web3 with a16z crypto

with @sambroner @meigga @darenmatsuoka @jneu_net @chrislyons and @rhhackett @smc90Welcome to our special end-of-year episodes -- which also look ahead to 2025 --  covering our annual Big Ideas lists, where various a16z crypto team members share what they are personally excited about. (You can see the firmwide list, also including all the trends of the crypto team,  here.)This episode is part 1 of 2 -- but you don't have to listen to them in any particular order -- covering the trends and themes of:stablecoins, payments, and where the early adopters will come from;app store distribution, curation, and discovery;where the next crypto users will come from, turning passive holders into active users;how builders improve, and better choose, infrastructure; andsimplifying user experience. Covering each of these -- and coming from the investing, go-to-market, data science, research, and media teams are:  Sam Broner, Maggie Hsu, Daren Matsuoka, Joachim Neu, and Chris Lyons; in conversation with hosts Sonal Chokshi and Robert Hackett. (Stay tuned until the end for some of our meta-commentary.) These are just 5 of the 14 trends we shared; you can check out the full list at a16zcrypto.com/bigideas.Also be sure to check out part 2, which covers all the trends at the intersection of crypto and AI. As a reminder, none of the content is investment, business, legal, or tax advice; please see a16z.com/disclosures for more important information -- including a link to a list of our investments.

with @atabarrok @skominers @smc90We've heard a lot about the premise and the promise of prediction markets for a long time, but they finally hit the main stage with the most recent election. So what worked (and didn't) this time? Are they better than pollsters, journalists, domain experts, superforecasters?So in this conversation, we tease apart the hype from the reality of prediction markets, from the recent election to market foundations... going more deeply into the how, why, and where these markets work. We also discuss the design challenges and opportunities, including implications for builders throughout. And we also cover other information aggregation mechanisms -- from peer prediction to others -- given that prediction markets are part of a broader category of information-elicitation and information-aggregation mechanisms.Where do (and don't) blockchain and crypto technologies come in -- and what specific features (decentralization, transparency, real-time, open source, etc.) matter most, and in what contexts? Finally, we discuss applications for prediction and decision markets -- things we could do right away to in the near-to distant future -- touching on everything from corporate decisions and scientific replication to trends like AI, DeSci, futarchy/ governance, and more?Our special expert guests are Alex Tabarrok, professor of economics at George Mason University and Chair in Economics at the Mercatus Center; and Scott Duke Kominers, research partner at a16z crypto, and professor at Harvard Business School  -- both in conversation with Sonal Chokshi.RESOURCES(from links to research mentioned to more on the topics discussed)The Use of Knowledge in Society by Friedrich Hayek (American Economic Review, 1945)Everything is priced in by rsd99 (r/wallstreetbets, 2019)Idea Futures (aka prediction markets, information markets) by Robin Hanson (1996)Auctions: The Social Construction of Value  by Charles SmithSocial value of public information by Stephen Morris and Hyun Song Shin (American Economic Review, December 2002)Using prediction markets to estimate the reproducibility of scientific research by Anna Dreber, Thomas Pfeiffer, Johan Almenberg, Siri Isaksson, Brad Wilson, Yiling Chen, Brian Nosek, and Magnus Johannesson (Proceedings of the National Academy of Sciences (November 2015)A solution to the single-question crowd wisdom problem by Dražen Prelec, Sebastian Seung, and John McCoy (Nature, January 2017)Targeting high ability entrepreneurs using community information: Mechanism design in the field by Reshmaan Hussam, Natalia Rigol, and Benjamin Roth (American Economic Review, March 2022)Information aggregation mechanisms: concept, design, and implementation for a sales forecasting problem by Charles Plott and Kay-Yut Chen, Hewlett Packard Laboratories (March 2002)If I had a million [on deciding to dump the CEO or not] by Robin Hanson (2008)Futarchy: Vote values, but bet beliefs by Robin Hanson (2013)From prediction markets to info finance by Vitalik Buterin (November 2024)Composability is innovation by Linda Xie (June 2021)Composability is to software as compounding interest is to finance by Chris Dixon (October 2021)resources & research on DAOs, a16z crypto  

with @baileyflan @ahall_research @rhhackettToday we’re dusting off an ancient practice that has become trendy once again: the old-but-new idea of “sortition,” or selecting representatives by lottery.Sortition was used in ancient Athenian democracy to elect public officials. It’s also been lately revived by tech companies like Meta and AI startups like OpenAI and Anthropic to tackle some of their thorniest policymaking challenges.Our guests today are experts on sortition, including Bailey Flanigan, a postdoctoral fellow at Harvard who is joining MIT as an assistant professor next year, and who has helped develop selection algorithms for sortition that are in use today. Also joining is Andrew Hall, Stanford University poli sci professor, advisor to Meta, and consultant to a16z crypto research.In this episode, we discuss why not to rely exclusively on expert authority, how the process of deliberation changes people’s minds, and how sortition can apply everywhere from the governance of countries to the governance of crypto projects, and more.Related resources:Algorithms for fair, manipulation-robust, and transparent sortition with Bailey FlaniganAs a reminder, none of the content should be taken as investment, business, legal, or tax advice. Please see a16z.com/disclosures for more important information, including a link to a list of our investments.

with @pmarca @bhorowitzToday we’re running a special episode featuring a16z cofounders Marc Andreessen and Ben Horowitz talking about AI bots and crypto. They discuss what happens when you mix postmodern theories and internet memes in an LLM. They also get into the sudden rise of a strange memecoin, the state of crypto regulation in the U.S., and more.This episode is a crossover from the Ben & Marc Show, which you can follow on YouTube or wherever you get your podcasts.See the original episode:How An AI Bot Became a Crypto Millionaire As always, none of the content should be taken as tax, business, legal or investment advice. See a16z.com/disclosures for more important information, including a link to a list of our investments.