Everyone Wants to Be Your One Place to Work

Hello,

This is Simon with the latest edition of The Weekly. In these updates, I share key AI related stories from this week's news, list upcoming events, and share any longer form articles posted on the website.

For many office workers, we often have to switch between a number of different platforms to find information, or undertake different tasks, all of which can be frustrating and time consuming. When I was working at Salesforce, there was a strong push to put Slack at the centre of our day-to-day work. Various integrations allowed us to interact with data from within Salesforce, right in the same place we'd discuss items with colleagues, quickly taking over from the old Chatter system that was embedded into Salesforce. The vision was to have everything you need at your fingertips, and less need to keep swapping between different tools.

Now that Salesforce has turned Slackbot into a full AI agent, it feels like they might have finally achieved that vision from four years ago.

And this week, I’ve also noticed an update to Claude, Anthropic’s chatbot, which is starting to mirror that same vision.

Through the power of the Model Context Protocol (MCP), Claude now connects to various apps and workplace tools, allowing you to interact with them all from within the chatbot. I can search my Google Drive, read and respond to emails, check my calendar, and interact with my Notion databases, all without leaving the conversation.

It’s interesting to see how the two systems are starting to overlap. Where Slack began as collaboration and added AI, Claude began as AI and is adding collaboration tools. They're meeting in the middle.

And it isn’t just these two tools alone that have the same vision.

ChatGPT has fully adopted MCP and is now letting business users connect it to their external tools and data. Microsoft is positioning Copilot Chat as "the centre of the new agentic workplace" and has added MCP support to Teams. Whilst Notion has built their own MCP server so that Claude, ChatGPT, and Cursor can all read and write directly to your workspace.

Everyone, it seems, wants to be the one place you work.

When MCP was first introduced in late 2024, it felt like another step change in how we could use AI at work. All of a sudden, we weren’t limited to simple back and forth with a chatbot, but could connect different systems together to undertake tasks. Exciting for early adopters, but still niche. But now, MCP is quickly becoming an everyday standard. There are tens of thousands of MCP servers available, and every major AI player supports it.

This is genuinely exciting. The friction of switching between apps, copying and pasting content, and manually connecting information across tools is starting to disappear, replaced with more efficient workflows.

But here's where I'd urge some healthy scepticism.

The lock-in question. If you build your workflows around one platform's integrations, how easy is it to switch? MCP is an open standard, which helps, but each platform is also building proprietary features on top of it.

The "everything app" trap. We've seen this before. Slack wanted to be where work happens. Teams wanted to be where work happens. Notion wanted to be where work happens. Now AI chatbots want to be where work happens. At some point, you have to ask, does consolidation actually help me, or is it just a way for these platforms to get all of our data in place?

The future I'm hoping for isn't one hub to rule them all. It's a standard that lets you choose your own adventure.

Are you experimenting with any of these AI hubs? Hit reply and let me know.

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In this section, I’m going to bring to you a real world example of AI use.

Real estate agents are increasingly using AI tools to handle the “busy work” of their day: writing property listings, analysing local markets, responding to enquiries, and preparing marketing materials. According to industry reports, some agents are saving 10+ hours a week by letting AI handle repetitive tasks.

Why this matters: This is a textbook example of how AI is being adopted in the real world: quietly, practically, and without hype. Many white-collar jobs will change in similar ways, even if job titles stay the same.

A new report from McAfee highlights an unexpected cost of AI: people now spend nearly three working weeks a year trying to work out what content is real. AI-generated spam, fake images, scam messages, and low-quality content are flooding inboxes and social feeds.

Why this matters: As AI-generated content becomes harder to spot, individuals and businesses alike will need better tools, habits, and safeguards

Singapore announced plans to invest roughly $785 million in public AI research through 2030. The funding will support universities, startups, and public-sector AI projects, positioning AI as a long-term national capability rather than a short-term tech trend.

Why this matters: Governments increasingly see AI as essential infrastructure, similar to transport or energy. This will influence regulation, skills training, and where global AI talent and businesses choose to locate.

Thanks for reading, and see you next Friday.

Simon,

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