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Building AI Workflows That Ship: From Prototype to Production

7 chapters · 32 lessons

1. 1. Problem Framing for AI Solutions

   4 lessons

   Learn to identify tasks where AI accelerates work versus where it introduces unacceptable risk or cost.

2. 2. Designing Workflows with Human Checkpoints

   4 lessons

   Structure AI systems with review points, fallback logic, and clear handoffs between automated and human steps.

3. 3. Building a Document Summarization Prototype

   5 lessons

   Create a working system that extracts key information from documents and flags items for expert review.

4. 4. Evaluating AI Outputs Systematically

   4 lessons

   Develop repeatable evaluation methods that go beyond subjective impressions to measure quality and reliability.

5. 5. Building a Classification and Routing System

   5 lessons

   Implement a workflow that categorizes incoming requests and routes them to the right team or process.

6. 6. Implementing Retrieval-Augmented Generation Workflows

   5 lessons

   Build a system that searches internal documents and generates contextually grounded answers with source citations.

7. 7. Documenting and Presenting Your AI Portfolio

   5 lessons

   Package your prototypes with clear problem statements, design decisions, test results, and lessons learned.