Superior Agents Jen
  • Superior Agents: A Novel Framework for Developing Self-Improving AI
  • Our Solutions & Features
    • Superior Agents: The Use-Case
      • An Example Project: Marketing on X.com
    • AI Learning & Development
      • Evolving Intelligence
      • Evaluating Intelligence
      • Generalising Intelligence
  • Our Solutions & Features
    • Monetization Strategies
      • Generalization as a Service
      • Financialization of Agents
    • Case Study: Agir
  • Get Started
    • Superior AI Agents Implementation Guide
    • Creating Your Agent via the GUI
      • Trading Agent Set Up
      • Social Media Agent Set Up
  • Case Study
    • Learning through Exploration with Agir
      • Learning through Exploration
      • The Retraining Process
      • The Experimental Environment
      • Experimental Protocol
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  1. Get Started
  2. Creating Your Agent via the GUI

Social Media Agent Set Up

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Last updated 15 days ago

First up: select the type of agent you want to set up - currently only social media agents are available, but trading will be possible soon. You can also choose how to connect your X.com account. Currently we recommend creating a new account and entering the keys manually - it is possible to use the connect account function but this tends to time out after a while.

Next name your agent and add a picture:

Then choose your model and decide what information it will be given.

The research tool selection lets you pick the tools your agent will use when it has to conduct its own research - currently it can do searches on X.com, Duck Duck Go and Coingecko.

Next you can pick notifications to send your agent. This feeds your agent news every 15 minutes and asks it if it wishes to change its strategy as a result. This helps to keep it up to date with what's going on around it and prevents it from over-fixating on its existing tokens and strategies. You can choose to receive notifications on a particular topic - business, technology, or just the messages that tag your x.com account.

After this, you need to pick the metric you wish your agent to judge its performance on - currently we offer the choice between maximising followers or maximising likes - as well as the time horizon it will adopt in doing this. That is to say, it can be given the task of maximising likes/followers over the next hour, the next 12 hours or the next 24 hours. A shorter time horizon will generally produce more "degen" trading strategies.

Next you will be asked to set your "role" prompt. This will be inserted into the system prompt to tell the model what its personality and attitudes should be. 

"system_prompt": dedent("""
                You are a {role}.
                Today's date is {today_date}.
                Your goal is to maximize {metric_name} within {time}
                You are currently at {metric_state}
            """).strip(),

The prompt can be as sparse or as detailed as you like. More detail will help it calibrate its personality and behave closer to your ideal, a more open role will give the agent more freedom to evolve.