§ 01
One-Page Snapshot
Workshop Overview
Learners move from "I use AI sometimes" to "I can design a simple system that captures work, routes it, adds AI judgment, and keeps a human in the loop."
Session Title
Build Your First AI Agent
What This Workshop Is About
Building useful no-code systems: first a simple automation, then an AI-enhanced workflow, then a narrow goal-driven agent.
Why It Matters
The biggest leverage comes from automating repetitive work, then adding AI where information needs to be summarized, classified, drafted, or evaluated.
Intended Audience
Beginners and working professionals who want practical automation skills without writing code.
Prerequisites
Comfort using web tools. Access to a form tool, Google Sheets, Slack or email, and Relay or a comparable no-code automation tool.
Running Example
A lead capture workflow: form submitted, lead stored, notification sent, AI summarizes and classifies, then an agent evaluates and drafts a response.
Recommended Timing
120 minutes total: concept framing, workflow mapping, live build, AI upgrade, agent design, and final share-out.
Final Output
A working first automation plus a scoped first AI agent with a goal, tools, instructions, boundaries, and review step.
Learning Outcomes
By the end of the workshop, participants will be able to:
- Identify tasks worth automating using repetition, low judgment, and friction as signals.
- Map a workflow in plain English before choosing tools.
- Build a simple Relay automation with one trigger and at least two actions.
- Add an AI step that summarizes, classifies, extracts, drafts, or transforms information.
- Explain the difference between a fixed automation and a goal-driven AI agent.
- Design a narrow AI agent with clear goals, tools, instructions, boundaries, and human review.
Core Thesis
Automation handles the structure. AI handles the flexible thinking inside the structure. Agents add a narrow goal and the ability to decide which steps to take.
Workshop Thesis
§ 02
Minute-by-Minute
Run of Show
Keep the build sequence linear. The same lead workflow should evolve across the full two hours so learners can see how automation becomes AI workflow, then agent.
| Time | Type | Topic / Activity | Facilitator Cues |
|---|---|---|---|
| 0:00-0:10 | Frame | Frame + Mental Model + Use Case Define automation, explain the automation to AI workflow to agent progression, and introduce the lead-capture use case. |
Make the workshop arc visible before opening tools. |
| 0:10-0:22 | Activity | Find Your Automation Target Learners list repetitive, low-judgment, annoying work and choose one target. |
Land the formula: Frequency x Time x Annoyance. |
| 0:22-0:38 | Map | Map the Lead Capture Workflow Map the shared use case using Trigger, Inputs, Steps, Output. |
Keep it plain-English and linear before touching tools. |
| 0:38-0:43 | Demo 1 | Basic Automation Show the Relay form trigger, Sheets row, and Slack/email notification. |
Five minutes. Show the target build end-to-end. |
| 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 or classification to their workflow. |
Demo for five minutes, then move directly into practice. |
| 1:35-1:45 | Concept | Agents: What They Are & How to Scope Contrast fixed automations with goal-driven agents, then define goal, tools, instructions, boundaries, output, and review. |
Push against hype and protect 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. |
End with a review checkpoint and named next test. |
If You're Behind
Compress tool setup, not the workflow mapping. If time is short, demo the Relay build live and make the final agent a scoped design instead of a live build. Never skip the distinction between automation, AI workflow, and agent; that distinction is the conceptual spine of the workshop.
§ 03
Deck Standards
Slide Deck Guide
Slides should make the system visible: one workflow, getting more capable across the two-hour session.
Design Requirements
One running workflow diagram appears throughout
Start with Form submission → Sheet → Notification. Add AI summary/classification after the build lab. Add research, evaluation, and draft response during the final agent build.
Use real interface screenshots
Include screenshots of the form, Relay trigger, field mapping, Google Sheet row, notification, AI step configuration, and final agent output.
Keep terms plain-language
Every technical word gets a working definition: trigger, input, action, output, AI step, agent, tool, boundary, human-in-the-loop.
Speaker notes carry exact build steps
The slide should not be a manual. Put precise click paths, field names, and backup instructions in presenter notes.
§ 04
How To Say It
Facilitator Talking Points
Use the transcripts' simple, direct language. The strongest move is to keep returning to the same question: what should happen automatically after the trigger?
Opening · What Is an Automation?
An automation is simple: when something happens, a set of steps runs automatically. It is not magic, and it does not need to be complex. If someone fills out a form, they get a confirmation email, their info goes to a spreadsheet, and you get notified.
