to do a tenth of the things people expect it to. Those emergent properties seem like actual reasoning, planning, or analysis. Get to production data though, then the emperor has no clothes. Those "emergent" skills end up showing you how much correlation in text is good enough - provided the person reviewing the text is already an expert.
gdubs 3y ago
I've been saying this a lot over the past year as people obsess over 'moats' and whether a future model will make an idea obsolete, or whether it's even worth getting into something because Big Co is already working on it, or will be working on it: You learn by doing. There's so much value in actually making something. People forget how much is in the details, or how much something like good design can differentiate. You can sit on the sidelines forever thinking that your idea isn't 'different' enough, but the ones actually making stuff, listening to users, gaining the end-to-end experience, will actually have a larger 'luck surface area'. Even if your idea gets taken, or someone comes along and does it better, or cheaper – there's value in _trying_. Specifically regarding AI: the models existed for quite a while, for free, for anyone to use in OpenAI's Playground. But suddenly they hooked it up to a chat UI and it blew up completely. You never know what the key thing is going to be. But if you sit around forever, you're guaranteeing failure.

83 points by egman_ekki 3y ago

As with all Hype Cycles; stick the buzzword into your company name (see "dot com" for examples) work it into every sentence of every conversation that you have and benefit from the torrential flow of investment chasing said buzzword. Ignore all else and get the company name infront of the cheque books as quickly as humanly possible. Product-market fit, MVP, bootstrapping and stealth are naughty words that have no place in Hype Cycles. No further strategy required, however, for the advanced entrepreneur - be aware that all cycles have a bust phase - and this time it is not different. (unless you wrote blog posts and "content" - in which case copy the article you wrote about Product Strategy in the Age of NFTs a couple of years ago and swap the crypto for ai - you will get lots of clicks and nobody will notice)

klysm 3y ago
Picking a time when interest rates are zero doesn’t hurt either
- blitzar 3y ago
  Blaming interest rates is for losers with blocks, chains, tokens and metas in their name. Interest rates were high in the "dot com" era and that didnt stop them. If you raise 100mil now you can make your payroll and your AWS bill from the interest alone.
keiferski 3y ago
Yes I find myself wishing that "AI" wasn't the term chosen for generative text and image tools, as this term has been pushed by culture/movies/games for the last half-century to mean something specific, not just (still very impressive) tools to generate images and text. Of course, this could have never happened, as the temptation of "AI" for marketing products is irresistible and the confusion between "real AI" and "new generative LLM tools" is actually beneficial for companies. I don't know what will happen to the term "AI" after this hype cycle dies down.
- suoduandao2 3y ago
  Serious question, do you think the current generation of llm cannot pass the Turing test? If you think it can, did you not put much stock on the Turing test before they passed it?
  - keiferski 3y ago
    Yes I think they can pass the Turing test, yes I think this was a poor test to begin with if we are attempting to clarify what machine intelligence is and how it compares to human intelligence.
    - suoduandao2 3y ago
      I genuinely do not understand how this attitude is so common on a site with so many experts. Surely two things being indistinguishable is a step change if we’re trying to compare them?
      - keiferski 3y ago
        The Turing Test is a test of mimicry, not of identity. It's based on a metaphysics that says appearance = reality, which has all sorts of issues. There are plenty of ways we can distinguish humans from machines and I expect this other "background information" (primarily biological in nature) will play an increasingly important role. Especially embedded cognition and the gradual realization that intelligence is embedded in its environment, not some kind of abstract, external entity. I wrote this comment a few weeks ago, maybe relevant here: https://news.ycombinator.com/item?id=37221294 https://news.ycombinator.com/item?id=37221294
- komali2 3y ago
  "crypto means cryptography" is bouncing around in my head. I guess we'll enjoy adding "AI means artificial intelligence, not generative text" to that statement for the rest of our lives.
- famouswaffles 3y ago
romanovcode 3y ago
Just out of curiosity I googled the title with AI replaced by Blockchain and viola - hundreds of similar type articles that have no meaning nowadays. I know it's a stupid comparison but still funny to me.
naillo 3y ago
This is all making me realize investors are just people with money (not these super intelligent market predictors that they're often portrayed). You'd do the same to market a product as you would to skim off the flood of money going into a hyped field I suppose.
- eru 3y ago
  Yes, investors are just people. Some of them smart, some of them less so.
- quickthrower2 3y ago
  Other People’s Money TM!
- re-thc 3y ago
  > not these super intelligent market predictors that they're often portrayed If that was true there wouldn't be that many funded failed startups. In fact there might not even be startups at all. The investors can take the funds and just find someone to do their binding instead of randomly "investing".
quickthrower2 3y ago
Content will be flooded with chatgpt waffling on too

janalsncm 3y ago

Here is the problem. Every investor is going to ask what your moat is. What differentiates your Whisper -> Llama -> Midjourney Pipeline.ai from the next one? And the answer is, if you’re just making API calls, nothing. Sorry. There’s nothing stopping Jian Yang from creating newpipeline.ai in a weekend. Here’s a couple of things which could set you apart off the top of my head. Customers. Having customers is an advantage over the next guy who doesn’t, because now you can start customizing your product for unique needs rather than having a generic crud app. Custom models. A custom model means some kid can’t just replicate your app easily. Unique data. Data which is infeasible for another company to acquire or replicate. Special people. People who will give your startup an edge in creating all of the above.

