cofounder / GM @monad 💜 Leave me feedback: forms.gle/BuvgVQozp5TwNpJp7
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What Monad has so far:
- High quality open-source C++/rust codebase with many HFT-style optimizations and architectural changes
- Public audits and clear docs that put the technology first. Transparency -- no hand-waving, no unsubstantiated claims
- High-performance system focused on true decentralization, running continuously in testnet with 186 globally distributed validators at 5000-10000 tps
- MonadBFT, a frontier consensus mechanism featuring 400ms block times, 800ms finality, large globally-distributed validator set, and tail-fork resistance
- Async Execution (while supporting EIP-7702 through the Reserve Balance mechanism)
- MonadDb for efficient merkle trie storage
- Native code compiler for frequently used contracts
- Interconnected community of smart, thoughtful crypto-natives who will grow in influence over the next few years
- Ecosystem of promising young startup founders, ready to take their shot
- Over $100m in ecosystem funding pre-mainnet
- Founder support through DeltaV, the Monad Founder Residency, Monad Madness, and more
- Monad Momentum, an incentives program focused on efficient UA and repeatable growth loops to help decentralized apps acquire normie users
- A north star of making open-source, decentralized systems more powerful
But there's still so much more to do. Are you excited?
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Check out the Monad September recap:
monad.xyz/blog/monad-ecosyst…
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In this timely and easy-to-digest paper, @liobaheimbach shares analysis on how some PropAMM operators fool aggregators into routing orders to them at wide spreads, by setting fees high at the start of a block and low at the end.
Since aggregators read the state at the end of the block, off-chain routers make the wrong routing decision.
Professional traders will exploit any available edge. It's important for the underlying system to give users the best execution by default. This is an expectation for users and fintechs coming over from TradFi.
Best execution comes from encrypting user orders until finalization (no one can react to them), and doing the routing fully on chain.
It is the endgame of crypto execution, where higher-level intents go into a sealed envelope, get finalized, and then get unsealed and executed.
We move from "buy 1 share of AAPL at venue X" because X looked like the cheapest place at the time, to "I want to buy 1 share of AAPL at the cheapest price", where the system figures it out at time of executing. It's how the world computer should work, and we are making it work like this on Monad.
🚨 New paper alert 🚨
Active Liquidity On Chain: Evidence from PropAMMs Across Chains
w/ Ozan Solmaz @jason_of_cs
Liquidity providers on traditional AMMs such as Uniswap are passive and suffer from adverse selection. As a result, their price only moves through trades. When an external market moves, these LPs get picked off on their stale quotes. PropAMMs, a new design, emerged in 2024 attempting to combat this. In them, a single operator quotes from its own inventory and reprices actively. By 2026, propAMMs carried more than half of SOL/USDC volume on Solana and had been found, among other chains, on Base and Monad.
Our work seeks to elucidate the benefits of this new design both for LPs and for retail users. Do propAMM operators really have an edge over passive LPs, and if so, where does this edge come from? Can propAMMs offer tighter quotes to retail users? We measured a full year of propAMMs on Solana, Base and Monad, and decoded the closed-source on-chain logic of Tessera, the largest propAMM on Base.
The result: propAMMs have a measurable edge over passive LPs: two seconds after a fill, propAMMs earn 0.37 bps on Solana, 1.19 bps on Base and 1.69 bps on Monad, while passive LPs on AMMs comparatively lose 0.22, 0.62 and 2.06 bps. We trace the edge to four sources:
🟠 Cheap, frequent repricing: updates use at least 25 times less resources than swaps on Solana, and 5 to 15 times less on Base and Monad. Generally, the default block order on all three chains is by priority fee per unit of computation. Thus, an update pays far less than a swap for the same priority placement.
🟠 Pricing by counterparty: five of the six largest Solana propAMMs offer tighter spreads to aggregator flow than to non-aggregator flow. For Tessera on Base, we show that it whitelists, penalizes or blacklists individual addresses.
🟠 Arbitrage against AMMs: when a reference price moves, propAMMs reprice while AMMs do not, and arbitrageurs trade the two. A propAMM fills at its updated quote, so it may break even on these legs on Solana and Base and even earn 1.55 bps on Monad.
🟠 Spoofing: aggregators route on the quote from the end of the previous block. For Tessera on Base, we show that the operator consistently raises its default fee early in the block and lowers it again late in the block, so aggregators read stale state that carries the lower fee. As a result, only 39% of swaps execute at the quoted price, and the average swap receives 1.08 bps less.
The second question we ask is: can propAMMs offer users tighter quotes as a result of their edge? The answer is yes: on fills that arrive while the price is not moving (our proxy for retail flow) propAMMs take 0.26 bps on Solana, 1.26 bps on Base and 1.62 bps on Monad, where AMMs take 2.59, 1.38 and 8.60 bps respectively. Retail also makes up a larger share of propAMM volume: 32%, 43% and 17% on Solana, Base and Monad, against 9%, 16% and 8% on AMMs.