01 · Repetition
Do you do it again and again?
Repeated emails, copied data, recurring follow-ups, and routine organizing are strong candidates.
02 · Low Judgment
Does it require little decision-making?
Standard responses, moving data, tagging records, and notifications usually belong in automation.
03 · Friction
Does it feel annoying, slow, or wasteful?
Friction is useful signal. If people avoid the work or forget it, the system should help.
04 · Formula
Frequency x Time x Annoyance
If it happens often, takes time, and annoys you, it is worth evaluating for automation.
Workflow First, Tools Second
The key line for the mapping segment is: if you cannot explain your workflow clearly in plain English, you will not be able to build it. Make the invisible process visible before anyone opens Relay.
01
Trigger
What starts the workflow?
02
Inputs
What data comes in?
03
Steps
What happens in order?
04
Output
What do you get at the end?
Automation vs. AI Workflow vs. Agent
| System Type | Best For | Workshop Example |
|---|---|---|
| Automation | Stable, predictable steps | Form submitted → add row to Google Sheet → send Slack notification. |
| AI Workflow | Understanding or transforming information | Form submitted → AI summarizes the message → AI classifies lead intent → notify with summary. |
| AI Agent | Narrow goals where the path can vary | Research this company, decide whether the lead is a fit, draft a personalized reply, and send the draft for approval. |
Automation moves data. AI interprets data. Agents reason across steps toward a goal.
Say this during the AI and agent segments
Common Misconceptions
"I should automate everything."
No. Automate repetitive, low-judgment, high-friction work. Keep humans involved where judgment, relationship, risk, or taste matters.
"I need to pick the perfect tool before mapping."
No. Start with Trigger, Inputs, Steps, Output. Tools are easier to choose once the workflow is clear.
"Adding AI means the system should make every decision."
No. Start with small AI tasks: summarize, classify, extract, draft. For important work, review the AI output before anything goes out.
"An AI agent is a fully autonomous employee."
No. A practical agent is a flexible workflow with a narrow goal, tool access, instructions, context, and boundaries.
§ 05
Step-by-Step
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
TASK: Summarize this lead inquiry in one sentence. Then classify the lead as high intent, medium intent, or low intent.
CRITERIA:
High intent: specific business problem, clear interest, asks for demo or next step.
Medium intent: interested but vague or exploratory.
Low intent: unrelated, unclear, or no business need.
OUTPUT FORMAT:
Summary:
Intent:
Reason:
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
GOAL: Evaluate inbound leads and draft personalized replies.
TOOLS: Lead form data, Google Sheets, web research, email draft.
INSTRUCTIONS: Research the company, identify the primary business problem, decide whether the lead is high quality, and draft a concise response.
BOUNDARIES: Draft only. Do not send automatically. If information is missing, ask a follow-up question.
OUTPUT: Fit assessment, reason, draft reply, recommended next step.
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.
§ 06
From Listening to Doing
Practice Activities
Only run these three hands-on blocks. The AI and agent practices happen immediately after their demos.
0:43-1:05 · Practice 1
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.
1:10-1:35 · Practice 2
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.
1:50-2:00 · Practice 3
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.
§ 08
Temperature Reads
Check for Understanding
Use these checks while learners build. The fastest way to fix confusion is before it becomes a broken workflow.
Quick Checks
- "What is the trigger in your workflow?"
- "What data comes in at the start?"
- "Which step is storage, and which step is notification?"
- "What is your AI step doing: summarize, classify, draft, or extract?"
- "Is this still an automation, or does it have a goal and flexible steps?"
- "Where does the human review happen?"
When Learners Are Confused
If they cannot name a trigger
Ask: "What happens first in the real world?" Form submitted, email received, meeting ended, file uploaded, row added. That is usually the trigger.
If they are overbuilding
Reduce the workflow to one path. One trigger, two actions, one output. Complexity comes later.
If their AI prompt is too vague
Ask what output they need and how it should be formatted. Then add criteria. "Analyze this" becomes "summarize in one sentence and classify intent as high, medium, or low using these criteria."
If they want the agent to do too much
Narrow the goal. "Help with sales" becomes "Evaluate inbound leads and draft personalized replies."
§ 09
Keep the Energy
Engagement Strategies
This workshop works best when learners keep applying the same concept to their own work, not only the lead-capture demo.
Start with weekly annoyances
Ask learners to name repetitive work from the last seven days. Recent pain creates better automation ideas than abstract brainstorming.
