The technology behind this AI agent is a multi-agent system that utilizes a core react-like loop and various tools to assist users in coding tasks.

An AI agent is defined as a system that allows a language model to autonomously decide how many times to run processes until it finds a resolution, rather than following a predefined path.

The goal is to enable every knowledge worker to become an agent manager, managing fleets of AI agents instead of just performing traditional knowledge work.

The development of AI agents involves creating systems that can autonomously handle tasks and communicate issues back to users for resolution.

AI agents are often defined as systems that perform complex planning and interact with external systems, but this definition overlaps with many current language models.

AI agents are expected to handle most mundane tasks, significantly lowering barriers for developers and making complex tasks like coding more accessible to everyone.

The biggest variation in AI agent behaviors is their ability to take real-world actions, influenced by software integrations and company trust in these tools.

Companies are focusing on workflows and multi-agent systems to mimic human decision-making processes in AI.

The future of AI agents may involve them being able to access and interact with data traditionally reserved for humans, such as logging into websites or executing commands on servers.