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A complex behavioral healthcare organization needed a way to produce high-volume marketing content — eBlasts, social posts, blog drafts — without sacrificing clinical accuracy or brand consistency. Manual processes were slow, and the risk of off-brand or non-compliant content was constant.
I designed and deployed an AI-powered content assistant that queries the organization's Notion knowledge base before every response. The system enforces brand voice, messaging guardrails, and compliance standards automatically — so the marketing team gets governed first drafts, not generic AI output.
The tool handles content generation, content review, and brand training. It's now being expanded to include SEO/AEO-driven content calendar automation.
Results:
- 4–12 hours/month saved on content creation
- Reduced risk of costly reprints and off-brand messaging
- Marketing team trained and using the tool independently
My role:
Discovery, system architecture, Notion database design, prompt engineering, integration, documentation, and team training.
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
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Finally, I don’t need to shrink my ideas to make them possible!
Isn’t that the dream?
My creative ideas are often technically complex. The gap between what I imagine and what I can build alone used to be the biggest bottleneck in my work
But now, with AI, I can finally spread my wings and fantasize fully 🧚♀️
We’re so lucky to live in this moment with all these slightly crazy technologies right at our fingertips!
I genuinely feel like I'm living my best creative life, having Claude Code as a creative-technical partner. I describe the concept, how it should feel, move, and respond, and it translates that into GSAP timelines, Three.js scenes, and Webflow integrations. Not just code, but structure I can work with
I stay in the creative layer
It handles the technical translation
So instead of simplifying ideas to fit my capacity,
I can finally follow them fully!
Curious, have you already integrated AI into your workflow?
Any interesting setups or tools?
Would love to steal them👀
Yes it's crazy what Claude can do. I spent the whole day yesterday trying to create systems that would work for me
Building a Zero-Touch Design Feedback Loop with Slack and the @Paper MCP
What if you never had to manually process a minor design revision again? As designers and developers, we easily waste 30% of our week fulfilling fast client requests—changing button colors, adjusting typography, or tweaking padding. I decided to completely automate this process.
In this project, I engineered an autonomous AI-driven workflow that physically alters native UI designs based on conversational Slack messages, proving the massive potential of the Paper MCP.
✨ The Power of the Paper MCP: Historically, AI agents have struggled to actually "see" or edit design files. By deploying the Paper MCP, I gave a raw Large Language Model the ability to programmatically traverse a 2D design canvas.
The Setup: I design the initial UI (like a Login Page) using Paper and post the screenshot to the client's Slack channel.
The Trigger: The client requests changes natively in Slack by mentioning a custom @DesignBot (e.g., "Make the login button green and change the title to 'Welcome'").
The Execution: Instead of guessing layout geometry, the AI uses the Paper MCP to dynamically query the canvas, isolate the precise target node, and duplicate the master to create a protected variant. It aligns the new design on the canvas grid and updates the styling properties natively.
The Delivery: The MCP server intercepts the final render state and pushes a flawlessly formatted screenshot right back into the Slack thread.
🛠️ Technical Stack Used:
Paper MCP: The absolute core of the project, enabling rigorous JSON-RPC access to native design layers, text bounds, and styling hooks.
Slack Bolt (Socket Mode): For threading logic, instant reaction processing, and conversational memory.
Agentic LLM Engine: Used native OpenAI tool-calling to map the complex MCP schemas directly into the AI’s brain so it never hallucinates commands.
The Result: Clients experience magical, instantaneous visual revisions directly inside their communication channels, while designers and developers win back hours of completely uninterrupted, deep-focus work.
Check out the video demo below to see the AI leverage Paper MCP to parse a layer tree and dynamically manipulate the UI!
This is the kind of workflow that quietly kills 30% of design busywork 👀
Built a Live Adaptive Sales Dashboard that updates itself — no manual edits, no refresh stress.
Here’s what I explored 👇
→ A dashboard that stays alive as your data changes
→ AI agents pulling, analyzing, and rewriting everything in real time
→ Fully generated inside Paper’s connected canvas
Stack I used:
• Cursor Agent (Claude-powered)
• Zapier MCP → fetches live data from Google Sheets
• Paper MCP → rewrites the dashboard directly on canvas
How it works:
Update sales data in Google Sheets
Run a single prompt in Cursor
Agent pulls + analyzes data (KPIs, trends, insights)
Instantly updates the entire dashboard UI on Paper
What gets generated automatically:
• KPI cards with smooth animations
• Monthly sales trend (line chart)
• Category-wise performance (bar chart)
• Region distribution (doughnut chart)
• Recent transactions + AI insights
Feels like dashboards are no longer static products…
they’re becoming living systems powered by agents.
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