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    Technology

    Hallway Chat

    Fraser & Nabeel explore what it means to build great products in this new world of AI.

    Two former founders, now VCs, have an off-the-cuff conversation with friends about the new AI products that are worth trying, emerging patterns, and how founders are navigating a world that’s changing every week.

    Fraser is the former Head of Product at OpenAI, where he managed the teams that shipped ChatGPT and DALL-E, and is now an investor at Spark Capital. Nabeel is a former founder and CEO, now an investor at Spark, and has served on the boards of Discord, Postmates, Cruise, Descript, and Adept.

    It’s like your weekly dinner party on what’s happening in artificial intelligence.

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    Copyright: © All rights reserved

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    Latest Episodes:
    Distilling Lessons from AI in 2024 Dec 26, 2024
    Show notes

    What lessons will we take from 2024's AI products into next year? How better to reflect on advancements in the field of AI over this past year than to ask AI itself? Today, Fraser and Nabeel use AI models like ChatGPT, Claude, and o1 to first look back and see if products and innovations of 2023 lived up to their hype in 2024. And to look at the show’s year in review, Nabeel puts these AI models to the test by feeding them episode transcripts and seeing which model produces a usable summary. Together, they also dive into the effectiveness of Google Gemini’s Deep Research tool, the rise of agentic computing in 2024, and whether products ever fundamentally change or just get constantly re-invented.


    • (00:00) - Introduction
    • (00:48) - Reflecting on a Year of AI Releases
    • (00:23) - The Rise of Agentic AI
    • (00:38) - Google Gemini’s Deep Research
    • (00:47) - Using AI Models to Review 2024 at Hallway Chat
    • (00:56) - The Role of Taste in Making Great AI Products
    • (00:06) - The Rollout of o1
    • (00:06) - WebSim - Self Expression Through Software
    • (00:36) - Same Products, Different Iterations
    • (00:39) - A Second Look at Apple Intelligence
    • (00:10) - Living Agentically with AI
    • (00:18) - Final Thoughts

    Coaching Up: Should your AI be teaching you how to use it? Nov 22, 2024
    Show notes

    Everywhere you turn, companies have shoved AI features into their products that no one is using. Today, Fraser and Nabeel ask each other—are there any AI features that you’re actually using in older products? Plus: How kids will be shaped using AI products daily. What would a fully unstructured Slack look like. AI email habits. Do we think incumbents will catch up with AI integrations? PREM framework for startup prioritization. Is this startups vs incumbents, or just startups vs the big llms?

    • (00:00) - Intro
    • (00:52) - Welcome to Hallway Chat
    • (01:05) - What have incumbents really done with AI?
    • (08:59) - Trends in AI integrations that work
    • (20:21) - Reflecting, it's still early
    • (23:42) - Creating AI that manages up
    • (28:47) - PREM: A framework for prioritization
    • (34:32) - Forget incumbents, how do startups fight fend off the LLMs?
    • (37:24) - What are the new horizontals?

    Q&A: Is NotebookLM an exception to a rule? When to copy? When are small improvements better than big bets? Will data privacy matter? Nov 01, 2024
    Show notes

    Open format Q&A this week. Fraser and Nabeel explore AI data privacy, the ethics of copying features, and maintaining innovation. They discuss enterprise data challenges, the importance of a strong product identity, and strategies for early-stage startups during fundraising season.

    • (00:00) - Open
    • (00:53) - Q&A Session Kickoff
    • (01:14) - The data you gather is your roadmap
    • (14:03) - The gravity of slowing down in your startup
    • (21:20) - Your quarterly goal: Something Fundamentally Changes
    • (21:57) - Low Risk, Low Outcomes
    • (24:31) - Large Organizations and Mediocrity
    • (30:58) - When to steal a feature?

    "Software should be soft" - Meter Command with Anil Varanasi Sep 30, 2024
    Show notes

    Join Fraser, Nabeel, and special guest Anil from Meter as they dive into the innovation behind Meter Command. Meter's new interface has been called the "future of software" and a far ranging interview talks about the problem of designing product around personas, how command interfaces bridge the gap between CLI and dashboards, the importance of owning your tech stack, how your data is your product roadmap, and the orientation to long term thinking while still staying on the cutting edge.

