Assemble the agent dossier of a real case
The final workshop brings the whole course together in one concrete deliverable: the design dossier of an agent for your own product, from the initial decision to the evaluation. You self-assess it with a grid, then leave with a reusable kit and a plan to put it to work with your team.
Lesson objective
By the end of this lesson, you will be able to assemble the agent dossier of a real case in your product (decision, workflow, tool cards, loop, control matrix, injection mitigations, trace and evaluation), self-assess it and plan how to apply it over 7 and 30 days.
Topics covered
- AI agents workshop
- agent dossier
- agent design
- exit kit
- action plan
Where it fits
Your agent dossier
How do I assemble the agent dossier of a real case in my product and apply it over the next 30 days?
Lessons in this module
- Assemble the agent dossier of a real case (this lesson)
What you will learn in this module
This lesson is part of the course Design reliable agents and tool calling
- Decide, with explicit criteria, whether a use case calls for a single call, a workflow or an agent, and choose the right pattern.
- Write tool cards the model uses well (name, description, parameters, return, errors, idempotency, risk level).
- Specify an agent's loop (goal, context, stop conditions, budgets, error handling) and judge whether an orchestrator and subagents are warranted.
- Place human approval points and an agent's permissions according to the blast radius of each action.
- Identify prompt-injection paths through tool outputs and specify structural mitigations that do not rely on the prompt alone.
- Specify the trace of a run and the evaluation of an agent (task success, trajectory, cost, latency, consistency over several trials).
Related courses
- AI & ProductAdvancedRegular practice: you already use the tools or work on this topic.
Build an AI assistant for your product
3 hr
- AI & ProductAdvancedRegular practice: you already use the tools or work on this topic.
Design a RAG architecture that fits your product
3 hr 30 min
- AI & ProductAdvancedRegular practice: you already use the tools or work on this topic.
Evaluate an AI feature: test sets, metrics and LLM judges
3 hr