๐†๐ž๐ซ๐š๐ฅ๐๐‚๐–—๐ฒ๐ฉ๐–™ ไบบ (@TweetByGerald) header
๐†๐ž๐ซ๐š๐ฅ๐๐‚๐–—๐ฒ๐ฉ๐–™ ไบบ (@TweetByGerald) profile picture

See you on the other side that prints. ๐Ÿ’ฐ

Cape
Joined March 2022
Photo by ๐†๐ž๐ซ๐š๐ฅ๐๐‚๐–—๐ฒ๐ฉ๐–™ ไบบ (@TweetByGerald)Photo by ๐†๐ž๐ซ๐š๐ฅ๐๐‚๐–—๐ฒ๐ฉ๐–™ ไบบ (@TweetByGerald)Photo by ๐†๐ž๐ซ๐š๐ฅ๐๐‚๐–—๐ฒ๐ฉ๐–™ ไบบ (@TweetByGerald)Photo by ๐†๐ž๐ซ๐š๐ฅ๐๐‚๐–—๐ฒ๐ฉ๐–™ ไบบ (@TweetByGerald)Photo by ๐†๐ž๐ซ๐š๐ฅ๐๐‚๐–—๐ฒ๐ฉ๐–™ ไบบ (@TweetByGerald)Photo by ๐†๐ž๐ซ๐š๐ฅ๐๐‚๐–—๐ฒ๐ฉ๐–™ ไบบ (@TweetByGerald)Photo by ๐†๐ž๐ซ๐š๐ฅ๐๐‚๐–—๐ฒ๐ฉ๐–™ ไบบ (@TweetByGerald)Photo by ๐†๐ž๐ซ๐š๐ฅ๐๐‚๐–—๐ฒ๐ฉ๐–™ ไบบ (@TweetByGerald)Photo by ๐†๐ž๐ซ๐š๐ฅ๐๐‚๐–—๐ฒ๐ฉ๐–™ ไบบ (@TweetByGerald)Photo by ๐†๐ž๐ซ๐š๐ฅ๐๐‚๐–—๐ฒ๐ฉ๐–™ ไบบ (@TweetByGerald)
The next 6 to 12 months are the ones where you change your life. But, If you don't understand this little concept on how to prepare yourself for the next bull run, then forget about a 100x.... ๐Ÿงต
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โžฅ 40+ projects are lining up for elysiumโ€™s launch. only a few will still matter a month later. @Enter_Elysium prepares for its mainnet launch on Nov 9th, competition on other token launchpads is already intensifying. @Enter_Elysium is built by @Kinetiq_xyz using Arbitrum Orbit and @conduitxyz. new apps get built on it, and the trading still runs through Hyperliquid. How it works โ†“ three parts: โ€ข Elysium: where the apps live (DEXs, launchpads, DeFi) โ€ข HyperEVM: where things settle and tokens move across โ€ข HyperCore: Hyperliquidโ€™s order books and trading engine it aims for 100 ms blocks and uses $HYPE for gas. the big one is a HyperCore upgrade planned about four weeks after launch. it would let apps on elysium see live prices, order books and positions directly, which helps market makers price and hedge better. itโ€™s planned, not live. donโ€™t count on it for day one. why it could matter โ€ข new tokens launch โ€ข people trade them โ€ข that trading brings liquidity โ€ข some of it flows back to Hyperliquid launching tokens is the easy part. the hard part is people still trading them after the rewards stop. where the money goes the proposed split of the fees the network earns: โ€ข 50%: buy and burn $KNTQ โ€ข 25%: builder incentives โ€ข 25%: Kinetiq treasury and operations more trading could also mean more HyperCore fees. none of it is guaranteed. I grouped the ecosystem by what each category needs to contribute to onchain activity. โœฆ Launchpads and token issuance @kilnpad, @AscendLaunch, @SignalFam, @oxleydotfun, @MontraXYZ, @ElysiumPump @CorePad_hl, @perpmefun, @Neuriio, @ChainzyLabs, @citadeldotxyz, @Bunnypadfun, @TheKleos_, @obolworld, @Boxa_Elysium, โœฆ DEXs and liquidity: @HyperFlow_fun, @NestExchange, @HybraFinance, @dawndottrade โœฆ Trading and DeFi: @Elypact, @Pantheonindex, @Pindar_finance, @truemarketsco โœฆ Derivatives and prediction markets: @hyperflip_xyz, @speculatexyz, @LiquidictionHL, @Bound_Exchange, @BranchpointXYZ, @outrivexyz โœฆ NFTs and marketplaces: @kalosfun, @AtlasHL โœฆ Gaming and consumer apps: @eloscapeHQ, @playelysa, @clashforelysium, @Hyperion_RPG โœฆ Infrastructure and analytics: @liquidterminal, @ElysiumEco, @Ellytradebot, @Alchemy, @ChainstackHQ, @Quicknode โœฆ Naming: @ElysiumNames this is a watchlist, not a promise that all of them will be live on day one. DYOR. โœฆ how to get $HYPE onto elysium 1. deposit USDC into Hyperliquid from Arbitrum 2. move it from perps to spot and buy $HYPE 3. send $HYPE from HyperCore to HyperEVM, and keep a little for fees when the official bridge is live, bridge from HyperEVM to Elysium one bridge to watch: blobmeme.com/bridge testnet numbers only show people are building. they donโ€™t show people are using it. the first few weeks of mainnet will tell us whether elysium brings in new money, or just moves the same users around.