    Links
    * See a demo of Meter Command
    * There's a lot of fine work from Bret Victor on visualization and interfaces, but here's one to get you started
    * Geoffrey Litt's Malleable SW in the age of LLMs
    * Hunter Walk's post on OKRs post his stint at Google

    • (00:00) - Intro
    • (00:19) - Meter Command and the future of software
    • (03:36) - What we forget about software making
    • (06:39) - Models make you reassess your own product
    • (07:27) - Why aren't there more AI explorations in software?
    • (09:38) - The "efficiency era" of startups
    • (13:21) - Software should be soft
    • (17:13) - The problem of "persona building" software
    • (21:29) - Enterprise software is reporting
    • (22:37) - Your data is your product roadmap
    • (25:13) - Emersing in the trends of AI as a founder
    • (27:27) - From janky prototype to custom model building
    • (29:55) - "No AI" - Build for the problem, not the technology
    • (36:50) - Full stack first, APIs over time
    • (40:14) - If you want to be early you have to be full stack
    • (48:28) - Long term orientation
    • (50:56) - What one thing would you work on now
    • (55:41) - End

    The New Muse: Hobbyists and AI Aug 07, 2024
    Show notes

    How would you design an AI product differently for a hobbyist vs prosumer vs professional? Using MidJourney as a case study in the passion economy, they delve into how AI tools can help build communities and support semi-professional creators. They explore how these tools can democratize creativity, the role of art vs craft, the role of grit in skill building, cheating vs copiloting, the missing middle of the creative markets, and more. They also touch on the broader implications of AI in different creative fields from music, writing and podcasts. It's an exploration of how AI can help users maintain creative flow and the underserved opportunity for AI to help unleash the hobbyist.

    • Nabeel also spoke on Midjourney's unique growth loops on Unsolicited Feedback
    • Le Jin has great writing on the passion economy and wrote about the creative middle class
    • Linus has an excellent article on Epistemic calibration that touches on taste, that we didn't get in the episode but worth seeing.
    • Simply Drawing - ai feedback meets art
    • Robert Morris' the Power Broker, which touches briefly on the rise of the professionalized class
    • a little more on why bees wiggle outside of near-term evolutionary needs


    00:00 Intro

    00:52 AI in Creative Endeavors

    01:58 Market Expansion

    03:01 The underexplored customer in AI

    08:23 Finding other AI hobbiest opportunities

    11:31 If they AI made it, are we building skill?

    13:36 Difference between art and craft

    14:40 Homework Helpers vs Writing Copilots

    16:07 Hobbiests are not quite the creator economy

    17:47 Product for hobbists

    21:03 The missing middle of creative markets

    26:42 AI's potential in the education of craft

    • (00:00) - Intro
    • (00:52) - AI in Creative Endeavors
    • (02:00) - Market Expansion
    • (03:02) - The underexplored customer in AI
    • (08:25) - Finding other AI hobbiest opportunities
    • (11:32) - If they AI made it, are we building skill?
    • (13:38) - Difference between art and craft
    • (14:42) - Homework Helpers vs Writing Copilots
    • (16:09) - Hobbiests are not quite the creator economy
    • (17:49) - Product for hobbists
    • (21:04) - The missing middle of creative markets
    • (26:44) - AI's potential in the education of craft

    Making product on the S curve of AI. Plus, Anthropic Artifacts Jul 21, 2024
    Show notes

    Fraser and Nabeel start by retcon'ing their earlier "maybe we should stop talking about models" and reflecting on the importance of adapting product strategy based how much disruption is happening in your market. The episode highlights the release of Claude Artifacts by Anthropic, and comparing it to other AI product innovations. They also nerd out on the Xbloom coffee machine and a robotic mop. Lastly, Fraser asks about how to navigate when a founder gets introduced to the wrong partner at a VC firm.

    • (00:00) - Product development early on the S curve, exploring Anthropic Artifacts
    • (00:43) - Welcome to Hallway Chat
    • (00:58) - Strong Convictions Loosely Held
    • (03:37) - Exploring Claude Artifacts
    • (10:48) - S Curve Product Design
    • (23:33) - The Instinct to Exhale: Post-Launch Reflections
    • (25:25) - Balancing Innovation and Stability
    • (27:00) - Leaning into risk
    • (32:30) - Question: Getting introd to the wrong partner at a VC

    Granola, Designing AI for User Agency, and how to compete with $$$ Jun 02, 2024
    Show notes

    Fraser and Nabeel dive into the evolving landscape of AI note-taking apps, focusing on a new product, Granola. They discuss Granola's unique approach of "enhancing your thought" instead of "thinking for you." They also explore: applying this idea to other categories, the influence of LLMs on UX, and the need for more experimental user workflows to unlock AI. They also discuss the challenges and dynamics of startup funding, the significance of capital in achieving market success, and how dynamics of AI team building are changing.

