> not that interested in getting good at it

I think they're interested in getting good at it. They just don't want to put in the human time and effort to do so. They expect their many failures and short-comings to be shored up by continuous model training.

But that, of course, means that in the meantime it will suck and nobody will use it.

Also having to wait for ChatGPT for a "thinking" response to search for information that is slower than a Google search loses them lots of money.

I believe that it can still work and I won't claim about being unsurprised about this failure. But this is a great opportunity to execute this problem really well if OpenAI and others are not interested in getting good at this.

Perplexity also attempted this, got sued by Amazon and it appears semi-abandoned.

The only problem is that it must be quicker or just as quick as a Google search, and also compatible with the existing checkout flows.

Just because you're not the target audience doesn't mean there's not a real target audience.

There a people today learning to use an LLM instead of an actual search engine. For these types of people whatever happens outside of the LLM app is invisible to them. The social media apps did similar where they started letting people purchase directly within the app. People started looking at these shops rather than doing searches for it elsewhere.

Buying things on a social media app is crazy to me, but I don't use the social media apps. Buying things from an LLM app seems crazy to you, (because it's new and it's borked is fixable), but to people that first turn to their LLM app of choice that decision isn't so crazy.

> Perplexity also attempted this, got sued by Amazon and it appears semi-abandoned.

Any details on that? I feel the answer is more likely there than in "friction".

Hardly any purchase of consequence is so sensitive to friction that the difference between Google Search and an LLM response matters (especially that in reality, we're talking 20+ manual searches per one LLM response). I.e. I'm not going to use LLMs advise on some random 0-100$ purchase anyway, and losing #$ on a ##$ purchase due to suboptimal choice is not that big of a deal - but I absolutely am going to consult it (and have it compile tables and verify sources) on a $500+ purchase and for those I can afford spending few more minutes on research (or rather few hours less, compared of doing it the usual way).

Social media apps generally opened up new markets though of their existing user bases as sellers. Perhaps chatgpt could know everything in your house, if you don't actually use it, and pair you with a neighbor that needs it!

When you're a solution in search of a problem, you'll try to shoehorn your "solution" into everything.

"This isn't what I wanted to buy, I said my feet are a size 10 and these aren't even shoes!"

"You're absolutely right! Shoes go on feet, and each of your 10 feet could wear shoes. Would you like me to research shoes and purchase them for you?"

As bad as the idea of a solution looking for a problem, this is peak science. Copernicus who figured out that the Earth was not at the center of the solar system, he had a solution. The general word is called deduction.

Personally I am an inductivist, I imagine you may be too.

Think top down decisioning is deduction. Bottom up is induction.

You might think induction is amazing but if you ask yourself "Are there any black swans?" and your answer is "No I've never seen any so there can't be any black swans." The issue is you've never actually seen every Swan and actually there are black swans in Australia.

Point being, we don't know if this is a good thing until it's tested.

This is an age-old problem.

The article says Walmart is not abandoning ChatGPT but is going to use their own app in Chat’s ecosystem

Considering you can't have chat bots be honest even if you don't make them marketing tools I suspect I know which way companies are going to go

LLMs do not have a concept of “honesty”. Nothing they say is honest or dishonest. Anyway, “What’s the best XYZ?” is not a question that has a definitive answer for most XYZs.

I think they're operating beyond their current (human) capacity, trying to test out too many things at a time.

But a dreamer in me entertains another idea: perhaps they're just holding back, because they realize that actually succeeding at this will instantly kill (or at least mortally wound) e-commerce as we know it.

(This is a more narrow version of my belief that general AI tools like LLMs fundamentally don't fit as additions to products, but rather subsume products, and this makes them an existential threat to the software industry. Not to software or computing, just to all the software vendors, whose job is to slice off pieces of computational universe, put them in boxes to prevent interoperability, and give each a name so it's a "product" that can be sold or rented).

They practically want to funnel users like cattle and not let them think about it or compare things.

It’s like corporations are angry that they need to go through us to get our money.

Why is this good? I want an impartial consistent system for shopping. If I can find it at a different site for a lower price, I should be able to do so. I should also be able to have it give me non-bot reviews and ask relevant questions about the product.

The same way I think shopping at Amazon is better than a place like Nike due to objectivity and comparison, I think a chat interface has the potential to take this to another level since places like Amazon have degraded considerably in terms of things like fake third party products and fake reviews.

> (Good) E-commerce has been ruthlessly optimised to get shoppers to products they'll actually buy and then remove all distractions from buying.