inductive_magic 3y ago
>There’s nothing stopping Jian Yang from creating newpipeline.ai As someone leading a product team which "only calls apis" in this context: this is a very premature take. Hear me out :-) Robust LLM-powered software requires * very thoughtful design of prompt templates * understanding of top_p and temperature in the context of said templates and their parameter space * very thoughtful design of representative test cases for a given combination of prompt template and api params. without these, you're not even able to reason about the value range of the function you're developing * execution and evaluation of those tests * maintenance of all above ...and that's just talking about ensuring the desired output types in one closed context. I won't go into the creativity required to solve more complex problems (content injections, for one). Let me just say this: I won't lose sleep because anyone could just replicate our applications. The opposite is the case: I invite anyone to try and catch up. Good luck with that. What you wrote might apply for prototypes of zero-shot applications, but not for production-ready software, letalone production-ready software that solves problems which involve more than one isolated LLM-call.
- benob 3y ago
  I think the point of the parent was that you can build expertise in all of those in a relatively short time frame (esp. when more developers will start building up experience), compared to acquiring a large customer base or a large dataset.

infixed 3y ago

In their conversation, they bring up mobile as a recent platform shift that caused a lot of disruption. But I think it's interesting to remember how slow that took. The iPhone was released in 2007, but the real winners of mobile were launched years later -- Uber (2010), Snapchat (2011), and TikTok (2016) -- and those winners took several more years to even start to gain true traction in the market. I don't think a lot of people back in 2007 could have predicted that the biggest thing to come from mobile would be an app that let teens remix music videos and share with their friends. This is why I think it is a little pointless to try and create mental models for what products and features to build to capitalize on AI (though it can be fun). It's so early that we're not capable of understanding what's possible yet. If anything, we're probably at the viral "fart app" stage that mobile was in for its first few years.

disgruntledphd2 3y ago
>I don't think a lot of people back in 2007 could have predicted that the biggest thing to come from mobile would be an app that let teens remix music videos and share with their friends. I think that the biggest thing to come from mobile was always available location, exemplified by Google Maps which already existed before mobile happened. Many of the most successful apps relied on this. TikTok is different, in that it could have existed on desktop (but would have looked very different) whereas Uber (for example) definitely couldn't.
- eru 3y ago
  Something like Uber could have been built on top of SMS, though. It didn't necessarily need Smartphones. (Perhaps SMS plus some feature-phone-level of GPS integration.)
  - varjag 3y ago
    Not really. The hard thing here is not the network transport but user interface.
    - 3y ago

gpt5 3y ago

One realization I had is that tech advantage might in fact become a disadvantage. Consider companies that have invested heavily in building a technological edge. Google Translate, for instance, faces challenges as a simple prompt can overshadow its billion-dollar product. Similarly, Grammarly's competitive edge may now rely more on its momentum and user interface than on its underlying tech. As ChatGPT introduces new capabilities, countless products see their technological edge vanish. To illustrate, the introduction of the image input feature means that, with a single prompt, it could serve as a top-tier school homework assistant, a photo-based calorie counter, and a plant identifier all at once. This dynamic raised into question the viability of ML research as a core business strategy. Take Midjourney, for example. They've made significant strides and achieved dominance with their advanced text-to-image generation technology. But if a product like DALL-E 3, or its successors, could render their entire offering redundant in a few short years, than it's a tricky path for a company to take. To me, this suggests that the actual "new strategy in the age of AI" is that tech companies need to transition from relying on their tech edge as their competitive advantages, to relying more on more stable moats. For example, the network effects rooted in two-sided marketplaces. It also hints that tech giants like Google, who above all relied on their tech advantage, could face existential challenges in the coming decade. A sort of a win-or-die situation. While companies like Amazon might be in a more stable ground for now.

