From fixed workflows to adaptive systems
Traditional software generally follows predefined rules and workflows. AI agents introduce another approach where systems can interpret goals, decide what steps may be required, and adapt their behavior based on available information.
The role of tools and context
An AI agent becomes more useful when it can access relevant tools, data, and external systems. This can allow an agent to retrieve information, interact with applications, and perform actions instead of simply generating a response.
Where agents may create value
Agentic systems may support tasks involving research, information retrieval, workflow coordination, customer assistance, software operations, and other multi-step processes where fixed automation can become difficult to maintain.
The importance of evaluation
Greater autonomy also introduces new challenges. Agents need clear boundaries, reliable tools, useful context, and evaluation methods that help measure whether their actions are actually producing the intended result.