Crypto Enters the Era of Value Investing I’m getting more interested in tokens I can value using the money their protocols actually earn. Crypto now has businesses with paying users, recurring revenue, and mechanisms that return part of that revenue to the token. That gives me a much stronger reason to research something beyond its next catalyst. Zeneca’s latest research estimates annual spending on token buybacks and burns grew from $190M in 2021 to $1.85B in the year to Oct 2026. Coverage has expanded, but the scale is still worth paying attention to. So I believe we’re getting more opportunities to price a token against measurable demand funded by its own business. From a macro perspective, I still care about liquidity, rates, and risk appetite. Those conditions affect what investors are willing to pay. But I also want to understand what can sustain demand for a token when fresh speculative money slows down. A protocol earning money from customers and consistently buying its token gives me something concrete to evaluate. Hyperliquid is a clear example, its Assistance Fund converts trading fees into HYPE, and those tokens are burned. Usage creates a direct source of token demand. Pendle offers a different model: 80% of V2 yield and swap fees fund PENDLE buybacks, with repurchased tokens distributed to eligible active sPENDLE holders. That rewards participation, but has different supply effects from a permanent burn. I can be bullish on a protocol and still pass on its token. The product might be growing while most of the economics go to liquidity providers, the team, or the treasury. Fees, protocol revenue, and value returned to holders are separate numbers. So I’m paying closer attention to: → Revenue that holds up after incentives decline. → The amount actually reaching holders. → Buybacks relative to emissions and upcoming unlocks. → The growth already assumed by today’s valuation. If a token’s price halves while its dollar buyback budget stays unchanged, that budget can purchase twice as many tokens. For a business that keeps earning and burning, a drawdown can make each dollar of buybacks more effective. The difficult part is checking whether the revenue will hold up. Annualizing one exceptional trading week can make an expensive token look cheap. I think some of the best research opportunities are finding protocols whose earnings are more durable than their valuation suggests. I’m ranking conviction in the business and token mechanics; valuation still determines whether I’d buy. [1] $HYPE - Trading fees flowing through Hyperliquid’s Assistance Fund buy HYPE & burned. [2] $PENDLE - 80% of V2 yield and swap fees fund buybacks distributed to eligible active sPENDLE holders. [3] $SKY - Protocol surplus funds SKY purchases for burns or staking rewards, with new emissions disabled. [4] $RAY - 12% of pool trading fees fund RAY buybacks + trading activity and competition determining how durable those purchases are. [5] $PUMP - Its current program commits 50% of revenue to buybacks and burns for one year from April 2026. [6] $PONS - Its published V1 model directs 80% of protocol fees into PONS buybacks and burns. [7] $STONK - StonkFun has measurable spending on STONK purchases. But the recent revenue slowdown makes me cautious about projecting last month’s earnings forward. PONS and STONK are particularly interesting research candidates because small valuations and meaningful buybacks can coexist. The opportunity depends on how much revenue survives when activity cools. A low multiple calculated during a launch frenzy can disappear quickly if earnings fall faster than the token price. For anyone who wants to research this themselves, this i the quick calculation: Buyback multiple = market cap ÷ annual spending on token buybacks. A $1B token receiving $50M in annual buybacks trades at 20× that spending. I’d also check FDV and future supply, then recalculate using quieter periods. Tools that make this easier: - @DefiLlama: compare revenue and holder revenue across 7-, 30-, and 90-day periods. Read each protocol’s methodology. - @coingecko: check market cap, FDV, supply, and trading markets. - @Tokenomist_ai: check available unlock and emissions schedules. - @solscanofficial / @blockscout: verify purchases, burns, supply, and treasury movements. The setup that excites me is a growing business, meaningful value reaching its token, and a price that still underestimates both. That gives me a thesis I can track, update, and build conviction around.

➥ My quantum-resistant token wishlist I’m spending more time on this sector because the migration is already happening. Google targets 2029 for post-quantum readiness, with Google Cloud publishing a detailed migration roadmap in August. That’s a deadline to prepare infra, not a prediction that Bitcoin gets broken in 2029. I believe wallets, custodians and institutions will need to evaluate quantum exposure before a capable quantum computer arrives. But I’m checking what actually protects user funds: native signatures, optional account upgrades, or unfinished implementations. Here’s my wishlist: → base:0x37696cd8f723ce541ac376f79fc109080e505ba3 - the operating history I want to study. Native transactions have used hash-based XMSS signatures since 2018. Next checkpoint is Zond: whether its post-quantum smart-contract stack can attract developers beyond the security thesis. → $QTC - the newer implementation I’m following closely. @QuantusNetwork native ML-DSA transaction signing. I want to see sustained usage, accessible liquidity and demand that can absorb mining emissions. → $CKB - cryptographic flexibility interests me. Its SPHINCS+ Lock Script and Quantum Purse let users adopt post-quantum protection today. It’s optional, so wallet adoption matters as much as protocol capability. → algorand:native - a concrete migration path on an established chain. Native Falcon-1024 accounts are supported. I’m watching wallet and app compatibility. → $NEAR - migration without changing the account address. ML-DSA-65 signing went live in July. Fireblocks demonstrated rotating a funded account in 2 transactions, then receiving and sending funds with the new key. That’s the kind of practical integration I care about. → abelian:native - privacy and post-quantum security together. @PQabelian uses lattice-based cryptography for private transactions. I want to understand whether that translates into recurring payment demand and stronger liquidity. → $CELL - the ability to change algorithms over time. @cellframenet supports multiple post-quantum signature schemes. I’m watching adoption of its native infra, while checking which chain and token representation users actually hold. → $STRK - promising architecture, with dependencies. Hash-based STARK proofs and working Falcon account implementations give Starknet a migration path. Those account implementations remain early-stage, and full protection still depends on Ethereum’s transition. I’m also tracking $ZEC’s quantum-recoverability work. It supports a future migration; it doesn’t make current Zcash fully quantum-resistant. Where I expect growth: → wallets that make key migration usable. → custody systems that can support new signatures. → infra that handles their higher verification costs. → networks that turn those capabilities into retained users and fees. Existing chains can upgrade too, so post-quantum cryptography alone won’t guarantee token demand.