Use pair critique before build time
Have learners explain their trigger, steps, and output to a neighbor. If the neighbor cannot understand it, the workflow is not ready for Relay.
Make testing public
Celebrate test runs, including broken ones. A failed test is useful if learners can name which field, step, or prompt caused the issue.
Keep returning to the same diagram
Update the lead workflow visually at each major segment. Learners should see exactly what changed when AI and agent behavior were added.
Use "draft, don't send" as the safety mantra
When learners get excited about agents, make the first version produce drafts and recommendations, not irreversible actions.
§ 10
Contingency Plans
What Could Go Wrong
Most problems are caused by unclear workflow thinking, broken field mapping, or oversized agent scope.
Learners start in tools too early
Pause tool use and return to Trigger, Inputs, Steps, Output. Require a plain-English workflow before building.
Relay trigger does not fire
Check that the form was submitted after the automation was enabled. Run a fresh test and use the simplest possible form fields.
Fields map incorrectly
Reduce to name, email, and message. Verify each field one at a time before adding optional fields.
AI output is vague
Add criteria and output format. Do not ask the AI to "analyze"; tell it exactly what categories, fields, or draft structure to produce.
Agent scope gets too broad
Narrow the goal to one job. Good: "Evaluate inbound leads and draft replies." Bad: "Manage my sales pipeline."
Learner wants full autonomy
Move the first version to recommendation or draft mode. Human approval comes before sending, scheduling, deleting, purchasing, or changing records.
Tool access or login fails
Switch to the worksheet version. Learners can still map the workflow, write AI prompts, and scope the agent without live tool access.
§ 11
Anticipated Questions
FAQ & Q&A
Short answers facilitators can use without turning the workshop into a technical lecture.
Automation Questions
"How do I know if something should be automated?"
Look for repetition, low judgment, and friction. If it happens often, takes time, and annoys you, it is a candidate.
"What should not be automated?"
Anything that requires nuanced judgment, trust, personal relationship, high-stakes decision-making, or sensitive data should start with human review.
"What if my workflow has lots of branches?"
Start with one path. Build the most common path first. Add branches only after the basic version works.
"Do I have to use Relay?"
No. Relay is the workshop example. The principles transfer to Zapier, Make, n8n, Airtable automations, or other workflow tools.
AI Workflow Questions
"Where does AI fit best inside an automation?"
Use AI where information needs to be summarized, classified, extracted, drafted, compared, or transformed.
"Can I trust the AI classification?"
Treat it as a useful first pass. For important outcomes, review it or route uncertain cases to a human.
"Why not make the AI do everything?"
Broad AI tasks are less reliable. Simple, narrow AI steps are easier to test, debug, and trust.
Agent Questions
"What makes an agent different from an automation?"
An automation follows predefined steps. An agent has a goal and can decide which steps to take within boundaries.
"Do agents need tools?"
Useful agents usually do. The AI model reasons; tools let it search, read, write, update, draft, or retrieve information.
"What is a good first agent?"
A narrow one: lead qualification, meeting summary, content research, email drafting, or vendor intake. One goal, few tools, clear output.
"Should the agent send emails automatically?"
Not for v0.1. Have it draft emails and send them to a human for approval. Add autonomy only after repeated successful tests.
§ 12
Plain-Language Definitions
Glossary
Use these definitions consistently across the workshop.
- Automation
- When something happens, a set of steps runs automatically.
- Trigger
- The event that starts a workflow, such as a form submission, email received, file uploaded, or row added.
- Input
- The data that enters the workflow, such as name, email, company, message, date, or file.
- Action
- A step the automation performs, such as adding a spreadsheet row, sending a notification, creating a task, or running an AI prompt.
- Output
- The result at the end of the workflow: saved record, message sent, draft created, decision prepared, or summary delivered.
- AI Step
- A workflow step where AI summarizes, classifies, extracts, drafts, or transforms information.
- Classification
- Assigning information to a category, such as urgent vs. not urgent or high-intent vs. low-intent lead.
- Human-in-the-Loop
- A review point where a human approves, edits, or rejects the system's output before consequential action.
- AI Agent
- A goal-driven AI system that can use tools and make decisions about how to complete a narrow task.
- Tool
- An external capability the agent can use, such as web search, email, Google Sheets, a CRM, or documents.
- Boundary
- A rule that limits what the agent can do, such as drafting but not sending emails.
- v0.1
- The smallest useful first version. It should work on one realistic case before you expand it.
§ 13
Pre & Post Flight
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 final agent builds or scoped designs
- 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?