Edward Leo (@edwardleoz) header
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Joined January 2016
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"My current view is that we should try harder to push them into a totally different use case: hedging, in a very generalized sense (TLDR: we're gonna replace fiat currency)" On it 🌱
Recently I have been starting to worry about the state of prediction markets, in their current form. They have achieved a certain level of success: market volume is high enough to make meaningful bets and have a full-time job as a trader, and they often prove useful as a supplement to other forms of news media. But also, they seem to be over-converging to an unhealthy product market fit: embracing short-term cryptocurrency price bets, sports betting, and other similar things that have dopamine value but not any kind of long-term fulfillment or societal information value. My guess is that teams feel motivated to capitulate to these things because they bring in large revenue during a bear market where people are desperate - an understandable motive, but one that leads to corposlop. I have been thinking about how we can help get prediction markets out of this rut. My current view is that we should try harder to push them into a totally different use case: hedging, in a very generalized sense (TLDR: we're gonna replace fiat currency) Prediction markets have two types of actors: (i) "smart traders" who provide information to the market, and earn money, and necessarily (ii) some kind of actor who loses money. But who would be willing to lose money and keep coming back? There are basically three answers to this question: 1. "Naive traders": people with dumb opinions who bet on totally wrong things 2. "Info buyers": people who set up money-losing automated market makers, to motivate people to trade on markets to help the info buyer learn information they do not know. 3. "Hedgers": people who are -EV in a linear sense, but who use the market as insurance, reducing their risk. (1) is where we are today. IMO there is nothing fundamentally morally wrong with taking money from people with dumb opinions. But there still is something fundamentally "cursed" about relying on this too much. It gives the platform the incentive to seek out traders with dumb opinions, and create a public brand and community that encourages dumb opinions to get more people to come in. This is the slide to corposlop. (2) has always been the idealistic hope of people like Robin Hanson. However, info buying has a public goods problem: you pay for the info, but everyone in the world gets it, including those who don't pay. There are limited cases where it makes sense for one org to pay (esp. decision markets), but even there, it seems likely that the market volumes achieved with that strategy will not be too high. This gets us to (3). Suppose that you have shares in a biotech company. It's public knowledge that the Purple Party is better for biotech than the Yellow Party. So if you buy a prediction market share betting that the Yellow Party will win the next election, on average, you are reducing your risk. Mathematical example: suppose that if Purple wins, the share price will be a dice roll between [80...120], and if Yellow wins, it's between [60...100]. If you make a size $10 bet that Yellow will win, your earnings become equivalent to a dice roll between [70...110] in both cases. Taking a logarithmic model of utility, this risk reduction is worth $0.58. Now, let's get to a more fascinating example. What do people who want stablecoins ultimately want? They want price stability. They have some future expenses in mind, and they want a guarantee that will be able to pay those expenses. But if crypto grows on top of USD-backed stablecoins, crypto is ultimately not truly decentralized. Furthermore, different people have different types of expenses. There has been lots of thinking about making an "ideal stablecoin" that is based on some decentralized global price index, but what if the real solution is to go a step further, and get rid of the concept of currency altogether? Here's the idea. You have price indices on all major categories of goods and services that people buy (treating physical goods/services in different regions as different categories), and prediction markets on each category. Each user (individual or business) has a local LLM that understands that user's expenses, and offers the user a personalized basket of prediction market shares, representing "N days of that user's expected future expenses". Now, we do not need fiat currency at all! People can hold stocks, ETH, or whatever else to grow wealth, and personalized prediction market shares when they want stability. Both of these examples require prediction markets denominated in an asset people want to hold, whether interest-bearing fiat, wrapped stocks, or ETH. Non-interest-bearing fiat has too-high opportunity cost, that overwhelms the hedging value. But if we can make it work, it's much more sustainable than the status quo, because both sides of the equation are likely to be long-term happy with the product that they are buying, and very large volumes of sophisticated capital will be willing to participate. Build the next generation of finance, not corposlop.
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Edward Leo retweeted
We built a new kind of reserve. We call it a prediction reserve. Prediction markets handled almost $20 billion in bets in a single month. They are very good at one thing: answering a question on a date. A prediction reserve takes the same idea, people backing their predictions with something at stake, and applies it to a question that never ends: which assets deserve a place in a shared basket? In a prediction reserve: • Anyone, person or AI, can pick an asset and back it with stake • Every pick is checked again and again over months, not once • Picks that hold up gain more say, and the basket belongs to the people who hold it We built it because today a manager or a vote decides what a fund holds, and nobody answers for being wrong. We’re just getting started. The first test rounds are running now. Follow along.
