Tactical AI

Our project was to run a low cost simultaneous series of agents that interact with the same environmental conditions and collaborate on the same output documents. We initially had the ambition to run 10 Upper Level Suite agents (long term themes/short term goals: 3 year to 3 month); 30 supporting agents (2 week check ups; daily repeat functions) but we were unable to get enough domain knowledge sets for this particular project. So we ran with the domain knowledge we had and eventually decided on testing a "Human - Machine Teaming" model that would be designed to help humans trust the power of the technology without it seeming threatening by identifying the sources of our domain knowledge sets, setting the map of their agenda, storing the information of their agenda in pinecone and synthesizing that with domain knowledge specific to the role. Also, Super AGI has a tool that allows for document modification and that allowed us to have the agents interact on the same document from multiple perspectives. The end result was actionable data with very few errors. The amount of work done in the time to actually set up the agents, set the map of the project and process goals for each agent was nothing compared to the amount of work we received from the agents. It was about 40 hours of labor for 4 people produced in 1 run which you can see the outputs in Github. Anyways, thank you for hosting the space. Be well.