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AI agent design

Design a reliable AI agent before writing code

We define the agent's role, tools, limits and the moments when a person takes over before adding complexity.

Book an agent scoping session
Goal and limits
Tools and evaluations
Controllable agent

This is a good fit when

  • Multi-source research
  • Qualification and preparation
  • Knowledge assistance
  • Controlled task orchestration

You leave with

  • A readable architecture
  • Required tools and permissions
  • Tests and success criteria
  • Human escalation rules

A method that produces an observable result

01

Define the contract

We specify the goal, data, permitted actions and refusal cases.

02

Build the minimal path

We prototype the useful scenario without premature complexity.

03

Evaluate

We test accuracy, cost, latency, errors and human recovery.

Frequently asked questions

Does an agent need full autonomy?

No. Limited autonomy with human approval is often more reliable.

Which model should we choose?

The model follows the task, data, cost and evaluations.

Can you review an existing prototype?

Yes. We can diagnose its architecture, errors and evaluations.

Scope the agent before adding more tools

Define the minimal architecture and first useful evaluation.

Book an agent scoping session
AI agent consulting and design | JD Teach AI