The only e-commerce site that fits this standard is that old one for buying (IIRC) nuts and bolts or such, that pops up on HN every other year, and whose name sadly escapes me now. Everyone else is ruthlessly optimizing their experience to fuck shoppers over and get them to products the vendor wants them to buy, not the products the shoppers actually want (or need).

> A chat interface is just fundamentally incompatible with this. The agent makes it too easy to ask questions and comparison shop.

That is precisely the point.

Chats may suck as an interface, but majority of the value and promise of end-user automation (and more than half the point of the term "User Agent" (as in, e.g., a web browser)) is in enabling comparison shopping in spite of the merchants, and more generally, helping people reduce information asymmetry that's intertwined with wealth and power asymmetry.

But it's not something you can generally sell to the vendors, who benefit from that asymmetry relative to their clients (in fact, I was dumbfounded to see so much interest on the sales/vendor side for such ideas, but I blame it on general AI hype).

Adversarial interoperability is the name of the game.

It depends on the product, if we are talking commodities or mass produced products like groceries, sure.

If we are talking custom products or complex appliances that need a lot of guidance, then maybe chat interface is appropriate.

> (Good) E-commerce has been ruthlessly optimised to get shoppers to products they'll actually buy and then remove all distractions from buying.

I don't think so. I know for a fact that search terms are a minefield of gotchas and hacks caused by product decisions that reflect ad-hoc negotiations with partners and sellers. It's an unstable equilibrium of partners trying to shift attention to their products in a certain way. I think that calling this fragile equilibrium optimized has no bearing with reality.

The entire point of shoehorning AI into everything is to make people stop thinking for themselves and allowing a corporation to do it for them.

“””If I could just press “buy” from within Gemini and pay via Google Pay (or better still, Apple Pay) I’d do it in a heartbeat”””

Yeah, until that becomes enshittified and you don’t notice because you no longer do research on components.

I would assume the average purchase in Walmart is significantly more low-tech than this though

Things that are not doing the thing. https://strangestloop.io/essays/things-that-arent-doing-the-...

Why do you foresee OpenAI’s involvement in the software business mitigating the resistance to interoperability and companies making money through productization? If they were actually interested in solving those problems instead of trying to secure themselves the biggest slice of economic pie, wouldn’t they have been happy about Chinese companies distilling their models? Are they engagement-juicing inn their heavily subsidized service à la Uber because they’re interested in promoting a better future for humanity? I’m skeptical.

> perhaps they're just holding back

Considering the money they need, they over promise and under deliver.

Shopping research has been pretty funny to me at least, a straightforward way for them to do product placement that people actually want, but implement it so poorly that half of the links it returns are broken.

It's an interesting question.

I am behind schedule on developing a "summer phase" [1] for my foxographer costume and was chatting with Gemini about a crash priority "spring phase" [2] and asked it for suggestions and it gave me a 10-pack of results that had one good thing in it at rank #8, a similar query run against a normal search engine actually got something better at #1. Now sure I am talking w/ Gemini with big words like "supergraphic" whereas a normal search would be heavy on 3-letter and 5-letter words used in the product descriptions.

It makes think though of expert system based product configurators back in the 1980s

https://en.wikipedia.org/wiki/Xcon

thing is that kind of product configurator is based on an ontology, constraints and rules as opposed to embeddings which might capture the "feel" of things like clothing.

[1] Busytown meets Arknights

[2] supergraphic shirt + camera gets resonance with my promotional system and people keep approaching me (e.g. laugh but every KPI in the system has an extra zero on the left)

> But a dreamer in me entertains another idea: perhaps they're just holding back, because they realize that actually succeeding at this will instantly kill (or at least mortally wound) e-commerce as we know it.

Sam Altman doesn’t give a shit about anyone but himself and has time and again shown he has no restraint for trampling over others to further his own goals. Why would e-commerce be where he draws the line?

> E-commerce has been optimized to the last decimal point for the last 30 years.

It certainly hasn't been optimized to anything in 1996. In 1996 it was people clumsily scanning print catalogs, spending 5 hours to upload 10 images on dialup and making a simple HTML page (no DB or any kind of backend) and putting their landline phone on it with a message to "call to checkout"

I know you were exaggerating for effect, but E-commerce and catalog normalization are definitely not "solved" everywhere.

McMaster Carr is a good example of a company that has 90%+ of their stuff ironed out, but most websites and especially small ecommerce isn't like that.

