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By Fraser Kelton & Nabeel Hyatt
The podcast currently has 28 episodes available.
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
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.
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
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.
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.
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.
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
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:
Josh Miller, Founder and CEO of The Browser Co, joins this week. We loved the experience with Arc Search, a new AI-enabled mobile search experience, we decided to talk to Josh directly about how it all came together.
Topics:
* How Arc Search came to be spawned out of basically a side project
* The core value of "we don't know"
* How the key AI feature 'Browse for Me' was not the initial concept, but came to be added last minute
* Josh's initial skepticism about AI, up until just a few months ago, and what flipped him
* Three strategies for AI integration
* The perils of leading with consumer hooks, how that derailed Browser Co, and focusing on solving problems
* Should cost be a key consideration when developing AI?
Hope you enjoy us mixing it up this week by talking with someone wrestling with building in the space. Drop us a line on twitter at @nabeel and @fraser with what you want to hear more (or less) of.
Two former founders, now VCs, play with AI products and see where that leads...
Fraser and Nabeel discuss the differences between horizontal disruption and vertical market disruption and the patterns of the phases of this disruption in the mobile age. From Adaptation, to Evolution, and eventually Revolution. Next, they dive into AI email app Shortwave AI. This leads to a conversation around what AI models are optimizing for, and how speed and polish can sometimes be part of the baseline usability of a product.
They also explore the default Agent workflows we should be trying as we figure out the right knowledge worker AI copilot. Using the analogy of the history of web development and AI no code, from webflow to squarespace, what those design approaches might tell us about how AI workflow tools will develop.
Finally, we discuss the potential value of talking to VCs when you're not raising, and the perils of taking even good generalized advice all the time.
* Shortwave email
* Avi Goldfarb and his book Prediction Machines
* Avi also spoke with Patrick O'Shaughnessy
* Yahoo Pipes wikipedia page, or see Retool's amazing history of Pipes
* TLdraw's Makereal
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