Roadmap
AutoLayer aims to increase the opportunities for yields and airdrops provided by Ethereum's Liquid Restaking, by leveraging several LRTs of our partners and supporting different blockchains.
Last updated
AutoLayer aims to increase the opportunities for yields and airdrops provided by Ethereum's Liquid Restaking, by leveraging several LRTs of our partners and supporting different blockchains.
Last updated
We started on Arbitrum and have expanded to Ethereum and BNB Chain, with upcoming launches on Linea, Mode, Gnosis, and Optimism. Each network will feature native products tailored to their respective ecosystems, including support for new Ethereum Layer 2 solutions like megaETH from its testnet phase. This expansion allows us to innovate and deliver robust solutions across a wider range of blockchain technologies.
LRTs can be used as collateral in markets and leveraged positions can be obtained by looping them. While this is a valuable feature with market potential, it also carries certain risks. An extreme event leading to a sudden depeg could trigger a cascade of automatic liquidations, resulting in the creation of bad debt in money markets. However, markets on DeFi are generally transparent. This allows us to determine the amount of collateral in money markets compared to their Total Value Locked (TVL), providing insight into the level of rehypothecation of an asset, at least within the DeFi space. This information can contribute to a risk/reward profile, enabling users to make more informed decisions about their purchases.
We will integrate additional Restaking protocols like Symbiotic and Nektar. Our initial products will be using the Renzo and EtherFi stack, with plans for deeper integrations and more structured products in the future.
Multi LRTs represent leveraged products where we first acquire an LRT and subsequently use it as collateral to acquire other LRTs, such as those from Symbiotic/Karak/Nektar, driven by incentives and APY. This strategy aims to diversify yield sources and generate rewards across multiple assets with a single click.
Similar to the above structures, LRT Vaults dynamically allocate capital among different LRTs, capturing incentives from various AVSs over time. Through rehypothecation mechanisms, the vault automatically rebalances in response to overheated AVSs, ensuring stability.
Our first native BNB Chain product will be a structured product generating various layers of yield. It will have a vault leveraging an LRT as collateral to secure BNB on money markets. This BNB will later be converted into a BNB LST.
By doing that, we are gathering:
Ethereum Staking Rewards.
EigenLayer Points.
LRT Points.
AVS Points
AutoLayer Points.
Bridge points (if using DeBridge by example)
BNB Staking Rewards.
These rewards are gathered all while remaining completely liquid. At any moment, users can close their positions and recover their collateral. Also, many of these layers of yield generate compounding interest, resulting in more yield over time, and all of this can be done with just one click.
AutoLayer Version 2 will elevate EigenLayer and AVSs to new heights by introducing a new layer for information and automation aimed at streamlining, automating, and securing all ecosystem interactions.
AutoLayer users will be able to create a Virtual Operator, configure it, and run it. This Operator can validate different AVSs. Once an Operator is created, AutoLayer will try to qualify it for all AVSs involved at a small cost. If an AVS has a cap that has been reached, we will notify the user trying to create an Operator for it. A minimal amount of ETH might be used to pay for the infrastructure needed to start the Operator. The vaults themselves may have different rules when it comes to automation, autocompounding, opt-out, and others, but we will manage all the infrastructure behind it. Once the Operator has started, any user can allocate funds to it.
The Vault Manager is where users can allocate funds to our Operators. Every Operator inside AutoLayer will validate a different set of AVSs, creating different products with different yields and risk profiles. These vaults will gather both illiquid and liquid assets, so we will use different strategies to increase yield, from auto-compounding liquid rewards to converting illiquid assets to liquid ones by creating wrapped versions of said assets. The Vault Manager will also measure profitability, showing realistic dollar-based APRs (this means incentive inflation will also be measured). The Operator inside a vault can change the AVS composition based on information and the automations AutoLayer provides.
AVSs might be the biggest question mark in today's crypto cycle as they will be the driving force behind yields during this time. How well or how poorly they behave will shape the future of the DeFi industry as we know it. This is why auditing AVSs will be important. For every AVS on AutoLayer, we will create a risk score based on two metrics:
Professional Operators TVL: This metric will gauge the involvement of institutional and professional Operators (such as P2P, Ankr, Nethermind, etc.) in an AVS by assessing the amount they have staked on it. This measurement generates a risk profile based on factual data from funds deposited by professionals, rather than subjective opinions.
Community TVL: This metric will quantify the level of support an AVS receives from retail investors, with insight into the amount of retail money backing it. This also contributes to the creation of a risk profile for the AVS.
Sudden changes to these risk scores can help our users stay informed.
LRTs can be used as collateral in markets and leveraged positions can be obtained by looping them. While this is a valuable feature with market potential, it also carries certain risks. An extreme event leading to a sudden depeg could trigger a cascade of automatic liquidations, resulting in the creation of bad debt in money markets. However, markets on DeFi are generally transparent. This allows us to determine the amount of collateral in money markets compared to their Total Value Locked (TVL), providing insight into the level of rehypothecation of an asset, at least within the DeFi space. This information can contribute to a risk/reward profile, enabling users to make more informed decisions about their purchases.
When it comes to rewards, the EigenLayer ecosystem will share both liquid and illiquid assets. Our vaults will have two functions:
Auto-compounding the results, getting AVS tokens/incentives, converting them to ETH, and reinvesting them.
Gathering points (which are non-transferable) until the next Token Generation Event (TGE), account for each user's share, and mint a wrapped version of all their reward tokens.
AutoLayer will not create markets for these tokens, but users can. Users will also be able to mint and burn these tokens at any moment. During a TGE, we will allow every user to claim their EL/AVS tokens with a 1:1 ratio by burning the wrapped versions of said tokens.
We will create a bounty system wherein if a user identifies that a slashing condition is met, instead of directly claiming the bounty, they can trigger an auto-delayed process where they can earn the same rewards with additional bonuses. This contract will play a crucial role in safeguarding our users from slashing by halting the validation of the AVS before the slashing event occurs. The same contract will also execute the slashing to prevent the possibility of double-dipping. Stakers will be charged a small fee to contribute to the bounty fund.
Like any other leveraged strategy, rehypothecation is not easy, but it can unleash the potential of large yields. In AutoLayer, we will create a rehypothecation manager to wisely boost these yields:
By separating the principal from the yield and rehypothecating it, you can compound more yield over time while protecting your principal.
By leveraging and deleveraging the principal, AutoLayer will allow stakers to Loop their LRTs wisely, reducing liquidation risks (however, this is still risky and the staker should understand this).
