Thanks for your interest! We decided to split the AI system into Thinkers, Actors, and Communicators for several reasons.
Firstly, it makes each part more reliable and easier to maintain. This division allows us to craft specific prompts for each component based on their function and the information they deal with. The segregation also allows for better data management and focused improvement in case of performance issues or potential upgrades.
Secondly, it provides a smooth data flow. The Thinker receives a prompt tied to the user's question and starts gathering relevant data. This data then flows to the Actor, which uses it to respond to the user's query or to execute tasks. For example, if a user says "build an automation to buy the dips for the top 10 stocks by market cap in the US," the Thinker first gathers the top 10 stocks from our screener, then the Actor creates the strategy.
Finally, the Communicator receives the outcomes of the actions from the Actor, and it's responsible for relaying the information back to the user in an easy-to-understand format. It ensures that the actions taken by the AI and the results are transparent and understood by the user.
Regarding the prompts for each agent, they outline the commands each agent can access, as provided by DionysusDSL. We use the inputs to these commands to form a "tree" of possible types the AI might need to use. Then, we build a prompt demonstrating these types, allowing for accurate and context-specific responses. Each agent's prompts differ based on their role and the tasks they need to perform.
Just curious, how did you come to the conclusion to split up the different agents? What’s the difference in each of their prompts?