Over the years, I've worked with hundreds of projects and agencies across the crypto space, and @surgence_io is one of the teams I've had a great experience collaborating with. A few things I appreciate about working with them: – smooth communication and clear expectations – professional coordination throughout campaigns – a good understanding of how to work with crypto KOLs and creators Surgence Labs also has a pretty solid presence in the industry, with 66K+ followers on X and a focus on GTM, marketing, and community growth for crypto and AI projects. They also highlight some impressive numbers on their profile: – 10M+ followers across their network – $5B+ capital raised – 300M+ generated reach – 2,000+ KOL and community partners If you're building a crypto or AI project and looking for an agency to help with marketing, KOL campaigns, or expanding your community, I think @surgence_io is definitely worth considering. Appreciate the collaboration so far, and looking forward to working together again.

Everyone is trying to make tokenized stocks yield-bearing assets now. But stocks don't magically generate extra cash flow just because they're onchain. So who's actually paying for all this yield? Apparently, 42% of tokenized stock supply was classified as DeFi-eligible collateral, but: – $81M, or 2.6% of total issuance, was sitting in lending markets. – $188.9M, or ~6% of issuance, was deployed across broader DeFi (AMMs, Pendle, and vaults). I'm also seeing that deposited capital doesn't necessarily mean productive capital. Just look at the lending numbers: – @kamino Opening Bell: ~$38M deposited, only $7.5M borrowed – Kamino xStocks: ~$29M deposited, $5.2M borrowed – @SentoraHQ xStocks: $7.8M deposited, just $600K in debt – @lista_dao bStocks: ~$7.64M collateral, ~$3.67M borrowed Lots of collateral sitting there. Not nearly as much borrowing happening against it. Makes me think debt growth relative to deposits is gonna matter way more than headline TVL. @krakenfx's xStocks vaults were offering estimated net yields of ~1.8–2%, with a 25% performance fee. Underneath, the vault takes your stock token, posts it as collateral, borrows stables, puts those in DeFi, then compounds whatever spread is left back into the stock position. So users get whatever is left after downstream strategy returns, stablecoin borrowing costs, fees, and other frictions are accounted for. Compare that with STRCx on @pendle_fi, which gives us a glimpse of what tokenized equity yield markets could eventually become. STRCx had a 12% annualized variable dividend rate. Unlike a typical growth stock, there's an actual external distribution stream to work with. – $33.5M of STRCx exposure was on Pendle – ~97% of DeFi-deployed STRCx was sitting in one yield-splitting venue – Nov 25 maturity showed ~24.4% implied APY vs ~12.22% underlying APY Pendle is pricing and redistributing claims on that future cash flow between PT and YT buyers. We're starting to see an actual market for the time value of tokenized security income. Because for something like NVDAx or TSLAx to generate extra yield, someone somewhere has to pay. You can wrap the same asset five times, but you can't wrap your way into five independent sources of cash flow. Which is why I suspect preferred shares, dividend-paying ETFs, and other cash-flow-heavy securities could develop deeper yield markets before the most speculative single-name stocks do. Another thing to watch is which stocks people actually want to borrow against. ~21% of SPYx supply was in lending markets versus only ~5–6% for NVDAx and TSLAx. Makes me wonder maybe the sexiest stock to trade isn't necessarily the best collateral? Also worth remembering that equity perps had ~$3.3B OI vs ~$81M in lending collateral, ~40x. Demand for leveraged stock exposure is overwhelmingly choosing perps over borrowing against spot tokens. And tbh that makes sense when a perp is one click, while spot-backed leverage has to deal with collateral haircuts, oracle updates, issuer redemption, and U.S. market closures. A token trading 24/7 doesn't automatically mean the underlying stock can be liquidated safely over the weekend. That might be the biggest bottleneck in this entire stack. So yeah, I think we're still insanely early in the tokenized stock game. The TVL is starting to show up, but the actual yield economy behind all of this still very much a work in progress.

$744B in trading volume in ~48 hours. Papertrade might be one of the craziest Perp DEX launches we've seen. @papertrade_xyz launched on HyperEVM on Oct 10, and its early numbers are pretty wild. According to its live dashboard: – $744B cumulative trading volume – $24.1B liquidation volume – 238,320 trades across 16,023 users – $26.2M in reported rewards – $64.7M TVL – $423M current OI across $BTC and $ETH – traders sitting at -$32.1M in aggregate PnL on the 1D chart What's driving this activity? Papertrade introduced a pretty unusual model where losing traders mint $PAPER based on their realized losses. The protocol offers up to 1,000x leverage on BTC and ETH, with zero trading fees, funding fees and slippage under its advertised model. $PAPER holders can stake their tokens to earn USDC distributions linked to the protocol's economics. Basically, trading losses help fuel the token distribution mechanism, creating a new kind of Loss-to-Earn narrative. I can see why degens are interested. However, the numbers deserve a closer look. OI has dropped sharply, TVL has pulled back from its peak, and recent reports have raised concerns about price manipulation. Also, $744B in volume doesn't necessarily translate into sustainable revenue, especially with extreme leverage and farming incentives. I'm keeping an eye on $PAPER and how this model develops. If Papertrade can maintain organic trading activity, healthy liquidity and sustainable rewards, this could become an interesting experiment for the next wave of Perp DEXs.