What the hell would AI even bring to the table here?

Already your favourite e commerce site has all your data. You can switch on the "buy this automatically" feature.

30 years? E-commerce hasn't been around that long - try 5 years of optimization MAX.

FWIW OpenAI is desperately trying to monetize and they think e-commerce is a "simple" problem to solve. I mean they do need to convert their funnel without alienating their users. I assume they are going to have some big payouts for agentic purchases gone awry or leave merchants on the hook.

In due time it will serve ChatGPT more than either

They have a solution and are trying to find a problem.

source?

Yeah, but consumers can't buy Waymos. They can get dangerously unsafe Teslas and pretend it's the same tech.

> I don't think so. I know for a fact that search terms are a minefield of gotchas and hacks caused by product decisions that reflect ad-hoc negotiations with partners and sellers. It's an unstable equilibrium of partners trying to shift attention to their products in a certain way. I think that calling this fragile equilibrium optimized has no bearing with reality.

You think a crude, unoptimised "minefield" is the route that leads to something as delicate as a "fragile equilibrium?" I don't see something as carefully balanced as your unstable equilibrium even being something that could exist without the processes involved having been refined down to a science. The only real alternative that meets your narrative would be that this is an industry that runs entirely on hope and luck (and enough human sacrifices to keep ample supplies of both on hand).

Catalog is an ad, the SKU database behind the catalog is impartial (at least as much as it gets), but no one is giving you access to that.

Just made an order from them. It's weirdly comforting to know there's a company that knows I need clevis bolts and is willing to sell them to me for a transparent price.

Wow, that's amazing

It's the one, thank you!

Maybe? I'm not sure which way the OP is arguing, in particular because of that "(Good)". So perhaps I misread the comment as arguing the opposite of what it is.

Where are these sites? Everywhere I shop online is full of distractions and attempts to funnel me away from what I wanted and confuse me along the way.

Not that a chat interface would be an improvement.

What’s your example for this? Because my experience in e comm is that targeted advertising is awful (I bought a lawnmower last week, Amazon knows I bought it. I am now getting ads for lawnmowers, suggested products for lawn mowers, rather than lawn care, gardening tools, or anything to do with the lawnmower I’ve already bought), sites are absolutely overrun with ads and suggested placements for the product they want to sell me rather than the one I’ve searched for, and that everyone except Amazon interrupts the checkout flow with multiple up-sells, verifications, 2FA prompts, 3d Secure validations…

And quickly after that, we were meassuring traffic data with simple "how-many-requests-were-done" (including images) :-D

You were thinking of McMaster-Carr, but Digikey is also that good for electronics parametric shopping.

Sadly Sigma-Aldrich, the hyphenated retailer for chemistry, appears to have been covered in javascript sludge.

I do agree with your conclusion, but the catalog in most online shops is certainly not impartial. Amazon sells the entire first page of search placement, for example.

The use case for chat interfaces would be as follows:

Grandma wants to buy a good bike, but doesn't know about types of wheels or how many gears they need, or what type of frame is appropriate for their body type.

Chat bots don't belong to an e-commerce site; chat bots belong on the outside, specifically to comparison-shop and pull in some external information to de-bullshitify offers, correct "mistakes" and "accidental omissions" in the listings, resolve the borderline-fraudlent crap companies play these days with store-specific and season/promotion-specific SKUs with different parameters all resolving to same model/make name (think Black Friday/Cyber Monday deals that are not actually deals, just inferior hardware with dedicated SKU).

What would it even mean for an ai to solve e-commerce? Is that a claim made here? Is e-commerce a problem to be solved? It seems like e-commerce does just fine, if plagued by poor quality product, fake reviews, and relentless borderline fraudulent marketing.

Was anyone suggesting AI would help with it? It seems from the article that Walmart (presumably experts in e-commerce) themselves willingly collaborated with open ai. Especially at Walmart's level, what even was the theory?

In any case. It seems that despite this poor result, Walmart decided to essentially go ahead anyway and partner with open ai to put their "own chatbot" inside the open ai app?

> don't want to put in the human time and effort to do so

In most circles, that is "not that interested in getting good at it".

If I can tell ChatGPT to order me what I need to replace the bottom element on my water heater, and here’s a picture of the ridiculously long model number, that saves me quite a bit of time.

I used that as an example because I did that last week, apart from me just going to the store to get the links that it brought up.

