By Cosmo Jiang, Portfolio Manager, Liquid Strategies, and Erik Lowe, Head of Content


We are often asked by investors, “How are various tokens correlated in the bull cycle?”


To provide some perspective on this, we’ll analyze the two most-recent cycles when the investible universe of tokens beyond bitcoin had meaningful market share.


We’ve observed that bull cycles have two pronounced phases.  Phase 1 is the early stage of the rally when bitcoin has tended to outperform the rest of the market.  Phase 2 is the later stage when altcoins have tended to outperform.


In our view, bitcoin’s outperformance in phase 1 may be a byproduct of a few reasons.  First, it is the most broadly offered and liquid digital asset in the market.  In 2023, Bitcoin’s average daily trading volume was $18 billion.  Ethereum traded $8 billion daily by comparison.  Second, first-time investors often buy bitcoin first before seeking out exposure to other tokens.  It has a 15-year track record and a brand that many would consider to be synonymous with the industry itself.


While some investors’ journeys end at Bitcoin, many will go down the crypto rabbit hole.  The investible universe of tokens beyond bitcoin is vast and bull markets seem to accelerate the expansion of that universe as more entrepreneurs and developers enter the space.  Phase 2 is when investors begin seeking out higher growth tokens underpinning different use cases, often driven by new innovations i.e., ICOs in 2017-18, DeFi and NFTs in 2020-21.  This phase may coincide with what Sir John Templeton would describe as the “optimistic” stage of bull markets.


Here is a visual of the two phases highlighted in gold shading.  You’ll notice how altcoin market share declines in phase 1 of cycles while total market capitalization inches upward, indicative of bitcoin’s outperformance.  Around 60-70% through the bull cycle, altcoin market share spikes up – fast.



Below are the actual returns of bitcoin and altcoins in terms of market capitalization growth, as well as how much each contributed to the overall growth of the cryptocurrency market.



In these cycles, bitcoin consistently outperformed altcoins in phase 1 of the upswing.  In phase 2, altcoins substantially outperformed bitcoin.  What’s interesting is that the magnitude of outperformance is so large that altcoins have outperformed bitcoin across the full length of both cycles.


While one of the highest sources of alpha has historically come from a perfectly timed rotation from bitcoin into altcoins as phase 2 commences, that relationship won’t necessarily always hold true nor is timing that rotation perfectly a reality for any trader.


Perhaps the most feasible way to generate alpha in the space is by maintaining consistent exposure, investing in altcoins that have fundamental reasons to appreciate multiples more than bitcoin in total.


Our thesis is that altcoins underlying protocols that have product market fit and are generating real revenues with strong unit economics will perform best in the coming cycle, just as one would expect across other asset classes like equities.  Just as not all equities are created equal, not all tokens are created equal.  Over the long term, token selection will be paramount because outperformance will be on a case-by-case basis and not necessarily in a certain sector or based on fickle, short-lived speculative narratives.


So far in this cycle, bitcoin is up 2.8x and altcoins are up 1.7x.



By Paul Veradittakit, Managing Partner


Since Q1 2022, blockchain funding for private deals has been decelerating.  Quarter over quarter funding and deal count have decreased according to The Block data.



The average deal size has come off significantly since the peak in early 2022.



The caveat is that the data is based on press funding round announcements, and in my experience, tends to be a quarter or two lagged.


Based on what we’re observing at Pantera, we believe the trough in funding and deal activity was likely last summer.  Recently, we’ve been seeing a major pickup in deal activity driven by entrepreneurs that came in during the previous bull market – those whose businesses have had time to mature, potentially find product market fit, or have been executing on the right strategies – and are now coming back and raising at reasonable valuations.


It may have took a bit longer than most would have expected because during the bull market, a lot of VCs like ourselves were advising companies to raise an extra year of runway.  So, instead of raising for two years of runway, they raised for three years, and now we’re beginning to see them come back to market.


We believe this is a great time to be investing because deal activity has picked up – I expect it will continue this year should the public markets continue to rally.



By Paul Veradittakit, Managing Partner


1. The Resurgence of Bitcoin and “DeFi Summer 2.0”


In 2023, Bitcoin has staged a comeback, with bitcoin dominance (Bitcoin’s share of total crypto market cap) rising from 38% in January to around 52% in December, making it one of the top ecosystems to look out for in 2024.  There are at least three major catalysts driving its renaissance in the next year: (1) the fourth Bitcoin halving due for April 2024, (2) the expected approval of several bitcoin spot ETFs from institutional investors, and (3) a rise in programmability features, both on the base protocol (such as Ordinals), as well as Layer 2s and other scalability layers such as Stacks and Rootstock.