If you're looking for a safe place to store your retirement savings, I'd still trust traditional banks or a properly secured multisig wallet over a regular crypto wallet. For larger crypto holdings, I'd personally go with a 3-of-3 multisig setup, with each key stored separately and at least 2 keys kept completely offline on a dedicated hardware signer. One compromised device should never be enough to wipe out your life savings. Losing $3M is painful, but losing your retirement funds and your kids' future is devastating. Security should always come before convenience.

$STONK is down over 60% from ATH, but I still see several potential catalysts for its next leg up. Currently trading around ~$129M MC, $STONK remains one of my picks for the next onchain coins season. Here’s why I'm still bullish: [1] Real revenue + buyback & burn – StonkFun generated $28.69M in Q3 revenue, with $14.41M recorded in buybacks. – around 60% of platform revenue is targeted for buying back and burning $STONK. – over 20% of the original 1B supply has already been burned, leaving ~797M tokens. [2] A different launchpad model – @LaunchOnSF allows creators to launch tokens paired with xStocks, SPYx, altcoins and other supported assets instead of only SOL. – as tokenized equities and RWAs expand on Solana, more quote assets could bring more trading volume and fees. [3] Revenue continues after graduation – tokens graduate into Raydium pools, where StonkFun can continue earning creator and locked LP fees. – this gives the platform multiple revenue streams beyond initial launches. [4] Potential for another onchain season – over $840M in DEX volume during the last 30D shows there's still meaningful activity. – if Solana memecoins and RWA narratives heat up again, StonkFun could benefit from both. [5] More liquidity + potential CEX expansion – additional major listings, deeper liquidity and wallet integrations could improve access to $STONK. – a broader investor base could support demand alongside the existing buyback mechanism. Ofc, there are risks. Revenue has cooled from its peak, competition from is growing, and buybacks alone won't guarantee higher prices. Still, at ~$129M MC, I think $STONK deserves a spot on my watchlist. If StonkFun can maintain strong revenue while supply keeps shrinking, a return to ATH becomes a scenario worth considering. I'm still betting on another onchain coins season, with $STONK and $PONS among my preferred picks. NFA.

6 narratives I’m positioning around for this cycle [1] The monetary endgame starts playing out As sovereign debt, currency debasement and financial surveillance become harder to ignore. I expect capital to move toward 2 extremes: Transparent scarcity through $BTC Private money through $XMR, $ZEC and $RAILGUN BTC remains the institutional answer. XMR is private by default, while ZEC gives users programmable privacy and selective disclosure. [2] Social trading becomes the new casino People no longer want to trade alone. They want live positions, public conviction, leaderboards and instant speculation around every event. Prediction markets, perps and memecoin launchpads are all competing for the same attention. Aligned: @RobinhoodApp, @HyperliquidX, @Pumpfun, @ponsdotfamily, @longdotxyz, @jumperapp Tokens: $HYPE, $HOOD, $PUMP [3] USA perps happen in a major way This one still feels underpriced. Kalshi has already introduced regulated BTC perps, while Coinbase and Kraken are moving toward broader perpetual products. Coinbase is even pursuing single-stock perps. If US users finally get compliant 24/7 perps, derivatives volume enters a completely different phase. Aligned: Coinbase/Deribit, Kraken, @Polymarket, @Kalshi, @HyperliquidX Exposure: $COIN, $HYPE and potentially solana:7E17FfBVYfQLAdQiSMK3ESNwkiYGdZPTVvB5b5oypump [4] DATs make a comeback, but most will not The first DAT wave showed that simply raising capital and buying tokens is not a sustainable business. The next winners need liquid holdings, reliable financing and an operating engine that can survive mNAV compression. I’m mainly watching Strategy for BTC and BitMine for ETH. For smaller DATs, I need to see more than a treasury announcement. Aligned: $MSTR, $BMNR, $BTC, $ETH [5] A real AI coin emerges Most AI tokens still depend more on branding than actual demand. My strongest candidate remains $TAO because Bittensor is building an active market for machine intelligence rather than attaching AI to an unrelated token. I’m also watching the supporting infrastructure: Aligned: $TAO, solana:rndrizKT3MK1iimdxRdWabcF7Zg7AR5T4nud4EkHBof, $AKT, $NEAR, $VIRTUAL But I expect one asset to capture most of the monetary premium. Right now, TAO has the clearest path. [6] RWAs outperform RWA is no longer just tokenized Treasuries. We now have stocks, private credit, gold, stablecoins and institutional settlement moving onchain. More importantly, these assets are becoming usable across lending, collateral and yield markets. Aligned tokens: $ONDO, $LINK, $CC, $MNT Projects I’m watching: @arc, @saturn_credit, @Theo_Network, @pendle_fi and @centrifuge Not every aligned token will win, but I think the eventual leaders are already somewhere on this list.

