The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
Back to feedPost
Basic automatic Gmail email labelling with OpenAI and Gmail API
The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
Trending
retrofuturism
Share your favorite designs from the past exploring the distant future. Or your own take on the aesthetic 🚀
halftone
Dots. Texture. Grain. Let's see your designs using the halftone technique.
Midjourney
Creatives are showing off what they're making with Midjourney.
colorgrade
Video editors sound off: How do you enhance the mood of your video in color grading?
Related posts
Built an AI-powered email automation workflow for SugarBliss Bakes using n8n. The workflow helps manage customer emails, identify and organize messages, and automate responses for bakery orders and customer inquiries.
OCR extracts business names, formation dates, and addresses from uploaded documents automatically. But users still need to trust what the system found before anything gets submitted.
We designed the confirmation flow around editable fields that surface extracted data clearly. Users review what the system found and correct where needed, rather than typing everything from scratch. The design choice was to make the AI output feel transparent and controllable.
The design choice was to make the AI output feel transparent and controllable. The result is a flow that reduces data entry to the minimum while keeping users fully in control of what gets submitted.
The editable-fields approach is smart, letting people verify OCR output instead of trusting it blindly probably saves you a ton of support tickets down the line.
This is the difference between automation and an AI agent. 🤖
A traditional automation says:
“When X happens → do A → then B → then C.”
It’s predictable, reliable, and perfect for repetitive processes. But what happens when the next step isn’t always the same? That’s where an AI agent comes in.
Instead of following one fixed path, an agent can:
→ Understand the goal
→ Analyze the situation
→ Decide what information it needs
→ Choose the right tool
→ Take an action
→ Check the result
→ Decide what to do next
For example, imagine a lead-generation workflow in n8n.
Traditional automation:
New lead → Scrape website → Find email → Add to CRM → Send email
Every lead follows the same path.
Agentic workflow:
New lead → AI Agent
The agent decides:
🔎 Does this company fit the target profile?
🌐 Should I research the website further?
📊 Is there enough information to qualify the lead?
✉️ Should I generate a personalized message?
⚠️ Is human approval needed before outreach?
The workflow becomes goal-driven instead of purely step-driven.
And this doesn't mean replacing automation.
The most powerful systems combine both:
n8n handles the reliable execution.
AI handles decisions where the path isn't always predictable.
That’s what makes an agentic workflow different from simply adding ChatGPT to an automation.
The future isn't: Automation OR AI
It's: Automation + AI agents + the right tools.
Great visual! "Automation does the work, AI agent decides the work" is probably the clearest way to explain this shift to clients.