By most yardsticks, Google’s Gemini is on a serious winning streak. It’s improved fast, become impressively strong at image generation, and even secured Apple’s business. So when Google announced a new feature called Personal Intelligence, it sounded like a confident victory lap.
Personal Intelligence lets Gemini reference your past conversations and—if you opt in—pull context from other Google services like Gmail, Calendar, Photos, and Search history, without you explicitly asking it to check those sources every time. You control which apps it can access, and it’s currently in beta for AI Pro and Ultra subscribers.
The big change: less “babysitting”
In the past, Gemini could connect to Workspace apps, but it often required manual prompting—“check my email,” “look at my calendar,” and so on. Now it can decide on its own that a prompt might require looking up an email (like a concert ticket) and go fetch it automatically.
That shift is meaningful. If an assistant needs constant micromanagement, it’s not much better than the basic voice assistants we’ve had for years.
When it works, it’s genuinely impressive
After enabling Personal Intelligence, Gemini suggested prompts like personalized book recommendations—and the suggestions were “annoyingly accurate.” In another example, it helped plan backyard lawn strategies, offered native plant ideas, created calendar reminders, and built a shopping list in Google Keep. The author notes that only a couple months earlier, Gemini often failed at tasks like “add this to my calendar,” so this feels like a real leap.
The catch: details still break the magic
Where Gemini stumbles is accuracy at the granular level.
When asked to brainstorm bike routes with a coffee stop, Gemini’s high-level ideas were fine—but the specifics got messy. It claimed to create routes in Google Maps, but the links didn’t match what it described. Some route suggestions also sounded risky or unrealistic.
The same pattern showed up when recommending neighborhoods for photo walks and coffee. Gemini correctly used personal context (like excluding areas the author had lived in), but then recommended specific places that were wrong: mislocated businesses, cafés that didn’t exist where Gemini claimed, and even shops that appeared closed on Google Maps.
The result: the user ends up fact-checking and reprompting so much that it feels like more work than it’s worth.
Accuracy and privacy collide
This is Gemini’s immediate challenge: it can now do “personal” reliably, but wrong details are a dealbreaker in real life. You only have to show up once at a vacant storefront to lose trust.
And beyond correctness, there’s the privacy discomfort. At one point, Gemini referenced the author’s husband and child by name—something that’s technically possible with email/calendar access, but still unsettling when it happens in conversation.
A useful tool—if you watch your step
Despite those concerns, Personal Intelligence expands what Gemini can be used for—at least a bit. It’s helpful for early-stage planning (yard work schedules, shopping lists, idea generation), even if the user still relies on humans to validate the final decisions.
In short: Gemini is becoming more capable and more integrated, but the more it behaves like a personal assistant, the more accuracy and trust become non-negotiable—and the more its “helpfulness” can start to feel intrusive.
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