On the infrastructure level, we believe we will see a proliferation of Bitcoin L2s and other scalability layers to support smart contracts.  The Bitcoin ecosystem should coalesce around one or two Turing-complete smart contract languages, with top contenders including Rust, Solidity, or the extension of a Bitcoin-native language such as Clarity.  This language will become the “standard” for Bitcoin development, similar to how Solidity is considered to be the “standard” for Ethereum development.


We also see the fundamentals for a possible “DeFi summer 2.0” on Bitcoin.  With Wrapped BTC (WBTC) today having a market cap and Total Value Locked (TVL) of around $6 billion, there is clearly an enormous demand for Bitcoin in DeFi.  Today, Ethereum has about 10% of its $273 billion market cap in TVL ($28 billion).  As Bitcoin DeFi infrastructure matures, we could potentially see Bitcoin DeFi Total Value Locked (TVL) rise from the current $300M (<0.05% of market cap) to ~1-2% of bitcoin market cap (~$10-15 billion at current prices).  In this process, many Ethereum DeFi practices are likely to be transferred and “naturalized” on Bitcoin, such as the recent rise of BRC-20 inscriptions and ideas such as staking like Babylon’s L2.


Bitcoin NFTs, such as those inscribed on Ordinals, may also see increased popularity in 2024. As Bitcoin has much higher cultural recognition and memetic value, it is possible that web2 brands (such as luxury retailers) will choose to release NFTs on Bitcoin, similar to how Tiffanys partnered with Cryptopunks to release the “NFTiff” pendants collection in 2022.


2. Tokenized Social Experiences for New Consumer Use Cases


Whereas Web2 has moved from social to finance, Web3 is moving from finance to social.  In August 2023, pioneered a new form of tokenized social experiences on the Base L2, with users able to buy and sell fractionalized “shares” of others’ X (fka. Twitter) accounts, reaching a peak of 30k ETH TVL (~$50 million USD at the time) in October, and inspiring several “copycat projects” such as on Arbitrum.  It seems that, through financializing Twitter profiles, has successfully pioneered a new tokenomics model for the SocialFi space.


In the upcoming year, we expect more experiments in the social space, with tokenization (both as fungible and non-fungible tokens) playing a key role in reinventing the social experience.  Fungible tokens are more likely to be novel forms of points and loyalty systems, whereas non-fungible tokens (NFTs) are more likely to serve as profiles and social resources (such as trading cards).  Both would be able to be traded on-chain and participate in DeFi ecosystems.


Lens and Farcaster are two of the leading web3-native applications integrating DeFi with social networks.  Projects like Blackbird will also popularize tokenized points systems for loyalty programs in specific verticals (such as restaurants), using a combination of stablecoin payments and tokenized rebates to reinvent the consumer experience, functionally providing an on-chain alternative to credit cards.


3. An Increase in TradFi-DeFi “Bridges” Such as Stablecoins and Mirrored Assets


2023 has seen a lot of legal action in crypto, including several high profile wins for the industry such as the XRP ruling and the Grayscale ETF litigation win, and justice being served for financial fraud in Binance and FTX.  Alongside this is a large increase in institutional interest and potential ETF approvals for Bitcoin and Ethereum.


In 2024, we expect to see a dramatic increase in institutional adoption, who not only seek for ETFs, but also tokenized real-world assets (RWA) and TradFi financial products.  In other words, TradFi assets will be “mirrored” in DeFi, while crypto assets will have increased exposure in TradFi markets, thus creating TradFi-DeFi “bridges” that bring these two worlds closer together for increased liquidity and diversification for investors.


Stablecoins will serve as one of the most important links between the TradFi and DeFi worlds, with stablecoins such as USDC and PYUSD being more widely accepted as both portfolio options and payment tools. With Circle said to consider a 2024 IPO, we also may see an increase in the issuance and usage of non-USD stablecoins, most notably Euro-backed stablecoins such as Circle’s EURC, as well as British Pound, Singaporean Dollar, and Japanese Yen stablecoins.  Some of these stablecoins may be launched by state-backed actors.  This may also lead to the growth of an on-chain fiat foreign exchange market.  Tokenized treasuries have already gained traction with $800m tokenized through platforms like Ondo.