I think you're misinterpreting what his comment meant. I read it as meaning that e-commerce has been optimised repeatedly over the 30 years, from a basic start (which as you pointed out was haphazard) to the point where it is now optimised to extract every possible cent from the user, whether by encouraging them to buy with one click (the Amazon one-click patent must be around 20 years old now), time-limited promo spot pricing, sending you e-mails about what you had in the basket if you don't complete a sale, etc...

Right now, by comparison, it sounds like AI based shopping is still in the very early stages. Maybe further along than the early e-commerce, but still with a long way to go in its evolution. That'll probably happen quicker than with e-commerce, because a lot of the knowledge about what does or doesn't work has already been learned, but it sounds like it's still a long way behind. Caveat - I've never used it myself, so I don't know how far it is along that path, I'm just basing that from the article.

I remember having to describe a standard model to predict online shopping behaviors for my ML class exam in university. That was close to 10 years ago now.

Also remember a teacher telling us about that story of a company finding a woman was pregnant from her shopping behavior and pushing relevant recommendation. Prompting people around her like her dad or something to find out she was pregnant

Ssshhh there’s an “VP of AI Transformation” getting paid $600,000 to do this plus the budget. They need their “AI transformation journey” to show to the board.

So, you're proposing we've been optimizing E-Commerce since...2021? Amazon was founded in 1994. It was not the first site selling things online (but it's the most recognizable one). E-Commerce has been getting attention for a *very* long time [0]

[0] https://en.wikipedia.org/wiki/Timeline_of_e-commerce

This is a very confusing comment to me. How were people buying books from Amazon in the 90s if it wasn't e-commerce?

Not so much and I'm certainly guilty of buying something from amazon because I'm already on amazon.com.

I have my favorite set of retailers that I use for a fair number of my purchases, I'm sure a lot of people are like that.

Since LLMs are trained on "random people online", why are they not of equal rank?

I don't think there is any line drawn here. I think if they executed well (and by they I mean any one of the three SOTA LLM vendors), they could already mortally wound the entire software industry today.

Whether or not they want, or will want, to do it at some point, is unknown; the reasons to not do it now are obvious:

1) it's more profitable to keep renting intelligence per token to everyone, preserving the status quo and milking it indefinitely (i.e. while the models aren't yet good enough to reliably single-shot complex software products from half-baked prompts, because once they get there, disruption will happen organically)

2) trying to compete with ~every other software product today is not likely to succeed in the end; a serious attempt would still burn down the software industry, but the major players don't have the capacity to handle it all at once, and doing it gradually will give enough time for regulatory agencies to try and stop it; either way, no one wins

More targeted ads.

Today, ads are based on user information you can reasonably collect from the users historical actions on your website, and then whatever search term they enter.

But soon, ads can be based on your current chat context + (derived interests of yours from your entire chat history across all chats. Shhhh.) passed in full to the e-commerce website that will use it to choose ads, generates creatives on the fly, all that crap, hyper-specific to you.

I'm so excited. Aren't you?

Now, as a side effect, searching through these can become better experience wise as well. They can use all that context and genuinely surface fewer, better results. But that's not the motivation of the e-commerce player anyways. If the ads work they'll be happy.

30 years ago is 1996. Amazon had been around for 2 years (they were incorporated in 1994).

Is there a way to measure users "making the best choice?" You could measure the amount of time spent comparison-shopping, but most people are terrible at that anyway; it's an acquired skill for sure. Besides a willingness to spend time, it seems like an impossible-to-quantify metric even in the abstract.

Catalog is impartial? Then why are ~40% of every search I do on Amazon a sponsored product? There is no pure "catalog" especially with cheap crap coming out every day from no-name Chinese labels.

Am I the only one that think Amazon has gotten pretty awful in the last 5 years?

That's a cynical way to look at it. Most likely the LLM will take a cut of sales and they'd be more or less indifferent who cuts the check. There's a market for this sort of thing. People will go to the best LLM for shopping. If the LLM is a shitty product, people will switch. LLMs are increasingly commoditized.

All you say is true for an aggregator like Amazon. But Amazon is better than Nike.com because as an aggregator they go from 1 to many retailers. LLMs will go from 1 aggregator (Amazon) to many so it will be better. And they don't have to invest a lot in UI/UX as chat is the interface.

Reliable information on this does not exist on vendor sites, though. It exists on Reddit and in books and in med/physio papers and bunch of other places a SOTA model has read in training or can (for now) access via web search.