    • (00:00) - Introduction
    • (01:05) - Introducing Granola: The AI Note-Taking App
    • (02:19) - Granola's Unique Features and User Experience
    • (04:54) - Challenges and Innovations in AI Note-Taking
    • (06:53) - Granola's Practical Use Cases and Feedback
    • (09:54) - Reducing Friction in Product Experience
    • (13:04) - Where is the AI innovation?
    • (16:11) - The Role of Incentives in Innovation
    • (21:51) - When competitors raise 10x more than you
    • (23:11) - Introducing Granola: The AI Note-Taking App
    • (23:18) - Granola's Unique Features and User Experience
    • (24:35) - Challenges and Innovations in AI Note-Taking
    • (25:07) - Granola's Practical Use Cases and Feedback
    • (25:19) - Reducing Friction in Product Experience
    • (26:44) - Where is the AI innovation?
    • (27:12) - The Role of Incentives in Innovation
    • (27:59) - When competitors raise 10x more than you
    • (28:34) - Overcapitalization and Its Consequences
    • (29:21) - Customer-Centric Approach in Startups
    • (30:22) - How AI Startups are Building Teams Differently
    • (42:41) - Final Thoughts and Product Recommendations

    Should we stop talking about models? May 12, 2024
    Show notes

    Is it still worth it to discuss models when discussing startups? Nabeel and Fraser discuss how that may be the wrong question to ask in the current landscape, and why customer-centric questions and user experience should be the basis of product experience. Later, they deliberate who might come out on top in the “horse race” for AI product dominance, and whether it will come from a large, established company, or if the frontier of capabilities belongs to small innovators.

    • (00:00) - Decoding the Future: Puzzles vs. Mysteries in Tech
    • (01:22) - Welcome to Hallway Chat: Podcast or Tweets?
    • (01:35) - Exploring the Venture Firm USV's "Hallway Chat" Tweets
    • (02:27) - The atomization of media
    • (03:17) - Rethinking the Focus on AI Models in Startups
    • (04:38) - The Importance of Use Cases Over Models in AI Innovation
    • (07:45) - What makes a Foundational Model... Foundational
    • (18:23) - AI for Consumers: Navigating the S Curve of Innovation

    Devin & the Autonomous Engineer Wave. Plus, .Com lessons as a model for today Apr 10, 2024
    Show notes

    What is the extent of autonomous coding engineer Devin’s ability to generate real, functional applications with little to no help? Nabeel and Fraser dive into the buzz about Cognition’s ‘Devin’, what makes it different, and the transformative potential of AI in software engineering, particularly focusing on autonomous coding software. Later, they get into the innovator's dilemma and the lessons the .com era can lend to this new time in AI.


    (00:00) Intro

    (01:23) The buzz about Cognition’s Devin

    (07:44) What makes Devin different?

    (12:19) Tolerance for time

    (16:07) The interface of the future

    (22:19) Innovating around the incumbent’s advantage

    (25:30) Cutting edge products mean new user bases

    (29:52) Netscape was the Open AI of the Mobile Revolution

    (33:42) Optimism as the engine of capitalism

    (37:56) The model is not the product


    AI Models. Weighing the chances of commodity vs differentiation. Mar 23, 2024
    Show notes

    This week is a discussion of the points of differentiation vs commodification in various AI models. Including how these points might change over time, and might change between language, image, and video models. Then Fraser pivots to orienting around jobs to be done in AI, and how the various models have a huge gap between being capable of doing something, and doing it well.

    We then talk about Claude 3, the nature of benchmarking, and the rapid dropping LLM prices. Lastly, we cover a startup subject, debating the merits of SAFE (Simple Agreement for Future Equity) vs. priced equity rounds in early-stage funding.

    Links

    1. Claude 3 from Anthropic
    2. LMSys Chatbot Leaderboard for which models are sticking out right now
    3. For areas where models don't differentiate, we are back to the 7 powers framework. Hamilton Helmer's website with overview of the 7 Powers framework: https://7powers.com/, Sachin Rekhi has a good detailed primer on the 7 Powers as well.
    4. Carta guide on priced rounds vs SAFEs, which we don't really agree with all the pros and cons, but is a decent overview
    • (00:00) - Opening
    • (00:31) - Are models an inevitable commodity?
    • (05:58) - How image, video, and other models may pan out differently than language
    • (08:20) - It's not the model, it's the customer
    • (10:20) - Jobs to be done in AI - 1. Can it do it... 2. very well.. 3. exactly how I want it to.
    • (22:13) - Claude 3 by Anthropic
    • (25:25) - ELO Leaderboard Results
    • (26:25) - Claude 3 Haiku and Falling LLM Prices
    • (30:33) - SAFES vs priced equity rounds

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