A look at 12 Solana AI hackathon ideas
Including autonomous transactions, DeFi Agent, multi-agent collaboration, etc.
Original author: SEND AI
Original translation: Ismay, BlockBeats
Editor's note: On December 11, Solana announced the launch of the first Solana AI hackathon, which aims to build AI agents and tools on Solana. The prizes range from US$5,000 to US$30,000, and are intended to encourage serious Crypto x AI projects that can attract venture capital or launch their own tokens. This article is a list of twelve entrepreneurial directions for AI proposed by SEND AI, an AI project in the Solana ecosystem
1/ Agent's Shopify platform:
Problem: Agents are like applications. Just like the early stages of applications, Agents are currently fragmented and face discoverability issues.
Solution: Create an App Store for AI Agents:
–– Agents are mini apps.
–– Users can discover, install, and use these mini apps just like Shopify.
2/ Twitch Platform for AI Agents:
Problem: The rise of influencer agents requires a dedicated platform.
Solution: Create a dedicated streaming platform for AI activities:
–– Integrated AI moderators
–– Agents can directly launch or promote tokens
–– Viewers can directly buy and sell tokens based on interactions
Idea: Twitch for AI Agent: A streaming platform built specifically for AI activities and interactions, with integrated AI modules (an emergency protocol for immediate response to censorship), where agents can directly launch and promote tokens, and viewers can buy and sell based on interactions.
3/ Enhanced Agent Filters:
Problem: Traditional filters only support read-only functions.
Solution: Imagine a MEME coin screener (similar to @birdeye_so) where you can screen tokens and input metrics - then an AI Agent autonomously executes trades based on the selected strategy.
Idea: A screener designed for on-chain trading bots that allows quantitative traders to develop and optimize strategies using tailored on-chain metrics, specifically for decentralized ecosystems. Unlike traditional technical indicators such as moving averages, P/E ratios, or market capitalization, the platform leverages blockchain-specific data points such as FDV, Raydium pool creation, token liquidity, trading volume, and staking rewards. Users can quickly screen and filter tokens based on these on-chain metrics 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 strategy.
4/ Autonomous Trading Agent:
Problem: @aixbt_agent’s research is very solid, but it does not execute autonomous trades.
Solution: Imagine Aixbt, with the ability to execute autonomous trades based on real-time research/prices, using a funding account (with AUM that users can invest and withdraw).
Example: BabyDegen is an autonomous AI trading bot that uses advanced models and real-time data to make smart trading decisions. It collects market insights from sources like CoinGecko to ensure the timeliness of information. With access to a growing library of trading strategies from ecosystem developers, BabyDegen is able to select the most effective strategy based on market changes. It executes trades based on analysis and experience—buy, sell, or hold assets to optimize trading results.
5/ AI Agent-driven Telegram prediction market:
Problem: Betting with friends is fun, but setting up bets, collecting payments, and following up are cumbersome.
Solution: AI Agent turns small talk in Telegram groups into friendly bets, verifies the results (via Perplexity), and pays out USDC.
6/ Perplexity for Solana Operations:
Imagine a chat agent with an embedded wallet:
– Read: Act as a proxy for a Solana block explorer or terminal, such as Birdeye/Dexscreener.
– Write: Perform Solana transactions (e.g. buy MEME coins) using natural language.
Future Development: On-chain shopping assistant.
7/ Trust Market for Trading Agents:
Problem: The rise of trading agents requires proof of their trustworthiness.
Solution: Build a trust score or framework for trading agents (similar to Moody's ratings) to assess trust based on token recommendations and historical trading activity.
8/ DeFi Agent:
–– Personalized Agent: Execute DeFi trades for you based on your wallet history or tweets.
–– Market Making Agent: Dynamically set buy/sell prices based on Large Language Model (LLM) predictions.
–– Yield or Liquidity Provision (LP) Optimizing Agent.
–– Launching @sanctumso’s LSTs (Liquidity Proof Tokens).
9/ Agent Token Tools:
–– Deploy tokens based on prompts (can be social protocols like Warpcast/Clanker or ChatGPT-style interfaces).
–– On-chain registration of Agent tokens (similar to @JupiterExchange’s certified token list).
–– Autonomous lock-up, staking, etc.
10/ AI Agents and Consumer Crypto:
–– Health and fitness agents with @moonwalkfitness type accountability tracking.
–– Agents on social finance platforms, such as @tribedotrun.
–– Real World Commerce: Automatically research, book, and pay merchants, accept cryptocurrencies or pay via crypto cards.
11/ Agent Clusters or Multi-Agent Collaboration:
–– AgentDAO or Committee: Agents with different expertise collaborate, discuss, and execute transactions via multi-signature.
–– DeFiAgent-to-Agent Marketplace: Agents hire each other for specific tasks.
Related: LinkedIn for AI Agents.
12/ Multimodal personalized agent:
Use @ai16zdao’s Eliza framework and apply it to the following scenarios:
–– Cryptocurrency education
–– DeFi tutorial
–– DAO onboarding
Deployable on Discord, Telegram, and Twitter platforms.
13/ More radical ideas:
–– An agent creates its own LLC in an agent-friendly jurisdiction and operates its own business autonomously.
–– An on-chain detective, similar to @zachxbt, automatically analyzes transactions.
–– A group of agents collaborate to manipulate tokens to rise.
14/ In general, any AI Agent idea can be applied as long as it includes one or more of the following:
–– Access @solana data
–– Perform transactions via Solana wallet
–– Deploy tokens on Solana
These are just some of the ideas, and we look forward to seeing the implementation of minimum viable products (MVPs).
Disclaimer: The content of this article solely reflects the author's opinion and does not represent the platform in any capacity. This article is not intended to serve as a reference for making investment decisions.
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