AI Agents

The difference between a chatbot and an agent is not language ability but latitude. A chatbot answers a question. An agent is given a goal, decides for itself which steps lead there, calls tools to take them - database queries, APIs, file access - and evaluates the results before choosing the next step.

That makes agents strong where a task is clearly describable but not programmable as a fixed sequence: checking an invoice whose format every supplier chooses differently; a piece of research whose next step depends on the last finding; a ticket that belongs in different systems depending on its content. A classic workflow would have to know every case in advance. An agent does not.

That same latitude is the risk. An agent allowed to change systems can change the wrong thing. What makes it production-ready is guardrails: narrowly scoped tools rather than general system access, write permissions only where they are needed, a ceiling on steps and cost, and escalation to a human as soon as the agent is uncertain or something irreversible is at stake.

The second point is traceability. If nobody can reconstruct why an agent acted as it did, you can neither fix a fault nor defend an outcome. So we log every tool call with its input and result - that is the basis for tests, for debugging, and for the conversation with an auditor.