This article presents twelve entrepreneurial directions related to AI Agents proposed by SEND AI, an AI project within the Solana ecosystem, compiled and edited by BlockBeats. (Background: Focus on AI Agents) Solana will host its first artificial intelligence hackathon, with ai16z, ELIZA... concept coins all rising.) (Background context: Behind the hype of AI Agents, what can they really do for people?) On December 11, Solana announced the launch of its first Solana AI hackathon, aiming to build AI agents and tools on Solana, with prizes ranging from $5,000 to $30,000, designed to encourage serious Crypto x AI projects that can attract venture capital or launch their own tokens. This article outlines twelve entrepreneurial directions related to AI proposed by SEND AI, an AI project within the Solana ecosystem. 1/ Shopify platform for Agents: Problem: Agents are fragmented like applications. Just as early-stage applications faced discoverability issues, Agents currently also face fragmentation problems. Solution: Build an app store for AI Agents: –– Agents are mini-apps. –– Users can explore, install, and use these mini-apps just like using Shopify. 2/ Twitch platform for AI Agents: Problem: The rise of influencer Agents needs a dedicated platform. Solution: Create a dedicated streaming platform for AI activities: –– Integrate AI moderators –– Agents can directly launch or promote tokens –– Viewers can buy and sell tokens based on interactions Idea: Twitch for AI Agents: a streaming platform specifically designed for AI events and interactions, integrating AI modules (emergency protocols for real-time response to censorship), where agents can directly launch and promote tokens, and viewers trade based on interaction. 3/ Enhanced Agent filter: Problem: Traditional filters only support read-only functionality. Solution: Imagine a MEME coin filter (similar to @birdeye_so), where you can filter tokens and input indicators — then an AI Agent autonomously executes trades based on the selected strategy. Idea: A filter designed for on-chain trading bots that allows quantitative traders to develop and optimize strategies using tailored on-chain indicators, specifically serving decentralized ecosystems. Unlike traditional technical indicators (like moving averages, P/E ratios, or market cap), this platform leverages blockchain-specific data points, such as FDV, Raydium pool creation, token liquidity, trading volume, and staking rewards. Users can quickly filter and sift through tokens based on these on-chain indicators to identify high-potential assets. Ultimately, the platform simplifies the process of applying these conditions to on-chain trading bots, which can autonomously execute trades based on the selected strategies. 4/ Autonomous trading Agent: Problem: @aixbt_agent's research is solid, but it does not execute autonomous trading. Solution: Imagine Aixbt, capable of executing autonomous trades based on real-time research/prices, using a fund account (with user-manageable assets for investment and withdrawal). Case: BabyDegen is an autonomous AI trading bot that makes informed trading decisions using advanced models and real-time data. It collects market insights from sources like CoinGecko to ensure the timeliness of information. By accessing an ever-growing library of trading strategies from ecosystem developers, BabyDegen can select the most effective strategies based on market changes. It executes trades — buying, selling, or holding assets — based on analysis and experience, optimizing trading outcomes. 5/ AI Agent-driven Telegram prediction market: Problem: Betting with friends is fun, but setting up bets, collecting payments, and following up can be cumbersome. Solution: The AI Agent transforms casual chat in Telegram groups into friendly bets, verifies results (via Perplexity), and pays in USDC. 6/ Perplexity for Solana operations: Imagine a chat agent with an embedded wallet: – Read: acting as a Solana block explorer or terminal, like Birdeye/Dexscreener. – Write: executing Solana trades using natural language (e.g., buying MEME coins). Future development: on-chain shopping assistant. 7/ Trust market for trading Agents: Problem: The rise of trading Agents requires proving their credibility. Solution: Establish a trust scoring or framework for trading Agents (similar to Moody's ratings), assessing trustworthiness based on token recommendations and historical trading activity. 8/ DeFi Agent: –– Personalized Agent: Executes DeFi trades based on your wallet history or tweets. –– Market-making Agent: Dynamically sets buy/sell prices based on large language models (LLM). –– Yield or liquidity provision (LP) optimization Agent. –– Launch LSTs (liquidity staking tokens) of @sanctumso. 9/ Agent token tools: –– Token deployment based on prompts (could be social protocols like Warpcast/Clanker or ChatGPT-style interfaces). –– On-chain registration of Agent tokens (similar to the certified token list of @JupiterExchange). –– Autonomously locking, staking, etc. 10/ AI Agents and consumer crypto: –– Health and fitness Agent with responsibility tracking features like @moonwalkfitness. –– Agents on social finance platforms, such as @tribedotrun. –– Real-world business: automatically researching, booking, and paying merchants, accepting cryptocurrency or payments via crypto cards. 11/ Agent clusters or multi-Agent collaboration: –– AgentDAO or committee: Agents with different expertise collaborate, discuss, and execute trades through multi-signature. –– DeFiAgent for Agent market: Agents mutually hire each other for specific tasks. Related: LinkedIn for AI Agents. 12/ Multi-modal personalized Agent: Utilizing the Eliza framework of @ai16z dao, applied in the following scenarios: –– Cryptocurrency education –– DeFi tutorials –– DAO onboarding training Can be deployed on Discord, Telegram, and Twitter platforms. 13/ More radical ideas: –– An Agent establishing its own LLC within a jurisdiction friendly to Agents,...

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