🐂 Bullpen Brief - 9.03.25 🐂

How Does Price Discovery Actually Work in Crypto?

Crypto pricing operates without consistent frameworks. Protocols switch between being valued on TVL multiples, token velocity, governance premiums, or pure speculation within single trading sessions. The same project can trade at vastly different revenue multiples based on narrative momentum rather than fundamental changes in business performance.

The structural issue is market maker agreements and unlock schedules creating persistent selling pressure. Most tokens launched in 2024 face 2-4% monthly dilution from team/investor unlocks while lacking organic buying demand. Venture funds betting on these structures are seeing 60-80% drawdowns across portfolios, making follow-on fundraising nearly impossible. This results in compounding knockon effects on the funds that are able to raise, natural selection at work.

The data shows clear separation emerging. Revenue-generating protocols trade with predictable multiples: AAVE at 12x P/E based on $290M annual protocol revenue, JTO trading at 35x earnings from MEV capture and staking fees, HYPE maintaining premium valuations tied to $6B daily volume. These have actual cash flows supporting token prices. Meanwhile, infrastructure tokens with $500M+ FDVs but no revenue sharing—regardless of technical merit—face continuous downward pressure as unlocks exceed demand.

Market structure changes driving this:
- Alameda-style market making replaced by systematic funds requiring fundamental justification
- Retail shifting from narrative speculation to yield-bearing assets (staking, revenue sharing)
- Institutional buyers concentrated in 15-20 tokens with clear earnings visibility
- VC deployment requiring proof of sustainable token demand before investment

The central question now being asked for every alt coin: who is the marginal bidder? Projects without clear answers get filtered out through sustained selling pressure. Monad's upcoming launch will be the real test case—despite genuine technical innovation and massive VC backing, the token faces the same fundamental question of sustainable demand beyond speculative interest.

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🐂 Bullpen Brief - 9.08.25 🐂

USDH: Watching stablecoin giants bend the knee to Hyperliquid

Hyperliquid opened the floodgates by announcing that teams could submit proposals to win the USDH ticker through a governance vote, effectively crowning the native stablecoin for the ecosystem. The ensuing ticker battle reveals more about stablecoin issuers than Hyperliquid itself. Circle fumbled their early lead through sheer negligence—collecting 10% of their revenue from Hyperliquid while treating it as an afterthought, slow-walking native issuance until competitors forced their hand. M^0, Paxos, Sky, VanEck, Agora, and others rushed in with proposals ranging from DeFi composability pitches to institutional trust plays. The scramble exposes an uncomfortable truth: most established issuers view Hyperliquid as just another deployment target rather than a unique trading ecosystem requiring specialized infrastructure.

Stablecoins absolutely need distribution to achieve utility, but distribution without product-market fit is worthless. The critical requirements for USDH aren't generic compliance frameworks or multi-chain bridges—they're Hyperliquid-specific optimizations that most proposals barely address. Seamless atomic bridging between HyperEVM and HyperCore, integration with spot quote asset changes, minimal fees that don't cannibalize trading margins, and technical architecture built for sub-second settlement times. These aren't nice-to-haves; they're fundamental to whether USDH actually gets used or becomes another ignored ticker. The established players offer to port their existing infrastructure, essentially asking Hyperliquid to adapt to their systems rather than building for what traders actually need.

Native Markets with Bridge infrastructure represents the most coherent approach precisely because they're building from first principles. Their CoreRouter contract isn't marketing fluff—it's proof they understand the technical requirements of a perpetuals-first exchange. Bridge provides the regulatory backbone through BlackRock and Superstate reserves while Native Markets maintains complete product control. The 50/50 yield split ensures economic alignment rather than rent extraction. Most importantly, they're committed to becoming permanent infrastructure providers, accumulating HYPE and building complementary products rather than treating USDH as a revenue line item. The question isn't whether Circle or Paxos have bigger balance sheets—it's whether they'll prioritize Hyperliquid when their core business demands attention elsewhere. Native Markets doesn't have that optionality problem. Their success depends entirely on getting USDH right, creating the accountability structure that drives actual innovation rather than checkbox compliance. Distribution can be bought or incentivized; technical excellence and ecosystem commitment cannot.

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🐂 Bullpen Brief - 9.09.25 🐂

Prediction Markets Need Liquidity Solutions, Bonding Curves Probably Aren't a Panacea

Prediction markets cleared $270 million in volume yesterday, with Kalshi commanding 80% of the action. That's 38% of total Solana memecoin volume, a meaningful shift toward financializing real-world outcomes over speculative tokens. Yet the infrastructure remains fragmented. Kalshi dominates through regulated market structure, while Polymarket captures narrative-driven volume without monetization. The gap between centralized prediction markets and onchain alternatives highlights a structural problem: liquidity provision for binary outcomes requires different primitives than spot trading.

The bonding curve solution, successful for memecoins, fundamentally misaligns with prediction market mechanics. Bonding curves worked for memecoins because they enabled sniping and convexity with immediate liquidity. Prediction markets invert this: returns vest until resolution, eliminating the fast-money dynamics that made curves profitable. The long-tail markets that would benefit from bootstrapped liquidity often lack the quality or regulatory clarity to graduate to formal venues like Kalshi or Polymarket anyway.