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What if the next big opportunity on $HYPE isn't another trading platform, but everything being built around it? โ†’ @Enter_Elysium wants to bring more apps, assets, and liquidity to @HyperliquidX. Its mainnet goes live November 9. โ—ข Hereโ€™s what you should know; โ†“ โ†’ Built by @Kinetiq_xyz using Arbitrum Orbit and @conduitxyz. โ†’ Elysium is an EVM Layer 2 targeting; โ€ข 100ms block times โ€ข 300 Mgas/s throughput โ€ข $HYPE for gas It connects Elysium, HyperEVM, and HyperCore to bring applications closer to Hyperliquidโ€™s trading infrastructure. โ—ข HyperCore's integration A planned upgrade could let Elysium apps access HyperCoreโ€™s order books, prices, balances, and positions. This could improve liquidity management and trading efficiency. โ—ข How demand comes in The idea is simple: Token launches โ†’ DEX liquidity โ†’ More traders โ†’ More trading activity. The real test will be whether these applications attract sustainable demand and liquidity. โ—ข The Revenue model Proposed sequencer revenue allocation: โ†’50%: funds $KNTQ purchases and burns โ†’25%: to builders โ†’25%: to Kinetiq's treasury More activity could also create additional fee opportunities for hyperliquid. โ—ข Ecosystem Map โ†’ Launchpads: @AscendLaunch, @SignalFam, @oxleydotfun, @CorePad_hl, @perpmefun, @Neuriio, @ChainzyLabs, @MontraXYZ, @citadeldotxyz, @kilnpad, @Bunnypadfun. โ†’ NFTs/marketplaces: @kalosfun, @AtlasHL. โ†’ DEXs and liquidity: @HyperFlow_fun, @NestExchange, @HybraFinance, @dawndottrade. โ†’ Derivatives and prediction markets: @hyperflip_xyz, @speculatexyz, @LiquidictionHL, @Bound_Exchange, @BranchpointXYZ, @outrivexyz. โ†’ Trading and DeFi: @Elypact, @Pantheonindex, @Pindar_finance, @truemarketsco. โ†’ Analytics/infrastructure: @liquidterminal, @ElysiumEco, @Ellytradebot, @arbitrum, @conduitxyz, @Alchemy, @ChainstackHQ, @Quicknode. โ†’ Gaming/consumer apps: @eloscapeHQ, @playelysa, @clashforelysium, @Hyperion_RPG. โ†’ Naming infrastructure: @ElysiumNames. โ—ข How to bridge to elysium with no fees >deposit usdc on @HyperliquidX and send usdc on $arb to hyperliquid. > move your usdc from perps to spot, buy hype in the hype/usdc spot market. > in the hyperliquid app, transfer your hype from hypercore to hyperevm, make sure you keep a little extra for gas. >then bridge hyperevm to elysium, use blobmeme(.)com/bridge. make sure to remove the brackets in the site "()" there are actually other bridges like volta which had a 2% fee, but this is the only one currently with zero fees. โžคgoodluck anon, NFA!
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We all thought @arc had been forgotten, but its TVL has been quietly growing while everyone was looking elsewhere. I went through DefiLlama's data, and @arc is now sitting at roughly $633M in DeFi TVL. What's even more surprising is where that money is going: โ€ข @Morpho Blue: $298.5M โ€ข @aave V4: $184.7M โ€ข Extended: $106.3M That's nearly $483M sitting in Morpho and Aave alone, accounting for about 77% of Arc's TVL. And lending isn't the only activity picking up. Arc also has around $1.16B in stablecoin supply, with weekly perpetual trading volume approaching $1.9B. But I wouldn't rush to call this organic growth just yet. Depositing capital into lending protocols is one thing. Having people actively borrow against it is another. I'd be watching: โ€ข how much of that liquidity is actually being borrowed โ€ข whether trading volume holds up โ€ข how much capital stays when incentives slow down @arc may have gone quiet on the timeline, but the numbers suggest people haven't stopped putting capital to work there.
