We are launching Phind 3 (https://www.phind.com), an AI answer engine that instantly builds a complete mini-app to answer and visualize your questions in an interactive way. A Phind mini-app appears as a beautiful, interactive webpage — with images, charts, diagrams, maps, and other widgets. Phind 3 doesn’t just present information more beautifully; interacting with these widgets dynamically updates the content on the page and enables new functionality that wasn’t possible before.
For example, asking Phind for “options for a one-bedroom apartment in the Lower East Side” (https://www.phind.com/search/find-me-options-for-a-72e019ce-...) gives an interactive apartment-finding experience with customizable filters and a map view. And asking for a “recipe for bone-in chicken thighs” gives you a customizable recipe where changing the seasoning, cooking method, and other parameters will update the recipe content itself in real-time (https://www.phind.com/search/make-me-an-recipe-for-7c30ea6c-...).
Unlike Phind 2 and ChatGPT apps, which use pre-built brittle widgets that can’t truly adapt to your task, Phind 3 is able to create tools and widgets for itself in real-time. We learned this lesson the hard way with our previous launch – the pre-built widgets made the answers much prettier, but they didn’t fundamentally enable new functionality. For example, asking for “Give me round-trip flight options from JFK to SEA on Delta from December 1st-5th in both miles and cash” (https://www.phind.com/search/give-me-round-trip-flight-c0ebe...) is not something that neither Phind 2 nor ChatGPT apps can handle, because its Expedia widget can only display cash fares and not those with points. We realized that Phind needs to be able to create and consume its own tools, with schema it designs, all in real time. Phind 3’s ability to design and create fully custom widgets in real-time means that it can answer these questions while these other tools can’t. Phind 3 now generates raw React code and is able to create any tool to harness its underlying AI answer, search, and code execution capabilities.
Building on our history of helping developers solve complex technical questions, Phind 3 is able to answer and visualize developers’ questions like never before. For example, asking to “visualize quicksort” (https://www.phind.com/search/make-me-a-beautiful-visualizati...) gives an interactive step-by-step walkthrough of how the algorithm works.
Phind 3 can help visualize and bring your ideas to life in seconds — you can ask it to “make me a 3D Minecraft simulation” (https://www.phind.com/search/make-me-a-3d-minecraft-fde7033f...) or “make me a 3D roller coaster simulation” (https://www.phind.com/search/make-me-a-3d-roller-472647fc-e4...).
Our goal with Phind 3 is to usher in the era of on-demand software. You shouldn’t have to compromise by either settling for text-based AI conversations or using pre-built webpages that weren’t customized for you. With Phind 3, we create a “personal internet” for you with the visualization and interactivity of the internet combined with the customization possible with AI. We think that this current “chat” era of AI is akin to the era of text-only interfaces in computers. The Mac ushering in the GUI in 1984 didn’t just make computer outputs prettier — it ushered in a whole new era of interactivity and possibilities. We aim to do that now with AI.
On a technical level, we are particularly excited about:
- Phind 3’s ability to create its own tools with its own custom schema and then consume them
- Significant improvements in agentic searching and a new deep research mode to surface hard-to-access information
- All-new custom Phind models that blend speed and quality. The new Phind Fast model is based on GLM-4.5-Air while the new Phind Large model is based on GLM 4.6. Both models are state-of-the-art when it comes to reliable code generation, producing over 70% fewer errors than GPT-5.1-Codex (high) on our internal mini-app generation benchmark. Furthermore, we trained custom Eagle3 heads for both Phind Fast and Phind Large for fast inference. Phind Fast runs at up to 300 tokens per second, and Phind Large runs at up to 200 tokens per second, making them the fastest Phind models ever.
While we have done Show HNs before for previous Phind versions, we’ve never actually done a proper Launch HN for Phind. As always, we can’t wait to hear your feedback! We are also hiring, so please don’t hesitate to reach out.
– Michael
For example, it feels like Google's featured snippet (quick answer box) but expanded. But the thing is, many people don't like the feature snippet, and there's a reason it doesn't appear for many queries - it doesn't contribute meaningfully to those.
This functionality is doing exactly the opposite of the process of building good web apps: Rather than "unpacking functionality" and making it specific for an audience, it "packs" all functionality into a generalized use case, at the cost of becoming extremely mediocre for each use case, which makes it precisely worse than any other tool you'd use for that job.
As a specific example, I clicked your apartments in LES search (https://www.phind.com/search/find-me-options-for-a-72e019ce-...) and it shows us just 4 listings...? It shows some arbitrary subset of all things I could find on StreetEasy, and then provides a subset of the search functionality, losing things such as days on market, neighborhood, etc.
