What makes it different from a chatbot
An AI agent receives a goal and then plans its own steps, calls tools, verifies outputs and retries if needed.
Where chatbots answer questions, agents say 'I will plan and execute the steps to solve the problem.'
Where the enterprise value is
Agents excel at long tasks, multi-system coordination and operations needing human-level decisions.
Examples: proposal preparation, contract comparison, ticket triage, financial analysis, campaign optimization.
Right scope for the first agent project
Skip 'autonomous everything' early. Start narrow — e.g. only ticket triage or only GDPR-form replies. Confidence is built that way.
Agent success requires crisp tool definitions, clear goals, bounded scope and human review points.
Pitfalls to avoid
Weak tool docs cause agents to call the wrong endpoints. Without observability, failures compound silently.
Healthy agent delivery includes observability, cost budgets and security layering from day one.
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