DrScientist 3y ago
Does Google rely soley on it's tech edge? I'm not so sure. Don't they have a huge data moat that's hard to compete with in a data driven age? I'm thinking the data that optimises advertising rather than the data that feeds google translate etc.
- flagrant_taco 3y ago
  I'm not so sure that Google's data is even their moat, their monopoly on everything related to ads might be the main thing keeping that so afloat.
CuriouslyC 3y ago
Midjourney basically used RLHF on their model, so they have a bit of a data moat in terms of human aesthetic preference, but DALL-E 3 isn't bad in terms of aesthetics and its prompt adherence is vastly superior so that preference moat might not save them. They'll need to improve prompt adherence quite a bit to stay relevant. Data is the new oil in the age of AI. The companies that do well will have products that siphon context enriched user behavior, build a strong brand with user loyalty, and effectively capitalize on the collected data to automate some expensive task. These data collection apps will be designed to break down and gamify tasks in such a way as to maximize the training value of the resulting data stream. For example, imagine an IDE with an integrated stack overflow type service, where people could do collaborative coding or request help and get answers inside the application. That would give edit-by-edit updates, console output, problems with solutions and user solution preference. The company that owned that data would have a huge leg up on the competition in terms of creating AI software generation tools.

loondri 3y ago

This article praises AI for improving products, but what about the jobs it might take over, like customer service roles? And can AI truly understand human emotions to handle sensitive customer issues or create artwork that resonates with people on a deeper level? There might be more to consider than just the cool tech.

jakeeee 3y ago

[flagged]

keiferski 3y ago

To me, these brainstorming sessions theorizing the future of AI tools always miss a key thing, which is that human beings are still human beings. They don't follow logical rules of adoption and they often rebel against the things you force them to do. For example, they talk about AI-generated copies of your voice becoming the way people communicate with each other. But who wants to listen to a computer copy of someone else's voice? No one. Maybe it will replace the pizza shop guy answering the phone, but it certainly isn't going to replace real conversations between friends and family members. I saw another app that uses a small number of family photos to generate the surrounding scene where the photos were taken. Again, it's just a gimmick – family photos have value because they are memories of real events, not because of the intrinsic nature of the photographic paper. If I were a betting man, I would bet on a major backlash to this sort of "automate everything" approach and a serious counter-culture to arise in the next decade or two.

sensanaty 3y ago
I think most of the people hyping it up are just thinking about the pure money-saving/generating side of it. You can automate away entire teams of people, imagine all the savings! You can generate infinite content with 2 clicks for basically free, think of the money to be made there! They of course ignore the fact that most people don't want to be talking to a robot and would take the human any day of the week. And most people create things as an outlet for their creativity or whatever else, not (solely) as a way to make oodles of money. The company I work for provides tools for Support teams, and there's been talks from the higher ups about "automating away 90% of conversations", which basically translates to us auto-closing 90% of all incoming messages for our customers based on some "AI" decisions. The only people who buy into it are the CEO/CTO and their direct underlings, everyone else in the company realizes how fucking stupid and shortsighted that is, but they don't care. It's the big hype thing, all the competitors do it regardless of how idiotic it is, and our customers want to get rid of as much human labor as possible.
- wildrhythms 3y ago
  It's pretty clear the implementation of these 'AI's is not solving a user problem. At my workplace we have mountains of user requests for maybe ~5 key features from years ago that no staffing has been assigned to; instead, the PMs and VPs and Directors are focused on shiny new features (yes, like 'AI') that they can put into marketing materials and get promoted. It's all hype. I have never seen a single customer request for the 'AI' features that these multi million dollar engineering teams are working on now.

padjo 3y ago

They mention that “mobile-first companies killed companies that weren’t mobile-first”, can anyone point to a good example? My memory is that “mobile first” was a big hype cycle. A few years later everyone fired their native mobile teams because they realised most businesses don’t actually need a mobile app.

infixed 3y ago
Agreed with this sentiment. I personally find it funny that Craigslist is still very much alive and kicking, and is my go-to for apartment hunting amongst other things, despite an underwhelming mobile experience and a design that hasn't been updated in literally decades.
altdataseller 3y ago
MyFitnessPal > SparkPeople iPhone games > Yahoo Games
destraynor 3y ago
every b2c app needed a native app (two actually) every web only consumer product basically died what is true is that b2b products didn't need them, or needed them as "companion apps", not full replacements.

epups 3y ago

It's interesting, I feel excited as I haven't felt in a long time because wherever I look, there is a possible side project where I can explore AI and LLM's. On the other hand, I would feel very scared to try to transform any of them into a business due to some of the issues discussed in the article.

