Concept

AI agents are systems that leverage large language models (LLMs) to independently accomplish tasks on your behalf. They can perform workflows with a high degree of independence.

Key aspects of AI agents described in the sources include:

• They have evolved beyond simpler models or "agentic if-statements" towards more autonomous systems.
• They are trained to observe, reason, plan, and use tools and resources to act within their environments.
• They use an LLM to manage workflow execution, make decisions, recognize workflow completion, self-correct, and handle failures by transferring control.
• They have access to various external tools and APIs to gather context and take actions, dynamically selecting the appropriate tools.
• Agents can also work together in networks and with humans to accomplish complex tasks or automate multi-step processes, forming multi-agent systems.

In their fundamental form, agents consist of three core components: the Model (the LLM for reasoning and decision-making), Tools (for interacting with external systems), and Instructions (guidelines and guardrails). Unlike conventional software, agents are particularly suited for workflows involving nuanced judgment, complex decision-making, difficult-to-maintain rules, or heavy reliance on unstructured data.