4. The Cross-pollination of Modular Blockchains and Zero Knowledge Proofs


Both the idea of modular blockchains and ZKPs have greatly matured over this past year, such as the recent Celestia mainnet launch, Espresso’s Arbitrum integration, RiscZero’s open-source Zeth prover, and Succinct’s launch of a ZK marketplace. One interesting trend is how these two narratives have merged together, with companies in the ZK space “modularizing” by focusing on specific verticals, such as co-processors, privacy layers, proof marketplaces, and zkDevOps.


In the upcoming year, I expect this trend to continue, with Zero Knowledge Proofs emerging as an interface between different components of the modular blockchain stack. For example, Axiom’s ZK co-processor leverages ZKPs to provide historical state proofs, which can then be used by developers to perform computations in DApps. With ZKPs being the common interface between these different providers, we will see a new era of smart contract composability. This provides developers building DApps with a far greater flexibility for providers and reduces the barrier to entry for the blockchain stack. On the consumer side, ZKPs may see increased use cases as a way to preserve identity and privacy, such as in the form of ZK-based decentralized IDs.


5. More Computationally Intensive Applications Moving On-chain, Such as AI and DePIN


There has been a lot of time, energy, and capital poured into the scalability problem for decentralized applications. Today, much of the scalability problem has been solved – gas fees on Ethereum L2s are less than 0.02 USD (compared to 11.5 USD for Ethereum mainnet), and on Solana the fees are 3-4 orders of magnitude even lower.


As this trend continues in the next year, we believe computationally expensive applications (applications can use up gigabytes of RAM) will become much more economically feasible on-chain in the near future. This includes vertical applications such as on-chain AI systems, Decentralized Physical Infrastructure Networks (DePIN), on-chain knowledge graphs, and fully on-chain games and social networks. All this may radically reshape the on-chain data economy, greatly improve both user and developer experience, as they are freed from onerous gas fees and stringent constraints on compute power.


Examples of computationally expensive projects that can take advantage of this much cheaper on-chain “compute” include Hivemapper’s efforts to create a decentralized Google Maps on Solana, Bittensor’s creation of a decentralized machine learning platform, Modulus Labs’ efforts in ZKML and AI-generated NFT art, The Graph’s plans for on-chain knowledge graphs, and the Realmsverse creating an on-chain game world and lore on Starknet.


6. Consolidation of Public Blockchain Ecosystems and a “Hub-and-Spoke” Model for Appchains


There has been a proliferation in infrastructure projects over the past few years. Despite the commonplace technical categorization of Layer 1 (L1) and Layer 2 (L2), from a user experience perspective there is not much of a difference. This is especially true for a general-purpose public blockchains; today an L1 such as Solana or Avalanche is a direct competitor to an L2 such as Arbitrum or zkSync for users, projects, and volume.


With this homogeneity in place, liquidity serves as a concentrating force for general-purpose public blockchains, benefiting larger incumbent players such as Arbitrum, Optimism and Solana, with the top four ecosystems today accounting for ~90% of Total Value Locked (TVL). Smaller ecosystems must concentrate their efforts on specific verticals (such as social, gaming, DeFi) to retain an edge, effectively becoming “appchains” or “sector-chains.” Already, three of the Top 10 L2s by TVL (dydx, Loopring, Ronin) are effectively appchains that specialize in a single vertical. The TVL “break-in” of smaller, newer L2 chains such as Base and Blast also rely heavily on single “killer-apps” (eg. and Blur respectively) to establish beachheads in volume.


Moreover, most leading general-purpose public blockchains have released appchain toolkits (OP Stack, Arbitrum Nitro, StarkEx, etc.) to allow appchains to tap into the liquidity on these public networks and place them within their ecosystem orbits. Thus, we’re beginning to see a “hub and spoke” model where there a few general-purpose public blockchains acting as central “hubs,” around which there are numerous “spokes” of specific appchains. In 2024, it may be worth paying attention to major rollup-as-a-service vendors such as Caldera, Conduit, and Eclipse that take advantage of this “hub-and-spoke” move.




As we enter 2024, we have perhaps made it through the worst of the bear market, turning over the page on the series of brutal collapses that we have seen over the past year and a half, and ready to begin exploring novel use cases.  Today, we’re at an inflection point, where crypto is no longer solely about financialization, but rather a broader idea of how we redefine consumer, social, and developer experiences using blockchains.  I’m very excited to see what this year holds for the future of our still nascent industry, as we use decentralized technologies to reimagine our digital culture.