What did we learn? PropAMMs avoid the losses of passive liquidity provision, yet still manage to give retail tighter quotes. However, users also have to bear the cost of spoofing, which we expect to change as aggregators move to an on-chain methodology.
Link: arxiv.org/abs/2609.38056
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Keone Hon retweeted
🚨 New paper alert 🚨
Active Liquidity On Chain: Evidence from PropAMMs Across Chains
w/ Ozan Solmaz @jason_of_cs
Liquidity providers on traditional AMMs such as Uniswap are passive and suffer from adverse selection. As a result, their price only moves through trades. When an external market moves, these LPs get picked off on their stale quotes. PropAMMs, a new design, emerged in 2024 attempting to combat this. In them, a single operator quotes from its own inventory and reprices actively. By 2026, propAMMs carried more than half of SOL/USDC volume on Solana and had been found, among other chains, on Base and Monad.
Our work seeks to elucidate the benefits of this new design both for LPs and for retail users. Do propAMM operators really have an edge over passive LPs, and if so, where does this edge come from? Can propAMMs offer tighter quotes to retail users? We measured a full year of propAMMs on Solana, Base and Monad, and decoded the closed-source on-chain logic of Tessera, the largest propAMM on Base.
The result: propAMMs have a measurable edge over passive LPs: two seconds after a fill, propAMMs earn 0.37 bps on Solana, 1.19 bps on Base and 1.69 bps on Monad, while passive LPs on AMMs comparatively lose 0.22, 0.62 and 2.06 bps. We trace the edge to four sources:
🟠 Cheap, frequent repricing: updates use at least 25 times less resources than swaps on Solana, and 5 to 15 times less on Base and Monad. Generally, the default block order on all three chains is by priority fee per unit of computation. Thus, an update pays far less than a swap for the same priority placement.
🟠 Pricing by counterparty: five of the six largest Solana propAMMs offer tighter spreads to aggregator flow than to non-aggregator flow. For Tessera on Base, we show that it whitelists, penalizes or blacklists individual addresses.
🟠 Arbitrage against AMMs: when a reference price moves, propAMMs reprice while AMMs do not, and arbitrageurs trade the two. A propAMM fills at its updated quote, so it may break even on these legs on Solana and Base and even earn 1.55 bps on Monad.
🟠 Spoofing: aggregators route on the quote from the end of the previous block. For Tessera on Base, we show that the operator consistently raises its default fee early in the block and lowers it again late in the block, so aggregators read stale state that carries the lower fee. As a result, only 39% of swaps execute at the quoted price, and the average swap receives 1.08 bps less.
The second question we ask is: can propAMMs offer users tighter quotes as a result of their edge? The answer is yes: on fills that arrive while the price is not moving (our proxy for retail flow) propAMMs take 0.26 bps on Solana, 1.26 bps on Base and 1.62 bps on Monad, where AMMs take 2.59, 1.38 and 8.60 bps respectively. Retail also makes up a larger share of propAMM volume: 32%, 43% and 17% on Solana, Base and Monad, against 9%, 16% and 8% on AMMs.
What did we learn? PropAMMs avoid the losses of passive liquidity provision, yet still manage to give retail tighter quotes. However, users also have to bear the cost of spoofing, which we expect to change as aggregators move to an on-chain methodology.
Link: arxiv.org/abs/2609.38056
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StraitsX is bringing XSGD and XUSD natively to Monad in 2027
StraitsX is a leading payment service provider in SEA, and a Major Payment Institution licensed by the Monetary Authority of Singapore
It's been great to work with @Tian_wei @EauDoon and rest of the @StraitsX team. LFG!
XSGD is set to become the first SGD-denominated stablecoin natively issued on Monad in early 2027.
We’re collaborating with @monad to bring $XSGD and $XUSD natively to their high-performance EVM network.
This integration expands on-chain currency options while opening up future cross-border settlement and card program use cases.
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For the world to use the world computer, transactions must be encrypted until finalization
- The world computer is an apt framing for crypto's value proposition. Exchanges, money markets, and other DeFi primitives exist as shared global state, accessible by people anywhere, who send transactions “from their keyboard to the mainframe”
- If we have many users typing commands at their keyboard to send to the mainframe, then it would be super unfair to allow other users to see what people are typing before their commands get executed
- The solution is to encrypt transactions until finalization. Like sending sealed vs unsealed envelopes, it reduces temptation by the mailman to open up your mail. This is the only way to definitively stop extraction by middlemen (wallets selling order flow to searchers, validators selling access to pending transactions, etc)
It is kind of insane that we are all working on a system based on cryptography, but there is no trustless secure transmission method for landing transactions. Practical encrypted mempools are the key
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Met up with a @category_xyz researcher for drinks late last week. He had just wrapped up submitting 8 (!) papers to the Financial Cryptography (FC) conference on behalf of the team
Obviously, wait to judge the papers based on their merit, but the depth and breadth of the Category Labs research team is insane. This is a team hell-bent on knocking down all of the technical hurdles to delivering the proper cryptographic world computer that matches user expectation - sub-second final, MEV-resistant, quantum-secure - in very short order
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The real use case for Jev in algo trading is in using it to quickly pathfind toward useful signals while in research mode
It is not a replacement for making individual trading decisions in realtime. Structured fits over lots of historical data, with well-crafted signals, in an optimized event loop, are much better-suited for this problem, both for precision, latency, and reproducibility
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Keone Hon retweeted
Card taps approved on the spot. Trades signed the moment you hit buy. Agents executing onchain without pausing between steps.
