Module 6 of 6Lesson 4 of 4~12 min
Assemble the design dossier
The final workshop brings the whole course together in one concrete deliverable: your assistant's design dossier, from framing to running it in production. A self-assessment grid helps you judge how solid it is before sharing it with your team, and you leave with resources to go further.
Lesson objective
By the end of this lesson, you will be able to assemble and self-assess a complete design dossier using a grid that covers the course's seven outcomes.
Topics covered
- AI assistant workshop
- design dossier
- self-assessment grid
- AI product design
- PM deliverable
Where it fits
Evaluate, ship, monitor
How do you know the assistant is ready, launch it safely and improve it?
Lessons in this module
- Design the evaluation plan
- Choose how to build it
- Launch and run in production
- Assemble the design dossier (this lesson)
What you will learn in the course
This lesson is part of the course Build an AI assistant for your product
- Identify a use case that justifies an AI assistant and write its framing brief (problem, users, allowed actions, out of scope, success criteria).
- Design the conversational experience: entry point, tone, handling uncertainty, handoff to a human and response format.
- Choose and justify a knowledge strategy (instructions, injected context, RAG, fine-tuning) and a conversation memory strategy.
- Specify the assistant's tools and actions (data read, actions written, confirmation, permissions) and choose how to build it.
- Identify the risks (injection, leaks, excessive actions, costs) and design layered guardrails that go beyond the prompt.
- Design an evaluation plan with a reference dataset, criteria, grading methods, release thresholds and a regression rule.
- Define production metrics (product, quality, cost, latency), alert thresholds and the loop from user feedback to the evaluation set.
Related courses
- Design a RAG architecture that fits your productAdvanced · ~3 hr 30 min
- Evaluate an AI feature: test sets, metrics and LLM judgesAdvanced · ~3 hr
- Ship and monitor an AI feature in productionExpert · ~3 hr