Make AI Agents

make ai agents is available in open beta to all customers on paid plans as a beta feature, both product functionality and pricing may change ai agent is an autonomous system that acts within the defined context and constraints to achieve a goal to achieve the goal, the ai agent uses reasoning powered by a large language model (llm) the ai agent is like your assistant who performs tasks for you and uses its best judgment to complete them this makes the agent flexible, but it might be also harder to predict the agent's results using agents changes the way you approach automation instead of thinking about how to reach a goal, and which modules and transformations you need to use, you can now focus on just defining the goal with the ai agent, your automation design becomes goal oriented instead of process oriented when you create an ai agent, you provide the agent with its definition, purpose, and constraints in the agent's system prompt these definitions form the base of how your agent operates when you use an agent in a {{scenario singular lowercase}} , you provide the agent with tools to reach the goal you send in the message the agent's tools are {{scenario plural lowercase}} that the agent runs on your behalf to complete the task you requested the agent uses {{scenario singular lowercase}} name and description to determine when to use them to achieve the goal all {{scenario plural lowercase}} used as tools for ai agents must be scheduled on demand or triggered by a custom webhook {{product name}} doesn't add {{scenario singular lowercase}} blueprints to the ai agent's context all agent's reasoning happens based on the information in the agents description and its tools ( {{scenario plural lowercase}} ) names and descriptions {{product name}} doesn't share {{scenario singular lowercase}} data anywhere providing the right agent with the right tools can reduce the complexity of your automations the agent can use reasoning to decide which tools to use depending on the inputs, which can substitute for having multiple routes and filters if you want to send data to the agent, you have to use scenario inputs and scenario outputs docid\ di1pkxe4s6 striu9spvv and the scenarios > return output module the make ai agent's reasoning is transparent and easy to review however, llms are still evolving, which could impact agent outcomes always check outputs to ensure their accuracy and reliability