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Your AI agent might be smarter than you, but its payment system is more expensive than yours. And that's a problem crypto is quietly trying to solve. How do these agents actually pay for things? โžค The hidden cost of agent payments AI agents often canโ€™t simply use your personal debit card. They rely on virtual cards issued through their developers or agent startups. These transactions can be classified as commercial card payments, which often carry higher interchange fees. In some cases, merchant costs can reach 2.5โ€“3%. A $100 purchase could cost a merchant $2.80 instead of $0.27. Imagine millions of agents making purchases at that cost. Thatโ€™s a serious problem for merchants. โžค Enter crypto-native payments. What if agents could pay directly using wallets and stablecoins? No traditional card issuance, fewer intermediaries, and programmable settlement. This is where x402 comes in. Built around HTTP 402 Payment Required, x402 enables internet-native payments, allowing agents to pay for API calls, services, and digital resources programmatically. Instead of subscriptions, imagine paying for exactly what an agent consumes. โžค The ecosystem is already forming. I mapped startups building this infrastructure: Agent cards & tokens: @agentcardhq @prayapayments @getpayos @evervault @basis_theory Wallets & accounts: @crossmint @openfort_hq @turnkeyhq @1shotapi @HallidayHQ Banks & networks: @naturalpay @catena_labs @GoKiteAI @PaymanAI + ATXP Pay-per-call & x402: @daydreamsagents @merit_systems @PayWithLocus + Nevermined, Lava Trust & identity: @VouchedID @trySkyfire @sapiom @t54ai @Mnemopay Checkout & merchants: @rye @nekuda_ai @bitrefill @meshpay + Firmly โžค The bigger opportunity AI agents will need wallets, stablecoins, payment rails, identity, spending controls, and settlement infrastructure. Thatโ€™s an entirely new financial infrastructure market. My takeaway: The next wave of crypto adoption might not come from humans buying tokens. It could come from millions of AI agents using stablecoins to pay for software, APIs, services, and real-world goods. Weโ€™ve built financial infrastructure for humans. Now weโ€™re building it for machines.
The killer use case for crypto might not be humans using crypto. It might be machines. @BlackRock latest paper on the โ€œmachine-native economyโ€ lays out why. โžค The thesis is pretty simple: AI = machine-native intelligence Crypto = machine-native money And as AI agents become capable of actually doing things, this starts getting interesting. Agents wonโ€™t just answer questions. Theyโ€™ll call APIs, buy data, hire compute, talk to other agents and even execute transactions. And theyโ€™ll need to pay for all of it and thatโ€™s where things like x402 come in. Instead of a human pulling out a card every time an agent needs an API, an agent can potentially pay programmatically; including tiny, high-frequency payments. Thatโ€™s a very different payment environment from the one weโ€™re used to. But the part I found even more interesting: โ€œcompute itself could become a financial asset.โ€ BlackRock points to $1.1T in projected 2030 revenue across AWS, Microsoft Intelligent Cloud and Google Cloud segments. As compute becomes scarce and increasingly expensive, you can imagine markets emerging around claims on compute capacity. An agent could eventually: โžค discover available compute โžค compare price/performance โžค provision it โžค pay for it โžค use it โžค settle everything programmatically What Iโ€™m saying basically is: AI agents become economic actors. And this is where the AI + crypto convergence starts making more sense to me. If machines are going to participate in the economy, they need machine-readable money, assets and settlement. The interesting stack is already taking shape: MCP โ†’ agents access tools/data A2A โ†’ agents communicate x402 โ†’ agents pay Stablecoins โ†’ machine-native money Blockchains โ†’ settlement Compute markets โ†’ machine-accessible resources @AnthropicAI , @Google , @coinbase , @stripe , @OpenAI , @Visa and others are already building pieces of this infrastructure. The ecosystem is obviously still early. But the direction is fascinating: humans โ†’ agents โ†’ agents โ†’ machines โ†’ money โ†’ compute The next economy may have a lot fewer humans clicking โ€œbuy.โ€
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What happens when an NFTโ€™s rarity is hidden from everyone, including potential buyers? Thatโ€™s the experiment @FungoLabs is running with its encrypted NFTs. Each NFT has two layers: 1. The Look: The artwork is sealed at mint. Only the holder can reveal it, and once published, the reveal is permanent. 2. The Essence: This holds the NFTโ€™s class, four stats and element. These details remain encrypted. The NFT and its owner are still public, but the attributes behind the asset aren't. On OpenSea, an unrevealed NFT displays a mark with the status โ€œRevealed: Noโ€. Thereโ€™s also an interesting ownership rule. When an NFT is sold, the previous holder loses access in the same transaction. The new holder can activate access with one transaction after roughly 19 minutes (96 blocks). So the encrypted attributes move with ownership, rather than staying accessible to the previous holder. The class distribution is: โ†’ Common: 50.0% โ†’ Rare: 30.1% โ†’ Ultra Rare: 14.8% โ†’ Legendary: 5.1% What I find interesting is how hiding the attributes changes the way people trade them. Buyers usually assess rarity, traits and appearance before deciding what an NFT is worth. Here, some of that information isn't available upfront. hidden attributes could make discovery more interesting, but they could also make pricing and valuation harder. I'd want to see how collectors respond when they can verify ownership but cannot inspect the full attributes before buying. you should check it out : fungolabs.org/launchpad/c/cfโ€ฆ