LLMs are already very good for shopping, but only as long as they sit on the outside.

For me, for now, they are. And being "many random people" and not "random person", they average out into something much more trustworthy than even recommendations from most individuals I know personally.

Operative word is "for now" - LLMs caught entrepreneurs unprepared, but they'll catch up and poison this too, same thing that happened with search giving rise to SEO.

How would they mortally wound the software industry as of today?

I find their software to be of subpar quality and resilience anyways.

It depends. For home improvement projects, you can see what tools people are using. If a home repair channel is trustworthy, that may be a good start. General market research can help as well. For instance, post-China-buyout Craftsman should be avoided. For nearly anything else, it really depends. Name-brand electronics are usually safe unless they're small items (eg, power adapters, USB cords. Batteries are nearly impossible to purchase online without getting ripped off.) For clothing, I would just generally recommend only buying from thrift stores. For a lot of physical items (eg: door knobs, fuel hoses, etc.) it is actually quite difficult to purchase online. In person, we can tell a lot about quality just by touching the object with your hands. (eg: a flimsy shelf is not self-evident online, but is obvious in the hardware store.)

I suppose that's a long-winded way of saying that nearly every category of item requires its own strategy. For a brief period consumers were winning the information war and you could just go to Amazon, read the reviews, and get a superior product for cheap. We're now in a modern-but-old-fashioned situation. It's quite difficult to know if you're going to get ripped off, and you're forced to rely on more blunt heuristics. (eg: trust specific brands, buy things in person, etc.) None of these are perfect, but they are quickly becoming the best of some bad options.

> but rather subsume products, and this makes them an existential threat to the software industry.

The US stock market has priced this in already. Many software only companies are perceived to be under threat by ai. It represents a wonderful arbitrage opportunity for ai skeptics in fact.

> they're just holding back, because they realize that actually succeeding at this will instantly kill (or at least mortally wound) e-commerce

They definitely would if they could. They desperately need money. They already told the whole world they want to replace them, they just can’t.

> This is a more narrow version of my belief that general AI tools like LLMs fundamentally don't fit as additions to products, but rather subsume products

That seems reasonable, its just yet to be seen if LLMs are a form of artificial intelligence in any meaningful sense of the word.

They're impressive ML for sure, but that is in fact different from AI despite how companies building them have tried to merge the terms together.

So we need a Walmart MCP then...

RockAuto also has what some might consider a "dated" interface, but honestly it's light years better than trying to use NAPA's or CarQuest's website or god forbid looking through dealership parts counter websites. I honestly wish regular retailers would have stuck more closely with what worked for more B2B focused ecommerce, i.e. I wish shopping Best Buy or Home Depot was more akin to McMaster, Fastenall or some of the nicer supply house web portals.

Agree. AI is (currently) fantastic at "de-bullshitifying" the internet. "Give me a table that compares Products A & B by z, y, and z." Companies have gone out of their way to make comparison shopping near impossible. Specs are hidden, if they're shown at all. Just figuring out if a certain TV had an ARC-HDMI out required downloading the manual.

I dread the day when ads inevitably make their way into the main AI models. One of the things its currently good at will be destroyed.

Idk I earnestly tried using LLMs to find me the smallest by volume regular ATX PC case 3 months ago and it was a nightmare. That info is out there, but it could not avoid mentioning ITX, mini atx (sometimes because Reddit posters messed up) and just missed a bunch of cases. And letting in any mistakes meant I had to double check every volume calculation it did.

I found the Jonsbo D41 without the help of LLM despite trying. (There might be a few smaller but they are 3x the price)

LLMs don’t weigh and surveil the options well. They find some texts like from Reddit in this case that mention a bunch subset of cases and that text will heavily shape the answer. Which is not what you want a commerce agent to do, you don’t want text prediction. I doubt that gives the obscure but optimal option in most cases.

Why would investors keep paying their OpenAI’s engineers and power company, if they were on an obviously self-destructive trajectory?

> 30 years ago is 1996.

as an aside, fall of '96 is when i started college. There was an elementary school on my drive to class where I would routinely get caught in drop-off traffic. All those kids i remember crossing the street are at least in their mid 30s now. ...I think i need to lay down and it's not even 9AM my local time.

It's not cynical it is materialism.

Shoppers do not want to pay to shop. Retailers pay thousands to encourage you to shop with them. They are the economic buyers of this feature.

b-b-b--but muh AGI? just two more weeks of training, please

Well everyone is desperate to show that they’ve built and deployed some AI thing. Few have done so and demonstrated meaningful value that justifies all the expense of doing it.

