Degenai is a very popular AI meme project today. My friend asked me to help take a look, although it can achieve simple AI automated trading, it is still too simple and singular. We have reviewed the Github code. Let's briefly talk about this project. Spartan is a DeFi quantitative trading agent based on Solana, with a multi plugin architecture that supports multiple functions such as automated trading, intelligence collection, community investment, LP management, and AI model access. It has a front-end and back-end (React) display interface, emphasizing multi platform integration (Discord, Telegram, Twitter). Core advantages: one ️⃣ Technical Architecture and Capability Multi plugin architecture: highly modular, easy to expand and maintain. Multi platform integration: Supports Discord, Telegram, Twitter, suitable for community driven and automated operations. Deep integration of blockchain: The core is Solana blockchain, which can directly interact with DEX (Orca, Raydium, Meteora) on the chain and has LP management and automatic transaction capabilities. AI capability: Supports large model plugins such as OpenAI, Anthropic, Groq, etc., with intelligent analysis and automatic decision-making capabilities. Data analysis and visualization: Built in data capture, intelligence analysis, market trend tracking, and a React front-end for data visualization. Task scheduling and caching: Built in task system and data caching to improve performance and automation level. two ️⃣ Teamwork and Maintainability The code structure is clear: the layers of plugins, services, tasks, and front-end are obvious, making it easy for multiple people to collaborate and maintain in the later stage. Testing System: Built in Vitest testing to ensure functional reliability. The drawbacks are also quite obvious: one ️⃣ Technology stack limitations The blockchain platform is single: currently only Solana is supported, and there is no mainstream chain support such as Ethereum (such as Web3.js/others. js), with slightly limited scalability. Limited Python capabilities: The main code is TypeScript/Node.js, and there is very little Python related content, which is not suitable for scenarios that require a Python ecosystem. two ️⃣ Dependency and complex environment Multiple dependencies: Multiple API keys (AI, DeFi, social platforms, databases, etc.) need to be configured, there are many environmental variables, and the threshold for getting started is high. Security challenge: Involving sensitive information such as private keys and API keys, special attention should be paid to security during deployment. three ️⃣ other The document is somewhat brief: although the structure is clear, there are few detailed use cases and plugin extension explanations, making it difficult for beginners to get started. Lack of outstanding crawling ability: Although there is intelligence gathering, traditional crawling techniques such as Scrapy/BeautifulSoup have not been seen, and more reliance is placed on APIs. Overall, the rating is only 57 points, and we usually only consider AI projects that score above 80 points. in compliance with 👇 The picture. In the end, it's better not to get in the car. 😅