Happy weekend fam, Post-Quantum Cryptography could become one of the next major security narratives in crypto. NIST has already finalized its first PQC standards, while Ethereum, Bitcoin and several other ecosystems are exploring how to prepare for quantum threats. I think this narrative deserves more attention, especially as AI and quantum computing continue to advance. Here's why: – most major blockchains still rely on elliptic-curve signatures, which could become vulnerable to sufficiently powerful quantum computers. – Shor's algorithm could potentially break these signatures, putting exposed public keys and associated funds at risk. – NIST has standardized PQC algorithms such as ML-DSA, SLH-DSA and ML-KEM, giving the industry a clearer path toward migration. – upgrading blockchain security could create demand for new wallets, custody solutions, signature systems and migration infrastructure. Ofc, this threat isn't expected to materialize overnight. No publicly demonstrated quantum computer can currently break Bitcoin or Ethereum's production signatures at scale. But preparing major blockchain networks could take years. 20 tokens I'm tracking around the Post-Quantum narrative: Post-Quantum Cryptography could become one of the next major security narratives in crypto. NIST has already finalized its first PQC standards, while Ethereum, Bitcoin and several other ecosystems are exploring how to prepare for quantum threats. I think this narrative deserves more attention, especially as AI and quantum computing continue to advance. Here's why: – most major blockchains still rely on elliptic-curve signatures, which could become vulnerable to sufficiently powerful quantum computers. – Shor's algorithm could potentially break these signatures, putting exposed public keys and associated funds at risk. – NIST has standardized PQC algorithms such as ML-DSA, SLH-DSA and ML-KEM, giving the industry a clearer path toward migration. – upgrading blockchain security could create demand for new wallets, custody solutions, signature systems and migration infrastructure. Ofc, this threat isn't expected to materialize overnight. No publicly demonstrated quantum computer can currently break Bitcoin or Ethereum's production signatures at scale. But preparing major blockchain networks could take years. 20 tokens I'm tracking around the Post-Quantum narrative: [1] base:0x37696cd8f723ce541ac376f79fc109080e505ba3 – quantum-resistant L1 using XMSS since 2018. [2] algorand:native – Falcon-based State Proofs already live, with broader PQ initiatives. [3] $CKB – flexible cryptographic architecture with PQ signature support. [4] abelian:native – PQ-focused L1 combining lattice-based cryptography and privacy. [5] $CELL – modular blockchain infrastructure focused on PQ cryptography. [6] $QANX – EVM-compatible blockchain developing PQ security. [7] $MCM – early PQ blockchain using WOTS+ signatures. [8] $NAORIS – decentralized security infrastructure focused on PQ protection. [9] $STRK – STARK proofs offer a quantum-resistant foundation, while account signatures remain a separate challenge. [10] $ZEC – privacy ecosystem exploring long-term cryptographic resilience. [11] $NXS – security-focused blockchain with signature-chain architecture. [12] $QUBIC – quantum computing-related ecosystem, with a less direct PQC investment thesis. [13] minima:native – decentralized blockchain with quantum-related security ambitions. [14] $QTC – Quantus, a PQ-focused blockchain project. [15] $FHE – Mind Network, focused on encrypted computation rather than native PQ signatures. [16] $QONE – quantum-security and migration-focused infrastructure. [17] $AME – smaller blockchain project associated with PQ security claims. [18] $GEEQ – security-focused blockchain infrastructure. [19] solana:AUuCEHQ7sm2i5GmaHrpE961voWcTY8U6mgrkhcV7pump – QuStream, a smaller project making quantum-security claims. [20] $TDC – Tidecoin, an early hash-based PQ blockchain project. These projects are at very different stages. Some already use PQ signatures, others offer partial protection, while several remain roadmap-driven or only indirectly exposed to the narrative. My view: I would prioritize projects with actual cryptographic implementations over those relying mainly on quantum-related marketing. base:0x37696cd8f723ce541ac376f79fc109080e505ba3 and algorand:native are worth a closer look from a technical perspective. $STRK is also interesting because of its STARK-based architecture, although quantum-resistant proofs alone don't make an entire blockchain quantum-safe. I also think established ecosystems such as $ETH could benefit from a successful transition toward PQ security. The real opportunity may extend beyond individual L1 tokens into wallets, custody, interoperability and security infrastructure.

I think tokenized compute is becoming a distinct digital asset class. Most AI investing still focuses on models and applications. The market is becoming more interested in the resource every one of them must continuously pay for = compute. The reason is a basic supply-demand imbalance. Digital demand can scale almost immediately. A new AI agent can launch in hours, operate continuously and execute multi-step tasks that consume significantly more compute than a normal chatbot request. Physical supply cannot expand at the same speed. New capacity requires electricity, grid connections, permits, data centers, cooling systems, GPUs, high-bandwidth memory, networking equipment and specialized labor. Grid connection alone can take years. This creates a financial setup I find increasingly difficult to ignore: Demand is software-scaled. Supply is physically constrained. If agent activity continues growing, more value should accrue to the companies and protocols that own, finance or efficiently allocate active compute capacity. Crypto is starting to make that exposure investable in several forms. @Compute_Labs and @gaib_ai focus on the ownership and financing side. They turn GPUs, infrastructure financing and the resulting cash flows into onchain assets. This is the closest category to an RWA investment in productive AI infrastructure. @AethirCloud, @ionet and @akashnet_ operate compute marketplaces. Their networks aggregate hardware from different providers and let users rent capacity for AI workloads. Here, the main questions are utilization, customer revenue and how much economic activity reaches the token. @orbiodotso and @Cerebro_RH are testing another model: tokenized inference credits. Instead of tokenizing the GPU itself, they make access to AI inference transferable and programmable. Trading fees can fund credits that agents later consume. @opentensor approaches the market differently. Its subnets produce digital commodities such as compute, inference, storage and prediction. While TAO coordinates incentives between miners, validators and capital. @virtuals_io belongs mainly on the demand side. Its agents need inference, memory and runtime to operate. As agents begin paying these costs directly from their wallets and earned revenue, compute becomes a recurring operating expense within the agent economy. This is why I would not value every “compute token” in the same way. One may represent ownership of hardware cash flow. Another may provide access to future inference. Another coordinates a marketplace. Another captures demand generated by productive agents. I do not think every project in this sector will benefit equally. Compute is only scarce when it has the right chips, available power, suitable location and real customers. But the broader direction is becoming clear to me. Tokenization can turn GPU ownership, inference rights and compute-generated cash flows into liquid onchain assets. AI gave compute economic demand. Crypto may give it an open capital market.