You can skip sponsored products

That is spot on.

They forgot the first thing. Why would a customer use it and does it help them buy more stuff so I make more money?

Just putting an AI in there for the heck of it is doomed to failure.

I can think of a few different ways AI could be used inside a shopping app especially at the size of a company like walmart. Such as 'hey try our picknick planner?', 'need some sort of DIY project? Ask our bot for help'. Guide the user on what they need for a project and hey look here we have that stuff in stock at your local store today.

The cart experience one of the last places I would put an AI. At that point the customer is 'done' and they want out.

Of course anecdotal but 2 months ago I tried to do that for a missing bolt in a popular scooter (roughly 7 years old, bought 2nd hand so didn't know exact specs). I fed it various images that I took + internet images. It found a bunch of local shops but always found the wrong part (but very similar looking). I double-checked everything multiple times, via multiple contexts, even different pre-prompts from various sources, and asking plenty of questions. We chatted in thinking mode for what felt like ages, and according to paragraphs explaining why it HAD to be the right one, multiple times, with evidence that it sometimes gladly generated in image form (often completely garbage imagery e.g. with half-drawn bolts extruding from multiple surfaces). Eventually it found something very plausible which I ordered. It was the wrong part.

I had to get someone on the phone to help me find and order the right part (which was on their website, for many years according to waybackmachien).

I love LLMs but it's still totally hit/miss what you get. I'd rather not give it write-access to my bank account just yet.

more like 20 years. Basically when they introduced third party sellers.

In fairness to your point, I also find that Amazon reviews can no longer be trusted, and I really try to buy as little as possible from Amazon. Due to this, and other reasons, I find it quite difficult to have a good sense for whether I've bought something high quality, or if it'll be a piece of trash.

But we know it and it's obvious.

We are talking about a hypothetical sales chatbot which would be built alongside the business, so they absolutely have the capacity and information necessary to train the chatbot to advise their own clients.

I see LLM as the average of multiple random people and traditional common sense from wikipedia and books.

Conversely, I did something similar, but I took a picture of the model number, copy/pasted the text from the image into a search engine, and that was that. Either way you're taking a picture and performing a manual step (query an LLM, query a search engine)

I would never trust an LLM to accurately identify and purchase something for me based on a picture, a prompt, and a prayer.

Maybe in yours?

Someone can want a thing, even very badly, without wanting to put in the work for it.

Conversely, someone can work very hard for something they do not want.

The linkage between wanting a thing and wanting to do the work to get it is not absolute, or necessary there at all.

It's really hard to be a generalist and better than all the specialists at everything. OpenAI wants to focus on the G in AGI, and optimizing for ecommerce is just not that interesting to them, so of course it can't compete with Walmart.

ChatGPT doesn’t know what the best-converting dog food in Scranton, PA is. Amazon does.

Anything that starts with chat history presumes the theoretical limit for ad effectiveness is higher than it is now, and chat is a better way of getting there than actual purchase history. I have a feeling it’s not.

Imagine a person who shops on Amazon for basically everything. So theoretically Amazon should know a ton about them, more than enough to put together a profile on that person.

To say OpenAI could do a better job of selling products is to say they can do better than Amazon already does if you scroll through their personalized product recommendations. There is some better feed out there, or some better way of presenting the feed that Amazon hasn’t thought of.

I don’t doubt it can be marginally better.

I do doubt whether it can be double or triple digits better that can justify trillion dollar valuations. And I do doubt whether a model trained on Internet text rather than user interactions can do better.

Buying astral to get uv is a wound but not a mortal once because it got forked this weekend.

Maybe the best proxy metric is whether the customer returns the product. But the store will also be willing to eat more returns on a higher margin item if they make more profit at the end of the day.

By embracing adversarial interoperability - instead of chasing hundreds of integration deals across industries that put LLMs in products, they focused fully on integrating product access into chat, by combination of business deals, apps/MCPs, and engineer/designer support for users, all directed towards the goal of having the LLM become the "superapp" where work is done, gradually replacing product classes in order of how easy it is.

There's lots of easy but drudge work to enable this that needs to be done at the fringes. For example, LLMs today could easily replace most people's smartphone homescreen experience, or travel/commute experience, as the data is there and LLMs have the capability, even prices are acceptable - what's missing is explicit first-party support to wire it up, keep it wired up.

