The problem with this approach is precisely that these apps/widgets have hard-coded input and output schema. They can work quite well when the user asks something within the widget's capabilities, but the brittleness of this approach starts showing quickly in real-world use. What if you want to use more advanced filters with Zillow? Or perhaps cross-reference with StreetEasy? If those features aren't supported by the widget's hard-coded schema, you're out of luck as a user.
What I think it much more exciting is the ability to completely create generative UI answers on the fly. We'll have more to say on this soon from Phind (I'm the founder).
That said, I used it a lot more a year ago. Lately I’ve been using regular LLMs since they’ve gotten better at searching.
Conservational user interfaces are opaque; they lack affordances. https://en.wikipedia.org/wiki/Affordance
I immediately knew the last generation of voice assistants was dead garbage when there was no way to know what it could do, they just expected you to try 100 things, until it worked randomly
For a concrete example, think a search result listing that can be broken down into a single result or a matrix to compare results, as well as a filter section. So you could ask for different facets of your current context, to iterate over a search session and interact with the results. Dunno, I’m still researching.
Have you written somewhere about your experience with Phind in this area?
Per the docs: 'Every app comes from a verified developer who stands behind their work and provides responsive support'
That's thinly veiled corporate speak for, Fortune 500 or GTFO
Sure, but deploying a website or app doesn't mean anyone's going to use it, does it?
I could make an iOS app, I could make a website, I could make a ChatGPT app... if no one uses it, it doesn't matter how big the userbase of iOS, the internet, or ChatGPT is...
MCP standardizes how LLM clients connect to external tools—defining wire formats, authentication flows, and metadata schemas. This means apps you build aren't inherently ChatGPT-specific; they're MCP servers that could work with any MCP-compatible client. The protocol is transport-agnostic and self-describing, with official Python and TypeScript SDKs already available.
That said, the "build our platform" criticism isn't entirely off base. While the protocol is open, practical adoption still depends heavily on ChatGPT's distribution and whether other LLM providers actually implement MCP clients. The real test will be whether this becomes a genuine cross-platform standard or just another way to contribute to OpenAI's ecosystem.
The technical primitives (tool discovery, structured content return, embedded UI resources) are solid and address real integration problems. Whether it succeeds likely depends more on ecosystem dynamics than technical merit.
Personally I don't hope thats the future.
I was really hoping Apple would make some innovations on the UX side, but they certainly haven’t yet.
“CEO” Fidji Simo must really need something to do.
Maybe I’m cynical about all of this, but it feels like a whole lot of marketing spin for an MCP standard.
They want to be the platform in which you tell what you want, and OAI does it for you. It's gonna connect to your inbox, calendar, payment methods, and you'll just ask it to do something and it will, using those apps.
This means OAI won't need ads. Just rev share.
Ads are defenitely there. Just hidden so deeply in the black box which is generating the useful tips :)
If OpenAI thinks there’s sweet, sweet revenue in email and calendar apps, just waiting to be shared, their investors are in for a big surprise.
OpenAI’s moat will only come from the products they built on top. Theoretically their products will be better because they’ll be more vertically integrated with the underlying models. It’s not unlike Apple’s playbook with regard to hardwares and software integration.
They obviously want both. In fact they are already building an ad team.
They have money they have to burn, so it makes sense to throw all the scalable business models in the history, eg app store, algo feed, etc, to the wall and see what stick.
In 2024, iOS App Store generated $1.3T in revenue, 85% of which went to developers.
Edit: yes I understand it is correct, but still it sounds like an insane amount
We now know why Flash was murdered.
I had a lot of hopes after the Adobe buyout that Flash would morph into something based around ActionScript (ES4) and SVG. That didn't happen. MS's Silverlight/XAML was close, but I wasn't going to even consider it without several cross-platform version releases.
This is a stupid conspiracy given Apple decided not to support Flash on iPhone since before Jobs came around on third-party apps. (The iPhone was launched with a vision of Apple-only native apps and HTML5 web apps. The latter's performance forced Cupertino's hand into launching the App Store. Then they saw the golden goose.)
That 1T figure is real, but it includes things like if you buy a refrigerator using the Amazon iOS app.
I'm genuinely surprised these companies went with usage-based versus royalty pricing.
Connecting these apps will, at times, require authentication. Where it does not require payment, it's a fantastic distribution channel.
"Find me hotels in Capetown that have a pool by the beach .Should cost between 200 dollars to 800 dollars a night "
I don't see how this is a significant upgrade over the many existing hotel-finder tools. At best it slightly augments them as a first pass, but I would still rather look at an actual map of options than trust a stream of generated, ad-augmented text.
This time will be different?
e.g. Coursera can send back a video player
I could see chat apps becoming dominant in Slack-oriented workplaces. But, like, chatting with an AI to play a song is objectively worse than using Spotify. Dynamically-created music sounds nice until one considers the social context in which non-filler music is heard.
There's a whole bizarre subculture in computing that fails to recognize what it is about computers that people actually find valuable.
Getting an AI to play "that song that goes hmm hmmm hmmm hmmm ... uh, it was in some commercials when I was a kid" tho
Absolutely. The point is this is a specialised and occasional use case. You don't want to have to go through a chat bot every time you want to play a particular song just because sometimes you might hum at it.
The closest we've come to a widely-adopted AR interface are AirPods. Critically, however, they work by mimicing how someone would speak to a real human by them.
Everyone wants the next device category. They covet it. Every other company tries to will it into existence.
I’m not very bullish on people wanting to live in the ChatGPT UI, specifically, but the concept of dynamic apps embedded into a chat-experience I think is a reasonable direction.
I’m mostly curious about if and when we get an open standard for this, similar to MCP.
