🤖 Agent & Autonomous Prompting Techniques

ReAct (Reasoning + Acting) prompting interleaves chain-of-thought reasoning with concrete actions like searching, calculating, or calling APIs. The model thinks about what it needs to do, takes an action, observes the result, then reasons about the next step.

Prompt chaining breaks a complex task into a sequence of simpler prompts, where each prompt's output becomes the next prompt's input. Like an assembly line, each step handles one specific sub-task, producing higher quality results than a single monolithic prompt.

Reflexion is a technique where the AI agent reflects on its failures from previous attempts to improve future performance. After a task attempt fails or produces suboptimal results, the model generates a verbal reflection on what went wrong and uses that insight for the next attempt.