Why Most Chain-Specific Funds Are Misallocated

Funds bet on a single chain's success, creating misaligned incentives. They prioritize native dApps over superior cross-chain solutions, ignoring the multi-chain reality.

• Problem: Forces portfolio companies to build on inferior tech to access capital.
• Result: $20B+ in TVL trapped in suboptimal liquidity pools and bridges.
• Example: A fund backing an EVM chain will ignore a superior Solana DEX aggregator.

Massive grants are deployed to bootstrap empty chains, creating artificial activity that evaporates when incentives dry up.

• Problem: Funds metrics like total value locked (TVL) and transaction count are gamed by mercenary capital.
• Result: ~90% of grant-funded projects fail post-funding, wasting billions.
• Data Point: Chains like Avalanche and Fantom saw TVL collapse >70% after incentive programs ended.

Funds over-index on consumer-facing dApps and under-invest in the critical middleware and interoperability layer.

• Problem: Neglects the pipes that enable multi-chain UX, like intent-based solvers (UniswapX, CowSwap), cross-chain messaging (LayerZero, Axelar), and shared sequencers.
• Result: Creates fragmented user experiences and limits composability, the core innovation of DeFi.
• Opportunity Cost: The infrastructure layer captures more durable value than most application layers.

Paying for hardware directly solved the capital-intensive bootstrapping problem for decentralized consensus. This created a flywheel: more validators improved Nakamoto Coefficient and liveness, attracting more developers.

• Direct Problem-Solving: Funded bare-metal servers and high-performance SSDs, not generic grants.
• Measurable Outcome: Drove Nakamoto Coefficient from ~20 to over 30, making attacks prohibitively expensive.
• Contrast: Generic "ecosystem funds" often subsidize marketing for derivative DEXs with no unique value.

Targeted capital at specific, novel use cases (DeFi, NFTs, GameFi) on subnet infrastructure, proving the tech stack. This attracted builders who needed custom VMs, not just another EVM clone.

• Strategic Focus: Funded application-specific chains (e.g., Dexalot, DeFi Kingdoms) that required Avalanche's architecture.
• Platform Validation: Each successful subnet became a case study for the Avalanche Warp Messaging and custom VM thesis.
• Pitfall Avoided: Did not fund the 100th Uniswap fork on the C-Chain, avoiding liquidity fragmentation.

Throwing $1B+ at dApp migrations without a compelling technical moat. Funds were used for liquidity bribes, not to solve the core problem of ZK-prover cost and speed. This left them vulnerable to more performant rollups like zkSync Era and Starknet.

• Symptomatic Spending: Incentives went to TVL, not to R&D for a faster prover or better developer tooling.
• Result: Failed to achieve dominance despite massive spend; ~$150M TVL vs. zkSync Era's ~$600M.
• Lesson: Capital cannot buy technological lead; it must amplify an existing architectural advantage.

Allocating community pool funds to pay for shared security services is a canonical example of capital solving a core ecosystem need. Consumer chains rent security from the Hub, creating a sustainable revenue model for ATOM stakers.

• Product-Market Fit: Solves the "sovereign but insecure" problem for new Cosmos chains.
• Sustainable Model: Transforms the Hub from a governance forum into a security provider, with fees flowing to stakers.
• Strategic Impact: Incentivizes alignment and makes the Hub's high $2B+ staked value economically useful.

The $50M Short-Term Incentive Program successfully bootstrapped liquidity but entrenched the foundation's centralized sequencer. Capital was spent on outcomes (TVL) rather than decentralizing a critical point of failure.

• Tactical Win, Strategic Loss: Drove ~$2B in TVL to Arbitrum One, but did nothing to advance permissionless sequencing.
• Missed Opportunity: Funds could have seeded a decentralized sequencer set or a shared sequencing layer like Espresso.
• Verdict: Capital allocation that ignores core infrastructure decentralization is a long-term liability.

Coinbase used modest incentives to catalyze activity, but the real strategic capital is the OP Stack and shared sequencing roadmap. Funding is directed at shared infrastructure (like the Base Bridge) that benefits the entire Optimism Superchain.

• Leverage: Uses Coinbase's distribution to onboard users, but invests in public goods (OP Stack codebase).
• Network Effects: Every app built on Base is a potential future OP Stack chain, compounding value.
• Blueprint: Shows how a chain-specific fund should act as a seed for a broader ecosystem standard.

Allocating to a single chain's ecosystem fund is a bet on its winner-take-most potential, ignoring the commoditization of execution layers. The real value accrues to application-layer protocols (e.g., Uniswap, Aave) and interoperability infra (e.g., LayerZero, Axelar) that are chain-agnostic.

• Value Capture: An L2's native token often captures less long-term value than the major DeFi dApps built on it.
• Commodity Risk: Execution is becoming a low-margin commodity; differentiation is minimal post-EVM-equivalence and ZK-rollup convergence.

Capital is most efficiently deployed into the cross-chain communication layer and shared security models. This is where true network effects and defensible moats are being built, as seen with protocols like Chainlink CCIP and EigenLayer.

• Protocol Revenue: Cross-chain messaging and bridging generate fee revenue agnostic to which chain wins.
• Architectural Leverage: A single interoperability investment benefits from the growth of all connected chains, not just one.

Chain funds often overlook the critical, high-margin infrastructure that developers actually use daily: RPC providers, indexers, and oracle networks. These are recurring revenue businesses with low customer churn.

• Sticky Demand: Projects rarely switch RPC providers (Alchemy, QuickNode) or data indexers (The Graph) once integrated.
• Revenue Certainty: Fees are based on API calls, providing predictable cash flows versus speculative token appreciation.

Focus capital on modular components (DA layers, shared sequencers, prover networks) that serve multiple rollups. This avoids chain-specific risk and bets on the fragmentation of the stack, as championed by Celestia and Espresso Systems.

• Horizontal Scaling: A single Data Availability layer can secure dozens of rollups, creating a leveraged bet on modular growth.
• Economic Moats: Specialized networks (e.g., RISC Zero for proving) achieve scale and cost advantages that are hard to replicate.

Ecosystem funds often deploy capital as illiquid token grants to attract mercenary developers, leading to unsustainable inflation and minimal long-term protocol alignment. This creates a grant farm cycle instead of genuine ecosystem building.

• Capital Efficiency: Grant-driven projects have high failure rates and low user retention post-incentives.
• Value Drain: Native token emissions dilute existing holders and rarely translate to permanent TVL or fee generation.

Superior returns come from taking equity or token warrants in the foundational infrastructure companies (e.g., RPC providers, wallet SDKs, audit firms) that service the entire multi-chain landscape. This mirrors traditional VC investing in picks-and-shovels.

• Real Equity: Captures profits and dividends, not just speculative token volatility.
• Diversified Exposure: A single infra company's success is correlated with the growth of the entire sector, not a single chain's narrative.