You Might Stop Using a User Interface

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.

I've been talking a fair bit about MCPs recently, which is probably quite a technical topic for this audience, but as I play around with the technology more and more, I can’t help feel how it’s going to fundamentally change how we interact with software systems over the coming months and years.

For example, I spoke to a client last week, or told me they want to work with our platform through external AI tools as much as possible. Whilst they are very happy with our user interface, they want to interact with us through coding and AI tools as much as possible as they find that the most efficient way.

With AI tools like Claude adding more and more Connections to their platform, I can foresee a future where we wont login in to a number of different platforms to make updates, such as adding data in a CRM, but rather prompting our AI tool to do instead. And it won’t just be the CRM, but nearly all of the business applications we work with in our working day. Your AI tool will become your main command centre allowing you to orchestrate many different platforms.

You might naturally ask if this is safe and secure, but if you’re using Enterprise subscriptions for platforms like Google Gemini and ChatGPT, they ensure that no data is used to further train their models and provide robust security and governance controls.

Personally, I find this potential future pretty exciting. If anyone has spent time copying and pasting data from excel sheets or notes into platforms, no doubt you will too.

2026 is the inflection point for customer experience.

AI agents are becoming infrastructure — not experiments — and the teams that win will be the ones that design for reliability, scale, and real-world complexity.

This guide breaks down six shifts reshaping CX, from agentic systems to AI operations, and what enterprise leaders need to change now to stay ahead.

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Exclusive for subscribers.

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

OpenAI introduced Frontier as a platform to build, deploy, and govern multiple AI agents (including third-party ones) in one place—aimed at solving “agent sprawl” and tightening

Why it matters: This is the “Operations layer” for agentic AI, expect more firms to move from pilots to managed fleets of AI coworkers, with compliance and access controls becoming a buying criterion.

Microsoft announced general availability of 35 new Copilot connectors, extending Copilot’s reach into more external systems (project management, ITSM, content and some vertical tools).

Why it matters: Copilot gets more useful as it can “see” more of your real work context. But connectors also raise governance stakes: permissions, data leakage, and auditability become board-level topics faster than many expect.

AI is supposed to be more efficient and save us time working on tasks, but a new HBR piece argues that instead of shrinking work, AI can intensify it, raising pace and expectations.

Why it matters: If your AI strategy is “do more with less,” watch for burnout and quality drift. The winners will be the companies that can pair AI rollout with operating model changes.

Thanks for reading, and see you next Friday.

Simon,

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