A workflow list with forty items called "New Workflow" is a trap. A simple naming habit helps: start with the client or area, then the trigger, then the goal. For example, "Dental | Missed Call | Text-back". When something breaks at 9pm, you'll find the right one in seconds instead of opening five. What's your naming convention for workflows?

When SMS stops landing, the workflow is often fine and the cause is somewhere else. Start with the registration status of your sending number, since unregistered or pending numbers get filtered. Then look at the message itself: shortened links, all caps and heavy punctuation get flagged faster. Check that the contact actually opted in and is not marked do not disturb. Look at quiet hours and the contact's time zone, because a message can be held or sent at a bad hour. Last, check the conversation log for the exact delivery status of one failed message before changing anything. Working through those in order usually finds it in a few minutes.

I'm using GoHighLevel (GHL) with a Conversational AI bot that handles incoming WhatsApp messages, answers customer questions, and qualifies leads before handing them over to my sales team. What I'm trying to build: An internal AI assistant that I can chat with in natural language to analyze conversations and CRM data across my entire GHL sub-account. For example, I want to ask: - How many customers contacted us today? - How many were qualified leads versus irrelevant inquiries? - How many requested actual quotations? - Which leads are waiting for a response or follow-up? - Which conversations should my sales team prioritize? - Can you summarize today's conversations and identify potential lost sales opportunities? What I've already tried: 1. Claude in Chrome: I've been using Claude to read and summarize conversations directly from the GHL interface. It works, but it's inefficient and not scalable. 2. Claude + GoHighLevel MCP: I also connected HighLevel to Claude through MCP. However, the connection keeps disconnecting every other day without any clear explanation. I have to reconnect it manually, and I don't always realize when it has stopped working. This makes it unreliable for daily business operations. What I'm considering: - GoHighLevel Managed AI Agents - GHL MCP Server integration - Claude or ChatGPT connected directly to GHL - Custom API integrations or automation workflows My main questions: 1. Has anyone successfully built an AI agent that can access and analyze conversations across an entire GHL sub-account, rather than just individual contacts? 2. Has anyone experienced frequent MCP disconnections between Claude and GHL? If so, how did you fix them? 3. Can GHL Managed Agents handle this type of internal reporting and analysis? 4. What's the most reliable architecture for keeping an AI assistant connected to GHL without constantly reconnecting or manually exporting data? My ideal setup: I want to open an AI chat, ask questions about my WhatsApp conversations and sales pipeline, and receive accurate, actionable answers based on real CRM data.