Found a crazy opportunity for creators who are actively on here. @FungoLabs just launched its $FUNGO campaign and they're putting 300M $FUNGO into its content campaign. but the scoring rule is what I noticed. Only your 5 best posts count toward the campaign. That puts more weight on the quality of your content than on how often you post. few details you might want to note: โ†’ Eligible posts must have been published from November 1, 14:00 UTC. โ†’ The reward pool is 300M $FUNGO. โ†’ Rewards are scheduled for distribution at TGE. I prefer campaigns where the rules are clear and good research has room to stand out. you should check it out : fungolabs.org/launchpad/c/cfโ€ฆ
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โžฅ 11% apy means nothing until you ask where is it comes from so hereโ€™s where @grvt_io says it comes from. four yield sources โ€ขreal world asset financing โ€ขtokenized fixed income โ€ขcrypto credit โ€ขmarket neutral strategies this sources are very important because most yield products lean on one engine. when that engine stalls, the yield stalls with it four independent sources means one weak spot doesnโ€™t sink the whole thing. exposure limits are also built in to reduce concentration risk maintain moderate risk. Code: 9HW7U3Z grvt.io/?ref=9HW7U3Z dyor, not financial advice
Idle stablecoins earn nothing. @grvt_io just launched High Yield Earn up to 11% target APY An 11% target APY got my attention. What matters more to me is where that yield comes from. GRVT High Yield Earn combines traditional finance and crypto strategies. they including tokenized fixed income, real-world asset financing, crypto credit and market neutral strategies. The underlying mechanics deserve a closer look. Whitelist is open ๐Ÿ‘‡ Code: 9HW7U3Z grvt.io/?ref=9HW7U3Z DYOR.
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๐†๐ž๐ซ๐š๐ฅ๐๐‚๐–—๐ฒ๐ฉ๐–™ ไบบ retweeted
How do you know an AI agent actually did the work it claims to have done? This is one of the bigger problems in the agent economy. You can't simply take an agent's word for it. You need a way to verify its work without necessarily exposing the data behind it. That's where the two @termix_ai technologies become interesting: TEE and zkVM. 1. TEE (Trusted Execution Environment) Think of it as a secure room inside a computer chip. Code runs in an isolated environment. Sensitive inputs stay protected from the rest of the system. Useful when agents handle private information 2. zkVM (Zero-Knowledge Virtual Machine) Think of this as a machine that can produce evidence that a computation was executed correctly. โ€ข Executes a program. โ€ข Generates a cryptographic proof of its execution. โ€ข Allows another party to verify the result without repeating the entire computation. 3. Why does this matter for AI agents? Agents are moving beyond answering questions. They're beginning to handle tasks, process data, interact with applications and execute workflows. But if an agent is going to handle valuable work, users need more than a completed task notification. They need evidence. TEE helps protect the execution environment. zkVMs help establish computational correctness. They approach different problems, but together they point toward something important which is private execution with verifiable results. The next phase of AI agents won't just be about what they can do. It will be about whether anyone can independently verify what they did. That's a much bigger conversation than simply making agents smarter.
The agent economy becomes interesting when agents can do more than complete tasks. when they can find work, follow instructions, and get paid. I think that's the next challenge for autonomous agents. Giving an agent more skills is useful, but skills alone don't create an economy. There also needs to be a way to connect those skills to real demand and handle payment. That's why I'm looking at what @termix_ai is building with Agent Skills. They announced integrations include Grok, Muse, and Claude, although the exact capabilities may differ across agents. I'm interested in seeing whether this can move beyond a good concept and become a practical way to get useful work done. Want to explore it yourself? Check out the TermiX Agent Skills and follow the installation guide. Personally, i think the agent economy won't be built on intelligence alone, It needs a way for agents to turn skills into income.
