Most people lose momentum the moment they switch AI models.
Claude hits its limit → open ChatGPT.
Need to code → jump to VS Code.
Every switch = start from zero.
Rewrite the prompt. Re-explain the project. Rebuild the context.
That's not an AI problem. That's a workflow tax.
I found a way to carry your AI context across tools, so the work continues instead of restarting.
Here's how it works:
1. Save your conversation context
2. Drag and drop it into the next tool
3. Pick up exactly where you left off
Works with Claude, ChatGPT, VS Code, MCP servers, and more.
AI workflows are evolving from isolated chats into persistent systems with shared memory.
Most people think automation is just for big companies. Here’s what they’re missing 👇
The AI automation market just crossed $169 billion in 2026 and most small business owners still think it’s too expensive or complicated for them.
Here’s the truth:
77% of the devices people use daily already run on AI — and most people have no idea. Your phone camera, your email spam filter, your bank fraud detection — all automated.
Businesses using automation save 15–25 hours per week on repetitive tasks. That’s almost an extra full-time employee — for free.
Error rates drop by 85% in data entry and processing when automation handles it. No tired eyes, no Monday mistakes.
97% of executives say their company deployed AI agents in the last 12 months. The shift isn’t coming it already happened.
The companies winning right now aren’t the biggest ones. They’re the fastest ones to automate the boring stuff and focus human energy on what actually grows a business.
A WhatsApp chatbot answering customer questions at 2am. A workflow that follows up with every lead automatically. An AI agent booking appointments without anyone lifting a finger.
This is what I build for businesses every day.
If you’re still doing it manually — let’s talk.
I’ve been experimenting with how AI and automation can improve guest communication in hotels.
I built a simple workflow where a guest submits a request through a chat interface. For example, a guest might ask for a late checkout, room service, housekeeping, or a spa booking.
Once the request is submitted, it’s sent to an automation workflow built in n8n. The AI reads the message, understands what the guest is asking for, and classifies the request.
From there, the request is automatically routed to the correct department. A late checkout request goes to the front desk, a room service request goes to the food and beverage team, and so on.
The workflow also stores every request in Google Sheets, creating a simple record of guest activity that staff can review at any time.
At the same time, an email notification is automatically sent to the relevant team with the guest’s request, the AI’s interpretation of the request, and a suggested action.
What I find interesting is that the entire process happens in seconds. The guest submits a request, the AI understands it, the request is logged, and the right team is notified without anyone manually forwarding emails or passing messages between departments.
The goal isn’t to replace hotel staff. It’s to remove repetitive admin work so teams can focus on delivering a better guest experience.
Still learning and improving it, but it’s exciting to see the workflow running end to end.
#AI #Automation #Hospitality #Hotels #n8n #BuildInPublic #Automation #n8n
Is anyone using #MTNFibre X? Are you able to browse or connect to the internet this week? I’m experiencing challenges and also getting poor responses from their customer care.
And to @MTNNG@MTN180@MTNFoundation you should always inform your customers on time, maybe through email or a direct message, if there is any outage or service disruption, so we are aware. The way you treat customers is unacceptable.
#mtn
Prediction 2 is the one nobody in the room wants to say out loud but a lot of people are thinking quietly. We’re essentially watching companies spend billions to prove whether this is a gold rush or just… really expensive autocomplete. The neurosymbolic angle is interesting though, if something more efficient does emerge, the switch could happen faster than people expect. What’s your timeline on prediction 1? 5 years? 10?
@Ronald_vanLoon@antgrasso The accessibility angle here is massive, imagine someone in a rural area getting reliable medical guidance at 2am without traveling hours to a clinic. But I’m curious, how do we handle cases where the AI misreads symptoms? Who takes accountability then?