AutoLayer Explained: The Evolution of Restaking Protocols

Author: Dewhales Research Source: dewhales Translation: Shan Ouba, Golden Finance

1. Introduction

There are currently many re-staking protocols and layers built on them, from EigenLayer, Babylon and similar solutions to Symbiotic, Puffer, Swell, Kelp, and add-ons/extensions such as Mellow, Gearbox, Lyra, and Anzen. As LRTFi has grown, the number of niche protocols has also increased, making it increasingly difficult for users to navigate the numerous differences between the various protocols and re-staking mechanisms. The re-staking landscape has evolved into a multi-layered structure that is very different from the early state of LSDFi.

AutoLayer is the largest pre-staking market, integrated with companies such as EigenLayer, Symbiotic, Renzo Protocol, and others. It offers over 20 different assets, including re-hypothecation options for Bitcoin and Ethereum. With its advanced risk-reward analysis, point management, and structured products, AutoLayer enables users to leverage multiple LRT/LST options with a single click, while maximizing and complicating their yield strategies.

2. Autolayer Review

Essentially, AutoLayer is the continuation of Tortle Ninja - a DeFi visual programming language that allows anyone to easily create and understand DeFi products. Tortle Ninja provides users with an advanced experience in algorithmic DeFi trading, enabling them to execute spot and derivatives strategies, measure their performance with real-time data, and quickly adapt to changing market conditions.

In AutoLayer, Tortle Ninja's mechanisms are applied to products and strategies related to re-hypothecation. As a re-staking protocol aggregator, AutoLayer provides several key features:

• Liquidity Redistribution and One-Click Liquidity Allocation – This allows users to re-stake any token in a single transaction. Users can earn ETH staking rewards, EigenLayer points, LRT points, re-staking rewards, and AutoLayer points with a single click, starting with any asset.

• Analytics Engine – It calculates all incentives and key performance indicators (KPIs) generated by users.

• Risk Structure – In addition to rewards, AutoLayer also provides a comprehensive LRT risk assessment. We are currently focusing on decoupling risk, calculating in real time the amount of LRT used as collateral in decentralized applications like Aave, Gearbox, Morpho, and Prisma, and comparing it to DEX liquidity and contracts to be liquidated. This data allows us to analyze the likelihood of liquidation cascades, providing users with important information about their exposure to these risks.

• AVS Assessment – Re-hypothecated assets are placed on AVS. For each AVS on AutoLayer, a risk assessment is created based on two metrics: TVL of professional operators and TVL of the community.

• Re-allocation Strategies – LST and LRT can be used in DeFi, and issuers can reward those who use them. AutoLayer users can easily execute these strategies with a single click, permissionless. Users can also assess how their positions change over time by reintegrating their receipts (LP positions, NFTs, etc.) into the interface and redeem them for any asset they want.

Currently, AutoLayer runs on multiple chains, including Ethereum, Arbitrum, and BNB Chain. More chains are planned to be added in the future (see the "Partners and Integrations" section for more details).

It is worth noting that AutoLayer does not abandon Tortle Ninja's DeFi-centric tradition, but provides users with DeFi-related strategies. These strategies are powered by Balancer and Camelot pools.

In addition, AutoLayer also introduced a consistent development strategy to welcome v1.5 and v2. In v1.5, the plan includes expanding the EigenLayer-based re-pledge protocol and launching native structured products (the first of which is an integration with BNB Chain). Version 2 will bring more extensive updates, including virtual operators and vaults, AVS storage managers, AVS and LRT scoring mechanisms, compounding and liquidity, LRT re-pledge, slashing tests, and bounties.

As part of further development, and to improve user experience and yield, AutoLayer plans to launch a new feature called Stripped Liquid Restaked Tokens (SLRT). To achieve this, a liquidity pool containing a mix of all wrapped credits will be created in Balancer, and the wrapped credits in the pool will be traded on the open market. The off-chain credit representation will be stored in the vault, which in turn will allow the minting of SLRT. These SLRTs enable users to claim a specific number of credits and are the on-chain representation of credits. Each claim mints one SLRT and allows them to be destroyed, with a 1:1 ratio between credits and SLRTs. In addition, AutoLayer plans to create a Balancer pool with liquidity for wrapped credits to ensure its liquidity.

3. AutoLayer Architecture and Components

As a multi-functional protocol, AutoLayer consists of several components:

• Dashboard, the front-end interface, includes three products: Click Liquid Staking/Restaking, Staking/Restaking Strategies, and DeFi Strategies (as described above).