Ken Rogoff wrote a fantastic book, Why This Time is Different: Eight Centuries of Financial Folly.  Having read the book with humility and thought about some of my own experiences feeling “But, this time is TOOOOTALLY different”, I will take the plunge and share some of the differences I see.


This rally is remarkably different from the previous one.


The 2021 peak saw a massive churn in the top tokens.  Fourteen of the top-20 tokens at the peak of the 2017 ICO-lead boom dropped out of the top-20 soon after.  They fell a long way.  Thirteen of those fallen tokens now average #123 – by market capitalization.  (Tron is the only project that dropped out of the top-20 and returned.)  In hindsight one can say that was speculative froth and hype on unproductive tokens.


The fourteen tokens that fell out of the 2017 top-20 were all replaced by tokens that didn’t even exist at the time of the prior peak.  That’s wild.  Pure creative destruction.



What’s been interesting about this rally is how little change there has been.  It’s the polar opposite of the previous cycle. 


This time all of the top six – which account for 83% of market capitalization – are the same.  Eight of the top-10 are the same.  Fourteen tokens stayed in the top-20.


Over all those cycles, Bitcoin is the constant.  Only six tokens are in all three lists (shown in gold above).  In the twelve years since Litecoin launched, only four tokens have held the #2 position:  Litecoin, XRP/Ripple, Ethereum, and Bitcoin Cash.  Bitcoin Cash only held it for one day!  Bitcoin has always held the title belt.


We spoke a lot during 2022 about the idea that while the downdraft was similar in magnitude to prior bear markets, that it was unique because blockchain was not facing an existential crisis.   Most of the price action was driven by leverage and the headlines caused by bad actors.  That’s why it is not surprising that we see the same projects coming back.  They were not down because they were not good projects, they were down in sympathy with the overall market.  Solana is a particularly good example.  




If you abstract out – to just the three main flavors of blockchain:  Bitcoin, Ethereum, and all other projects combined – you can see the cycles.


The first thing to note is once Ethereum became established in 2017-18, it has had a fairly steady share.  The only major pullback was during the 2020-21 bull market when competing layer 1 hyper-scalable blockchains like Solana and Avalanche gained meaningful market share. 


It’s Bitcoin and the other things that gyrate.


One of the earliest non-bitcoin tokens and Pantera’s first venture investment Ripple and their XRP token exploded to a remarkable 27% of the entire market on May 17, 2017. 


The graph below depicts the three main things in blockchain over the recent extremes in Bitcoin market share since 2016.



When Bitcoin and Ethereum were at their historical low market share in January 2018 — the non-Bitcoin+Ethereum share was 55% of the market.






The pace in which innovation occurs in the blockchain tech ecosystem produces new niches and verticals cycle-over-cycle.  The research we do to expand our theses helps us stay ahead of the curve, but also helps us maximize our coverage when it comes to sourcing and investing in deals.  Over the next couple letters, we’ll share our theses on areas we are actively looking at.



By Chia Jeng Yang, Principal, and Caroline Cahilly, Intern


AI: Melding Human & Computer Intelligence


The outputs generated by AI models, like large language models (“LLMs”), should be a result of optimal interaction between human and computer brains, data, and incentivization systems. 


The ability to speak in natural languages is what makes LLMs exciting, as humans and AI can use the same language to expound on complex processes. This is a big step toward a future of coordinated systems that bring humans in the loop. To make this collaboration even better, we still need to develop strong human-computer frameworks, mechanics, and tooling, which would encourage AI systems to think more effectively, produce more useful answers, and achieve optimal results.


How Web3 Can Advance this Interaction


Computer-native incentive frameworks are going to determine how humans interface/interact with AI by incentivizing crowdsourcing, accountability, etc. We want to consider products that maximize/optimize the interaction that occurs between the computer/AI brain on one end and the human brain on the other (e.g., token-holders, developers), in particular focusing on mid-to-long term use cases.


Going forward, we delve into the following three facets of human-machine interaction in the age of AI:



The following are a few highlights of what crypto can offer AI, which will be relevant throughout the thesis:


1. Payments – TradFi payments have defined borders. Crypto rails require just a few lines of code. The programmability offers (i) streamlined integration for software products where developers simply embed a wallet address into the codebase and (ii) flexible payments based on compute, which require too much audit cost in existing infra. By avoiding outdated global financial infrastructure, it lowers the barrier to market entry for products with international user bases. Additionally, crypto transactions can offer lower fees than conventional payment gateways. Easy and low-cost integration is particularly beneficial for open-source projects, where resources are often limited and simplicity is key for collaboration and adoption.