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โžฅ 11% apy means nothing until you ask where is it comes from so hereโ€™s where @grvt_io says it comes from. four yield sources โ€ขreal world asset financing โ€ขtokenized fixed income โ€ขcrypto credit โ€ขmarket neutral strategies this sources are very important because most yield products lean on one engine. when that engine stalls, the yield stalls with it four independent sources means one weak spot doesnโ€™t sink the whole thing. exposure limits are also built in to reduce concentration risk maintain moderate risk. Code: 9HW7U3Z grvt.io/?ref=9HW7U3Z dyor, not financial advice
Idle stablecoins earn nothing. @grvt_io just launched High Yield Earn up to 11% target APY An 11% target APY got my attention. What matters more to me is where that yield comes from. GRVT High Yield Earn combines traditional finance and crypto strategies. they including tokenized fixed income, real-world asset financing, crypto credit and market neutral strategies. The underlying mechanics deserve a closer look. Whitelist is open ๐Ÿ‘‡ Code: 9HW7U3Z grvt.io/?ref=9HW7U3Z DYOR.
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๐†๐ž๐ซ๐š๐ฅ๐๐‚๐–—๐ฒ๐ฉ๐–™ ไบบ retweeted
So we're getting Primus sooner than later expected.. @primus_labs just dropped a teaser about this NOV likely to be their TGE I joining primus_labs on @KaitoStudio_ cause the allocation was worth looking at. 0.3% of $PRIMโ€™s total supply is allocated to the campaign, with 0.24% for creators and 0.06% for Kaito stakers. Thatโ€™s a larger creator allocation than Axisโ€™s 0.25% campaign pool. Second, thereโ€™s still time to get involved. Epoch 2 runs until November 21, followed by Epoch 3 from November 22 to December 21. Points carry across epochs, and only your four best posts count per epoch. Donโ€™t rush to flood the timeline with low-effort content. Use the time to understand what Primus is building and publish a few posts that actually explain the tech. Its zkTLS technology verifies web data without exposing the underlying information, while zkFHE enables computation on encrypted data. Privacy is becoming a bigger conversation in crypto. The opportunity here is to understand the technology, contribute something useful, and let the quality of your work speak for itself. Still early enough to make your entry count. Make sure you start earning your XP here: s.kaito.ai/zJlvAyo
Most privacy solutions only address part of the problem. They either hide everything or reveal everything. Neither is enough when real capital and real decisions are involved. What's missing is the ability to prove facts without exposing the underlying data, and to compute on sensitive information without decrypting it. That's the gap Primus is building to address. Not more secrecy. Not more transparency. But a way to keep sensitive data private while making it usable and verifiable. Primus is building that cure.
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How do you know an AI agent actually did the work it claims to have done? This is one of the bigger problems in the agent economy. You can't simply take an agent's word for it. You need a way to verify its work without necessarily exposing the data behind it. That's where the two @termix_ai technologies become interesting: TEE and zkVM. 1. TEE (Trusted Execution Environment) Think of it as a secure room inside a computer chip. Code runs in an isolated environment. Sensitive inputs stay protected from the rest of the system. Useful when agents handle private information 2. zkVM (Zero-Knowledge Virtual Machine) Think of this as a machine that can produce evidence that a computation was executed correctly. โ€ข Executes a program. โ€ข Generates a cryptographic proof of its execution. โ€ข Allows another party to verify the result without repeating the entire computation. 3. Why does this matter for AI agents? Agents are moving beyond answering questions. They're beginning to handle tasks, process data, interact with applications and execute workflows. But if an agent is going to handle valuable work, users need more than a completed task notification. They need evidence. TEE helps protect the execution environment. zkVMs help establish computational correctness. They approach different problems, but together they point toward something important which is private execution with verifiable results. The next phase of AI agents won't just be about what they can do. It will be about whether anyone can independently verify what they did. That's a much bigger conversation than simply making agents smarter.
The agent economy becomes interesting when agents can do more than complete tasks. when they can find work, follow instructions, and get paid. I think that's the next challenge for autonomous agents. Giving an agent more skills is useful, but skills alone don't create an economy. There also needs to be a way to connect those skills to real demand and handle payment. That's why I'm looking at what @termix_ai is building with Agent Skills. They announced integrations include Grok, Muse, and Claude, although the exact capabilities may differ across agents. I'm interested in seeing whether this can move beyond a good concept and become a practical way to get useful work done. Want to explore it yourself? Check out the TermiX Agent Skills and follow the installation guide. Personally, i think the agent economy won't be built on intelligence alone, It needs a way for agents to turn skills into income.
