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Chatbots are overrated. AI needs a UI revolution. Here, I break down the 4 types of innovative interfaces for AI products that I've observed (with demos of 8 great AI products, including Granola NotebookLM Huxe Snipd | AI Podcast Player quillmeetings Particle News )

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Zara Zhang

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31,417 görüntüleme • 1 yıl önce •via X (Twitter)

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Why most AI products fail: Lessons from 50+ AI deployments at OpenAI, Google & Amazon Aish and Kiriti Badam have built 50+ enterprise AI products across companies like OpenAI, Google, Amazon, and Databricks. Based on these experiences, they’ve developed a small set of best practices for building and scaling successful AI products. Our goal with this conversation is to save you and your team a lot of pain and suffering while building your AI products. We discuss: 🔸 Two key ways AI products differ from traditional software 🔸 Common patterns and anti-patterns when building successful AI products 🔸 Their framework for iteratively building AI products 🔸 Why evals aren’t a cure-all 🔸 Why obsessing about customer trust and reliability is an underrated driver of successful AI products 🔸 The skills that matter most for builders in the AI era Listen now 👇 • YouTube: • Spotify: • Apple: Thank you to our wonderful sponsors for supporting the podcast: 🏆 Merge — The fastest way to ship 220+ integrations: 🏆 Strella — The AI-powered customer research platform: 🏆 Brex — The banking solution for startups:
1:32

Why most AI products fail: Lessons from 50+ AI deployments at OpenAI, Google & Amazon Aish and Kiriti Badam have built 50+ enterprise AI products across companies like OpenAI, Google, Amazon, and Databricks. Based on these experiences, they’ve developed a small set of best practices for building and scaling successful AI products. Our goal with this conversation is to save you and your team a lot of pain and suffering while building your AI products. We discuss: 🔸 Two key ways AI products differ from traditional software 🔸 Common patterns and anti-patterns when building successful AI products 🔸 Their framework for iteratively building AI products 🔸 Why evals aren’t a cure-all 🔸 Why obsessing about customer trust and reliability is an underrated driver of successful AI products 🔸 The skills that matter most for builders in the AI era Listen now 👇 • YouTube: • Spotify: • Apple: Thank you to our wonderful sponsors for supporting the podcast: 🏆 Merge — The fastest way to ship 220+ integrations: 🏆 Strella — The AI-powered customer research platform: 🏆 Brex — The banking solution for startups:

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0:50

"Prototypes are fast becoming the gold standard for design and product artifacts." Here's my new episode with David Kossnick 🇮🇱 (Head of AI Products at Figma) with an inside look at Figma's new AI prototyping tool. We had a great chat about: - Make's unique visual editing features - 4 types of evals to improve Make's output - How Figma learned from its past AI launches David also shared the best way for PMs and designers to navigate the "maze of choice" to build useful AI products. 📌 Watch now:

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"Maybe the right UI for AI is a generative UI." Here's my new interview with Stephen Chau featuring a live demo of Cove's ground-breaking visual AI interface that breaks free from chatbots. We had a great chat about: - Real world use cases for visual AI interfaces - Generative UI and just-in-time AI apps - How Stephen scaled Uber Eats to $25B ARR Some quotes from Stephen Chau: "In computing, we moved from the command line to graphic user interfaces. Chatbots are like the command line era of AI. What's next is this..." "Imagine the entire layout of the workspace and all its contents is something made just in time, based on what you're trying to do..." "Our goal with Uber Eats was to build a business that's the same size as the Rides business. Here's what mattered..." 📌 Watch now:
1:09

"Maybe the right UI for AI is a generative UI." Here's my new interview with Stephen Chau featuring a live demo of Cove's ground-breaking visual AI interface that breaks free from chatbots. We had a great chat about: - Real world use cases for visual AI interfaces - Generative UI and just-in-time AI apps - How Stephen scaled Uber Eats to $25B ARR Some quotes from Stephen Chau: "In computing, we moved from the command line to graphic user interfaces. Chatbots are like the command line era of AI. What's next is this..." "Imagine the entire layout of the workspace and all its contents is something made just in time, based on what you're trying to do..." "Our goal with Uber Eats was to build a business that's the same size as the Rides business. Here's what mattered..." 📌 Watch now:

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Made a simple podcast using AI on the Echoes of War play 😅😅😅😅 .. tell me if this is the future of podcasts AI Tools: Heygen AI and Google NotebookLM for the news sources Non AI tools: Capcut for video and Audacity for Audio editing
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Made a simple podcast using AI on the Echoes of War play 😅😅😅😅 .. tell me if this is the future of podcasts AI Tools: Heygen AI and Google NotebookLM for the news sources Non AI tools: Capcut for video and Audacity for Audio editing

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I love podcasts, but I can’t keep up anymore. My backlog is 400+. I tried AI summaries — they suck! They lose what makes podcasts great. I still want the *original pod*. Just… only the best parts. So I gave AI control of my podcast app to guide me through the best moments. It's sooo good 🤯 We call it "AI DJ". It's now live in Snipd | AI Podcast Player.

