> For the complete documentation index, see [llms.txt](https://docs.inceptionlrt.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.inceptionlrt.com/mission/problem.md). # Problem As institutional and retail capital moves on-chain, a new set of challenges emerges. The growth of curated vaults has made opportunity design more dynamic, but accessing and composing these opportunities has become **operationally difficult** and **technically fragmented**. Let’s break it down: ### **▸ Fragmentation across ecosystems** Each curator operates in isolation. Vaults built on Morpho are siloed from those on Symbiotic, EigenLayer, or Gearbox. Even when strategies offer similar exposure (e.g., stETH restaking), they live in separate systems with different wrappers, constraints, and interfaces. This fragmentation makes it difficult for users to build coherent portfolios or understand comparative risk. ### **▸ Limited composability** The diversity of vault structures: fixed income, restaking, LPs, or tokenized credit, creates reward streams that are difficult to unify. Protocols lack standardized interfaces. Positions can’t be composed into a single ERC-20 or ERC-4626. This limits users’ ability to **stack multiple sources of reward** into one liquid, capital-efficient solution. ### **▸ Liquidity constraints** While shared security unlocks new rewards, it introduces friction: * Unbonding periods of 7–21 days * Lockup mechanics that delay liquidity * Exposure to infrastructure-level risk This reduces capital mobility, particularly painful for approaches that require flexibility, such as liquidity provisioning or looping strategies. ### **▸ Operational complexity** Today’s curated DeFi requires: * Managing multiple vault interfaces and strategies * Navigating custom wrappers and unstaking logic * Tracking asynchronous rewards and emission schedules * Assessing risk and decentralization parameters For sophisticated institutions, this means more overhead. For retail users, it creates a barrier to entry. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://docs.inceptionlrt.com/mission/problem.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.