2. Crowdsourcing – As Human Feedback for LLM models become an increasingly important avenue for greater context mining and alignment, Web3 incentivization enables data crowdsourcing to be done at much greater speeds and scales. Structured reward (and punishment) systems should also promote high quality information and attract large numbers of contributors from a wide range of backgrounds.


3. Data Control – Controlling one’s own data — which requires both data provenance and privacy — should become increasingly relevant because:


a. Users will likely be motivated to control their own data if it means they get paid or receive better experiences without much effort, which now seems possible. With the rise in autonomous agents, users would be able to get paid for their data without active intervention. And, users who control their data should receive better experiences than the subpar experiences currently provided by personalization algorithms which only see a narrow view of a user’s digital behavior. Unlike previous attempts at data wallets, LLMs now (i) can automate large-scale, cross-platform manual data collection and (ii) are getting much better at contextualizing unstructured natural language data. 


b. Companies will likely lead the charge on controlling their data to protect confidential information. The new standards will then flow through to individuals.


Three ideas we’re particularly excited by are:


1. Human-Feedback Reasoning: Logical reasoning through crowdsourced (zk) knowledge graphs.


2. Machine Learning (“ML”) Tracing for AI-Generated Content (“AIGC”) Royalties: Using ML tracing to calculate royalties for the original data content behind AIGC


3. Digital Twins for Advertisement: As LLMs overtake search engines as the form factor for information retrieval, user preferences will be represented by interactions with LLMs, not website cookies. Advertising in the AI world will require infrastructure that enables advertising technology to automatedly extract personal preferences from digital twins.




Despite market hype, LLMs struggle with planning, reasoning, understanding the physical world, and other similar tasks that humans are designed to be good at.[2] These errors likely occur because large LLMs mimic reasoning based on patterns in the data without truly understanding the underlying logical/physical principles, thus underperforming by human standards.


Principled reasoning’s value lies in the ability to handle unseen problems, especially given strong evidence that transformers cannot generalize beyond training data.[3]  We look for solutions to solve the reasoning problem that can help both foundational models and any LLM-integrated system today, focusing on human feedback mechanisms for better reasoning.




Knowledge graphs – which use structured databases to capture relationships between entities, events, and concepts – offer one interesting approach to incorporate logical reasoning into LLMs.


Below are examples of how they can be incorporated:


1. Dynamic Knowledge Retrieval: During inference, dynamically retrieve relevant information from the graph as determined by some attention mechanism.


2. Feedback Loops: If the output deviates significantly from the graph’s understanding, use this feedback for further fine-tuning.


Crowdsourced Knowledge Graphs – Crowdsourcing will redefine information collection and authentication, helping develop “the repository of all human knowledge and cultures” as described by Yann LeCun, Meta’s Chief AI Scientist.[4] 


Crowdsourced knowledge graphs will incentivize users to contribute data and their logical connections via automatic payments when models access their contributions. To maintain accuracy, incorrect contributions will be penalized, as determined by a group of validators enforcing a set of agreed-upon standards. Defining these standards—which will be specific to each graph—will be one of the most important considerations for success.


Web3 provides a way to incentivize knowledge graph creation at the necessary scale. Additionally, gaps in LLM reasoning will be a moving target, and Web3 offers a way to incentivize contribution of specific data as gaps arise. 


Moreover, the structured reward (and punishment/slashing) system will promote high quality information and attract large numbers of contributors from many backgrounds. Notably, users are actually creating value by sharing data to be used by LLMs in a productive non-zero-sum manner, differentiating this from zero-sum prediction markets and decentralized oracles.


Lastly, crowdsourcing these graphs at the limits of current AI will help maintain relevant accuracy (i.e. not replicating the reasoning capabilities of existing LLMs).


Trust & Accountability Mechanisms


1. Data Privacy


The control AI is developing over user data will soon become comparable to that of Apple’s hardware ecosystem. Privacy must be considered exponentially more carefully across all parts of the funnel because:


– The surface area of data collection for AI is increasing exponentially, as AI seamlessly infiltrates numerous facets of our lives from smart home devices to healthcare applications.


– We are approaching an inflection point in (i) AI’s ability to create personalized content for users (e.g., with LLMs) and (ii) users’ beliefs in this capability. As users turn to AI for truly personalized experiences/products at much greater frequency/scales, the velocity of data sharing with AI will skyrocket.


Thus, data privacy is critical to (i) building user trust in AI systems and (ii) enabling developers to avoid data misuse (e.g., unauthorized access, identity theft, and manipulation).


