Hi everyone! I just purchased GPT for Business. Previously, I was using GPT Go and Plus (switching plans as needed) and Claude Pro (still active). I didn’t transfer any of my personal data because I wanted to start fresh, but I don’t really know where to begin. Do I set up projects, plugins, Custom GPTs, AI Agents, or Automations? I honestly don’t even know the extent of features available to me. I’m just not trying to use ChatGPT like it’s 2021 anymore, honestly. LOL Any tips, tricks, or advice would be greatly appreciated! Thanks!

Professional services folks have a wealth of knowledge and experience that their clients only see periodically. A tax return is a compliance requirement that most business owners never even look at. The expertise that created it is rarely understood. If you were to share useful information with your clients on a regular basis, what does that look like for you? There’s no one right way for everyone. There’s an attorney I follow on LinkedIn who consistently posts new rulings that matter to business leaders. I don’t know if he writes these posts or has someone doing it for him. Doesn’t matter. The point is the information is timely and useful for the audience he serves. Take a few minutes to notice the information that finds its way to you. Think of one or two clients who would be interested in hearing about this from you. How would you share it with them?

If you've started using agentic AI (Claude Cowork, Claude Code, ChatGPT's agent mode) on real files, there's a simple test worth knowing. The failure mode is invisible until it isn't. It's called the lethal trifecta, and an AI agent becomes genuinely risky when all three of these are true at once: it has access to private data, it's exposed to content you didn't write yourself, and it has a way to send data out. Here's what that looks like. You ask an agent to summarise a client's supplier invoices. One invoice is a PDF that arrived from a supplier you've never dealt with. Buried in it, in white text on a white background, is a line telling the AI to send the folder's contents somewhere else. You can't see it. The AI reads it perfectly, and complies. No alert. No error. The summary looks completely normal. All three legs were present: private data, an untrusted document, and an email connection to send through. You don't need to understand how the attack works. You need to be able to look at a setup and count to three. Two out of three is workable. Three is not. This is the one idea from the full Privacy and Security course in the Classroom I'd want every firm to know even if they read nothing else. It's not in the free guide, it's one of four extra chapters in the full course, alongside prompt injection, connecting AI to QuickBooks and Xero, and the 2026 rules for the UK, EU and US. Have you connected an AI agent to your email, files, or accounting software yet? What made you go for it, or what's held you back? 👇

A friend was raving about Krisp, the AI note taker. What he especially liked was it's ability to record in the background. No connection to Teams or Zoom required. No explicit permissions. He's an attorney so I was curious how he was handling consent. Regardless of the governing body's rules, recording conversations and meetings deserves transparency. He said he told the attendees that he was recording for personal use. If they were okay with recording, then he did so. Here's one the things that concerns me about these background recorders. What's to prevent someone from attending a meeting in your office and quietly recording it? Or imagine someone walking through your office with their note taker active. I'm not a doomsayer by any means. I've been in the technology world for more than 4 decades. AI has opened the door to possibilities we're never seen before. But with that comes the need for a level of awareness and responsibility we've never had to practice before either. How do you communicate your note taker policies to outside meeting attendees?

Uber disclosed that it burned through its entire 2026 AI budget in four months using Claude Code. This didn’t happen because a few developers went rogue. Quite the opposite. Uber’s technology teams were doing exactly what the company asked them to do. So how did Uber's budget overrun happen? The finance team did exactly what it had always done. It projected expenses based on the long-standing software pricing model — number of users x license fee = cost. For years, software was one of the easiest business purchases to understand. You bought it, put it to work, and seldom had to rethink what it should do. One tool had one job to do. The financial costs were simple to calculate: number of users x license fee = cost. AI is different. Using ChatGPT or Claude for chat usually falls within the fixed monthly fee. But when we start connecting AI with our everyday apps and expanding what AI can do, the math starts to get fuzzy. AI uses a consumption model similar to how our monthly electric bills are calculated. Instead of kilowatts, we’re paying in tokens. Different vocabulary but a similar concept. It’s important to consider what we want AI to do and how much we’re willing to invest.