Catalog
All paths
A path is a route with a start and an end. Browse every one here, or see how they stack up in the three tracks.
16 paths
- Build with Expedify40 lessons3 hr 41 min
Expedify in an Afternoon
Open a working Expedify org, understand every part of it, and be ready to demo it to a client.
- Build with Expedify8 lessons59 min
Your First AI Agent
Build an AI agent that knows your business, talks to customers, and updates your CRM.
- Build with ExpedifyReference9 lessons44 min
Get Started with the Workflow Builder
The canvas, the nodes, and how data moves between them — everything you need before building anything real.
- Build with ExpedifyReference10 lessons42 min
Triggers — every way a workflow starts
Ten triggers, grouped by the question they answer: something changed, someone contacted us, or a system or clock spoke up.
- Build with ExpedifyReference21 lessons1 hr 56 min
Actions — making things happen
Twenty-one nodes that do the work: write to the CRM, message a person, place a call, reach the outside world.
- Build with ExpedifyReference11 lessons1 hr 9 min
Logic & Data
Branch, loop, wait, pause for a human — then reshape, query and store what flows between nodes.
- Build with ExpedifyReference6 lessons58 min
AI & the Knowledge Base
The three AI nodes, and how to give them something true to answer from.
- Build with ExpedifyReference11 lessons1 hr 10 min
Webhooks, Debugging & Full Builds
Talk to other systems, find out why a run failed, then put it all together in three complete agents.
- Engineer AI Agents16 lessons2 hr 28 min
Building AI Agents for Sales, Onboarding and Support
Build the desk that answers, qualifies, onboards and hands off — on every channel, without ever inventing a fact.
- Engineer AI Agents21 lessons2 hr 59 min
Building Production-Ready AI Agents
Build an agent team that decides from your own policy and your own data, cannot act beyond the authority you gave it, and leaves an audit row you can defend.
- AI & ML Foundations5 lessons48 min
Quantitative Foundations: Elasticity & Margins
Think at the margin, read an elasticity, and know what a discount really costs before you approve it.
- AI & ML Foundations12 lessons2 hr 31 min
Introduction to AI
What AI actually means, how people have tried to build it, and why learning from data took over.
- AI & ML Foundations6 lessons1 hr 13 min
What learning is
Supervised, unsupervised, and the difference one line of feedback makes.
- AI & ML Foundations8 lessons1 hr 45 min
Decision Trees
Finding the questions that split — and knowing when a tree has stopped learning.
- AI & ML Foundations8 lessons1 hr 41 min
Regression I — predicting a number
Frame a business question as a prediction, fit a regression, and say honestly how good it is.
- AI & ML Foundations3 lessons35 min
How a Model is Fitted
The four steps every fitted model shares — and the model that only answers two of them.