Idk why, but I’m feeling increasingly uncomfortable with the current market. Just look at what’s happening in the US economy: – inflation remains elevated at 3.4%, well above the Fed’s 2% target – Brent crude is still trading around $100/barrel – US 10Y Treasury yield is around 5.2%, after recently hitting its highest level since 2002 – US added only 29K jobs in September, suggesting the labor market is losing momentum Yet the S&P 500 and Nasdaq just hit new ATHs on Oct 6. Even more concerning, the Magnificent 7 now account for 34.9% of the S&P 500's total weight. Meanwhile, crypto had a solid rally in recent weeks, although BTC and most alts are now showing signs of weakness. The disconnect between economic conditions and asset valuations is getting harder to ignore. Ofc, strong AI earnings expectations and market liquidity could keep equities elevated for longer than expected. But how much longer can this divergence last? I’m leaning toward a significant market correction before another sustainable rally. If we get a big dip, $BTC $ETH $SOL $NEAR $UNI $TAO will remain my top priorities for accumulation. I'd rather keep some dry powder than chase the market at these levels. ofc, personal thought. NFA

The Onchain Distribution Stack. Tokenization alone does not create a financial market. The asset also needs financing, risk underwriting, liquidity, and distribution. This is why I now look at tokenized products through 5 layers: [1] Asset issuer This is the fund manager running the underlying strategy. Key players include Circle through Hashnote, Janus Henderson, Federated Hermes, @SuperstateInc, Apollo, @FasanaraDigital, and @vaneck_us. Their role has not changed much from traditional finance. They originate the asset and manage the portfolio. What changes is everything that happens after issuance. [2] Tokenization platform Platforms such as @centrifuge, @Securitize, Superstate, @MidasRWA, and Circle package the strategy into an onchain instrument. This is similar to how a bank structures a fund, ETF, or credit product for distribution. But an onchain asset can also be integrated into lending markets, used as collateral, and allocated through smart contracts. That composability is the real upgrade. [3] Lending protocol @aave Horizon, @Morpho, and @kamino provide the financing infra. They handle lending, borrowing, interest accrual, and liquidations automatically. I see them as the onchain version of prime brokerage infrastructure. But the protocol only enforces the rules. It does not decide whether the collateral is good enough. That responsibility belongs to the next layer. [4] Risk manager This is the layer I believe the market still underestimates. Risk managers such as @SteakhouseFi, @gauntlet_xyz, and @Bitwise decide: – Which assets qualify as collateral – How much can be borrowed against them – What concentration limits apply – Where stablecoin liquidity should be allocated In simple terms, protocols execute while risk managers underwrite. A tokenized asset without credible underwriting and meaningful liquidity may exist onchain, but it cannot be financed at scale. Bitwise launching an allocation vault on Morpho in Jan 2026 was important to me because it showed that traditional asset managers are beginning to participate directly in this layer. Aave Horizon follows a different model. Its collateral rules and allocations are managed at the protocol level by Aave Labs with support from firms such as Llama Risk. Morpho and Kamino allow independent managers to build allocation vaults. Aave keeps more of the risk function inside its own system. [5] Distribution platform This is where the model can reach scale. Coinbase already routes user USDC into Steakhouse-managed Morpho vaults on Base. The user sees a simple yield product, while the lending and collateral infrastructure operates underneath. Aave is taking a more vertically integrated approach. MetaMask and Bitget have integrated Aave into their yield products, while Aave also launched its own consumer savings app in November 2025. So I currently see two different distribution models: – Morpho and Kamino provide infrastructure that other platforms can package and distribute – Aave increasingly owns both the lending infrastructure and the consumer distribution The next phase of tokenized finance will not be won by issuance alone. The strongest products will connect the full stack: Asset manager → tokenization platform → lending protocol → risk manager → distribution platform I think the most valuable layer to watch is risk management. That is where a tokenized asset moves from being available onchain to becoming acceptable collateral with real liquidity behind it.