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So we're getting Primus sooner than later expected.. @primus_labs just dropped a teaser about this NOV likely to be their TGE I joining primus_labs on @KaitoStudio_ cause the allocation was worth looking at. 0.3% of $PRIMโ€™s total supply is allocated to the campaign, with 0.24% for creators and 0.06% for Kaito stakers. Thatโ€™s a larger creator allocation than Axisโ€™s 0.25% campaign pool. Second, thereโ€™s still time to get involved. Epoch 2 runs until November 21, followed by Epoch 3 from November 22 to December 21. Points carry across epochs, and only your four best posts count per epoch. Donโ€™t rush to flood the timeline with low-effort content. Use the time to understand what Primus is building and publish a few posts that actually explain the tech. Its zkTLS technology verifies web data without exposing the underlying information, while zkFHE enables computation on encrypted data. Privacy is becoming a bigger conversation in crypto. The opportunity here is to understand the technology, contribute something useful, and let the quality of your work speak for itself. Still early enough to make your entry count. Make sure you start earning your XP here: s.kaito.ai/zJlvAyo
Most privacy solutions only address part of the problem. They either hide everything or reveal everything. Neither is enough when real capital and real decisions are involved. What's missing is the ability to prove facts without exposing the underlying data, and to compute on sensitive information without decrypting it. That's the gap Primus is building to address. Not more secrecy. Not more transparency. But a way to keep sensitive data private while making it usable and verifiable. Primus is building that cure.
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๐†๐ž๐ซ๐š๐ฅ๐๐‚๐–—๐ฒ๐ฉ๐–™ ไบบ retweeted
Found a crazy opportunity for creators who are actively on here. @FungoLabs just launched its $FUNGO campaign and they're putting 300M $FUNGO into its content campaign. but the scoring rule is what I noticed. Only your 5 best posts count toward the campaign. That puts more weight on the quality of your content than on how often you post. few details you might want to note: โ†’ Eligible posts must have been published from November 1, 14:00 UTC. โ†’ The reward pool is 300M $FUNGO. โ†’ Rewards are scheduled for distribution at TGE. I prefer campaigns where the rules are clear and good research has room to stand out. you should check it out : fungolabs.org/launchpad/c/cfโ€ฆ
1/6 10 billion $FUNGO: Who gets how much? Amounts, tokenomics and claim rules for Genesis NFT, Zama OG and the X Campaign. Details ๐Ÿ‘‡
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An AI agent wants to buy $0.10 worth of market data. The data costs 10 cents, but processing the payment through a conventional card could cost another 30 cents. Imagine that same agent making thousands of small purchases every day. Suddenly, the cost of moving money becomes a bigger problem than the service itself. This is one reason I've been paying closer attention to the ๐—ฒ๐—บ๐—ฒ๐—ฟ๐—ด๐—ถ๐—ป๐—ด ๐—ฝ๐—ฎ๐˜†๐—บ๐—ฒ๐—ป๐˜ ๐—ถ๐—ป๐—ณ๐—ฟ๐—ฎ๐˜€๐˜๐—ฟ๐˜‚๐—ฐ๐˜๐˜‚๐—ฟ๐—ฒ ๐—ณ๐—ผ๐—ฟ ๐—”๐—œ ๐—ฎ๐—ด๐—ฒ๐—ป๐˜๐˜€. And the numbers are getting difficult to ignore. According to @chainalysis, x402 recorded approximately 138.5 million cumulative transactions on Base through Q3 2026. Over 87% of the payments analyzed were worth $0.10 or less. That's a fascinating payment pattern because AI agents don't necessarily spend like humans. An autonomous research agent might need to purchase market data, pay for inference, access an API, and run security checks, all within a single workflow. Charging a conventional checkout fee for every tiny purchase becomes economically inefficient. ๐—ง๐—ต๐—ถ๐˜€ ๐—ถ๐˜€ ๐˜„๐—ต๐—ฒ๐—ฟ๐—ฒ ๐˜…๐Ÿฐ๐Ÿฌ๐Ÿฎ ๐—ฒ๐—ป๐˜๐—ฒ๐—ฟ๐˜€ ๐˜๐—ต๐—ฒ ๐—ฝ๐—ถ๐—ฐ๐˜๐˜‚๐—ฟ๐—ฒ. Developed by @CoinbaseDev, x402 allows software to: โ†’ request a resource โ†’ receive payment instructions through HTTP 402 โ†’ authorize a payment โ†’ access the service after verification Coinbase's facilitator offers 1,000 free monthly settlements, followed by $0.001 per settlement under its published pricing. But payment settlement is only one part of this emerging market. I've been following several companies building