Skip to contentSkip to navigationSkip to topbar
Page toolsOn this page
Looking for more inspiration?Visit the

What are autonomous agents?


Autonomous agents are artificial intelligence (AI) systems that can perform a series of complex tasks entirely undirected to achieve a goal. To do this, an autonomous agent needs to reason, plan, and interact with the necessary systems and real world to solve the problem.


How autonomous agents are built

how-autonomous-agents-are-built page anchor

Sparked by the rapid advance of Large Language Models (LLMs), researchers and companies build purpose-built "agents" that can perform a set of tasks. These agents use different techniques to leverage LLM capabilities and work around limitations. These techniques include prompting strategies such as "Chain of Thought" prompts(link takes you to an external page) where an LLM is asked to think through a problem step by step and outline what actions it would like to perform.

Some of the most known research projects that have been moving the exploration of agents forward are the Generative Agents(link takes you to an external page) paper that used GPT-3.5 to create a small town simulation of different agents interacting with each other, as well as the Voyager project(link takes you to an external page) an LLM-powered agent that was left alone to play and control Minecraft by being able to generate code and learn new skills.


Agents and the impact on customer engagement

agents-and-the-impact-on-customer-engagement page anchor

As AI companies develop increasingly-capable agents, more companies are looking to leverage agents for parts of their customer engagement, whether for customer support, initial sales engagements or to provide customers with a type of "copilot" that can help the customer navigate and set up their product.