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Edward Leo retweeted
1/ In 2016, Oliver Hart and Bengt Holmström won the economics Nobel for their work on contract theory. A central question: how do you align decision-makers with the people bearing the consequences? That question is at the heart of Sapio’s design🧵
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Another AI startup going live in Stockholm. Built to replace your daily inbox and capture your meetings, check it out:
We’ve raised $3.2M and spent 18 months building Scape. Scape is the first email inbox that works for you:
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Time to go full circle 🌱 See you tomorrow @arbitrum and @RobinhoodCrypto
Last week I was in Berlin presenting at @DeFiFounders event and now we're joining @arbitrum founder house in London with @SapioFinance. Looking forward!
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Edward Leo retweeted
I've spent months working on this. Today, it's live. If you've ever wanted to understand how encrypted money actually works → this is it. maxdesalle.com/mastering-zca…
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Edward Leo retweeted
ethereum's next big upgrade, fusaka, is happening on december third. here’s everything you need to know in one minute ↓
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This is well worth watching. HIGHLY recommended as to origins of Bitcoin / Chaum / Hal Finney / Cypherpunks.... Not an endorsement of ZCash. "I was working on this problem for 12 years, and I saw Bitcoin. I thought it couldn't work. I thought the problem was mathematically unsolvable" -- Zooko
Satoshi's Last Wish - The Full Story 00:00 Intro 00:41 Before Bitcoin: The Failure of DigiCash 01:37 The 12-Year Struggle: Cypherpunks vs. The Centralization Problem 03:01 Enter Bitcoin: Satoshi’s Proposed Solution To The Centralization Problem 05:20 Early Days: Bitcoin’s First Blogpost & Satoshi’s Webpage 10:07 Bitcoin’s Major Flaw: The Second Problem Satoshi Wanted to Solve 12:31 Satoshi Proposes A Solution To Bitcoin’s Privacy Problem 14:03 What Did Satoshi Mean By A More Useable Version of Bitcoin? 17:20 Passing The Torch: Solving What Satoshi Couldn’t
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Tune in (20 mins to go) before our inventor, @hewesterberg, goes live pitching as one of the top 30 teams out of 1500+ worldwide on World Computer Hackathon League 🌱 More to come @MultiCurrencyIO
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A recent reflection, based on conversations with economists and policy leaders, is that there are two superficially similar but importantly different perspectives one can hold with respect to US manufacturing: * Affinity for manufacturing and physical production is an anachronistic fetish, embodied by populists with outdated attraction to hard hats and clanging forges. A great deal of manufacturing has departed the US, which is certainly fine and probably even quite good. It's unpleasant labor, and countries ought to each specialize in their respective comparative advantages. * Manufacturing is the ultimate network effects and economies-of-scale business. As services are substituted by AI, and as datacenter deployment accelerates, the relative importance of manufacturing is likely to grow. To think that one can pick and choose sectors in which one will excel ("let's win in drones but not in dishwashers") is a fallacy. Manufacturing is hence of paramount strategic importance. However, we don't know how to make the US the world's preeminent manufacturing power (given its cost base and given the current center of gravity in China) -- indeed, we don't know whether it's even possible -- and this is a significant strategic problem for the country. I have zero direct expertise here, but my outside view is closer to #2 than #1: it seems that the ecosystems and supply chains create strong gravity across the board. I also asked @elonmusk, who has clearly done more over the past decade to advance sophisticated US manufacturing than anyone else, and this appears to be his view. Most economists, on the other hand, are much closer to #1, and I don't think that the economics profession considers the absence of good ideas for reviving US manufacturing to be a problem of particular significance. (There are lots of snide epithets about the efficacy of industrial policy.) It seems to me that there's even some amount of backwards reasoning happening, where, because we don't know how to do #2, #1 is subconsciously a much more comfortable position to hold. Talking about winning particular manufacturing sectors feels to me a bit like talking about winning individual biological research sectors or winning particular software sectors. That is: it seems that the strong default assumption should be that "the place that is best at biology research sector X will also be best at sector Y", and similarly in software, because the skills and inputs needed are so transferable. As such, my guess is that if the US seeks meaningful sovereignty or preeminence in any of drones, robotics, solar, batteries, pharma, etc., we need to bite the bullet, and win at manufacturing across the board. Overall, I'd love to read more arguments for and against these perspectives, particularly from those with direct expertise.
