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I'm building a Chief of Staff system for an EdTech founder.
The goal isn't to add another AI chatbot, but to build a system that helps a founder manage organisational information and operations more effectively.
I'm currently working on a workflow connecting Google Drive, document processing, a structured source of truth, change tracking, and an AI reasoning layer.
The system is designed to help with:
→ Finding relevant information across documents.
→ Building and maintaining organisational context.
→ Tracking changes and keeping information organised.
→ Bringing relevant information together to support decisions.
The bigger idea is to move beyond isolated automations towards a system that understands how different parts of a business fit together.
It's still a work in progress. The real test isn't whether the workflow runs, but whether it reduces operational friction and helps the founder make better decisions.
For those building AI agents and automation systems: what would you prioritise first when building something like this—organisational memory, task execution, or decision support?
#AIForBusiness #WorkflowAutomation #AIAgents #ChiefOfStaff #BusinessOperations
Memory first — and it's not close. Execution without organisational memory just automates the wrong things faster, and decision support built on stale context hands the founder confident answers drawn from old documents.
Exactly. That's why I've been building what I call a "Source of Truth" into the system.
Without reliable, up-to-date organisational context, even a well-designed AI agent can make decisions based on incomplete or outdated information. I think that's one of the most critical foundations for effective decision-making.
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I’ve built an entire Kajabi business system, website and all, with AI in hours.
Now I’m turning that process into a workflow other people can use.
It brings together the steps, instructions, and checks that guide AI from your initial idea through the build and launch. You use your own AI tools, with a clear process to follow.
This is for anyone starting a business on Kajabi, improving an existing one, or building for clients.
I’ve already done the build. What I’m developing now is the way to put that process in your hands. I’ll be sharing more soon. Who wants first dibs on access?
Building a whole Kajabi system with AI in hours is impressive. Looking forward to seeing the workflow.
🚨 A dental clinic was losing patients every single day.
Not because of bad service. Not because of high prices.
Because nobody was replying to messages.
Patients messaged on WhatsApp, Messenger, SMS… And waited. And waited. And left.
The clinic owner contacted me with one simple ask:
“I can’t hire someone to reply 24/7. Can you help?”
So, I built them an AI receptionist that never sleeps. 👇
Here’s exactly what it does:
✅ Omnichannel Support: Instantly replies to patients on WhatsApp, Facebook Messenger & SMS — all from one system.
✅ Human-like AI: Google Gemini AI understands the message, detects intent, and replies naturally.
✅ Smart FAQ Handler: Answers questions about services, pricing & clinic hours by pulling live data from Google Sheets.
✅ Automated Booking: Checks availability, blocks double-bookings, and confirms only after saving to the sheet.
✅ Instant Alerts: Notifies the clinic owner instantly via Gmail + Telegram on every new booking.
✅ Smart Reminders: Sends automated email reminders — 2 hours and 1 hour before the appointment.
✅ No-Show Recovery: Detects missed appointments and automatically sends a polite rescheduling email after 12 hours.
The Tech Stack 🛠️:
⚙️ Make.com — Automation backbone
🧠 Google Gemini 2.0 Flash — AI brain
📊 Google Sheets — Live clinic database
💬 Green API — WhatsApp integration
📱 Facebook Messenger API & Twilio — Chat & SMS
✉️ Brevo — Email reminders
📢 Telegram Bot — Owner notifications
💾 Make.com DataStore — Conversation memory per patient
The Result? 📈
Every patient gets an instant, intelligent reply — 24/7. No missed bookings. No forgotten appointments. No manual follow-ups.
The clinic owner now wakes up to confirmed appointments already in the sheet with zero manual effort.
This is what I build for businesses. If you’re still replying manually and losing leads while you sleep — DM me. Let’s fix that. 👇
#MakeAutomation #AIAutomation #NoCode #Makecom #GeminiAI #WhatsAppAutomation #BusinessAutomation #AIReceptionist #FreelanceAutomation #Upwork #Fiverr
Nice build, and very close to a WhatsApp assistant I just built for a dental-clinic use case on the WhatsApp Cloud API. Two things mattered a lot in testing: when a patient asks for a person, the bot has to go completely quiet for that chat until the owner hands it back, and the...
AI Agent vs Body
One AI agent is single-player.
Work is multiplayer.
Start with one agent. I explain it as a body.
The LLM is the brain.
It reads, writes, and reasons. It knows nothing about your business.
RAG is the brain with a library.
It looks things up in your documents before it answers.
MCP is the nervous system.
Model Context Protocol. One standard way to wire the brain to tools and data. Build the connection once, and any agent that speaks MCP can use it.
Skills are muscle memory.
Know-how saved once and loaded when a task calls for it.
The agent is the brain with hands.
It plans the steps, then carries them out in your tools.