different pieces of the infrastructure: โ€ข @CoinbaseDev โ€” x402 payment infrastructure for machine-to-machine transactions. โ€ข @crossmint โ€” Agent wallets, stablecoins, existing card integration, and merchant checkout. โ€ข @turnkeyhq โ€” Wallet infrastructure that developers can integrate into agent applications. โ€ข @evervault and @basistheory โ€” Secure payment credentials and sensitive-data infrastructure. โ€ข @nevermined_ai โ€” Usage-based payments, metering, and x402 settlement for AI services. โ€ข @Stripe โ€” Shared Payment Tokens that allow agents to initiate authorized purchases without exposing underlying card credentials. โ€ข @Visa โ€” Intelligent Commerce and Trusted Agent Protocol for recognizing and authorizing agent-driven transactions. โ€ข @Mastercard โ€” Agent Pay for Machines, combining agent credentials, spending permissions, and multiple settlement rails. Notice something here? ๐—ง๐—ต๐—ฒ ๐—ฐ๐—ผ๐—บ๐—ฝ๐—ฒ๐˜๐—ถ๐˜๐—ถ๐—ผ๐—ป ๐—ถ๐˜€๐—ป'๐˜ ๐˜€๐—ถ๐—บ๐—ฝ๐—น๐˜† ๐—ฐ๐—ฟ๐˜†๐—ฝ๐˜๐—ผ ๐˜ƒ๐—ฒ๐—ฟ๐˜€๐˜‚๐˜€ ๐˜๐—ฟ๐—ฎ๐—ฑ๐—ถ๐˜๐—ถ๐—ผ๐—ป๐—ฎ๐—น ๐—ฝ๐—ฎ๐˜†๐—บ๐—ฒ๐—ป๐˜๐˜€. Itโ€™s about which infrastructure can give machines purchasing power without sacrificing cost efficiency, security, or accountability. And thereโ€™s still an uncomfortable question: If an AI agent makes an unauthorized purchase, exceeds its spending limit, or pays for a service that never arrives, who takes responsibility? Cheap settlement doesnโ€™t automatically solve those problems. Thereโ€™s also a reason to be cautious about the adoption numbers. Chainalysis identified speculative activity contributing to earlier x402 growth, so transaction counts alone donโ€™t prove sustainable commercial demand. My expectation is that agent payments will develop across multiple rails: โ–ธ Stablecoins and x402 have compelling economics for micropayments. โ–ธ Card networks retain established merchant acceptance and dispute mechanisms. The infrastructure that connects both while enforcing verifiable spending permissions, could become an important part of autonomous commerce. AI agents are learning to do work independently. The next challenge is allowing them to pay for that work without losing human control over the money.
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๐†๐ž๐ซ๐š๐ฅ๐๐‚๐–—๐ฒ๐ฉ๐–™ ไบบ retweeted
Crypto tokens are getting easier to value when protocols return revenue to holders. Buybacks and burns are becoming a bigger part of token economics. Zenecaโ€™s research puts annual spending at $1.85B for the year to October 2026, up from $190M in 2021. But a protocol buying its own token doesnโ€™t automatically make that token undervalued. Here are six models Iโ€™m tracking: โ†’ $HYPE: Trading fees fund HYPE purchases through Hyperliquidโ€™s Assistance Fund. The tokens are burned. โ†’ $PENDLE: 80% of V2 yield and swap fees fund buybacks distributed to eligible active sPENDLE holders. โ†’ $PUMP: Its current program commits 50% of revenue to buybacks and burns for one year from April 2026. โ†’ $SKY: Protocol surplus funds SKY purchases for burns or staking rewards. โ†’ $RAY: 12% of pool trading fees fund RAY buybacks. โ†’ $STONK: The project has spent money buying STONK, but weaker recent revenue makes it harder to assume that pace will continue. โ†’ $PONS: Its published V1 model directs 80% of protocol fees to PONS buybacks and burns. The differences matter. Some tokens are burned, while others are bought and distributed to holders. Emissions and unlocks can also offset buybacks. When comparing these tokens, I look at three things: โ€ข Revenue: Is it holding up over 30โ€“90 days? โ€ข Supply: Are buybacks large enough to matter alongside emissions and unlocks? โ€ข Valuation: How much revenue growth is already priced in? A quick starting point is market cap divided by annual buyback spending. A $1B token with $50M in annual buybacks trades at 20x that spending. That isn't an earnings multiple, and it only helps if the buybacks can continue. โ€ข I use DefiLlama to compare revenue โ€ข CoinGecko for market cap and FDV โ€ข Tokenomist for unlocks โ€ข Block explorers to check buyback and burn transactions. if want to hold any of these tokens, youโ€™ll want to focus more on some of these protocols but focus more on the ones that keep earning while returning enough value to token holders.