It's a cool demo, but "on-demand software" is exactly "Solution-In-Search-of-a-Problem".
The difficult part you need to ask is, like feature snippet, what are the questions worth solving with this, and is the pain point big enough that it's worth solving?
I was hoping to get a map with arrows like "$35B in agriculture" from China to USA. I wasn't able to make it do that, but the information was still there presented in a reasonable way!
Rough edges: - aspect ratios on photos (maybe because I was on mobile, cropping was weird) - map was very hard to read (again, mobile) - some formatting problems with tables - it tried to show an embedded Gmap for one location but must have gotten the location wrong, was just ocean
I tried it out with a relatively basic Medicinal Chem/Pharmacology question, asking for an interactive Structure-Activity-Relationship viewer:
> "Build an interactive app showing SAR for a congeneric series. Use simple beta-2 agonists (salbutamol -> formoterol -> salmeterol). Display the common phenethylamine scaffold with R-group positions highlighted, and let me toggle substituents to see how logP, receptor binding affinity, and duration of action change."
https://www.phind.com/search/find-me-options-for-a-72e019ce-...
When I told Phind I'm a complete novice, it came up with very detailed instructions and troubleshooting tips.
Application error: a client-side exception has occurred while loading www.phind.com (see the browser console for more information).
Content-Security-Policy: (Report-Only policy) The page’s settings would block a script (script-src-elem) at https://www.phind.com/_next/static/chunks/c857e369-746618a9672c8ed0.js?dpl=dpl_4dLj9qrNQMh6evFNeDZbEJjTnT9B from being executed because it violates the following directive: “script-src 'none'”
GET https://www.phind.com/_next/static/chunks/4844-90bb89386b9ed987.js?dpl=dpl_4dLj9qrNQMh6evFNeDZbEJjTnT9B [HTTP/1.1 403 403 Forbidden 716ms]
>A geometry app with nodes which interact based on their coordinates which may be linked to describe lines or arcs with side panels for variables and programming constructs.
which resulted in:
https://www.phind.com/search/a-geometry-app-with-nodes-ed416...
which didn't seem workable at all, and notable was lacking in a side panel.
I’m curious to see how it evolves with more complex, multi-step queries.
I tried to make it generate an explainer page and it created an unrelated page: https://www.phind.com/search/explain-to-me-how-dom-66e58f3f-...
I tried generating your answer again: https://www.phind.com/search/explain-to-me-how-dom-78d20f04-....
First: my sense is that for most use cases, this will begin to feel gimmicky rather quickly and that you will do better by specializing rather than positioning yourself next to ChatGPT, which answers my questions without too much additional ceremony.
If you have any diehard users, I suspect they will cluster around very particular use cases, say business users trying to create quick internal tools, users who want to generate a quick app on mobile, scientists that want quick apps to validate data. Focusing on those clusters (your actual ones, not these specific examples) and building something optimized for their use cases seems likelier to be a stronger long term play for you
Secondly, I asked it to prove a theorem, and it gave me a link to a proof. This is fine, since LLM generated math proofs are a bit of a mess, but I was surprised that it didn't offer any visualizations or anything further. I then asked it for numerical experiments that support the conjecture, and it just showed me some very generic code and print statements for a completely different problem, unrelated to what I asked about. Not very compelling
Finally, and least important really: please stop submitting my messages when I hit return/enter! Many of us like to send more complex multi-line queries to LLMs
Good luck
if every response starts with "You're absolutely right -- ..." you know phind is hallucinating and you can immediately close the tab.
anyway I think you need better QA processes
But, assuming you are trying to be in between lovable and google, how are you not going to be steamrolled by google or perplexity etc the moment you get solid traction? Like, if your insight for v3 was that the model should make its own tools, so even less hardcoded, then i just dont see a moat or any vertical direction. What really is the difference?
Our long-term vision is to build a fully personalized internet. For Google this is an innovator's dilemma, as Google currently serves as a portal to the current internet.
I was surprised not to see a share and embed button. I would expect that could be huge for growth.
At least to me, this is totally fresh take on AI and providing answers. OpenAI is burning through billions without trying to make nicer interface or just come up with some innovation how to train models (Qwen and Minimax). Unlike Claude who tries to smother you with content and emojis, I got clean and focused answer to my query and an app.
Again, love it, thank you. If you have to sell yourself, make sure you get a lot of billions.
Not a single thing was actually shown or build. Astonishing what kind of crapware gets funded by YC if they slap AI on the application
Congrats on the launch and keep up the great work.