Real liquidity solutions focus on risk management, not token mechanics. Market makers in prediction markets operate more like F&O traders than spot LPs # they're pricing binary outcomes while managing tail risk and inventory exposure. The successful approaches involve resolution-aligned incentives where rewards vest post-resolution, aggregation layers that standardize markets across platforms, and liquidity vaults where passive capital backs sophisticated market making strategies. The sector's growth trajectory is clear, but the infrastructure needs to match the unique risk profile of binary betting rather than copying memecoin playbooks.

Current market breakdown:
- Kalshi: $61M volume, $691k estimated fees
- Polymarket: $37M volume
- Remaining platforms: <$15M combined

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🐂 Bullpen Brief - 9.15.25 🐂

Prediction Markets: Technical Architecture Drives Market Structure

The prediction market sector is undergoing rapid technical evolution as platforms race to solve fundamental infrastructure challenges. While Polymarket's mainstream breakthrough demonstrated the space's potential, the real battle lies in the technical architecture choices that determine scalability, liquidity, and user experience. Current market leaders employ dramatically different approaches, from Kalshi's regulated CLOB model with professional market makers to XO Market's permissionless LS-LMSR design optimizing for capital efficiency.

The resolution mechanism represents the most critical design choice. Oracle-based systems like Polymarket leverage UMA's optimistic oracles for speed and scalability, while hybrid approaches like XO Market deploy AI agents (MODRA) for initial resolution with human jury escalation for disputes. Pure algorithmic feeds work well for price-based markets but struggle with subjective events, forcing platforms to choose between automation and flexibility. The liquidity model creates equally stark trade-offs: CLOBs offer superior capital efficiency for professional traders but require deep initial liquidity, while AMMs ensure constant availability at the cost of price precision. Most successful platforms are converging on hybrid models—Kalshi combines CLOBs with internal market making, while emerging platforms experiment with specialized AMM variants.

Event creation mechanisms reveal the sector's philosophical divide between permissioned curation and permissionless innovation. Regulated platforms like Kalshi maintain strict control for compliance, while decentralized protocols enable user-generated markets with community vetting. The infrastructure layer (on-chain versus off-chain execution) determines everything from transaction costs to regulatory compliance. The next wave of innovation targets hybrid architectures that combine off-chain speed with on-chain settlement, particularly as projects like The Clearing Co work to bridge regulatory frameworks with decentralized infrastructure.

Key technical battlegrounds:
- Resolution speed vs accuracy trade-offs
- Liquidity bootstrapping for new markets
- Regulatory compliance without sacrificing decentralization
- Capital efficiency optimization across market types

source: -x

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🐂 Bullpen Brief - 12.17.25 🐂

All things liquidity: prediction markets and perps

The talk of the town has been liquidity on trading platforms, prediction markets, and onchain credit. What does that even mean? How do you quantify how good liquidity is? Is the quality of liquidity different if the dollars themselves are fungible? Let's discuss.

First, I'd like to define good liquidity as simply receiving an asset or contract as close to market value as quickly as possible. Market makers have now become a buzzword that has stretched the interpretation of the role. I think of market making as solving the timing mismatch between when a buyer wants to buy and a seller wants to sell. For taking the risk of being your counterparty, they earn the spread for which they hopefully profit. The microstructure of market makers is something I have already covered in depth; priority cancellation and speed bumps are a whole different animal.

If an exchange, onchain or centralized, is able to solve the cold start problem, they have solved the most difficult part. Without market makers, large orders are infeasible for retail. Without retail, market makers have no one to profit off of. Both Hyperliquid, Kalshi, and Polymarket have all partially solved the cold start problem. They are doing billions in volume with healthy OI/Volume ratios.

My strongest argument for why onchain exchanges will likely win mostly has to do with path dependence. Offchain exchanges have the lesser burden compared to their onchain counterparts that have to show global solvency, post oracle updates, and liquidation mechanics in the most adversarial environments. Creating a robust system in this environment means building a robust system without the proverbial tech debt. This, combined with far higher operational efficiency and quick asset issuance onchain, creates a breeding ground for highly profitable businesses today.

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🐂 Bullpen Brief - 9.20.25 🐂

The Boring Revolution: Why Basic DeFi Is Inevitable

Drawing from Vitalik's recent analysis, low-risk DeFi has quietly become crypto's sustainable revenue engine. The argument centers on something we've been tracking: stablecoins and basic lending protocols now generate meaningful economic activity without the recursive ponzi mechanics that defined early DeFi. USDC deposits on Aave earning 4-5% represent genuine value creation, not yield farming theatrics. The data supports this with over $200 billion in stablecoin supply and $5 trillion in annual volume proving product-market fit for basic financial services.

The emerging economy thesis deserves particular attention. Traditional banking infrastructure struggles in regions with currency instability, capital controls, and fragmented monetary systems. Nigeria's eNaira adoption remains negligible while crypto usage explodes precisely because decentralized rails sidestep these structural problems. For users in Argentina, Turkey, or Lebanon, the "tail risks" of DeFi protocols are demonstrably lower than their domestic banking systems. The permissionless nature isn't ideological but practical necessity when traditional correspondent banking relationships break down.

This creates the foundation for crypto's next evolution: becoming the default infrastructure for cross-border capital flows and currency hedging. The convergence of mature lending protocols, synthetic asset platforms, and regulatory clarity (see: GENIUS Act) positions crypto as the backbone for global financial services. Emerging markets don't need to build correspondent banking networks or currency swap facilities but can plug directly into Ethereum's financial infrastructure. The network effects compound when every additional economy increases liquidity and reduces costs for existing participants. We're witnessing the shift from speculation to utility as crypto becomes the global financial operating system rather than just a trading venue.

