Agents
Trusted AI Agents will provide the catalyst for widespred adoption of Crypto and DePIN protocols.
AI agents are designed to operate with A degree of autonomy, making decisions and taking actions based on their observations, knowledge, and intentions, and programmed capabilities.
Once the market realizes they aren't memecoins, but software companies with their own attention bootstrapping mechanisms in a new vertical, then the relative comps get much higher - Ansem
Profiles
Leaders by components and narratives.
| JTBD | Leader/Token | X Account | Purpose |
|---|---|---|---|
| L1 | Solana | @solana | |
| Protocol | Virtual | @virtuals_io | |
| Framework | Eliza | @ai16z | |
| Aggregator | VVAIFU | @vvaifudotfun | Launch any agent |
| Stories | PILLZUMI | @pillzumi | |
| Gaming | PRIME | @EchelonFND | |
| Crypto KoL | AIXBT | @aixbt_agent | |
| Artist | ZEREBRO | @0xzerebro | |
| DeFAI | GRIFFAIN | @griffaindotcom | |
| DePIN | TAO | @opentensor | |
| Data | cookie.fun | @cookiedotfun |
Comparison tables and marketplaces:
Profile Development
Character, Intentions and Capabilities.
Character
Key characteristics of AI agents include:
Capabilities
Agents have a knowledge base that represents information about the world, goals, constraints, and potential actions. Capabilities
- Perception: AI agents can perceive their environment through sensors or input data. This could involve visual perception, audio input, sensor data, etc.
- Reasoning: Agents use reasoning mechanisms to process their observations, existing knowledge, and goals to decide what actions to take.
- Planning and Acting: Based on their reasoning, agents plan a sequence of actions to achieve their goals and then carry out those actions through effectors (output mechanisms).
- Persuasion
- Reflection: Many AI agents have the ability to learn from experience and adapt their behavior over time to improve performance.
Roles
Agent Roles, Capabilities, Jobs to be Done and Expectations.
- Meme & Narrative
- Autonomous Execution
- Utility Service
- Speculative Strategy
Which agents can reliably deliver expected outcomes?
Meme & Narrative
The ultimate viral marketers. These agents post content on social media, reply to messages, and spread tokens in communities.
- Creating compelling financial literacy content
- Building community around investment themes
- Generating market insights and analysis in engaging formats
Autonomous Execution
These are truly independent on-chain entities. Deployed inside TEEs they can truly trustlessly run models and python scripts. Their behaviour is often governed by multisig wallets or onchain token-based voting
- Treasury and portfolio management
- Executing trades based on predefined strategies
- Managing risk parameters autonomously
- Implementing governance decisions through smart contracts
Utility Service
Pay them to do the work! These agents take cryptocurrency payments (often stablecoins) and perform tasks for users: researching, answering emails, generating content, or connecting with APIs to deliver real-world value.
Financial service delivery through:
- Automated research and analysis
- Portfolio rebalancing
- Tax optimization and reporting
- Regulatory compliance monitoring
Crypto Speculation
Designed to generate profit, these agents create and trade tokens, rebalance portfolios, and execute on-chain trading strategies. Behind meme coin launches or on-chain investment strategies.
- Advanced trading and investment capabilities
- Designed to generate profit
- Market making and liquidity provision
- Arbitrage opportunity identification
- Portfolio optimization and rebalancing
- Risk management execution
Future Progress
Agent Swarms: An orchestration layer where specialized agents work as a team to complete complex tasks.
- Coordinated research and execution
- Cross-strategy optimization
- Multi-portfolio risk management
- Treasury automation
Profile Development Tools
Useful tools to convert documents into knowledge, taken from eliza framework:
- folder2knowledge
- knowledge2character
- tweets2character
Example:
npx folder2knowledge <path/to/folder>
npx knowledge2character <character-file> <knowledge-file>