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Found a crazy opportunity for creators who are actively on here. @FungoLabs just launched its $FUNGO campaign and they're putting 300M $FUNGO into its content campaign. but the scoring rule is what I noticed. Only your 5 best posts count toward the campaign. That puts more weight on the quality of your content than on how often you post. few details you might want to note: โ†’ Eligible posts must have been published from November 1, 14:00 UTC. โ†’ The reward pool is 300M $FUNGO. โ†’ Rewards are scheduled for distribution at TGE. I prefer campaigns where the rules are clear and good research has room to stand out. you should check it out : fungolabs.org/launchpad/c/cfโ€ฆ
1/6 10 billion $FUNGO: Who gets how much? Amounts, tokenomics and claim rules for Genesis NFT, Zama OG and the X Campaign. Details ๐Ÿ‘‡
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๐†๐ž๐ซ๐š๐ฅ๐๐‚๐–—๐ฒ๐ฉ๐–™ ไบบ retweeted
Idle stablecoins earn nothing. @grvt_io just launched High Yield Earn up to 11% target APY An 11% target APY got my attention. What matters more to me is where that yield comes from. GRVT High Yield Earn combines traditional finance and crypto strategies. they including tokenized fixed income, real-world asset financing, crypto credit and market neutral strategies. The underlying mechanics deserve a closer look. Whitelist is open ๐Ÿ‘‡ Code: 9HW7U3Z grvt.io/?ref=9HW7U3Z DYOR.
JUST IN: High Yield Earn is LIVE for whitelisted users. Up to 11% target diversified yield across TradFi & crypto, with daily payouts and full self-custody. The bigger unlock is coming soon: the same capital that earns your yield will also back your trades. One balance. Two jobs. DM โ€œEARNโ€ for whitelist access.
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Idle stablecoins earn nothing. @grvt_io just launched High Yield Earn up to 11% target APY An 11% target APY got my attention. What matters more to me is where that yield comes from. GRVT High Yield Earn combines traditional finance and crypto strategies. they including tokenized fixed income, real-world asset financing, crypto credit and market neutral strategies. The underlying mechanics deserve a closer look. Whitelist is open ๐Ÿ‘‡ Code: 9HW7U3Z grvt.io/?ref=9HW7U3Z DYOR.
JUST IN: High Yield Earn is LIVE for whitelisted users. Up to 11% target diversified yield across TradFi & crypto, with daily payouts and full self-custody. The bigger unlock is coming soon: the same capital that earns your yield will also back your trades. One balance. Two jobs. DM โ€œEARNโ€ for whitelist access.
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๐†๐ž๐ซ๐š๐ฅ๐๐‚๐–—๐ฒ๐ฉ๐–™ ไบบ retweeted
Creator Season 1 is live. Create content about Sight and robinhood:0x238e40b75ae78a1388a14e517d855893e92e58db, earn points and compete for USDC and other rewards. Your content. Your points. Your rewards. Start here: creator.sighthood.com
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Crypto tokens are getting easier to value when protocols return revenue to holders. Buybacks and burns are becoming a bigger part of token economics. Zenecaโ€™s research puts annual spending at $1.85B for the year to October 2026, up from $190M in 2021. But a protocol buying its own token doesnโ€™t automatically make that token undervalued. Here are six models Iโ€™m tracking: โ†’ $HYPE: Trading fees fund HYPE purchases through Hyperliquidโ€™s Assistance Fund. The tokens are burned. โ†’ $PENDLE: 80% of V2 yield and swap fees fund buybacks distributed to eligible active sPENDLE holders. โ†’ $PUMP: Its current program commits 50% of revenue to buybacks and burns for one year from April 2026. โ†’ $SKY: Protocol surplus funds SKY purchases for burns or staking rewards. โ†’ $RAY: 12% of pool trading fees fund RAY buybacks. โ†’ $STONK: The project has spent money buying STONK, but weaker recent revenue makes it harder to assume that pace will continue. โ†’ $PONS: Its published V1 model directs 80% of protocol fees to PONS buybacks and burns. The differences matter. Some tokens are burned, while others are bought and distributed to holders. Emissions and unlocks can also offset buybacks. When comparing these tokens, I look at three things: โ€ข Revenue: Is it holding up over 30โ€“90 days? โ€ข Supply: Are buybacks large enough to matter alongside emissions and unlocks? โ€ข Valuation: How much revenue growth is already priced in? A quick starting point is market cap divided by annual buyback spending. A $1B token with $50M in annual buybacks trades at 20x that spending. That isn't an earnings multiple, and it only helps if the buybacks can continue. โ€ข I use DefiLlama to compare revenue โ€ข CoinGecko for market cap and FDV โ€ข Tokenomist for unlocks โ€ข Block explorers to check buyback and burn transactions. if want to hold any of these tokens, youโ€™ll want to focus more on some of these protocols but focus more on the ones that keep earning while returning enough value to token holders.
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