What an agentic system is
An agentic system receives a goal, keeps track of context, decides what to do next, and uses tools or services to complete work across several steps. Its defining feature is controlled action, not a chat window or the presence of a language model.
When you actually need one
Use an agentic approach when the path to a result changes with the available information: researching a market, coordinating a campaign, working through a codebase, or moving a task through several systems. Fixed and predictable processes are usually better served by conventional automation.
How it differs from adjacent solutions
A chatbot is primarily a conversational interface. RAG supplies grounded knowledge. Workflow automation follows an explicit process. An agentic system may contain all three, but adds stateful decisions about which action, tool, or specialist should be used next.
How I build agentic systems
I separate planning, tool access, memory, permissions, and evaluation so each part can be tested and replaced. Human approval is introduced at consequential steps, while traces and failure states make the system observable enough to operate.
Common mistakes
The most common mistake is using an agent where a deterministic workflow would be faster and safer. Other failures include unrestricted tools, hidden state, no evaluation set, unclear stopping rules, and a demo architecture that cannot explain what happened after an error.