One step up, what's missing is accepting this explicitly as a goal: to replace software, to make existing products (whether whole or in pieces) the tools AI uses to do work for you. All the vendors seem to carefully walk around the idea, but avoid engaging with it directly, because once they do, they'll be competing with everyone instead of milking them.

What I'm saying is not (directly) related to whether or not LLMs are "true AI" or not. It's sufficient that they are fully general problem solvers.

A software product (whether bought or rented as a service) is defined by its boundaries - there's a narrow set of specific problems, and specific ways it can be used to solve those problems, and beyond those, it's not capable (or not allowed) to be used for anything else. The specific choices of what, how, and on what terms, are what companies stick a name to to create a "software product", and those same choices also determine how (and how much) money it will make for them.

Those boundaries are what LLMs, as general-purpose problem solvers, break naturally, and trying to force-fit them within those limits means removing most of the value they offer.

Consider a word processor (like MS Word). It's solving the problem of creating richly-formatted, nice-looking documents. By default it's not going to pick the formatting for you, nor is it going to write your text for you. Now, consider two scenarios of adding LLMs to it:

- On the inside: the LLM will be able to write you a poem or rewrite a piece of document. It could be made to also edit formatting, chat with you about the contents, etc.

- From the outside: all the above, but also the LLM will be able to write you an itinerary based on information collected from maps/planning tool, airline site, hotel site, a list of personal preferences of your partner, etc. It will be able to edit formatting to match your website and presentation made in the competitor's office tools and projected weather for tomorrow.

Most importantly, it will be able to do both of those automatically, just because you set up a recurring daily task of "hey, look at my next week's worth of calendar events and figure out which ones you can do some useful pre-work for me, and then do that".

That's the distinction I'm talking about, that's the threat to software industry, and it doesn't take "true AI" - the LLMs as we have today are enough already. It's about generality that allows them to erase the boundaries that define what products are - which (this is the "mortal wound to software industry" part) devalues software products themselves, reducing them to mere tool calls for "software agents", and destroying all the main ways software companies make money today - i.e. setting up and exploiting tactics like captive audience, taking data hostage, bundled offers, UI as the best marketing/upsale platform, etc.

(To be clear - personally, I'm in favor of this happening, though I worry about consequences of it happening all at once.)

Drifting off topic now, but Amazon could easily implement a few measures to really lock down reviews, but they purposely leave it gameable because it drives sales.

> they absolutely have the capacity and information necessary to train the chatbot to advise their own clients.

That doesn't follow. In fact, having this capacity and information creates a moral dilemma, as giving customers objectively correct advice is, especially in highly competitive markets, bad for business. Ignorance is bliss for businesses, because this lets them bullshit people through marketing with less guilt, and if there's one thing any business knows, is that marketing has better ROI than product/service quality anyway.

It's worth keeping in mind that some of those random people are trolls.

And yet that’s what all the AI boosters are claiming.

What do you know. Reality does t match.

I wonder if returns on ChatGPT purchased items are also higher.

It's simple, just tell it not to hallucinate.

Within a few years people will be accustomed to the idea of AI chatbots selling them stuff and it will be obvious then too. The first time paid placements appeared in a catalog, it was probably also not obvious then.

> Someone can want a thing, even very badly, without wanting to put in the work for it.

Generally, such highly-motivated people end up being thieves and grifters

openai has.... I'm not sure but let's say 500m free users, and it's not unreasonable to assume they eventually hit 1b. That is a lot of advertising revenue, which is what powers companies like Google and even smaller companies with only 300m users like Twitter. If ecommerce isn't a major focus for OpenAI then their board members are asleep at the wheel.

Good luck with that at the shareholder meeting.

There’s a difference between being interested in getting good at something and being good at something

Did they stop teaching "actions speak louder than words" in schools, or something?

No... I'm not saying chatgpt will do better than amazon.

>> passed in full to the e-commerce website that will use it to...

I'm saying Amazon+chat data will do better than amazon.

Thats the agentic shopping play.

In the process note that the chat host also gets a lot of info over time.

They can’t even deliver their own flagship products without bugs, and terrible UX. So I’m doubtful of their abilities.

These are also the same companies allowing their AI to make decisions in war, have no qualms about the mental issues they’re causing in people, and have abused workers in 3rd world countries for years.

But you think they’re holding out on “destroying the software industry” out of the goodness of their hearts? Come on

> That's the distinction I'm talking about, that's the threat to software industry, and it doesn't take "true AI" - the LLMs as we have today are enough already.

