The Future of Onboarding: Simulating DeFi Strategies Before Capital at Risk

The onboarding funnel is broken. It presents DeFi as a series of simple, isolated swaps when real strategies involve multi-chain asset routing, yield vaults like Aave or Compound, and perpetual futures on dYdX or Hyperliquid. Users learn by losing money.

Simulation is the missing primitive. A user must test a cross-chain leverage farming loop on EigenLayer and Aave with fake money first. This is the Web3 equivalent of a TradFi paper trading account, but for composable smart contracts.

Protocols optimize for TVL, not comprehension. Platforms like Lido and Uniswap focus on lowering gas costs and improving APY, not educating users on impermanent loss or slashing risks. The educational burden shifts to the user.

Evidence: Over 30% of new user funds are lost to MEV, slippage, and failed transactions within the first 10 interactions, a cost that simulated onboarding eliminates before capital is at risk.

Simulation precedes capital risk. The current DeFi onboarding flow is ethically broken: users must commit real funds to learn. Platforms like Tenderly and Foundry prove simulation is possible, but it remains a developer tool. The next evolution embeds this capability directly into user-facing applications, creating a sandbox for every transaction.

The primitive is a state diff. A simulation engine, like those used by Safe{Wallet} for transaction previews, does not execute on-chain. It forks the current state, runs the user's proposed actions—a Uniswap swap, a Compound borrow—and returns a precise outcome. This creates a trustless preview without gas or slippage.

This kills 'simulation for profit'. Protocols like MEV bots and certain intent-based systems use private simulation to extract value. Public, user-accessible simulation inverts this model. It democratizes information parity, turning a predatory edge into a public good that builds user confidence and protocol loyalty.

Evidence: The success of testnets and EIP-7511 (Gas Estimation) demonstrates demand for pre-execution clarity. User studies show a >60% drop-off when transaction outcomes are uncertain. Simulation as a primitive directly addresses this, converting uncertainty into a convertible asset: knowledge.

On-chain simulation is the new standard for user onboarding. Platforms like Tenderly and OpenZeppelin Defender now let developers simulate complex transactions, but the next evolution is consumer-facing sandboxes. These environments must replicate mainnet state forks and mempool dynamics to be credible.

Fidelity requires economic equivalence. A sandbox must simulate gas fees and MEV extraction from bots like those on Flashbots. Simulating a Uniswap v3 position without accounting for impermanent loss or slippage from 1inch aggregators is a useless abstraction.

The endpoint is the bottleneck. Public RPCs from Infura or Alchemy lack the low-latency, state-forking capabilities needed for real-time strategy testing. This creates a market for specialized simulation-optimized RPCs that cache and mirror live chain data.

Evidence: The Ethereum Execution Layer Specification (EELS) project formalizes state transitions, providing the deterministic foundation these sandboxes require to achieve parity with mainnet behavior.

Protocols optimize for TVL capture, not user education. Their core business model depends on attracting and locking capital to generate fees and governance power. A perfect simulation environment that delays or reduces capital deployment directly conflicts with this primary KPI.

Simulation is a public good that individual protocols will not fund. The benefits of a more educated user base are diffuse and accrue to the entire ecosystem, while the costs of building and maintaining high-fidelity simulators are concentrated and significant. This is a classic free-rider problem.

Complexity creates liability. A protocol that provides a simulation must ensure its accuracy. Any discrepancy between the simulated outcome and the real on-chain execution exposes the protocol to reputational damage and potential legal risk, a burden they are structurally unwilling to assume.

Evidence: No major DeFi protocol like Aave or Uniswap has built a native, generalized strategy simulator. Educational tools are outsourced to third parties like DeFi Saver or Zapper, which themselves monetize through affiliate fees or premium features, not pure simulation.

Risk-free simulation is non-negotiable. Users will no longer deposit capital before testing strategies. This creates a simulation layer that sits between wallets like Rabby or MetaMask and the execution layer, abstracting away the trial-and-error phase that currently loses users.

The standard will be protocol-agnostic. Today's tools like Gauntlet or Tenderly are siloed. The future standard will be a universal sandbox that can simulate interactions across any EVM or SVM protocol, using forked state from providers like Alchemy or QuickNode.

This kills 'testnet faucet' onboarding. Simulating with real-time mainnet state is more accurate and user-friendly than managing separate testnet ETH. The user experience benchmark becomes: if a user cannot simulate a yield strategy in under 60 seconds, the protocol fails.

Evidence: Uniswap v4 hooks will be the catalyst. Their complexity demands simulation. We predict the first EIP for a simulation RPC endpoint will be proposed within 18 months, standardizing how clients request forked state simulations.