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New Coin Center report on digital identity by myself & Ian Miers: AML/KYC is ineffective, costly, causes breaches/hacks, and jeopardizes our democracy. Tech from crypto can protect American values in ID. We call for a new initiative, the John Hancock Project, to show the way.
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Crypto prediction market crash course #1 (1 hr read) 📚 You're going to want to bookmark this one. From the history of bookies to on-chain order books, trading strategies, oracle risks, and why prediction markets matter far beyond “gambling.” I’m catching up on these 6 pieces, they’re the best written articles I’ve found so far to grasp what's going on right now in this fast-moving space. Big claps to the writers! @nikarpit @factcheck1ntern @FabianoSolana @splinter0n @Defi_Warhol
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There is research, and then there is research. knowerofmarkets is onto something here, meriting genuine thought.
I'd like everyone to go read the Valis Research Manifesto We are coming to an internet near you very soon valisresearch.xyz
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We do a lil reading. Thanks for putting together, Michael! (see link in his comments)
Comment below if you want access to this Prediction Markets reading list
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Edward Leo retweeted
Introducing ETHConf: Ethereum's Conference 📷 @ETHGlobal is thrilled to bring 5,000+ attendees shaping the future of Ethereum to New York City in early June 2026. Join founders and builders, 200+ speakers, and 100+ exhibitors for 3 days dedicated to exploring what's next for Ethereum.This is where Ethereum's next chapter begins. Join the waitlist → ethconf.com
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Ethereum coded @ NextFinSummit #ETHNYC Who's around?
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Echoing something @karpathy recently said, it does frustrate me how a lot of AI development is trying to be as "agentic" as possible, when actually creating *more* paths for human input both creates a better output (now for quite a while going forward) and is better for safety.
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Ethereum’s endgame architecture: > ETH Mainnet: the liquidity layer for high value assets > ETH L2s: the high-octane execution layers Institutional grade asset security with zero downtime or counterparty risk; customizable execution across an ecosystem of L2s Powered by ETH.
Tarun Chitra's words from that @SuccinctLabs stream simply won't leave my head. he said something that I think reframes the entire purpose of L2s and ZK tech this isn't about "faster and cheaper" what @tarunchitra said... "...if ETH mainnet has ZK as a first class citizen, you'll be able to do this type of stuff, like using your collateral on mainnet somewhere else without bridging" he contrasted this with the current state of affairs, where bridging assets creates unnecessary friction and risk: "why can't I just bridge any spot asset over, why do I need to like have this separate protocol that like does verification and still relies on the multisig effectively" What This Actually Means: - we’re used to our assets "living" either on L1 or on a specific L2. to move them, we use a bridge. this is not only risky (bridges are the #1 target for hacks) but also inefficient. your funds get locked into one ecosystem. Tarun’s idea turns this model on its head imagine your 10 ETH are sitting in your wallet on the ETH mainnet. they don't move. but you need a loan from a DeFi protocol on an L2. instead of bridging your ETH to that L2, you simply generate a ZK proof that cryptographically confirms: "this address on L1 holds 10 ETH, and they are locked as collateral." the L2 protocol sees this proof and issues you the loan. your assets remain under the security of the most robust blockchain, but they are productively working elsewhere. Why This Changes Everything - The Death of Bridge Risk: if assets never leave L1, there's nothing to steal from a bridge. the most vulnerable part of the infrastructure simply becomes obsolete. this improves the security of the entire ecosystem by an order of magnitude. - Maximum Capital Efficiency: your assets are no longer fragmented. the same 10 ETH sitting on L1 could simultaneously serve as collateral in dozens of L2 applications. its like the money in your bank account working in three different investment funds at the same time without ever having to be moved. your capital becomes universal and hyper-efficient - True Composability & Interoperability: this is the holy grail everyone talks about. L2s can talk to each other not through clunky workarounds, but through a shared, absolutely reliable source of truth—L1. a protocol on one chain can instantly and trustlessly verify your financial state on another. this enables highly complex DeFi strategies that are simply impossible today. Simplification for Everyone: for the user, the ethereum ecosystem becomes a unified whole. no more headaches choosing a bridge, paying liquidity fees For devs, it means they can build their L2 applications counting on access to all of ethereum's liquidity, not just what users have bothered to bridge to their specific chain.
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polynya might be gone but he left behind 190 pages worth of blogs of the clearest thinking in crypto: polynya.mirror.xyz/ It’s still the best writing in the space. Closest thing we have to a textbook on blockchain & APPLICATIONS I turned it into a PDF, DM me if you want it
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