Mastering AI Automation.
A free eight-chapter path for teams building AI workflows that hold up after launch, from the first design decisions to safe permissions.
- Chapters
- 8
- Lessons ready
- 8 of 8
- Level
- Intermediate
- Reading time
- 149 min
Outcomes
What you will be able to do.
- Spot the five design mistakes that make AI workflows fail after launch.
- Explain the AI terms your team and your vendors use.
- Run a fair test that shows whether a task is worth automating.
- Write process and integration requirements before anyone builds.
- Set field rules so an automation never overwrites records you trust.
- Choose a platform by who fixes it, and approve only the access it needs.
Course outline
8 chapters, in order.
Where AI workflows break.
Five design mistakes a polished demo hides, and the fix for each.
Speak the same language.
The terms you will meet in every later chapter, in plain English.
Prove it is worth automating.
Time one task both ways and count every review and repair.
Define the process first.
Write what the process must record before you choose a plugin or a build.
Write the integration contract.
Trigger, action, receipt and done, agreed on one page.
Protect the records it writes.
Field rules so an automation adds to a record and never wipes it.
Choose who runs it.
Compare platforms on failures, upkeep and exit, not on features.
Approve exact permissions.
Grant each tool only the actions it needs, before you connect it.
Learn at your own pace.
The path is free and needs no account. Mark lessons complete as you go; your progress stays in this browser.