Every one runs on a signature. MPC Presignatures are live on Portal: instant signing with the full security of MPC.
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A team of humble experts, running faster and faster each day, building what's needed to deliver on the dream of self-sovereign middleman-free money
Check out our latest cryptography paper, Batched and Weighted Threshold Encryption with Silent Setup. Building on BTX, this scheme supports many desirable properties of an encrypted mempool:
⚡ Weighted decryption (ideal for Proof-of-Stake blockchains)
⚡ Silent setup (key generation no longer requires interaction between parties)
⚡ Batch and index independence (more user friendly and fewer constraints on decryption)
We’re excited about the future of encrypted mempools!
Paper link: eprint.iacr.org/2026/2087
Authors: Amit Agarwal, Champ Chairattana-Apirom (Category Labs intern ‘26), @sourav1547, Babak Poorebrahim Gilkalaye
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Welcome @tori_finance and @sharpbytexyz to Monad mainnet!
strUSD is live on @Monad. Borrow AUSD against it on @Morpho at 86% LLTV.
The AUSD(@withAUSD) comes from the SharpByte AUSD Tori Ecosystem vault, curated by @sharpbytexyz. You supply AUSD, the vault lends it into the market.
Supplying earns wMON and AUSD rewards, distributed through @merkl_xyz.
Market: app.morpho.org/monad/variabl…
Vault: app.morpho.org/monad/vault/0…
Bridge:
app.tori.finance/bridge
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It's been super interesting to watch OpenAI and Anthropic bounce from hyped to trashed to hyped and back again.
It feels like every tech product goes from insanely hyped, to beaten down, to hyped again, to beaten down again, and so on. As crypto folks will be well-aware, it is the nature of social media: people want to be smart, and the best way to do that is to be a little contrarian (while pointing out something that has a kernel of truth). But then other people keep piling on, motivated not by inherent belief but rather by observing that this opinion gets engagement. These voices become extremely loud and ultimately take things way too far in that direction relative to how things really are. Eventually that take becomes extremely consensus, and the loudness of consensus dies off because now it is just a boring old opinion. If the product is good and keeps improving though, then this cycle will get revisited again later; if not it will just fade out. And for the best products, the sine wave is upward-sloping, as the best builders make more hay than average when the sun is shining, and weather the storm of negative contrarianism better than average too. This dynamic is exacerbated in OpenAI/Anthropic because they release new models leapfrogging each other, but I think there is something fundamental about social consensus going on here too.
For builders, the answer is obviously just to keep building. It's never as good as it seems, and it's never as bad as it seems. For observers and future historians, maybe the takeaway is to try to be a little earlier to the inflection point. :)
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Crypto gives developers superpowers - seamless payment acceptance and instant network effects. And while AI has made crypto development easier, one of the pain points is still at the data layer - fundamentally, your agent still needs data from transactions, logs, etc.
Right now the query patterns are messy and incur a ton of waste. As one simple example, you might need data from logs, but you need one field from the transaction itself, so you pull a lot of data for both, filter them client-side, and join them.
MIP-16 is @category_xyz and @monad 's attempt to address longstanding problems in the RPC data interface by adding a new `eth_query` family of methods that allow for
- Filtering
- Relations (joins)
- Field selection (only request what you need)
- Better pagination
Filtering: The eth_getLogs method supports log filtering, but there is no way to filter transactions or traces. To query all transactions sent to a specific address, the user must fetch entire blocks and filter client-side
Relations: There is no way to join related objects in a single request. To fetch a set of logs and related transaction inputs, the user must make N+1 RPC requests (one to fetch logs, then one per unique transaction)
Field selection: Every RPC method returns a fixed object schema. Users that only need block number and timestamp have no choice but to fetch large unrelated fields like logsBloom, only to immediately discard them
Pagination: The eth_getLogs pagination design causes frequent timeouts and client-side workarounds. The RPC methods for blocks, transactions, and traces don't support range queries at all
We're excited to propose and ship this. We believe in repeatedly and iteratively giving developers better tools. Excellent effort from @typedarray @kyscott18 @andrthesnek and Jay Miller to make this happen
Excited to propose five new JSON-RPC methods to fetch EVM blockchain history: blocks, transactions, logs, traces, and native transfers.
These methods address longstanding Ethereum data problems at the protocol layer, through an open standard that any EVM chain can adopt.
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Herd is covering the Monad ecosystem!
The Herd team is doing a nice job of automatically disentangling chained dependencies across DeFi. I believe that with better information, we can all make better decisions. Now on Monad
We've fully integrated a new chain for the first time since launch: Monad has now joined the Herd!
This means full support across our explorer, onchain actions (hal), and doubleclick graphs - both in app and over mcp/cli/sdk!
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