AI4 mins read

Google Gemini’s Branding Problem Shows AI Apps Are Still Too Hard to Use

TechCrunch argues that Gemini’s growing set of branded features reflects a wider AI app problem: users are being asked to understand product architecture instead of simply getting help.

Gemini’s feature names are getting in the way

TechCrunch’s central argument is straightforward: consumer AI apps should not make people learn how a company has organized its product internally. Google’s Gemini app includes separate areas such as chat, Spark, and Daily Brief, each with its own icon and place in navigation. That structure can make the app feel more cluttered than helpful, even as Google says users should not have to guess which feature a task requires.

Daily Brief and Spark show two different UX problems

Daily Brief is described as an AI-enabled agenda that offers “proactive, personalized updates” using data from Google apps like Gmail and Calendar. The article argues that it can blur the line between useful, actionable information and unwanted nudges tied to past activity, including prior Google searches. Spark has the opposite issue: it may be useful as an AI agent that can act on a user’s behalf, but TechCrunch argues it does not need to be packaged as a separate stand-alone brand for mainstream users.

The issue extends beyond Google

The article frames Gemini as part of a broader AI industry habit: exposing internal product architecture directly to consumers. It points to Anthropic’s Claude and its Cowork mode, noting that until this week those two modes did not share memory of past conversations. It also cites ChatGPT’s split between “Chat” and “Work” as another example of AI interfaces asking users to choose between branded modes instead of simply making a request.

Simpler interfaces may be the real advantage

TechCrunch contrasts these branded AI surfaces with Apple’s approach to Siri, where existing tools such as Spotlight Search, Photos, the iPhone camera, and voice requests become smarter without forcing users into a new interface. The article also highlights text-based AI services, where users message a chatbot and expect it to act without extra setup. The key takeaway: AI products may win trust and usage by hiding complexity, not naming every layer of it.

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