Day 2

A Make.com scenario that monitors a Google Drive folder for new documents, runs AI analysis on each one, and posts a structured Slack summary with executive brief, key findings, and action items.

Zapier vs Make.com vs n8n

Three tools, same category, different tradeoffs. Pick the right one for each use case.

Zapier
  + Easiest to learn, largest app library
  + Best for simple 2-3 step workflows
  - Expensive at scale ($49+/mo for more than 5 Zaps)
  - Limited branching logic

Make.com
  + Visual canvas with branches, loops, filters
  + 1,000 free operations/month (vs Zapier's 100 tasks)
  + Much cheaper at scale
  - Steeper learning curve than Zapier

n8n
  + Open source, self-hostable (unlimited free)
  + JavaScript code nodes for custom logic
  + Best for technical users who want full control
  - Requires server setup for self-hosting

Rule of thumb: Start with Zapier for simple automations. Move to Make.com when you need branching or loops. Use n8n when you need to self-host or write custom code.

Make.com Fundamentals

Create a free account at make.com. What Zapier calls a "Zap," Make calls a Scenario. What Zapier calls a "step," Make calls a Module.

The big visual difference: Make shows you data flowing between modules. You can see exactly what data enters and leaves each module, which makes debugging much easier.

Key Make concepts:

• Router: The diamond shape. Creates branches — like an if/else statement. Different branches run based on conditions you set.
• Iterator: Processes a list of items one by one. Zapier handles this with "line items" — Make makes it explicit and visual.
• Aggregator: Collects multiple outputs and combines them into one. Useful after an iterator.

Build: Document Watch → AI Analysis → Slack

Create a new scenario in Make.com. Here's the flow:

Module 1: Google Drive — Watch Files in a Folder. Point it at a "Reports to Review" folder. Set the schedule to every 15 minutes. This triggers whenever a new file appears in that folder.

Module 2: Google Drive — Get a File Content. Use the file ID from Module 1 to get the text content. For Google Docs, use "Download a Document" in text format.

Module 3: OpenAI — Create a Completion. Add the OpenAI module. Set the model to gpt-4o-mini (fast and cheap for document analysis). Write this prompt:

Analyze this document and return a structured summary.

Executive Summary: (2-3 sentences)

Key Findings:
- (bullet 1)
- (bullet 2)
- (bullet 3)

Action Items: (explicit next steps, or "None identified")

Risk Flags: (anything that needs attention, or "None")

Document:
{{2.data}}

Map {{2.data}} by clicking the field and selecting the text output from Module 2.

Module 4: Slack — Create a Message. Add the Slack module, connect your workspace, and choose a channel like #reports or #team-digest. In the message body, map the OpenAI completion output and add the file name as a header. The final message will look like a clean professional brief every time a new document lands in the folder.

Go Further on Your Own

• Add a Router between the trigger and the AI step. Branch 1: documents smaller than 200 characters skip the AI and post 'File too small to analyze.' Branch 2: full analysis for larger documents
• Add a condition: if the AI output contains the word 'urgent' or 'critical,' send an additional direct message to yourself
• Try rebuilding this same scenario in n8n's cloud version — compare the experience and note what's different

Nice work. Keep going.

Day 3 is ready when you are.

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What's Next

The foundations from today carry directly into Day 3. In the next session the focus shifts to Day 3 — building directly on everything covered here.