Web3 technologies like zero-knowledge proofs (zk-SNARKs)[5] and fully homomorphic encryption (FHE)[6] will empower individuals to truly own/control their data by enabling encrypted interactions and ensuring sensitive information remains in the hands of the users.


The recent US Executive Order on AI highlights the importance of “strengthening privacy-preserving research and technologies, such as cryptographic tools that preserve individuals’ privacy” and introduces reporting requirements for large models. This implies increased regulatory openness to Web3 privacy/provenance approaches and even the possibility that these approaches become the standard for compliance.


Crowdsourced ZK Knowledge Graphs – With crowdsourced zk knowledge graphs, AI could benefit from connections in private data. Specifically, they’d have “public” nodes with public data and “private” nodes with encrypted data. The model could use logical connections between nodes to arrive at an answer without revealing the knowledge itself (i.e., while nodes referenced in the final answer would be public, the nodes used to get there don’t need to be.)


These graphs additionally could make it easier to delete user data because accessing them in real-time (e.g., via dynamic knowledge retrieval) avoids storing data implicitly in trained models.


2. Provenance


Without provenance, AI may be on track to create a “wild west” landscape of deepfakes and unchecked personal/private/proprietary data use. Web3 should provide many promising solutions by enabling us to determine where NFTs, other media assets, and the data used by models come from.


Machine Learning (“ML”) Tracing for AI-Generated Content Royalties – Beyond deepfakes, the rise of AI-generated content (“AIGC”) in the arts poses unique challenges around intellectual property rights and royalties. For instance, if an AIGC system creates a mash-up of songs by two prominent artists, how should credit and financial rewards be allocated to the original artists? Traditional models for determining such allocations are increasingly inadequate for AIGC given its complexity and variability.


Machine learning (“ML”) tracing offers a way to identify the original components of a piece of AIGC, whether it’s a note sequence from Rihanna or a lyric from Eminem. Controlling provenance at the time of AIGC generation will be critical to enabling this tracing.


In the absence of robust global payment infrastructure for AIGC, platforms like YouTube (which already have mechanisms for the payout of royalties) will have a head start and an opportunity to further concentrate their power/influence. 


To democratize AIGC creation and ensure fair compensation to original artists, a new payment system is needed. Blockchain payment rails integrated natively with AIGC models can facilitate instant payouts globally from Day 1. ML tracing and blockchain can then be integrated into various platforms, reducing the advantage that incumbents like YouTube currently hold.


Investment in this technology (1) supports the equitable distribution of royalties and (2) fosters innovation in AIGC by unlocking opportunities for more creators.


AI Incentivization


As AI models continue to act increasingly autonomously, we want to develop systems that incentivize them to act in line with human desires.


1. Autonomous Agents


Autonomous agents are models that can interact intelligently with their environment (e.g., utilize tools and generate API calls to access real-time data), interface with algorithms for reasoning and decision-making, and take actions without direct human control. They exhibit goal-directed behavior and can learn from experience but are only reliable in very narrow contexts (e.g., self-driving). As AI models increasingly move from information retrieval to executing actions on behalf of users, autonomous agents that are verifiably empowered by their human users, conducting commerce with digitally native currencies could increase in adoption.


Digital Twin Targeting – Traditional search-based advertising is declining as conversational AI models like ChatGPT are poised to become the primary source for information retrieval. This presents a challenge to the AdTech industry, as conventional advertising through search engines and cookies faces diminishing returns.


As the market begins to realize that these personal models, instead of cookies, are the atomic unit for understanding user preferences, models that allow advertisers to extract user preferences from existing other models may begin to dominate. Using these models, advertisers can achieve a level of personalization previously unattainable while maintaining user privacy through cryptographic methods.


A new platform that facilitates this interaction has the potential to bypass existing software and hardware gatekeepers in AdTech like Google and Apple.


Specifically, when a user decides to create a digital twin, they will give it access to their search history, current accounts (e.g., Google, ChatGPT, Amazon), hard drive, etc. The twin will develop an initial summary of their data, including companies they’ve interacted with, interests, etc. and keep it consistently updated.


The user can then set permissions as to how and to whom the twin is allowed to sell its data. For example, imagine a button that says “let my AdBot talk to GPT-4, Meta AI, etc.” The digital twin will then autonomously interact with the advertisers’ AI models. The advertisers’ models will determine if it’s worth targeting without even needing to know the user’s identity. When targeted, the user will receive ads in various forms (e.g., via text, in discussions with LLMs, etc.) and be paid as reward.