Today I call upon the blockchain industry to calmly begin planning for "bunker mode". My personal recommendation is to set in motion a controlled mass migration of assets to fresh addresses, i.e. addresses whose pubkeys remain hidden behind a hash. Holders, starting with large and sophisticated ones, should consider moving the bulk of their funds to addresses that have never signed a transaction. And when they do sign one, they should also move remaining funds to a new address (possibly generated from the same seed phrase). Don't rush. While I believe there is cause for action a rushed migration would do more harm than good. Don't panic either. Moving assets to protected addresses is a simple, preventative step which does not require new cryptography or new wallets. IMO it is now reasonable to brace for the possibility that ECDSA breaks before qday, in the worst case in months not years. By "break" I mean fast private key recovery (e.g. in one week) on available hardware (e.g. a large GPU cluster). Recent days have been humbling for human mathematical intuition. Long-held, unquestioned hypotheses have fallen. This includes the n log(n) bound for integer multiplication and the 3SUM conjecture. In hindsight, May's unexpected disproof of the Erdős unit distance conjecture was our warning shot. Yesterday's OpenAI drop made it clear that mathematical superintelligence is upon us. They say there are weeks where decades happen. We are about to live through weeks where centuries of mathematical progress happen. Could our magic 64-byte ECDSA signatures be too good to be true? Was it just security through obscurity all this time? Elliptic curves feel especially vulnerable to superintelligence. Curves carry rich structure, with room for fancy tricks like Schoof, Frobenius, pairings. (By contrast, hashes are designed to minimise algebraic structure.) Separately, as Ewin Tang can attest, an efficient quantum algorithm sometimes foreshadows an efficient classical one. We should be open to the possibility of a classical counterpart to Shor that breaks elliptic curves and RSA at once. Also noteworthy is the striking under-representation of cryptographic breakthroughs among the 722 mathematical results OpenAI published. I've witnessed first-hand the US government censoring academic quantum cryptanalysis results. Backroom interventionism is my base case. I urge large, sophisticated actors to lead by example. Project11's "risq list" (bitcoin-risq-list.projecteleven[.]com) is a great tracker of exposed BTC pubkeys. Binance, Bitbank, Robinhood, Bitfinex, and Tether have an opportunity to harden their cold storage. Next month I'll address institutions in London in a live Q&A (forum.ethereuminstitutional[.]org/london-2026). Again, please do not rush. Wallets holding under 50 BTC enjoy partial cover from "Satoshi's shield", i.e. his 20K exposed addresses that hold 50 BTC each. Load-bearing signers like oracles and L2 security councils should consider rotating ECDSA pubkeys with every signed message and/or multi-signing with a hash-based schemes like SPHINCS. Exiting bunker mode safely will require post-AI cryptography. My inclination is to go all-in on hash-based cryptography and avoid structured mathematical assumptions entirely, whether from curves, lattices, or isogenies. A single battle-tested hash (e.g. from the SHA or BLAKE families) yields plausible post-AI security. The Ethereum roadmap on strawmap[.]org fully embraces hash-based cryptography with end-to-end formal verification as a response to the quantum threat. Those timelines must now be revisited and accelerated in light of mathematical superintelligence. I'll be pushing for maximum defensive acceleration.

➥ @GenLayer has built an upgraded version of smart contracts called Intelligent Contracts. I like how GenLayer approaches one problem prediction markets still don’t handle well: outcomes that require judgment instead of just reading data. A clear example is Polymarket’s $242,2M market on whether Zelenskyy would wear a suit before July. The data and evidence can be public, but someone still needs to decide whether a specific outfit actually counts as a “suit” under the market rules. That’s exactly the type of problem GenLayer is trying to solve with Intelligent Contracts. – traditional oracles work well when the answer is a price, score or predefined data point – Intelligent Contracts can read public websites/APIs, interpret unstructured info and evaluate the result against written rules – the decision doesn’t come from one AI model, 5 randomly selected validators independently evaluate the evidence using different models – if the result is challenged, the validator set can expand from 5 → 11 → 23 In GenLayer’s public benchmark, its Intelligent Oracle resolved 97.2% of addressable Polymarket markets. Resolution can take around 3 mins, while disputed markets can take days to settle. Personally, I think this use case gets more interesting as prediction markets expand into politics, geopolitics, token launches, speeches and other real-world events. A lot of these outcomes need interpretation, not just another data feed onchain. If prediction markets keep scaling, decentralized judgment could become a new infra layer underneath them.

➥ Post-Quantum infra is starting to matter NIST has finalized its first PQC standards, while Ethereum is targeting broader quantum resistance by 2029. The risk is mainly around the cryptography securing wallets, signatures and validators today. If quantum computing reaches sufficient scale, crypto will need a major migration toward new security standards. That could create new markets around PQ wallets, custody, ZK, interoperability and blockchain migration. Projects I’m tracking: [1] base:0x37696cd8f723ce541ac376f79fc109080e505ba3 | @QRLedger: PQ-native L1, expanding into PoS + ML-DSA. [2] algorand:native | @AlgoFoundation: Falcon-based PQ protection already live onchain. [3] $ETH | @ethereum: building leanXMSS, leanVM and a broader PQ roadmap. [4] $QNT | @quant_network: institutional interoperability + future cryptographic migration. [5] $SUI | @SuiNetwork: exploring ML-DSA + SLH-DSA for PQ security. [6] $QANX | @QANplatform: quantum-resistant L1 + PQ wallet protection. [7] $XDC | @XDCFoundation: PQ security for RWA and trade finance infra. [8] $CELL | @cellframenet: quantum-safe L0 + cross-chain infra. [9] $NAORIS | @NaoXprotocol : post-quantum cybersecurity for Web2 + Web3. [10] abelian:native | @PQabelian: PQ-native chain combining privacy + quantum resistance. [11] $MCM | @MochimoOfficial: PQ-native blockchain using hash-based signatures. [12] @projecteleven: PQ security infra for BTC, ETH and wallets. The areas I’m watching most: – PQ-native chains – wallet/key migration – institutional custody – BTC/ETH migration infra – PQ ZK/proving – legacy ↔ quantum-safe interoperability Personally, $QNT is the one I like most here. Quant already sits between banks, legacy rails and DLTs, which could become a key position during PQ migration. If institutions need to upgrade cryptography without rebuilding everything, interoperability could capture real value. Still early, but $QNT is my main watch from this narrative.