Key developments accelerating this transition:
- Regulatory clarity through payment stablecoin frameworks
- Mature lending protocols with decreasing hack frequency
- Cross-border payment cost advantages over SWIFT rails
- Growing institutional adoption in emerging markets

soure: vitalik

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🐂 Bullpen Brief - 12.22.25 🐂

Aster, CZ's $13B Pet Project

CZ's Aster launch crystallizes crypto's core value propositions: asset issuance substrate meets unparalleled capital velocity. The metrics tell the story: six entities controlling 96% of token supply, $500k daily BTC spot volume, yet $13B FDV. The centralization and HL vs. Aster discourse misses the point entirely. Aster isn't competing with Hyperliquid on execution or decentralization; it's functionally a token launch with perp functionality (this is even questionable), and this distinction matters. The investment thesis remains straightforward: supply restriction by trusted parties, infinite war chest for incentives, and aligned motivations to capture flow from established players. As Hyperliquid grows, its derivative versions scale proportionally.

The wealth effect creates cascading ecosystem incentives that reveal crypto's underlying dynamics. Each incremental layer away from the original platform becomes increasingly extractive, most evident in the perp-DEX space and launchpad meta. Initial wealth generation funds secondary products: farms, ancillary platforms, derivative protocols. But each iteration focuses more on "playing the game" than solving fundamental problems. While this seems incongruous with decentralized finance narratives, it's actually durable given crypto's high beta on speculative behavior. The dissonance between verifiable infrastructure and financial ouroboros isn't contradiction. It's feature, not bug.

The nominal incremental opex to start a derivative product naturally leads to many derivative projects that are incrementally better. This forces the slope of commoditization of the tech (interop, market structure, pricing) to be extremely high while it becomes a war of attrition of user acquisition and costs. When building becomes trivial, differentiation collapses to marketing spend and token incentives. We're witnessing the natural evolution from infrastructure competition to attention capture, where technical moats erode faster than they can be built.

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🐂 Bullpen Brief - 9.28.25 🐂

Low-Risk DeFi Won't Save Ethereum, But It's Still the Foundation

I wanted to revisit Vitalik's latest post argues that low-risk DeFi (payments, savings, and lending) can be Ethereum's "Google Search," a revenue engine that's both profitable and culturally aligned. The logic is clean: mature protocols like Aave have proven resilient, tail risks have compressed, and global demand for permissionless access to savings and stable assets is real. Stablecoin supply hits $161B, DeFi TVL sits at $95B, and the regulatory environment is finally clarifying post-GENIUS Act. But the execution thesis has structural problems that undermine the vision.

The L1 scaling issue cuts deep. Serving underserved populations (Vitalik's stated goal) requires transaction costs in cents, not dollars. Ethereum L1 can't deliver that economics without sacrificing its security model. The working playbook is inverted: Solana generates massive revenue from high-fee MEV auctions and uses that surplus to subsidize low-cost payment rails. Loss-leader payments work when hotspot state access pays for network security. Ethereum's approach (isolating borrow/lend on L1 while trading and payments fragment across L2s) creates worse UX and breaks composability, the core advantage DeFi has over TradFi rails. Users won't tolerate bridging between execution environments as crypto UX continues improving.

The revenue math doesn't close either. Ethereum is tracking $36M in September fees despite ATH TVL and stablecoin supply. Low-risk DeFi generates thin spreads; repo markets and yield aggregation are low-margin businesses by design. If ETH's $500B valuation depends on protocol revenue, lending alone won't justify it, especially as it competes with purpose-built payment chains from Stripe, Tether, and Circle. The real revenue driver isn't passive yield. It's the ability to shift risk quickly through trading new and incumbent assets. Perps, derivatives, and liquid markets for emerging assets generate higher fees per transaction and drive more economic activity to the chain itself than static collateralized lending ever will.

Low-risk DeFi still matters. It's the stable foundation for consumer finance with cheap access to yield and onchain repo markets. But undercollateralized lending won't work onchain despite ZK-TLS hype; adverse selection around recourse is too pervasive. The path forward requires layering high-velocity trading and risk management on top of stable primitives, not hoping that culturally congruent lending can scale into a revenue engine. Ethereum needs localized fee markets that subsidize experimentation while capturing value from sophisticated financial activity, not a middle-ground compromise that satisfies neither revenue requirements nor its decentralization ethos.

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🐂 Bullpen Brief - 10.11.25 🐂

Yesterday's Liquidation Cascade: When the Vault Becomes the Liquidated

Hyperliquid processed one of the largest liquidation events in crypto history yesterday. Billions in positions unwound across 20 minutes as altcoins dropped 50%+ in tandem. The protocol maintained 100% uptime with zero bad debt, marking its first cross-margin ADL event in over two years of operation. What makes this significant isn't just the scale, it's that HLP's own liquidator child vaults became undercollateralized after backstop liquidating user positions, triggering ADL where HLP itself was the largest triggered address by more than an order of magnitude. The vault designed to absorb liquidations got liquidated.