In this marketplace of digital twins, crypto rails will likely present the most straightforward way to allow models to compensate other models they interact with, since transactions require only a few lines of code. Moreover, incentives should be designed such that targeted digital twins are of maximal value to the advertiser. So, advertisers should only target digital twins with clean and accurate data that represents user preferences.




The integration of AI and Web3 technologies has the potential to revolutionize reasoning, data privacy, and incentivization in AI systems. Blockchain-based solutions should facilitate secure, efficient transactions and data handling, while incentivizing contributions from diverse sources to enhance AI development and applications. This symbiosis between AI and crypto technologies has the potential to create more robust, efficient, and user-centric AI systems, addressing key challenges in the AI domain.





At the second Pantera Blockchain Summit, March 2014, I compared the total market cap of bitcoin to a similarly-valued public company:


At the dinner a few hours before the late-night poker game, Morehead had joked about the fact that, at the time, all the bitcoins in the world were worth about the same amount as the company Urban Outfitters, the purveyor of ripped jeans and dorm room decorations – around $5 billion. 

“That’s pretty wild, right?”  Morehead said.


“I think when they dig up our society, all Planet of Apes-style in a couple centuries, Bitcoin is probably going to have had a greater impact on the world than Urban Outfitters.”


= Nathaniel Popper, 2015, Digital Gold


I updated that comparison in 2020 – L’Oréal.  Waterproof mascara is undoubtedly an amazing invention, but Bitcoin seemed to have more legs. 


Bitcoin passed Berkshire Hathaway a while ago. 


It’s now tied with Meta (f.k.a. Facebook).



Photo sharing is really cool and all, but I think that financial inclusion for everybody with a smartphone on Earth is gonna be bigger.



All the best for 2024!




“Put the alternative back in Alts”



Our investment team hosts monthly conference calls to help educate the community on blockchain.  The team discusses important developments that are happening within the industry and will often invite founders and CEOs of leading blockchain companies to participate in panel discussions.  Below is a list of upcoming calls for which you can register via this link.


The Year Ahead Conference Call

A discussion of the blockchain opportunity set and how Pantera’s funds are structured to capture value in the current and evolving market environment.

Thursday, January 18, 2024 9:00am PST / 18:00 CET / 1:00am Singapore Standard Time

Please register in advance via this link:


Pantera Liquid Token Fund Investor Call

Tuesday, January 30, 2024 9:00am PST / 18:00 CET / 1:00am Singapore Standard Time

Open only to Limited Partners of the fund.


Regulatory Developments in Blockchain

Pantera Chief Legal Officer Katrina Paglia will provide a top-down overview of the current crypto regulatory landscape.

Tuesday, February 6, 2024 9:00am PST / 18:00 CET / 1:00am Singapore Standard Time

Please register in advance via this link:


Pantera Early-Stage Token Fund Investor Call

Tuesday, February 13, 2024 9:00am PST / 18:00 CET / 1:00am Singapore Standard Time

Open only to Limited Partners of the fund.


Investing in Blockchain Conference Call

An overview of the year ahead in blockchain, including discussions on investment themes Pantera is most interested in and how we anticipate the year to unfold.

Tuesday, February 20, 2024 9:00am PST / 18:00 CET / 1:00am Singapore Standard Time

Please register in advance via this link:


Pantera Venture Fund II Investor Call

Tuesday, March 5, 2024 9:00am PST / 18:00 CET / 1:00am Singapore Standard Time

Open only to Limited Partners of the fund.


Pantera Venture Fund III Investor Call

Tuesday, March 19, 2024 9:00am PDT / 17:00 CET / 12:00am Singapore Standard Time

Open only to Limited Partners of the fund.


Pantera Blockchain Fund Investor Call

Tuesday, April 2, 2024 9:00am PDT / 18:00 CEST / 12:00am Singapore Standard Time

Open only to Limited Partners of the fund.


Join us in learning more about the industry, the opportunities we see on the horizon, and our funds.



Interested in joining one of our portfolio companies?  The Pantera Jobs Board features 1,500+ openings across a global portfolio of high-growth, ambitious teams in the blockchain industry.  Our companies are looking for candidates who are passionate about the impact of blockchain technology and digital assets.  Our most in-demand functions range across engineering, business development, product, and marketing/design.


Below are open positions that our portfolio companies are actively hiring for:



Visit the Jobs Board here and apply directly or submit your profile to our Talent Network here to be included in our candidate database.