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EP02: 7 mental models for designing AI products Over the last year I've interviewed the people designing today's top AI products like: ✧ Perplexity ✧ Claude ✧ Dot ✧ Humane ✧ Visual Electric This episode shines a light on some of my key takeaways 🔦

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We’re on a mission to revolutionize AI-powered products with limitless potential By seamlessly answering questions & executing tasks, the future of AI is within reach. Our aims is to empower users with actionable intelligence, including the tokenization of AI Agents! 🧠🤖
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We’re on a mission to revolutionize AI-powered products with limitless potential By seamlessly answering questions & executing tasks, the future of AI is within reach. Our aims is to empower users with actionable intelligence, including the tokenization of AI Agents! 🧠🤖

PAAL AI 🧠🤖

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I predict 50% of companies will need new leadership, because the old management style won't work in the era of AI. That's exactly why I'm seeing 95%+ of so-called "AI Transformation" initiatives fail. Most are bolting on AI pilots for functional tasks, but never touching the business core. just launched TrueNorth AI Decision platform for executives (Boss AI, TopSales AI, Investor AI agentic products) More on enterprise AI transformation in this interview with Danilo McGarry:
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I predict 50% of companies will need new leadership, because the old management style won't work in the era of AI. That's exactly why I'm seeing 95%+ of so-called "AI Transformation" initiatives fail. Most are bolting on AI pilots for functional tasks, but never touching the business core. just launched TrueNorth AI Decision platform for executives (Boss AI, TopSales AI, Investor AI agentic products) More on enterprise AI transformation in this interview with Danilo McGarry:

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Phil Trubey’s first-ever podcast! “AI Robotics: What We Haven’t Solved… Yet” Phil Phil Trubey and Scott Humanoid Scott break down the latest AI robotics demos. I found this episode packed with insightful takes you won’t want to miss! Watch here:

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3:41

India contributes 16% to Global AI talent and is among top 3 talent markets. Indians are the 2nd Largest contributor to public Gen-AI GitHub projects. It is estimated that AI-enabled GCCs will likely contribute 30-35% of revenues of the India’s AI services market by 2028. Thus, India has the potential for becoming the global hub for building various AI products & services. Given the large population with 650 million smartphone users, we should create scalable models for sectors beyond finance such as healthcare, education, agriculture, MSMEs, exports, etc. India can also build AI products that fits diverse use-cases across the world. It can be a laboratory for developing and testing AI ideas. Our AI stack must be rooted in Indian languages, local contexts, and multimodal interfaces, so that it can be widely accepted and accessed by our citizens. Focused approach across the AI stack can make India the AI torchbearer for the Global South. - Smt Nirmala Sitharaman.

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OpenAI, Perplexity, Google and Microsoft have in recent months introduced AI-powered features that allow users to search for products through chatbots, with autonomous agents able to complete orders on behalf of consumers.
2:43

OpenAI, Perplexity, Google and Microsoft have in recent months introduced AI-powered features that allow users to search for products through chatbots, with autonomous agents able to complete orders on behalf of consumers.

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We are not just another AI Project, we are building 4 massive products on Hyperliquid 💠Preconfigured Prompts: Users can choose from a list of predefined prompts that align with their trading strategies or goals, including market analysis, risk management, and more. 💠Trading Assistance on the Hyperliquid DEX 💠Connect Your X Account to the AI Agent 💠Marketplace for AI Agents Check it out! $HYPEAI
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We are not just another AI Project, we are building 4 massive products on Hyperliquid 💠Preconfigured Prompts: Users can choose from a list of predefined prompts that align with their trading strategies or goals, including market analysis, risk management, and more. 💠Trading Assistance on the Hyperliquid DEX 💠Connect Your X Account to the AI Agent 💠Marketplace for AI Agents Check it out! $HYPEAI

Hyper DeFAI

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Users state the goal. xBubble handles the building path. With Bubble Code, xBubble helps users create different kinds of Code AI Agents & AI roducts. The key is not just generating a prototype. Bubble Code is built to turn user goals into ready-to-use products with real interfaces, logic, integrations, and deployment paths. AI products should not stop at a mockup. With xBubble, they can be built, deployed, and used directly.
0:30

Users state the goal. xBubble handles the building path. With Bubble Code, xBubble helps users create different kinds of Code AI Agents & AI roducts. The key is not just generating a prototype. Bubble Code is built to turn user goals into ready-to-use products with real interfaces, logic, integrations, and deployment paths. AI products should not stop at a mockup. With xBubble, they can be built, deployed, and used directly.