The mechanics reveal how extreme volatility tests perps infrastructure. When positions don't meet maintenance margin requirements during sharp moves, they're taken over by the system: first attempting market liquidations through the orderbook, then backstop liquidations via HLP, and finally ADL as the mechanism of last resort. HLP's philosophy of being a non-toxic, last-resort liquidator meant it absorbed massive positions without cherry-picking profitable ones. The result: HLP took heavy losses while ADL providers on the other side realized hundreds of millions in additional profit relative to prices shortly before and after the dislocation. Some individual ADL providing trades were unfavorable, particularly when only components of long/short portfolios closed, but aggregate outcomes favored those forced out of winning positions at temporarily extreme prices.

The transparency differential matters here. Every order, trade, and liquidation on Hyperliquid is verifiably onchain, while many venues significantly under-report liquidation data. This makes direct comparisons difficult, but the principle holds: exchanges with opaque liquidation engines could have extracted hundreds of millions in revenue by taking more risk with user funds. Hyperliquid's choice, treating HLP identically to other users under strict margin requirements, prioritizes solvency over revenue extraction. The tradeoff: ADL events feel punitive to winning traders, but they're the mathematical endpoint when one side runs out of counterparties. No exchange can guarantee infinite losers on the other side # that's the edge of the simulation, and yesterday traders hit it hard.

Key mechanics:
- Liquidation waterfall: orderbook → HLP backstop → ADL (last resort)
- ADL selection criteria: profitability + leverage + position size
- HLP operates as isolated child vaults to manage risk exposure
- Zero liquidation fees, HLP provides public good infrastructure

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🐂 Bullpen Brief - 10.20.25 🐂

Crypto's Growing Pains: Why Everyone Can Trade Everything

This post was inspired by Monk's recent piece on rejecting crypto pessimism. While the doomer sentiment has valid roots (broken tokenomics, proliferating grifts, fewer "investable" assets), the pendulum has swung too far. The structural issue isn't innovation failure; it's that crypto has democratized access to what were historically professional-only investments.

Traditional markets filtered assets through institutional gatekeepers. Companies raised private capital from VCs who conducted due diligence, then maybe went public after proving themselves, giving retail access only to the survivors. Even then, IPOs represented a tiny fraction of all startups. In crypto, every project launches with a tradeable token from day one. We've essentially given everyone VC-level exposure to venture failure rates without the corresponding expertise or risk management. Pump.fun takes this to its logical extreme: instant token creation with zero product requirement. Of course 99% of tokens trend toward zero when anyone can launch anything and everyone can trade everything.

The high FDV/low float meta compounds this problem. Traditional overvalued stocks face natural selling pressure from shorts and institutional rebalancing. Crypto's overvalued tokens? They're structurally difficult to correct. Low float limits available supply while the absence of borrowing markets prevents efficient shorting. These zombie valuations persist far longer than fundamentals justify, creating a graveyard of tokens that refuse to die. But here's the critical insight: dispersion between quality and garbage is finally increasing. Compare the market's treatment of leading stablecoin issuers versus their competitors#the price action and scaling trajectories diverge dramatically, resembling actual business competition. Put more bluntly, crypto exhibits the most severe power law dynamics of any asset class. Porter's Five Forces apply to crypto now, with some adjustments: your implied FDV becomes your war chest for point subsidies, token utility velocity matters more than traditional moats, and market makers function as your distribution network.

The maturation signs are unmistakable:
- Stablecoins processing $5+ trillion annually with sustained growth through bear markets
- Hyperliquid matching Robinhood's derivatives volume while returning revenue to tokenholders
- Protocols with genuine cash flows trading at premiums while governance tokens without revenue sink
- Clear product-market fit emerging in specific verticals (perps, stablecoins, market making vaults)

Yes, making outsized returns has become harder as the easy "buy anything in a bull market" playbook dies. That's not pessimism; it's professionalization. Crypto's superpower remains unchanged: frictionless capital formation and asset issuance at the speed of blocks, not business days. The infrastructure that enables 99% garbage also enables the 1% building generational protocols. We've given anyone with internet access an alternative financial system that's more free, open, and frankly more fun than what citizenship forces upon them. The industry has delivered remarkable primitives in just a decade of smart contracts, from DeFi yields to NFT communities to prediction markets. Now we're watching quality separate from noise as market forces do their work. Choose optimism, but choose it selectively.

source: -monk

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🐂 Bullpen Brief - 10.28.25 🐂

Morpho V2: Asset Management Gets Granular

Stablecoins solved the checking account problem onchain: $200B+ in supply proves the product-market fit. Morpho V2 is building the savings account infrastructure. The upgrade introduces institutional-grade asset management primitives that make DeFi lending markets significantly more flexible: borrowing against diversified portfolios rather than single collateral types, curators selecting custom collateral baskets they're willing to lend against, fixed-rate lending options, and compliance frameworks that actually integrate with institutional workflows. The key insight? Vaults become programmable buckets that allocate across any strategy within the same atomic environment, eliminating the intermediaries and integration costs that plague TradFi structured products.

The technical architecture matters here. Morpho introduced curation as a business model 18 months ago. Today, 30+ independent curators operate on the platform, generating tens of millions annually. V2 expands beyond single loan types to enable allocation across any Morpho protocol, with segregation of duties, timelocks, in-kind redemptions, accredited investor gates, and absolute/relative risk exposure limits. This isn't just DeFi tooling. Banks and institutions recognize these vaults as foundational infrastructure for onchain asset management at scale. The composability advantage is real: every integration costs significantly less than in traditional finance, liquidity flows freely between strategies, and users access institutional-grade products with just a wallet and stablecoins.