Layer 2s are changing direction this cycle. Last cycle, most L2s followed the same strategy: Lower fees, attract DeFi apps, offer incentives and compete for TVL. That model is no longer enough. Cheap blockspace has become common, and users rarely care about the underlying stack. This cycle, I think the winners are building around three advantages: – Existing distribution – A specific financial use case – Infra designed for that use case Only 5 Ethereum L2s currently secure more than $1B: [1] @base: $15.98B [2] @arbitrum - $ARB: $11.58B [3] @Optimism - $OP: $1.89B [4] @Mantle_Official - $MNT: $1.50B [5] @Lighter_xyz - $LIT: $1.47B But each one is reaching scale through a different method. [1] Base: consumer distribution Base has the strongest direct distribution through Coinbase. Expanding from a general L2 into a complete onchain financial platform covering tokenized assets, stablecoin payments, trading and AI agents. The Base App can connect users, assets and applications in one interface. Coinbase also provides fiat access, liquidity and trust that most chains cannot build independently. [2] Arbitrum: financial infra and custom chains Arbitrum’s strongest method is combining deep DeFi liquidity on Arbitrum One with app-specific Orbit chains. I have followed @RobinhoodCrypto closely, and I think it is the clearest catalyst for this model. Robinhood brings its own users, tokenized stocks, RWA trading and perpetual markets. Arbitrum provides the infra needed to move those products onchain. RH does not directly add its value to Arbitrum One’s TVS because it is a separate Orbit chain. However, it strengthens the wider Arbitrum eco and proves that major financial platforms can launch dedicated chains using its tech. [3] Optimism: infra for a network of chains OP Mainnet alone is not the full Optimism thesis anymore. Optimism’s strongest method is the Superchain: multiple OP Stack chains sharing standards, governance and eventually native interoperability. Base, @unichain, @inkonchain and other OP chains expand the network even when activity does not happen directly on OP Mainnet. The current catalyst is native Superchain interoperability. Upgrade 20 introduces the dispute-game structure required to represent the state of multiple chains. Optimism is also working with @SuccinctLabs toward ZK validity proofs and faster withdrawals. [4] Mantle: treasury-backed institutional liquidity Mantle is taking a more capital-driven approach. Its advantages are its large treasury, Bybit distribution and focus on institutional assets, structured yield and RWAs. Instead of competing for every type of application, Mantle is positioning itself as infra connecting exchange liquidity with onchain capital markets. The current catalysts are tokenized equities, regulated stablecoins such as USDG and deeper integration with Bybit. I think Mantle works best when its treasury and exchange relationships are used to seed sustainable financial products. [5] Lighter: application-specific execution Lighter represents the clearest change in L2 design. It is an app-specific ZK rollup optimized for perpetual trading. Its strongest method is vertical specialization: low latency, zero trading fees and cryptographically verifiable order matching and liquidations. Reaching the top five shows that one high-demand application can secure more value than many general-purpose chains. Overall, I see the L2 market is moving from “build cheaper Ethereum” toward “own distribution or dominate one financial vertical.” Capital is concentrating around the few networks with a clear reason for users and liquidity to stay. But I believe it’s the beginning of a new era for these L2 infra.

