Reliable AI Workflows

What you’ll learn

Build a controlled AI processing workflow with evidence checks, measured quality, human approval, and a reversible rollout plan.

• Separate model proposals from authorized actions
• Evaluate extraction and routing with explicit error costs
• Design a shadow rollout, stop conditions, and an operational runbook

1. 01
   Put AI Inside a Controlled Workflow15 min lesson + exercise estimate
   Free preview
2. 02
   Extract Fields with Supporting Evidence20 min lesson + exercise estimate
3. 03
   Classify Without Hiding Uncertainty20 min lesson + exercise estimate
4. 04
   Bind Approval to the Exact Action20 min lesson + exercise estimate
5. 05
   Evaluate Quality by Error Type22 min lesson + exercise estimate
6. 06
   Set Cost and Failure Budgets18 min lesson + exercise estimate
7. 07
   Keep Untrusted Inputs Away from Authority20 min lesson + exercise estimate
8. 08
   Capstone: A Measured Shadow Rollout30 min lesson + exercise estimate

What you’ll need

Practical AI Foundations and Workflow Automation Lab, or equivalent familiarity with prompts, JSON, validation, and retry behavior. Python programming is optional for running the supplied lab. A text editor and a modern browser for reading; Python 3.10 or newer for the optional offline capstones. No API key, AI subscription, or hosted service is required. AI outputs in the capstones are authored practice fixtures, not live model responses.

How access works

1. Try the first lesson. Read the preview and complete its exercise before deciding.
2. Pay once through Stripe. The price is $129 USD for this course. There is no recurring subscription.
3. Keep your private order link. After payment confirmation, your order page unlocks the lessons and ZIP download. The browser also saves the purchase in My learning.

Download the course and workbook for offline study. Online access lasts while the service operates. Live tutoring, certificates, and external tool subscriptions are not included.

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