The macro view: DeFi hangs on by a thread from Ethena emissions and incentive programs, but the underlying framework is becoming robust enough for mainstream adoption. Vaults will proliferate through consumer finance apps and every fintech looking to offer yield products. Tokenized RWAs bridge TradFi and DeFi, but they're transition tools. They improve distribution without improving the actual financial product. To build fundamentally better offerings, issuers need everything in the same blockchain environment where composability becomes native rather than bolted on. The path from Money 2.0 to Asset Management 2.0 runs through infrastructure like Morpho V2: programmable, noncustodial, and designed for institutional scale. While most of the market chases narrative, the serious builders are shipping infrastructure that actually works.

Key capabilities unlocked:
- Portfolio-based borrowing vs single collateral constraints
- Curator-defined collateral selection and risk parameters
- Fixed-rate lending markets alongside variable rates
- Institutional compliance controls without sacrificing noncustodial guarantees

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🐂 Bullpen Brief - 11.03.25 🐂

Balancer, Stream, and the Fragility of Yield Infrastructure

Balancer v2 fell this week. Roughly $70-117M drained across chains through a subtle authorization bug in the Vault's manageUserBalance path. The forensics are still settling, but the shape is clear: either the function compared msg.sender to an attacker-chosen field, or state mutations during withdrawal proxy setup left the Vault permissive when it shouldn't have been. The result? Crafted sequences could withdraw balances the caller didn't own. What makes this particularly striking: Balancer launched in May 2021, carries audits from Certora, OpenZeppelin, and Trail of Bits, and has secured billions since then. Maturity bought significant risk reduction, but not immunity.

The attack contract itself shows signs of AI assistance: console.log statements left in production code, a rookie mistake that ChatGPT would make but experienced exploit devs wouldn't. The broader 2025 pattern remains consistent: CertiK's H1 data shows over $2.1B in losses, with wallet compromises and social engineering dominating. The Bybit heist ($1.4B via Safe{Wallet} dev compromise into AWS into malicious frontend) and SwissBorg ($41M via third-party API) prove that supply chain and cloud security failures still outpace pure smart contract bugs. The lesson: centralized accounting hubs concentrate failure modes. Better gas economics and UX come with higher-value attack surfaces.

Stream Finance is now the industry's latest stress test. Withdrawals halted, team silent, and whispers of 10-30% haircuts circulating as protocols and lenders work through what appears to be a heavily looped portfolio that's proving difficult to unwind. Elixir's statement is instructive: they claim full $1 redemption rights on their lending position to Stream and are unwinding directly with the team. The core issue isn't novel. It's the same problem that's plagued yield products since inception: translucent visibility into reserves and illiquid/off-chain assets priced in real time don't make pristine collateral. When utilization spikes and everyone rushes to unwind simultaneously, reserves that showed $100 can quickly look closer to $50 as interest rates spike and looped positions become unprofitable.

The architecture of products like Stream and Midas is compelling until it isn't. Sophisticated strategies returning yields most onchain participants couldn't achieve independently, but the translucency of reserves and the liquidity characteristics of underlying positions make these dubious candidates for leverage, especially at high LTVs on lending markets like Morpho. The first lesson here is tactical: at the first sign of trouble, withdraw. The second is structural: hardcoding prices for anything beyond explicit 1:1 USD/treasury-backed stablecoins without proof of reserves is dangerous. Even with proof of reserves, the problem compounds. Unwinding cascades mean reserve values are path-dependent, not static. DeFi has gotten more robust over time. The percentage of TVL hacked has declined steeply. But new risk vectors keep emerging: hardcoded pricing without adequate reserves transparency, AI-assisted exploits leaving digital fingerprints, and the persistent gap between web2 operational security and web3 ambitions.

source: debank

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🐂 Bullpen Brief - 11.14.25 🐂

Ethena's Distribution vs. Capital Structure Reality

Multicoin just published their investment thesis on ENA—bullish on Guy Young's execution, distribution wins, and Ethena's resilience through multiple black swan events. The argument centers on synthetic dollars capturing yield-bearing stablecoin market share as perpification and tokenization expand addressable markets. Fair points. Guy has built exceptional distribution: USTB diversification, card integrations, cross-chain collateral proliferation. The team navigated Bybit's $1.4B hack and October's $20B liquidation cascade without losing user funds. That matters.

But distribution doesn't fix broken capital structure. ENA sits at the bottom, equity and sUSDe holders get paid first. The protocol subsidizes USDe yields through ENA dilution, creating a scenario where Ethena generates cash flow while the token bleeds value. This isn't theoretical: the project has been a net money loser despite operational revenue. Similar to buying UNI tokens when you should have bought Uniswap equity. The insurance fund remains undersized relative to circulating supply, and significant TVL comes from PT loops rather than organic demand. When a large portion of your "growth" is leveraged self-referential positions, sustainability becomes questionable.

