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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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