Workshop Snapshot
01120-Minute Agenda
02| Time | Segment | Facilitator Job | Learner Output |
|---|---|---|---|
| 0:00-0:10 | Frame + mental model + use case | Define automation, explain the automation to AI workflow to agent progression, and introduce the lead-capture use case. | Understands the workshop arc. |
| 0:10-0:22 | Find your automation target | Have learners list repetitive, low-judgment, annoying work. | One automation target. |
| 0:22-0:38 | Map the lead capture workflow | Map the shared lead-capture workflow using Trigger, Inputs, Steps, Output. | Shared workflow map. |
| 0:38-0:43 | Demo 1: basic automation | Show Relay form trigger, Sheets row, and Slack/email notification. | Sees the target build. |
| 0:43-1:05 | Practice 1: build & test | Learners build and test the basic Relay automation. | Working automation or documented blocker. |
| 1:05-1:35 | Demo 2 + Practice 2: add AI | Demo the AI step, then learners add summarization/classification to their workflow. | AI-enhanced workflow. |
| 1:35-1:45 | Agents: what they are & how to scope | Contrast fixed automations with goal-driven agents, then define goal, tools, instructions, boundaries, output, and review. | Agent scope. |
| 1:45-2:00 | Demo 3 + Practice 3: build the agent + close | Demo the narrow agent, learners build or draft their first version, then close with humans in the loop, share-out, and takeaways. | Narrow first agent, review checkpoint, and next test. |
What To Teach
031. What Is Worth Automating?
Use three signals:
- Repetition: it happens again and again.
- Low judgment: it does not require deep thinking every time.
- Friction: it is annoying, slow, forgotten, or wasteful.
Shortcut: Frequency x Time x Annoyance.
2. Workflow Mapping
Key line: If you cannot explain the workflow in plain English, you are not ready to build it.
3. Automation vs. AI Workflow vs. Agent
- Automation: fixed path. Example: form submitted to sheet to notification.
- AI workflow: fixed path with AI interpretation. Example: AI summarizes and classifies the lead.
- Agent: narrow goal with flexible steps. Example: research the lead, evaluate fit, draft a reply.
Demo Scripts
Keep demos tight. Demo 1 stands alone; Demos 2 and 3 immediately lead into the matching practice block.
Demo 01 · Automation
Open Relay template: lead-capture automationGoal
Show a simple fixed-path automation: form submitted, lead saved, notification sent.
Step-by-Step
- Open the pre-built Relay workflow.
- Point out the form submission trigger.
- Show the Google Sheets action and mapped fields.
- Show the Slack or email notification action.
- Submit one test form and show the Sheet row plus notification.
Facilitator Line
"This is automation: a trigger starts a fixed sequence of steps."
Demo 02 · AI Workflow
Open Relay template: lead-capture AI workflowGoal
Show how the fixed automation becomes smarter when AI summarizes and classifies the lead inquiry.
Prompt to Use
Step-by-Step
- Open the workflow with the AI step added after the trigger.
- Pass the form message into the prompt.
- Update the Slack/email notification to include summary, intent, and reason.
- Submit a lead with a long message and show the summarized notification.
Facilitator Line
"The automation still handles the structure. The AI handles the flexible thinking inside the structure."
Demo 03 · AI Agent
Open Relay template: lead-capture AI agentGoal
Turn the workflow into a narrow agent without making it dangerously broad.
Agent Brief
Step-by-Step
- Start from the AI-enhanced workflow.
- Replace the single classification task with the broader lead-evaluation goal.
- Add only the tools the agent needs.
- Write boundaries before testing.
- Run one test lead and inspect the draft before approval.
Practice Activities
Only run these three hands-on blocks. The AI and agent practices happen immediately after their demos.
Build Your First Relay Automation
Objective: Create one working automation with one trigger and at least two actions.
- Set the trigger.
- Add a storage action, such as Google Sheets.
- Add a notification action, such as Slack or email.
- Run one successful test.
- Submit what it does plus a screenshot or short description of it working.
Add One AI Step
Objective: Upgrade the automation by adding one simple AI task.
- Choose summarize, classify, draft, or extract.
- Write a specific prompt for the AI step.
- Use the AI result later in the workflow.
- Test and compare the output before and after the AI step.
Build a Narrow First Agent
Objective: Ship the first version of an agent that does one useful thing well.
- Define the agent goal.
- Choose the tools it can use.
- Write instructions and boundaries.
- Define the output.
- Run one test case and submit how it works, with screenshots or a link if possible.
FAQ & Q&A
Short answers facilitators can use without turning the workshop into a technical lecture.
"How do I know if something should be automated?"
"What should not be automated?"
"What if my workflow has lots of branches?"
"Do I have to use Relay?"
"Where does AI fit best inside an automation?"
"Can I trust the AI classification?"
"Why not make the AI do everything?"
"What makes an agent different from an automation?"
"Do agents need tools?"
"What is a good first agent?"
"Should the agent send emails automatically?"
Before & After
Click each item as you complete it. The state lasts only in the current browser session.
Before the Session
- Review source transcripts end-to-end
- Prepare the lead-capture form
- Create a clean Google Sheet for demo leads
- Confirm Relay account access
- Confirm Slack or email notification access
- Build the demo automation once before teaching
- Prepare a test lead message for AI summarization
- Prepare screenshots for each critical step
- Print opportunity and workflow worksheets
- Print agent design canvas
- Prepare fallback if tool access fails
After the Session
- Collect automation screenshots or descriptions
- Collect AI step prompts that worked well
- Collect agent capstone submissions
- Send recap with worksheets and prompt templates
- Send reminder to test workflows with real data
- Ask learners where the workflow broke
- Update FAQ with new questions
- Replace weak demo screenshots
- Note which workshop segment ran long
- Pick one learner build to feature next time
Facilitator Reflection
- Which segment produced the clearest learner outputs?
- Where did learners get stuck: idea selection, mapping, tool setup, AI prompting, or agent scoping?
- Did the lead-capture example feel relevant to this cohort?
- Which AI prompt generated the best output?
- Were learners too cautious, too ambitious, or appropriately scoped with agents?
- What should change before the next run?