The 10/10 depeg revealed structural contradictions. USDe traded at $0.65 on Binance while the onchain oracle stayed hardcoded at 1:1, preventing liquidations that should have occurred in a trustless system. Correct for limiting contagion, maybe. But it defeats the core premise of decentralized finance. The DAT issuance to early backers compounds this: mNAVs marked to market with no decay function while locked ENA from VCs and foundation creates asymmetric exposure. The reflexive loop between ENA and sUSDe means token price directly impacts protocol minting capacity. When funding rates compress or macro volatility drops, the entire mechanism contracts. Your thesis can be directionally correct on synthetic dollars, perpification, and tokenization, and you still lose money if you're wrong on capital structure positioning. The distribution narrative is compelling. The capital structure reality is not.

source: -mcc

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🐂 Bullpen Brief - 11.16.25 🐂

Tokens as Machine-Native Money: Why Crypto Infrastructure Wins the Agent Economy

I read Ribbit's recent token letter and caught their TBPN interview, which crystallized something increasingly obvious about the next decade of crypto. The thesis is straightforward: if AI agents are about to orchestrate trillions in economic activity, they need programmable money and verifiable credentials. Stablecoins and tokenized assets aren't speculative bets on decentralization ideology anymore. They're becoming the obvious rails for machine-to-machine commerce. The data backs this up. Stablecoins already settle over $2 trillion monthly, with 90% of volume coming from bots doing arbitrage, liquidity provision, and automated market making. Ribbit's argument is that this "bot volume" isn't a bug but rather proof of concept. When you make dollars programmable and eliminate settlement friction, software uses them relentlessly. The question isn't whether agents will transact in tokens but rather which token standards and which networks capture that flow.

The infrastructure plays are clear. Asset tokenization platforms that handle compliance, custody, and metadata become essential middleware. Oracle networks like Chainlink and Pyth, which already secure nearly $50 billion across 700 protocols, provide the verifiable data feeds agents need. Payment processors building agent-first interfaces (Stripe's Bridge acquisition for $1.1 billion signals where this goes) become the new Visa for autonomous systems. The DeFi primitives that survived 2022 (Morpho, Uniswap, Jito) suddenly have product-market fit as agent liquidity venues.

But here's the uncomfortable reality: crypto is fighting an existential brain drain to AI. The best technical talent is flowing toward foundation model research, agentic platforms, and enterprise AI tooling. When you can raise at a $100 billion valuation building LLMs or $5 billion building coding agents, why grind on MEV mitigation or ZK circuits? This isn't about crypto's technical merits but rather the opportunity cost of working on blockchain infrastructure when AI offers faster cycles, clearer commercial traction, and massive incumbent interest.

The projects that will matter are the ones building boring, reliable rails for agents to transact, not the ones trying to bolt AI onto every protocol. Think payment networks designed for microsecond settlement, identity systems that work across platforms, and asset tokenization platforms that make everything from compute credits to creator IP tradeable. The brain drain won't fix itself, but crypto's best path forward is embracing its role as financial infrastructure for an AI-driven economy rather than competing for the same talent and narrative oxygen.

source: ribbit

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🐂 Bullpen Brief - 11.17.25 🐂

Aave App: The Efficient Frontier of Yield

Aave Labs launched their savings app with up to 9% APY and $1 million in balance protection. The product integrates with 12,000+ banks for instant deposits and supports direct stablecoin transfers. What matters here isn't the consumer packaging # it's the infrastructure play for fungible onchain liquidity. Capital velocity onchain requires higher cost of capital. Traditional savings accounts pay 0.4% APY on average, high-yield options top out at 3-4% with monthly compounding. Aave App compounds every second with instant withdrawals, no lock-ups, no penalties.

The mechanics are straightforward. Aave already processes $70 billion in active deposits across 2.5 million users with $3 trillion in lifetime volume. The Auto Saver feature (recurring deposits earning an extra 0.5% APY) creates predictable capital flows that reduce utilization rate volatility. The dual-coverage model stacks Aave's standard Umbrella protection with App-specific coverage from Aave Labs via regulated subsidiary. Users get $1 million in protection versus $250K FDIC standard while earning multiples of traditional yield.

The real angle is composability. A mobile app that abstracts blockchain complexity while maintaining instant liquidity creates bidirectional capital flow between TradFi and DeFi. The app accepts both bank transfers and stablecoin deposits, building infrastructure for programmatic capital allocation at block speed rather than settlement cycles. If non-crypto users move serious capital here # and the math suggests they should # this meaningfully impacts DeFi liquidity depth. The efficient frontier of yield in crypto has always been constrained by UX friction and perceived risk. Aave App attacks both directly.

source: aave

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🐂 Bullpen Brief - 11.30.25 🐂

Quantum versus BTC

BTC used to be the least interesting thing about crypto for me; a public, mostly non-programmable version of currency that you couldn't do much on top of. I've done a 180 over the past year because of what it represents: the first version of private ownership that is becoming increasingly important. After reading both of Nic Carter's articles, it feels like quantum computing and its potential to crack the most important private/public key cryptographies have largely crystallized. Before becoming too glum, the odds that a non-governmental, small-time malicious player is the one to reach Cryptographically Relevant Quantum Computing (CRQC) are quite low by my estimation. However, large private and public institutions have accelerated their precision on the number of qubits, dollars in funding to startups, and dollars up for grabs if ECC is cracked. This doesn't only have implications for our small industry alone. It would break the internet as we know it: VPNs, all cloud providers, SSH, email, HTTPS, etc. would all no longer be feasible.

Before we begin the scenario plan for Q-day, we must define some basics of quantum computing and the mechanical flow of a BTC hash and its respective addresses. The main principle of most private/public key cryptography is the idea that the output is irreversible to garner an input. Nic uses the example of a deck of cards starting at point X and a fully shuffled deck at point Y. It is impossible without trying every possible combination to determine the number of times the deck was shuffled, Z. Similarly, there is no exploitable structure in the actual hashing function, therefore it remains infeasible to break without brute force, which stays infeasible even in a world of CRQC.

