The AI personalization race is ultimately a battle over who gets to hold the complete picture of your work and life.

Up until now, our digital context has been deeply split. Google has historically held a massive, unmatched advantage on the individual consumer side. They own the ultimate personal data layer: your private emails, calendar, maps, and search history. For solo personal productivity, that friction-free history is nearly impossible for anyone else to replicate.

But the real product battleground right now is where that personal history collides with your professional life. Google is attempting to seamlessly blend individual personal context with enterprise team data.

Meanwhile, pure-play AI companies like Anthropic are executing a completely different strategy. They don’t have access to your personal inbox, so they are hyper-focusing on building a deep, collaborative context layer exactly where you work.

Their recent launch of Claude Tag inside Slack is a perfect example. Instead of relying on your personal history, it embeds a shared AI teammate directly into multiplayer team channels. It absorbs organizational context from live threads and project data in real-time, personalizing itself to your team’s workflow rather than your individual past.

The takeaway? Google is scaling personalization from the individual’s lifelong data outward to the enterprise. Anthropic is building an enterprise context layer from the team inward.

The next few years won’t be about who builds the smartest model, but who captures the specific slice of your context that you rely on most to get things done.

In Scrum, there are just three roles. There is the Product Owner, Scrum Master, and Developer. Developers are the doers of the scrum team. It doesn’t matter if you are working on design, programming, or architecture. No matter what the actual work is, doers are still developers.

The great thing about AI, or maybe the worst thing about AI, depending on your viewing is this: AI is making everyone into developers. There is still going to be specialization, and backlog items are going to be assigned. But in this new world, it doesn’t matter if you went to school and got a CS degree, or if you’re an MBA — you’re still a developer. That’s because everyone has within their grasp the ability to do the job, even if it is poorly.

Post by @carnage4life@mas.to

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Want to speed up? Teams that embrace this dynamic are going to go further than teams that don’t. The less siloing and gatekeeping of functions, the more software will be produced, and the faster the teams will get. Reserving some types of work for specific people will slow things down. And if you see someone else doing something badly, and something you’re expert in, you can always pitch in and fix it or improve it.

This article on Substack¹ was sent to me by Nate — thanks!

Product Managers are suddenly essential. I agree with most of the article, but I’d add that successful Product Managers focus on the business model. Everyone needs product management, but given their wide range of responsibilities, it’s better to hire someone experienced than try to handle it yourself.

Also, isn’t that true for most fields? Sure, I can design with AI, but it often looks like AI design. I can do QA with AI, but I’ll have to accept its results, which aren’t always perfect. Or I can have AI write code, which is helpful but still needs supervision.

The big issue is that all of these pronouncements about specific careers, whether it is from one company eliminating a function or a big reorganization at a tech giant, is leading to massive shifts in sentiment and job activity. We’ve never been in a more precarious and risky place when it comes to careers.