Think PoUW might be one of the next crypto infra narratives ppl start waking up to. Because AI compute demand, GPU economics and verifiable computation are finally starting to converge into something that makes sense. The thesis now is that the same GPU can secure a chain while producing computation that someone outside crypto might actually pay for. And block rewards can subsidize part of the compute cost, making decentralized inference cheaper than it otherwise would be. A few projects are approaching this from completely different directions. 1/ @prlnet – uses NoisyGEMM + ~60KB Plonky2 ZK proofs to verify GPU matrix multiplication – independent measurement put network compute around ~24 exa-ops/s, equivalent to ~320K GPU-equivalents and ~112MW of power – @togethercompute launched a 31B-parameter Gemma inference endpoint with a 25%+ advertised discount, effectively using PRL mining rewards to subsidize AI compute – RTX 5090 mining revenue fell from ~$33.80/day around launch to ~$17/day by late May, and has compressed further as difficulty increased – announced a floating-point PoUW design targeting NVIDIA Blackwell with near-zero overhead over optimized vLLM inference – FP8 support is being actively developed across Hopper/Blackwell-class hardware. – partnered with Attestable around privacy-preserving proof-of-inference. So Pearl probably has the largest raw PoUW compute footprint today, but real paid inference is still tiny relative to all that work. 2/ @nockchain – runs dual mining lanes: ZK-PoW using STARK proofs + AI-PoW using Pearl-compatible matrix/INT8 MAC computation – current target is roughly 70% ZK / 30% AI, while the proposed Anthropos upgrade would flip this toward 30% ZK / 70% AI – ~2–2.5 minute blocks, with the dual-puzzle setup running pretty stably since the Logos upgrade – AI Compute Network peaked around ~19.6 ExaMAC/s in early September, roughly ~19.6K H100-equivalents at dense INT8 Longer term, NockVM + NockApps could turn Nock into a marketplace for arbitrary verifiable computation. 3/ @ambient_xyz – testnet is already live and serving real inference, not some late-2026 future launch – reported 134B+ tokens served by June, with single-day peaks above 13B tokens and 100K+ monthly users – OpenRouter integration + OpenAI/Anthropic-compatible API are already live, serving models including GLM and Kimi variants – Proof-of-Logits checks just 1 randomly selected output token + progress markers instead of recomputing the whole inference – claims around ~0.1% verification overhead, compared with materially higher overhead in Pearl's original matrix + ZK approach 4/ @gonka_ai – PoW 2.0 focuses on processing real AI model requests instead of pure hashing – clients submit inference jobs and GPU hosts compete to execute them – reward pool starts around ~323K GNK per epoch, distributed by Proof-of-Compute weight with an exponential decay / roughly 4-year halving schedule – supports model families including DeepSeek, MiniMax and GLM 5/ @dynexcoin – DynexSolve combines mining with useful computational workloads around optimization, simulations, protein folding and other scientific tasks – recent development seems increasingly focused on neuromorphic + quantum compute, including its Zeus architecture and room-temperature diamond-spin qubit work – scientific workloads like optimization, molecular simulation and protein research could eventually become their own compute markets 6/ @quipnetwork – architecture combines Ising-style optimization work for mining with a post-quantum asset-security layer – optimization jobs can theoretically be solved using CPUs, GPUs, ASICs or quantum processors – users submit computational problems with bids and miners compete to produce useful solutions – positioning is basically a distributed "worldwide quantum computer" + post-quantum security network There are also smaller experiments worth watching. @Tensorcash wants every model inference to generate its own PoW certificate. Arthur Hayes' @flop_labs, which appeared in August around the idea of machines paying machines for GPU compute. Overall, for PoUW to become a durable infra narrative, we need to see real fee flows, lower verification costs and some mechanism connecting customer spending back to token demand. 2026 is the first time the technical side looks credible enough to make this worth watching seriously. Now it needs customers. If that part starts showing up, PoUW becomes a new market for compute.

One of the biggest factors people don't talk about much nor understand when it comes to price action - is time. We may have bottomed price wise. But time-wise, could be another week or two before we leg up Or it could start now Daily MACD needs to work it's way through this consolidation here and go green I call 4hr/1d red MACD the torture chamber because no matter how bullish you are, it may just need more time. This is why often you see something pump and retrace, it's simply not ready to move. Not enough hands have changed and gotten into place before the next show.

Privacy in crypto used to mean hiding where money went. Confidential DeFi is becoming about hiding the financial information that should’ve never been public in the first place. It’s what happens when balances, positions, trade size, payroll, treasury flows and RWA ownership can stay encrypted while the capital still lives inside public DeFi. That distinction matters because institutions already showed they want less legibility. And the market is quietly getting less tiny. – Confidential DeFi TVL went from $73.3M in Mar 2025 to $197.6M now, +170% in 18 months – Protocol count went from 18 → 39 Still microscopic obviously. $197.6M is only ~0.21% of $96.2B total DeFi TVL, ~0.06% of $310.4B stablecoins and ~0.06% of the ~$350B already sitting onchain as tokenized RWAs. But I think that tiny denominator is exactly why this gets interesting. The privacy stack is also changing underneath it. – ZK still has the bigger installed base with ~$115.5M across the non-mixer cohort – FHE went from 23.1% of confidential DeFi TVL in May to 41.7% by Sep – ZK fell from 76.9% → 58.3% This is why @zama starts mattering beyond being another privacy coin. FHE lets contracts compute directly on encrypted data. Balances, trade size and lending positions can stay encrypted, but smart contracts can still operate on that state. The speed of adoption is also weird. Zama crossed $100M shielded only 25 days after mainnet launch, vs ~860 days for @monero, 1K+ for @RAILGUN_Project and @Zcash. Some of that early TVL was obviously event-driven, which is why I care more about what happened after. – shielded TVL normalized to $39.6M, then climbed back to ~$81.8M by late Sep – cumulative shielded volume reached $532.3M – total shield + unshield activity passed $982.8M – 10.9K wallets were holding shielded assets So basically almost $1B already moved through the confidential rails. The bigger signal for me is product depth tho. In June there was one institutional proof point, Steakhouse Confidential Prime USDC on @Morpho. It went from zero to $25.5M by month-end and ~$40M within 7 weeks. Then one vault turned into 16, and the curator set now includes Steakhouse, Armitage by Wintermute, Flowdesk, RockawayX and Bitwise. Confidential Vault TVL had already reached ~$58.5M by Sep 23. We’re already seeing the weird edge cases turn into production cases. – @GSR_io executed confidential OTC settlement – @dfnsHQ integrated confidential tokens into wallet infra serving 400+ institutional clients – tGBP had ~$30M supply with 17% shielded That’s a pretty important design choice imo. Confidential DeFi doesn’t need institutions to migrate onto a completely separate private chain. It can increasingly become an extra state layer on top of the DeFi rails they already use. RWA is the monster forward bet. T-REX already has >$32B tokenized, while Apex Group has committed to tokenize $100B through its infrastructure by June 2027 with Zama as the confidentiality layer. Even if only 2% of that $100B pipeline ever becomes shielded, which >10x the entire confidential DeFi category today. This is why measuring confidential finance only against current privacy TVL probably misses the point. The actual TAM is capital that doesn’t want to be publicly legible in the first place. I’m starting to think confidentiality is a missing requirement for the RWA sector.