However, the flow of an address goes something like the following: Private Key → Public Key → Address. The double hash function is the process to go from public key to address. This is the component that is quantum-resistant. But if a malicious user with CRQC capabilities had access to your public key (let's say from sending BTC to a brokerage) they could reverse engineer your private key and gain spending access to your UTXOs. This is a real threat for public keys that have been revealed, e.g., Binance's BTC cold-storage wallets holding ~250K BTC. Any wallet that has spent or sent BTC would be at quantum risk, including thousands of Satoshi's wallets, which represent ~9% of all BTC (image above).

Without diving too deep into the nuances of quantum computing that I cannot claim to fully understand, there are two reductive levers being pulled to improve quantum capabilities: the actual compute ability (the physical and logical number of qubits), and algorithmic improvements (error rates and coherence length). Progress on both fronts is accelerating, with the number of logical and physical qubits only being two or three orders of magnitude away from what's needed. The consensus seems to be that it's less a question of *if* quantum computing can reach this point, and more a question of *when* extremely difficult engineering problems are solved. 2025 was a significant year for breakthroughs in the industry, and while precise timelines remain uncertain, the trajectory is clear enough to warrant serious attention from anyone holding meaningful positions in Bitcoin.

some cool startups while researching
- SandboxAQ
- PQShield
- QuintessenceLabs
- Qrypt
- ID Quantique
- Quantum Xchange
- Post-Quantum

source: nic carter p1, p2

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🐂 Bullpen Brief - 12.2.25 🐂

Hyperliquid: The Numbers Behind the Noise

October 10th marked a step-function down for the entire perps industry. The largest liquidation event in crypto history wiped out an estimated $19-30 billion across centralized and decentralized venues. OI and volume contracted market-wide, and every platform felt it. The narrative emerging from some corners is that Hyperliquid is losing ground to competitors like Aster and Lighter, who briefly flipped HL on daily volume charts. This framing misses the structural picture entirely.

Hyperliquid is still run-rating at $3.15M in daily fees (30d EMA), annualizing to roughly $1.15B in revenue. Virtually all of this flows to HYPE buybacks via the Assistance Fund. The margin profile here is unmatched: an 11-person team generating over $100M per employee with near-zero cost structure. More importantly, while volume metrics can be gamed, open interest tells the real story. HL still holds ~63% of total OI across major perp DEXs, indicating where traders actually park capital rather than where they farm points. The volume/OI ratio reinforces: Hyperliquid sits at 1.57 (organic), Aster at 4.74, Lighter at 8.19.

Three observations on the competitive landscape. 1). excellent products grow the pie. CFDs on FX didn't cannibalize futures; they expanded the addressable market. New perp DEXs may do the same for onchain derivatives. 2). competitors are implicitly spending billions on CAC. Aster airdropped 704M tokens and enjoys Binance's distribution pipeline. Lighter offers zero maker/taker fees, subsidizing every trade. When incentives stop, so does volume. 3). long-term this is a question of team competency and shipping velocity. Jeff and the Hyperliquid team have shown no signs of complacency, continuously rolling out HIP-3, permissionless perps, Builder Codes, and BLP.

The bigger thesis isn't about perps market share. Jeff has articulated a vision of Hyperliquid as the "AWS of liquidity," an infrastructure layer for all financial operations. The form factor matters: Robinhood won consumer equity trading not by having the best execution but by owning the interface. Hyperliquid wants to be the settlement layer that frontends tap into, the hub where liquidity naturally aggregates. Meanwhile, the demand for speculation is only accelerating. 0DTE options now represent 50-60% of SPX volume. Short-dated contracts (≤5 days) account for 56% of retail options trading, up from 35% in 2019. The human appetite for leveraged directional bets isn't going away. The question is which infrastructure captures it.

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🐂 Bullpen Brief - 12.14.25 🐂

Breakpoint 2025: Solana's shipping season

Breakpoint conferences tend to generate more narrative than substance. This year had more to show. Firedancer, Jump's ground-up validator client rewrite, is now live on mainnet and producing full blocks since October. Firedancer nodes are currently the fastest voters on the network, and snapshot loading dropped from 20-40 minutes to under one minute. Ellipsis Labs shipped Phoenix Perpetuals, an on-chain order book targeting 3-5bps execution versus the ~15bps standard. Harmonic, a block building marketplace being tested on mainnet, hit 10,000 oracle updates per block. That's 25x the current mainnet average. The caveat: Firedancer still runs on limited stake, Phoenix Perpetuals is in closed beta, and Harmonic's production performance remains unproven at scale.

The product announcements were numerous. Kalshi, Phantom, and DFlow are partnering to bring prediction markets onchain with composability into Solana's DeFi stack. Doma Protocol announced plans to tokenize 46 million domain names as RWAs. MetaDAO introduced ownership coins, a structure letting teams convert early users into actual owners with legal backing. These solve real problems around distribution and capital formation, though each faces distinct execution risk. Prediction market composability sounds compelling until you stress test the liquidation mechanics. Domain tokenization requires sustained demand beyond the initial novelty. Ownership coins need legal frameworks that hold up across jurisdictions.

