From chatbots to agents
A chatbot answers. An agent acts. Given a goal — "follow up with all leads that haven't responded in three days" — an agent can look up leads, draft messages, send them through approved channels and update records.
How AI agents work
- Understand the request using a language model.
- Plan the steps needed.
- Use tools — APIs for search, databases, CRM, email.
- Observe results and adjust.
- Finish or escalate to a human.
Tools
Tools are functions the agent may call, each with a clear description and strict input validation.
Memory and state
Agents track conversation history and task progress. Frameworks like LangGraph make this state explicit.
Guardrails
Permissions, rate limits, approval steps and logging.
Business use cases
- Sales: qualify leads, schedule meetings, update CRM.
- Support: resolve common queries with cited answers.
- Operations: process documents, reconcile records.
- HR: answer policy questions, assist onboarding.
Deploying safely
Start with read-only tasks, then add write actions with approval. Evaluate against real scenarios and monitor continuously. Learn more about our AI development services and AI Agents.
Conclusion
AI agents are becoming a practical way to automate knowledge work. The winners will be companies that connect agents to real systems with the right controls.
