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Pipeline Rebuild & Automation Stack for a Service-Based Events Business — Salesforce
Developed a Salesforce-ready CRM architecture for Interworld Africa by migrating fragmented spreadsheet operations into a structured "revenue operating system." Using a "Done-With-You" model, I delivered a 4-stage pipeline, sanitized legacy lead data, and implemented automated workflows to enable precise revenue forecasting and lead tracking for their high-end event production business.
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Salon Appointment Booking Automation
This automation workflow makes the entire client scheduling journey using n8n, OpenAI, and Google Sheets. The process begins when a client interacts with the salon’s chat interface, where an AI Agent leverages simple memory to recognise returning customers and provide personalised service recommendations.
Automated my agency pipeline
I've recently worked on automating my agency pipeline using n8n, Groq, and DocuSign API - it's been a huge time saver
Follow for more: https://go.phonezait.de/
Figma Make isn't just a prototyping tool. I used it to ship a Claude-powered design system generator.
Most designers treat Figma Make as a quick vibe-coding sketchpad. I wanted to show it's something deeper — a full vibe-coding platform that integrates with external APIs.
The connection nobody writes about
There are three ways Claude connects to Figma today. Figma MCP — Claude reads and writes Figma files via MCP server. Figma's built-in AI — Figma calls its own models internally. And mine — a React app inside Figma Make that calls Claude API directly from the browser. Claude responds to the code, not to Figma. Figma Make is the hosting.
The new pipeline
Old approach: get brandbook and references from client → generate moodboard → align → write prompts for UI Kit. Separate steps, human in the center every time.
My approach: collapse all of that into one step. Run an AI analysis and output structured data — input for machines, not a result for humans.
We don't ask AI how the brand looks. We run an MRI on it and get structured data that machines use to build code.
What gets generated
11 files, all consistent with each other because they share one analysis. For Figma specifically:
tokens.json — W3C DTCG 3-tier format (primitive → semantic → component), imports directly into Figma Variables via Tokens Studio or Figma Make prompt
design-system.css — all tokens as CSS custom properties, ready to import
starter.tsx — paste into Figma Make, full design system renders instantly
figma-make.md — session context, paste once and the AI knows the entire design system
Add a content plan on top — generate a full design in one run with minimal token spend.
The entire tool was built and shipped inside Figma Make. No external hosting. No separate codebase.
#ConfigMakeathon #FigmaMake #DesignSystem #VibeCoding #ClaudeAPI #BuildInPublic
tNot gonna lie, I opened this out of curiosity and left with more questions than answers 😅 But that's usually a good sign. Really interesting exploration of what design workflows might look like in the AI era. And by the way, this link doesn't work figma-make.md
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