Workflow mastery
This course takes you from “AI is useful” to “AI is running parts of my business.” You’ll learn to spot the tasks worth automating, understand how automations are built, monitor them on your dashboard, improve them over time, and prove their value with real numbers.
What you’ll be able to do
By the end of this course you’ll be able to:
- Plot tasks on the frequency-complexity matrix and pick the quick wins to automate first
- Describe any automation as trigger, action, and data flow, and decide when a human-in-the-loop review step belongs in the design
- Read run history, statuses, and logs on your dashboard, and recognize when a failure pattern needs flagging
- Calculate the ROI of an automation with the formula and baseline metrics, and report it in terms stakeholders care about
Lessons
Work through the lessons in order — each builds on the last.
search1. Identifying opportunitiesWhat to look for, the frequency-complexity matrix, and the one question to ask your team. 2 min read.
workflow2. Automation basicsTriggers, actions, and data flow — the three building blocks behind every automation — plus human-in-the-loop design. 2 min read.
bar-chart3. Reading your dashboardRuns, statuses, and logs, the analytics worth watching, and when to flag something to your Advizr team. 2 min read.
settings4. Optimizing workflowsThe iteration timeline, A/B testing, error handling and fallbacks, and the most common optimizations. 2 min read.
trending-up5. Measuring ROIThree types of value, the ROI formula with a worked example, and why you must baseline before you automate. 3 min read.
Time and prerequisites
Total reading time is about 11 minutes.
If you haven’t yet learned to write structured prompts, complete Prompt engineering first — several lessons here assume you can already get good output from an AI tool.
Start with Identifying opportunitiesLast updated on