[1] Important Disclosures – Certain Sections of This Letter Discuss Pantera’s Advisory Services and Others Discuss Market Commentary. Certain sections of this letter discuss the investment advisory business of Pantera Capital Management and its affiliates (“Pantera”), while other sections of the letter consist solely of general market commentary and do not relate to Pantera’s investment advisory business. Pantera has inserted footnotes throughout the letter to identify these differences. This section provides educational content and general market commentary. Except for specifically marked sections of this letter, no statements included herein relate to Pantera’s investment advisory services, nor does any content herein reflect or contain any offer of new or additional investment advisory services. This letter is for information purposes only and does not constitute, and should not be construed as, an offer to sell or buy or the solicitation of an offer to sell or buy or subscribe for any securities. Opinions and other statements contained herein do not constitute any form of investment, legal, tax, financial, or other advice or recommendation.








[5]zk-SNARKs enable secure interactions by validating data without exposing the actual content, ensuring confidentiality.


[6]FHE enables computations to be performed on encrypted data without the need to decrypt it first.


[7] Important Disclosures – This Section Discusses Pantera’s Advisory Services.  Information contained in this section relates to Pantera’s investment advisory business.  Nothing contained herein should be construed as a recommendation to invest in any security or to undertake an investment advisory relationship, or as any form of investment, legal, tax, or financial advice or recommendation.  Prospective investors should consult their own advisors prior to making an investment decision.  Pantera has no duty to update these materials or notify recipients of any changes.


[8] This section does not relate to Pantera’s investment advisory services.  The inclusion of an open position here does not constitute an endorsement of any of these companies or their hiring policies, nor does this reflect an assessment of whether a position is suitable for any given candidate.


This letter is an informational document that primarily provides educational content and general market commentary.  Except for certain sections specifically marked in this letter, no statements included herein relate specifically to investment advisory services provided by Pantera Capital Management Puerto Rico LP or its affiliates (“Pantera”), nor does any content herein reflect or contain any offer of new or additional investment advisory services.  Nothing contained herein constitutes an investment recommendation, investment advice, an offer to sell, or a solicitation to purchase any securities in Funds managed by Pantera (the “Funds”) or any entity organized, controlled, or managed by Pantera and therefore may not be relied upon in connection with any offer or sale of securities.  Any offer or solicitation may only be made pursuant to a confidential private offering memorandum (or similar document) which will only be provided to qualified offerees and should be carefully reviewed by any such offerees prior to investing.


This letter aims to summarize certain developments, articles, and/or media mentions with respect to Bitcoin and other cryptocurrencies that Pantera believes may be of interest.  The views expressed in this letter are the subjective views of Pantera personnel, based on information that is believed to be reliable and has been obtained from sources believed to be reliable, but no representation or warranty is made, expressed, or implied, with respect to the fairness, correctness, accuracy, reasonableness, or completeness of the information and opinions.  The information contained in this letter is current as of the date indicated at the front of the letter.  Pantera does not undertake to update the information contained herein.


This document is not intended to provide, and should not be relied on for accounting, legal, or tax advice, or investment recommendations.  Pantera and its principals have made investments in some of the instruments discussed in this communication and may in the future make additional investments, including taking both long and short positions, in connection with such instruments without further notice.


Certain information contained in this letter constitutes “forward-looking statements”, which can be identified by the use of forward-looking terminology such as “may”, “will”, “should”, “expect”, “anticipate”, “target”, “project”, “estimate”, “intend”, “continue”, “believe”, or the negatives thereof or other variations thereon or comparable terminology. Due to various risks and uncertainties, actual events or results or the actual policies, procedures, and processes of Pantera and the performance of the Fund may differ materially from those reflected or contemplated in such forward-looking statements, and no undue reliance should be placed on these forward-looking statements, nor should the inclusion of these statements be regarded as Pantera’s representation that the Fund will achieve any strategy, objectives, or other plans. Past performance is not necessarily indicative of or a guarantee of future results.


It is strongly suggested that any prospective investor obtain independent advice in relation to any investment, financial, legal, tax, accounting, or regulatory issues discussed herein.  Analyses and opinions contained herein may be based on assumptions that if altered can change the analyses or opinions expressed.  Nothing contained herein shall constitute any representation or warranty as to future performance of any financial instrument, credit, currency rate, or other market or economic measure.


This document is confidential, is intended only for the person to whom it has been provided, and under no circumstance may a copy be shown, copied, transmitted, or otherwise given to any person other than the authorized recipient.