LLM Powered Autonomous Agents

An agent can be thought of as a logical wrapper around an LLM, allowing us to add several features to our AI systems, primarily:

• Tool usage, such as calling APIs for info, executing code,


• Internal thoughts over multiple generation steps


• Ability to use various tools and reasoning steps to answer more complex queries.


• Parallel agents can go and complete

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An LLM’s abilities are amplified when combined using emerging agent frameworks like BabyAGI, AutoGPT and ChatArena. These frameworks break down workflows into a series of discrete roles each handled by AI agents, which are given a defined objective and work together to automate a complex task.

Initially, this will take the form of human-AI collabora... See more

First off, a primer on autonomous agents: - Give them a task - Give them memory - Give them access to tools - They decide on-the-fly how to accomplish your task and remove you from this process because... it's autonomous - Watch them attempt to do the work

LLMs combine what they “learned” in training with any new context you give them. There are many ways to give the AI additional context, the most common is in the prompt that you provide (“You should act like a marketer and help me respond to a request for proposal”), or any documents you upload to the AI.