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The team at is pioneering what it means to design with AI... (and it's working 🚀) So I interviewed their Head of Design to learn the principles for designing AI products 👇
1:23

The team at is pioneering what it means to design with AI... (and it's working 🚀) So I interviewed their Head of Design to learn the principles for designing AI products 👇

Ridd 🤿

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Great #ces2026 Report #7: The company inside the coolest AI products at CES. Makes low power AI chips inside a wide range of consumer products. Watches, rings, AI glasses, medical devices, all use their chips because they are best at running neural networks at very low power. I've been touring the suites all morning, getting a look at augmented reality AI glasses. It's quite clear that the Pickle glasses are not possible with today's technology, and I'll have a video up someday soon about that with several different vendors. So agree with others that it is selling something that isn’t currently possible to manufacture. I got a look at the latest state-of-the-art technologies that go into the glasses, and this is the first part of that. This gives you a lot of insights into the future.
18:07

Great #ces2026 Report #7: The company inside the coolest AI products at CES. Makes low power AI chips inside a wide range of consumer products. Watches, rings, AI glasses, medical devices, all use their chips because they are best at running neural networks at very low power. I've been touring the suites all morning, getting a look at augmented reality AI glasses. It's quite clear that the Pickle glasses are not possible with today's technology, and I'll have a video up someday soon about that with several different vendors. So agree with others that it is selling something that isn’t currently possible to manufacture. I got a look at the latest state-of-the-art technologies that go into the glasses, and this is the first part of that. This gives you a lot of insights into the future.

Robert Scoble

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Building an AI factory is the next industrial revolution for the modern enterprise. In this episode of the NVIDIA AI Podcast, Justin Boitano, VP and GM of Enterprise Computing at NVIDIA, and Chris Wright, CTO and SVP of Global Engineering at Red Hat AI, break down the "five-layer cake" and the rise of autonomous agentic systems. 🎙️ Listen to the episode:
1:39

Building an AI factory is the next industrial revolution for the modern enterprise. In this episode of the NVIDIA AI Podcast, Justin Boitano, VP and GM of Enterprise Computing at NVIDIA, and Chris Wright, CTO and SVP of Global Engineering at Red Hat AI, break down the "five-layer cake" and the rise of autonomous agentic systems. 🎙️ Listen to the episode:

NVIDIA AI

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What's about using some AI Agents on #Web3? Or what about using predictive AI on the #blockchain? Here is a summary of ( $AWARE ) existing products: 🔹Subscriptions for businesses! 🔹Free for regular users! #AIAgents
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What's about using some AI Agents on #Web3? Or what about using predictive AI on the #blockchain? Here is a summary of ( $AWARE ) existing products: 🔹Subscriptions for businesses! 🔹Free for regular users! #AIAgents

ChainAware.ai

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We're entering a new era of software where a single person, working with AI agents, can build products that previously required entire teams. In this episode of the Lightcone Podcast, they break down the rise of AI coding agents, "tokenmaxxing", and the emerging workflows behind tools like Claude Code and OpenClaw. They discuss why AI systems today feel less like productivity tools and more like collaborators, why the future of AI should be personal and user-controlled, and how founders are starting to build software in completely new ways. 00:00 — Will you control your AI? 00:47 — Coding again after 13 years 01:56 — Rebuilding a startup with Claude Code 05:50 — Software that thinks like a journalist 07:09 — The rise of “tokenmaxxing” 10:07 — The accidental creation of GStack 14:21 — The workflow behind 400x output 20:59 — Thin Harness, Fat Skills 24:35 — AI agents are like Ferraris 27:12 — The future of personal AI 38:37 — Buying back time with tokens
41:29

We're entering a new era of software where a single person, working with AI agents, can build products that previously required entire teams. In this episode of the Lightcone Podcast, they break down the rise of AI coding agents, "tokenmaxxing", and the emerging workflows behind tools like Claude Code and OpenClaw. They discuss why AI systems today feel less like productivity tools and more like collaborators, why the future of AI should be personal and user-controlled, and how founders are starting to build software in completely new ways. 00:00 — Will you control your AI? 00:47 — Coding again after 13 years 01:56 — Rebuilding a startup with Claude Code 05:50 — Software that thinks like a journalist 07:09 — The rise of “tokenmaxxing” 10:07 — The accidental creation of GStack 14:21 — The workflow behind 400x output 20:59 — Thin Harness, Fat Skills 24:35 — AI agents are like Ferraris 27:12 — The future of personal AI 38:37 — Buying back time with tokens

Y Combinator

67,145 görüntüleme • 3 ay önce