Octavia AI presyoVIA

Elixir has announced that it will serve as the native path for Hamilton Lane SCOPE Fund holders to access DeFi through the decentralized stablecoin deUSD. Elixir will collaborate with Securitize to enable institutional asset holders of the fund to access DeFi directly via deUSD, while maintaining independent risk exposure.

𝐏𝐫𝐨𝐣𝐞𝐜𝐭 𝐈𝐭𝐞𝐫𝐚𝐭𝐢𝐨𝐧: 𝐀𝐈 𝐀𝐠𝐞𝐧𝐭 𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐦𝐞𝐧𝐭 If I am to build an AI Agent, name it Rubiks, for example, who is an AI-Powered Yield Optimization Agent. Below is the iteration for building this product: Project Name: Rubiks Agent Role: AI-Powered Yield Optimization Project Mindmap - Ideation - Roadmap - Product Development - Funding - Smart Contract Development - Marketing - Token Decision To launch a token: To not launch a token - Product Testing - Launch --- Building Rubiks: A Realistic Prototype for an AI-Powered Yield Optimization Agent Below is a detailed, step-by-step description of how we would build Rubiks. Each point represents actionable steps and realistic implementation processes for achieving the milestones. --- 𝟏. 𝐈𝐝𝐞𝐚𝐭𝐢𝐨𝐧 Cause of Actions 1. Market Research: - Identify inefficiencies in current DeFi yield farming practices by analyzing user behavior on major DeFi platforms, especially Pendle, Balancer, Uniswap, Curve, and Aave. - Use Dune Analytics and other tools to assess TVL trends, gas fees, and yield returns across protocols. - Conduct surveys or interviews with Yield farmers to understand their pain points regarding UI, complexity, and risk management. 2. Feasibility Study: - Collaborate with AI experts to explore whether reinforcement learning models can dynamically predict yield opportunities. - Analyze technical compatibility with protocols to determine how easily Rubiks can interact with smart contracts on Ethereum or Solana. 3. Concept Refinement: - Define clear, actionable goals and strategies for Rubiks, such as transaction cost and yield returns over manual strategy. - Document the user personas and outline their interaction with Rubiks. --- 𝟐. 𝐑𝐨𝐚𝐝𝐦𝐚𝐩 Cause of Actions 1. Phase Breakdown: Break down the roadmap into distinct phases: - Phase 1: Develop and integrate the AI algorithm with a single DeFi protocol on a testnet. - Phase 2: Scale to multiple protocols and chains while refining the UI. - Phase 3: Conduct beta testing. - Phase 4: Public launch with governance and community tools. 2. Milestone Prioritization: - Use project management tools like Jira or Notion to organize tasks and set deadlines. - Establish KPIs for each phase, such as user adoption and yield accuracy. 3. Risk Mitigation: - Identify risks like delays or resource contingencies and plan buffer times for each milestone. --- 𝟑. 𝐏𝐫𝐨𝐝𝐮𝐜𝐭 𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐦𝐞𝐧𝐭 Cause of Actions 1. AI Model Development: - Start with supervised learning using historical DeFi data to identify yield rates, token prices, looping, oracles, LST, and LRT strategies. - Train a reinforcement learning agent to optimize for risk-adjusted returns. - Integrate real-time data feeds using Chainlink or The Graph to keep the AI updated. Chainlink, most preferably. 2. Smart Contract Integration: - Write a simple Solidity contract to allocate funds to a single liquidity pool. - Test its functionality on testnet. - Expand to multiple protocols, ensuring smart contracts can handle cross-chain interactions using bridges. 3. UI/UX Development: - Build a web interface with React.js, enabling users to connect wallets via Web3.js. - Add basic features. Examples include yield strategies, tracking returns, and adjusting risk tolerance. --- 𝟒. 𝐅𝐮𝐧𝐝𝐢𝐧𝐠 Cause of Actions 1. Grant Applications: - Apply to the Ethereum or Solana Foundations or Hackathon to secure funding. - Create a detailed grant proposal highlighting the value proposition. 2. Fund Allocation: - Create a budget framework for using funds for AI model training, audits, and marketing. --- 𝟓. 𝐒𝐦𝐚𝐫𝐭 𝐂𝐨𝐧𝐭𝐫𝐚𝐜𝐭 𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐦𝐞𝐧𝐭 Cause of Actions 1. Development: - Build modular smart contracts with separate functions for fund allocation, yield collection, and risk monitoring. - Write optimized code to reduce gas, focusing on operations that involve withdrawals or yield reinvestments. 2. Audits: - Engage OpenZeppelin to perform smart contract audits. - Use MythX to catch common vulnerabilities. 3. Testing: - Deploy contracts on testnets and simulate stress scenarios (i.e., identifying feedback loops, such as rapid price change effects). --- 𝟔. 𝐌𝐚𝐫𝐤𝐞𝐭𝐢𝐧𝐠 Cause of Actions 1. Content Creation: - Publish beginner-friendly guides on yield farming and how Rubiks simplifies it. - Share technical insights into Rubik’s AI-driven architecture through blogs and videos. 2. Community Engagement: - TG launch and community building with potential users and developers. 3. Promotional Campaigns: - Referral program during the beta testing phase to attract early users. - Host a hackathon encouraging developers to build on top of Rubiks. --- 𝟕. 𝐓𝐨𝐤𝐞𝐧 𝐃𝐞𝐜𝐢𝐬𝐢𝐨𝐧 Cause of Actions 1. Option A: Launch Token - Design a community-driven tokenomics. - Create a link between the product and the token with possible incentive operations, demand side programs, and revenue framework for the Rubiks Backend Development. 2. Option B: No Token - Implement a subscription-based revenue model, offering tiered pricing for advanced features. - Focus on partnerships to secure direct revenue streams. --- 𝟖. 𝐏𝐫𝐨𝐝𝐮𝐜𝐭 𝐓𝐞𝐬𝐭𝐢𝐧𝐠 Cause of Actions 1. Internal QA: - Simulate different user scenarios (e.g., deploying $100 vs. $1M across pools) to identify edge cases. - Test Rubiks’ performance during sudden market shocks. 2. Performance Benchmarking: - Compare Rubik’s yields with popular optimization platforms and ensure it outperforms them in at least one area. --- 𝟗. 𝐋𝐚𝐮𝐧𝐜𝐡 Cause of Actions 1. Soft Launch: - Roll out Rubiks to a limited audience, focusing on gathering feedback and fixing any final bugs. - Monitor active users and TVL growth. 2. Hard Launch: - Launch Announcements. - Offer promotional rewards for early adopters. 3. Post-Launch Monitoring: - Continuously track user engagement and iterate on feedback to improve Rubik’s functionality. --- Total Duration: 6-8 months. This is Rubiks, an AI Agent built under a scrutinized development framework. Is this a feasible development plan, and how do you see the Agent's performance in the next few months after launch? Thanks for reading!!!

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