How to Build an AI Agent for Your Company

Step 1: Define one job

Write the agent's job like a role description: its goal, the inputs it receives, the outcome it must produce and when it must hand over to a person.

Step 2: List the tools it needs

Each capability becomes a tool — search the knowledge base, look up a customer, create a ticket, send an email, book a slot. Give the agent only the tools the job requires.

Step 3: Design guardrails

Decide which actions need approval, set limits (amounts, recipients, record types), validate outputs against rules and log every tool call.

Step 4: Choose model and framework

Pick the language model for the quality, speed and cost the job needs — OpenAI, Claude, Gemini or an open model such as Llama or Mistral. Use a framework such as LangGraph, CrewAI or AutoGen when orchestration is complex; lightweight custom code when it isn't.

Step 5: Test on real cases

Build an evaluation set from real historical examples, including awkward ones. Measure task success, wrong actions and escalations before launch.

Step 6: Launch supervised, then scale

Run with human approval first, monitor results and costs, then expand autonomy and volume as the agent proves reliable.

Frequently asked questions