The former is like a Waymo, the latter is like my car suddenly and autonomously deciding that now is a good time to turn into a Dollar Tree to get a COVID vaccine when I'm on my way to drop my kid off at a playdate.
What users want, which various entities religiously avoid providing to us, is a fair price comparison and discovery mechanism for essentially everything. A huge part of the value of LLMs to date is in bypassing much of the obfuscation that exists to perpetuate this, and that's completely counteracted by much of what they're demonstrating here.
So perhaps chatbots are an excellent method for building out a prototype in a new field while you collect usage statistics to build a more refined UX - but it is bizarre that so many businesses seem to be discarding battle tested UXes for chatbots.
I remember reading some not-Neuromancer book by William Gibson where one of his near-future predictions was print magazines but with custom printed articles curated to fit your interests. Which is cool! In a world where print magazines were still dominant, you could see it as a forward iteration from the magazine status quo, potentially predictive of a future to come. But what happened in reality was a wholesale leapfrogging of magazines.
So I think you sometimes get leapfrogging rather than iteration, which I suspect is in play as a possibility with AI driven apps. I don't think apps will ever literally be replaced but I think there's a real chance they get displaced by AI everything-interfaces. I think the mitigating factor is not some foundational limit to AI's usefulness but enshittification, which I don't think used to consume good services so voraciously in the 00s or 2010s as it does today. Something tells me we might look back at the current chat based interfaces as the good old days.
I'm not sure that claim is justified. The primary agentic use case today is code generation, and the target demographic is used to IDEs/code editors.
While that's probably a good chunk of total token usage, it's not representative of the average user's needs or desires. I strongly doubt that the chat interface would have become so ubiquitous if it didn't have merit.
Even for more general agentic use, a chat interface allows the user the convenience of typing or dictating messages. And it's trivially bundled with audio-to-audio or video-to-video, the former already being common.
I expect that even in the future, if/when richer modalities become standard (and the models can produce video in real-time), most people will be consuming their outputs as text. It's simply more convenient for most use-cases.
but if the apps are trusting ChatGPT to send them users based on those sort of queries, it's only a matter of time before ChatGPT brings the functionality first-party and cuts out the apps - any app who believes chat is the universal interface of the future and exposes their functionality as a ChatGPT app is is signing their own death warrant.
I'd much rather see a thriving ecosystem full of competition and innovation than a more stagnant alternative.
For example, React and TypeScript were hard to set up initially. I deferred learning them for years until the tooling improved and they were clearly here to stay. Likewise, I'm glad I didn't dive into tech like LangChain and CoffeeScript, which came and went.
You can see the hype cycle's timeline in HN's Algolia search: https://hn.algolia.com/?dateRange=all&page=0&prefix=true&que...
The big hype wave has finished now (we still have the "how dare you criticise our technology bros" roaming around though), the tooling is maturing now. It's almost time for me to actually get my feet wet with it :)
On a more serious note, it remains to be seen if this even sticks / is widely embraced.
so, best of luck to OAI. we'll see how this plays out
Why would I use a chat to do what could be done quicker with a simple and intuitive button/input UX (e.g. Booking or Zillow search/filter)? Chat also has really poor discoverability of what I can actually do with it.
Custom GPTs (and Gemini gems) didn't really work because they didn't have any utility outside the chat window. They were really just bundled prompt workflows that relied on the inherent abilities of the model. But now with MCP, agent-based apps are way more useful.
I believe there's a fundamentally different shift going on here: in the endgame that OpenAI, Anthropic et al. are racing toward, there will be little need for developers for the kinds of consumer-facing apps that OpenAI appears to be targeting.
OpenAI hinted at this idea at the end of their Codex demo: the future will be built from software built on demand, tailored to each user's specific needs.
Even if one doesn't believe that AI will completely automate software development, it's not unreasonable to think that we can build deterministic tooling to wrap LLMs and provide functionality that's good enough for a wide range of consumer experiences. And when pumping out code and architecting software becomes easy to automate with little additional marginal cost, some of the only moats other companies have are user trust (e.g. knowing that Coursera's content is at least made by real humans grounded in reality), the ability to coordinate markets and transform capital (e.g. dealing with three-sided marketplaces on DoorDash), switching costs, or ability to handle regulatory burdens.
The cynic in me says that today's announcements are really just a stopgap measure to: - Further increase the utility of ChatGPT for users, turning it into the de facto way of accessing the internet for younger users à la how Facebook was (is?) in developing countries - Pave the way for by commoditizing OpenAI's complements (traditional SaaS apps) as ChatGPT becomes more capable as a platform with first-party experiences - Increase the value of the company to acquire more clout with enterprises and other business deals
But cynicism aside, this is pretty cool. I think there's a solid foundation here for the kind of intent-based, action-oriented computing that I think will benefit non-technical people immensely.
I'mma call it now just for the fun of it: This will go the way of their "GPT" store.
Of course, part of it was due to the fact that the out-of-the-box models became so competent that there was no need for a customized model, especially when customization boiled down to barely more than some kind of custom system prompt and hidden instructions. I get the impression that's the same reason their fine-tuning services never took off either, since it was easier to just load necessary information into the context window of a standard instance.
Edit: In all fairness, this was before most tool use, connectors or MCP. I am at least open to the idea that these might allow for a reasonable value add, but I'm still skeptical.
> I get the impression that's the same reason their fine-tuning services never took off either
can you share anymore info on this. i am curious about what the usecase was and how it improved speed (of inference?) and accuracy.
Disclaimer: this was in the 3.5 Turbo "era" so models like `nano` now might be cheap enough, good enough, fast enough to do this even without FT.
It has the potential to bridge the gap between pure conversation and the functionality of a full website.
I can block adds on a search engine. I cannot prevent an LMM from having hidden biases about what the best brand of vodka or car is.
compacct27•2h ago