Infrastructure updates were tangible but forward-looking. Anza reported two years uninterrupted uptime and 200 billion transactions processed. Multiple Concurrent Proposers (MCP) finally has a concrete design targeting protocol-level censorship resistance by eliminating single-builder monopolies. Alpenlow consensus aims for sub-150ms finality. Rent reduction is on the roadmap with promises of "dropping a zero, maybe two." The timeline for these upgrades remains unspecified. The TradFi presence was notable. Baillie Gifford, a 120-year-old asset manager with $300B AUM known for early positions in Tesla and SpaceX, sent a portfolio manager to declare "the age of proof of concepts is over." ADGM's regulatory framework in Abu Dhabi offers clarity on custody, staking, and token issuance that most jurisdictions lack.

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🐂 Bullpen Brief - 12.19.25 🐂

Hyperliquid's Portfolio Margin: Why should I care?

Hyperliquid Labs recently announced their upcoming implementation of portfolio margining (PM). In its end state, PM allows a user to use their spot/perps accounts as a unified margin account, i.e., if you hold a lot of HYPE, you can borrow cash against that HYPE to use on another perp. To understand why PM actually matters, we need to understand why it's a marquee feature in TradFi for institutional flows. Reg-T was the first introduction for retail and institutions to lever trades, allowing static 2x leverage. You can now long a single name equity or index more capital efficiently, but it doesn't solve the more salient issue: risk-netting and correlation. TIMS (options) and SPAN (futures) are the TradFi analogs that solve this, tracking volatility and correlation across your positions, stress-testing scenarios to calculate max loss, i.e., your required maintenance margin. Instead of a market maker forced to use $500k to quote $1M, if they're perfectly hedged, they can potentially use 5% margin or $50k, vastly improving return on capital.

Ok, now we have an idea of why portfolio margining is huge: 80% of flows across equities are institutional, the vast majority using some version of netting and borrowing via prime brokers. Hyperliquid is introducing a similar, albeit far more restrictive (for now), version internally. They're functionally verticalizing a prime broker inside the exchange, allowing users to borrow only USDC against their HYPE to trade inside a unified margin account, paying out interest based on utilization.

Ok, now we understand the implications. Who cares? I do! PM in its end state allows a step-function improvement in capital efficiency with smart contracts housing the complex logic instead of traditional prime brokers. Ideally, onchain portfolio margining makes an Archegos situation infeasible: too difficult to hide the quality of collateral, degree of leverage, and potential cascade. Why is the rollout so slow? PM could single-handedly bring down Hyperliquid. Without externalizing risk to traditional prime brokers, the exchange ingests incremental units of risk. Imagine: HYPE has an organic sharp downtick, margining requirements rise as vol increases and correlations break, forcing partial liquidations. Everyone is equally unaware of how leveraged the system was on HYPE across exchanges, forcing a vicious cycle.

The HL team has interesting ideas on how PM could integrate with the EVM; a protocol could ask for deposits, issue that cash into a portfolio margin account, and mint an ERC receipt token for your share of the interest. PM is a step in the right direction, with a healthy dose of risk for the protocol itself.

sources: Hyperliquid Docs, CME SPAN Methodology, OCC TIMS

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🐂 Bullpen Brief - 12.29.25 🐂

PFOF Onchain: Is It Endgame?

Ostensibly, payment for orderflow (PFOF) improves prices for retail routed by traditional brokers. Your orders through Robinhood first check the national best bid offer (NBBO), i.e., the tightest spreads on public exchanges. If one of the wholesalers paying for access to Robinhood's orderflow is willing to give a tighter spread, that flow is theirs for the taking. This is better for everyone: market makers are more confident they're not trading against informed flow, and users are excited they got a spread tighter than a hedge fund. Right?

I would argue that while the traditional PFOF model has some benefits, it's not as sweet as one may think. A few subtle points create outsized impacts. A recent paper titled "What is the Value of Retail Order Flow" shows that the average Sharpe ratio trading against retail in German equity markets is ~18. These are statistically impossible numbers given an equities stochastic random walk and multiples higher than traditional market makers on public exchanges trading against other sharks. If we extrapolate, this creates a pattern: all retail goes through PFOF, wholesale market makers tighten spreads because they're confident, the lion's share of trading on public exchanges is now informed flow, this results in widened spreads, and the bar becomes lower for retail brokerages and wholesalers to beat NBBO. There are a long tail of other issues with PFOF that have been highlighted, but the space seems to have abided by the mantra "if it's not super broken, don't fix it (maybe)".

Why does this matter for trading onchain? #MarketStructureShift Proprietary AMMs and market makers providing liquidity to aggregators are now in fierce competition. The general consensus seems to be that market structure will head towards PFOF and zero-commission trading like Robinhood. Benedict Brady and Eugene Chen have both been the topical experts on market microstructure on Solana and have highlighted some clear issues before we reach equilibrium. It's pretty cool that onchain price impact (slippage) is now rivaling top centralized exchanges. But NBBO doesn't exist as we know it for BTC/SOL/ETH, let alone the long-tail of assets. How do you know how good of a price you're giving? One thing Benedict has pointed out is that we know for sure we are currently giving horrible prices to price-insensitive, execution-sensitive users on Axiom.

While I hope to have a more informed take on how to improve market structure, for now it seems like the common denominator must have two things:

- A legible and standardized fee market
- Some way for value to flow back to the user via zero-fee trading or rebates

Sources:
- "What is the Value of Retail Order Flow"
- Benedict Brady (@bqbrady) on Solana market microstructure
- Eugene Chen on Solana execution quality

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