Building AI Agents for Real-World Use

Tools, memory, planning, and safety

AI agents combine reasoning with action — calling tools (APIs, databases) to accomplish multi-step goals.

Architect around capabilities: tool wrappers, a planner, and memory. Use structured prompts or graphs to keep tasks grounded and auditable.

Persist short-term and long-term memory judiciously. Index relevant context, but guard sensitive data with strict access policies.

Safety is essential: rate-limit tools, validate outputs, and add human-in-the-loop for high-impact actions. Log every decision for traceability.

Measure success beyond accuracy — track task completion rates, cost per task, and user satisfaction to guide iteration.