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AI Agents

An AI agent is a software program or system that can perceive its environment, process that information, and take actions to achieve specific goals.

Multi-Agent Workflows: AI agents are designed to operate with some degree of autonomy, making decisions and taking actions based on their observations, knowledge, and programming.

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

Agents​

Engineering​

Characteristics​

Key characteristics of AI agents include:

  • Perception: AI agents can perceive their environment through sensors or input data. This could involve visual perception, audio input, sensor data, etc.
  • Knowledge Representation: Agents have a knowledge base that represents information about the world, goals, constraints, and potential actions.
  • 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).
  • Learning: Many AI agents have the ability to learn from experience and adapt their behavior over time to improve performance.
  • Drive
  • Archetypes
  • Biases
  • Character
  • Capabilities
  • Persuasion

Roles​

Use jobs to be done analysis to determine what products could you recruit to streamline traditional business roles to free up human resources to tackle more valuable tasks that require deep thought and imagination.

How will crypto agent roles impact traditional work roles performed by humans and formation of new business opportunities?

  • Meme & Narrative
  • Autonomous Execution
  • Utility Service
  • Speculative Strategy

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

Speculative Strategy​

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

Prompting​

Basic interaction with AI, need to build agents to do anything really valuable.

The five most important components of engineering a prompt for an AI Agent are:

  1. Model
  2. Purpose
  3. Variables
  4. Examples
  5. Output

See Prompt Engineering

Open Source Code​

Attachments​

YouTube Creators​

Social​