msoad 3y ago

Honestly the way the models are improving I don’t see a ton of “product” work needed anymore. Any UI is worse than a good AI assistant that I can chat/talk to. Why do I need your forms and data rendering if the AI assistant is smart enough to figure it out on its own? I am a lot more pessimistic about the startup scene in this area. Look how ChatGPT can teach languages[1], good luck building an AI powered language learning app… It gets worse for startups because Google and OpenAI have a ton more context about me. For example in the language learning conversation Google can refer to my spoken samples from other places to improve the experience. And yet, no PM at Google needs to think of this, they only need to hook up the data and throw more compute at their models. [1] https://twitter.com/dmvaldman/status/1707881743892746381 https://twitter.com/dmvaldman/status/1707881743892746381

deleted 3y ago
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aurareturn 3y ago
Hence why Bill Gates said the biggest winner in AI will be the first company who can build a true AI assistant. I thought the same and agreed with him. Everything we do now is just working towards that super assistant. I think in the future, your "phone" is just an interface between you and your assistant. Not much else. As an Apple shareholder, this is my biggest worry. iOS is suddenly a lot less necessary.
jclulow 3y ago
> Any UI is worse than a good AI assistant that I can chat/talk to Speak for yourself. I have zero interest in having a conversation with the computer, whether typing or (especially) speaking out loud. Product and UI and UX work will continue to be valuable; if anything, good quality work will stand out even more amongst the oncoming tidal wave of low quality AI/LLM stuff.
sensanaty 3y ago
> Any UI is worse than a good AI assistant that I can chat/talk to. Good lord no. Never. Not in a trillion years will I be okay with interacting with these data hoovering blackboxes rather than just fucking clicking on the button with my mouse.

danielovichdk 3y ago

I am headed in the other direction. Making something AI or a computer can't do. Times are changing and I can't handle another hype cycle. My CTO is already running around the halls talking to people about "have you done anything with ChatGPT in our projects...you should".

wildrhythms 3y ago
I have experienced this as well, also from higherups. They demand I interact with AI. What's the user problem it's solving for me? That's never actually defined.

xmcqdpt2 3y ago

> While AI can streamline tasks in SaaS categories like sales and customer service, offering relief from repetitive work, the impact on project management is more nuanced. Every single AI hype article includes some version of this sentence! "While AI can be helpful for the repetitive boring work that other people do, the impact on MY work is more nuanced." It's basically the face eating leopard meme. "AI wouldn't automate MY job" says president of AI job automation company.

destraynor 3y ago
I think we addressed this specifically when I spoke about Bloom's taxonomy.

robviren 3y ago

My personal take as a PM is to find narrow opportunities for the tech where it makes most sense and poses the least risk. One project we are looking at it to tune a model against our website with URL links to make a more natural search function given the utter labyrinth of a website we currently have. Not insane given the two search giants are applying the same idea. We can reduce hallucination by validating URLs it produces before hitting the user. Also build up a list of questions and not just search queiries. Other avenues are more human accelerators than replacement. I have been around long enough that I if a tool presents a risk to someones job the tool often gets thrown down the stairs "accidentally". GE bought in hard to Google glass back in the day and tried having it walk through procedures for complex repair processes. A great idea if literally anyone in the field asked for it. I'm with many that the hype train hit hard for "AI" and block chain, but LLMs for me do have real value and real application for some excellent use cases. I also find it an excellent sounding board for my own ideas, though the models tend to not want to disappoint you.

chasd00 3y ago
i work for a large consulting firm that is cheerleading LLMs very hard. I've yet to see a use case beyond a better chat bot and knowledge base search. I've also yet to hear about a large client putting an LLM in production, it's all been experimental and the total sum earned on generative AI projects in our firm last year was < $500M I'm not saying the hype isn't real but i'm definitely skeptical. edit: for context my firm screamed to high heaven how the whole metaverse thing was a game changer too. I called that one BS right out of the gate.

intended 3y ago

ctrl-F "eval" = no hits in article. The reason there is so much debate on Gen AI is due to the emergence of unpredicted abilities. Yes GenAI is insanely impressive - this is not a luddite argument. I have personally spent months on it, and continue to do so. ITS AWESOME. However it really isnt going to do a tenth of the things people expect it to. Those emergent properties seem like actual reasoning, planning, or analysis. Get to production data though, then the emperor has no clothes. Those "emergent" skills end up showing you how much correlation in text is good enough - provided the person reviewing the text is already an expert.

gdubs 3y ago

I've been saying this a lot over the past year as people obsess over 'moats' and whether a future model will make an idea obsolete, or whether it's even worth getting into something because Big Co is already working on it, or will be working on it: You learn by doing. There's so much value in actually making something. People forget how much is in the details, or how much something like good design can differentiate. You can sit on the sidelines forever thinking that your idea isn't 'different' enough, but the ones actually making stuff, listening to users, gaining the end-to-end experience, will actually have a larger 'luck surface area'. Even if your idea gets taken, or someone comes along and does it better, or cheaper – there's value in _trying_. Specifically regarding AI: the models existed for quite a while, for free, for anyone to use in OpenAI's Playground. But suddenly they hooked it up to a chat UI and it blew up completely. You never know what the key thing is going to be. But if you sit around forever, you're guaranteeing failure.