They most certainly are not. With the current state of LLMs, anyone who puts them in charge of things is being a fool. They have zero intelligence, zero ability to cope with novel situations, and even for things in their training data they do worse than a typical skilled practitioner would. Right now they are usable only for something where you don't care about the quality of the result.

I don't think I agree. If I overpay by 10%, I'll never know it and probably wouldn't return it even if I did know--once the shrinkwrap is off, too late. If a superior product exists but I don't find it, by definition I wouldn't know and wouldn't return the thing I did buy.

What you lose is control. Even in the case of an actually-intelligent agent, if you task a subordinate with producing a document for you, they are going to come up with something that is different from exactly what you had in mind. If they are really good, they might even surprise you and do a better job than than you'd have done yourself, but it still will be their vision, not yours.

Your notion of a "mortal wound" to the software industry seems to assume that today's SaaS portals are the only form that industry can take. Great software is "tool calls for agents". Those human agents who care about getting exactly the result they want will not be keen on giving up Photoshop for Photoshop-but-with-an-AI-in-front-of-it.

> and it doesn't take "true AI" - the LLMs as we have today are enough already.

I believe that relatively few people would agree with you on that point. LLMs aren’t good enough (yet?), and very obviously so, IMO, to be autonomous problem solvers for the vast majority of problems being solved by software companies today.

Exactly. Just because you're not good at something doesn't mean you don't want to be.

Did they start teaching that all idioms are always true without nuance in schools, or something?

"Someone can want a thing, even very badly, without wanting to put in the work for it."

Pretty much the impetus behind a lot of theft. Sure, there's thieving because people can't afford food, but that's all theft. There's theft because they are addicts and don't want to sober up long enough to earn money, so they still things. There's others that can't afford something so rather than saving for it, they just take it.

Ok fair point, and the general principle of “more data=higher accuracy” probably applies.

I think the issue is the tradeoff between accuracy and cost (on the seller’s side). If you get more accurate and convert more but your costs go up too much, you actually lose money.

Current systems are basically in a sweet spot of speed, cost, and accuracy.

And I will go back to my previous point that I believe there is simply a limit to how much people will buy, and it might already be saturated. I could be wrong though.

I think his reasoning was pretty clearly presented as not the goodness of their heart but rather the medium to long term predicted outcome on their bottom line. Ultimately failing or getting tangled up with regulators any more than necessary is to be avoided. If you move too early and it chases people away from your platform which undermines your ability to keep innovating then a competitor who held back will ultimately eat your lunch.

Is 'the work' not reflected in 'consequences' in terms of theft?

I'm not sure how to convey this idea properly...Can't you view the repercussions of theft (Legal action, distrust, etc) as 'work' being put in? Sure, it's a different kind of work, but while I have a lack of motivation to want to work to buy a Lambo as I find them not worth the value, I also have a lack of motivation to steal a Lambo as I find it not worth the consequences.

But then there is no safe way for them to "mortally wound" the software industry. The full argument is moot.

I would add there are more reasons why this wouldn't work: costs due to OOM more usage, adoption/AI backlash, adversarial environment, players with big head starts (Google).

I understand what you are saying but nonetheless struggle to view the possibility of maybe getting caught and then maybe getting punished, as "work". It (the abstract concept of something possibly happening) fits into none of the definitions of "work" I have heard. Moreover, many crimes are committed without the perpetrator even thinking of the consequences.

Consider an alternative viewpoint: rather than contorting the definition of "work" in such a way and convincing everyone to accept the new definition, we might instead be content saying "someone can want a thing, even very badly, without wanting to put in the work for it."

In normal society, people earn money within the legal confines of the society they are in. If you're a thief and trying to skirt that normal "earning of money", which is what normal people equate to "work", your work is scheming a plan to obtain the item without getting caught and possibly how to fence the item for money if you're not just using the item directly.

Equating "work" as the repercussions is looking at things in strange way. That's just punishment for "working" outside of the legal confines of society.

Yes, I believe the original commenter made that exact point.

You don't need to personally win in order to mortally wound someone. It can be informative to speculate about whether or not something is possible regardless of it being strategically advisable in the current context.

Oh, I'm with you mate, I'm not trying to die on a hill over here re-defining 'work'. I was just looking from a more esoteric view, "Do you count the risk of consequences as potential effort" I think is at least more proper phrasing.

“Effort” is a great wordchoice.