A month with Alexa+: Amazon's smart assistant falls flat

A month with Alexa+: why Amazon's smart assistant isn't that smart

Amazon has long promised that voice technology would change how we interact with devices at home. When the company unveiled Alexa+ as a next-generation assistant built on powerful language models, expectations ran high. The reality turned out to be far more mundane. After a month of daily use of an Echo Show 15 with Alexa+ in the kitchen, one thing became clear: Amazon's flagship product falls well short of the bar its competitors set today.

Context matters here. The voice AI assistant market is in the middle of a sharp shift. OpenAI's ChatGPT and Google's Gemini have already trained users to expect meaningful, context-aware answers, assistants that can follow the thread of a conversation, and support for multi-step requests. Against that backdrop, Amazon bet on Alexa+ as its answer to the new era of conversational AI. The company positioned it as an assistant woven deeply into everyday life, one that understands not just commands but intentions. The marketing promised smooth, natural conversation. A month in the kitchen showed a chasm between the promise and the delivery.

The problems started almost immediately. Alexa+ consistently fails to hold context within a single conversation. Ask a follow-up question after an initial request, and the assistant often loses the thread and answers as if the previous exchange never happened. Simple household tasks — timers with explanations, recipe questions with follow-ups, controlling the smart home through a chain of commands — turned into tests of patience. Intent-recognition errors happened so often that trust in the device quickly evaporated. The irony is that the kitchen, the very environment the Echo Show 15 was designed for first and foremost, exposed the product's weaknesses most harshly.

The technical root of the problem appears to lie in how Amazon integrated a language model into Alexa's existing architecture. The classic Alexa was built as a collection of skills: rigidly structured, predefined scenarios. Layering generative AI capable of free-form conversation on top of that system is much harder than building such an assistant from scratch. Companies like OpenAI and Google built their products around a language model as the core, while Amazon apparently is trying to adapt an old paradigm to new demands. That structural contradiction shows up in every awkward answer and every lost bit of context.

The consequences for Amazon reach far beyond a single product. For decades, Alexa has been the company's main trump card in the smart home: an ecosystem of devices, millions of users, deep integration with services. If Alexa+ can't handle basic tasks, that entire infrastructure is at risk. Users who have switched to the voice interface of ChatGPT or Gemini and gotten a fundamentally different experience are unlikely to want to return to an assistant that regularly gets confused. That's especially true as Apple actively develops Siri with ChatGPT integration and Google builds Gemini directly into Android. Amazon risks falling behind in a race it once led.

For the average consumer, the Alexa+ story is above all a story about inflated expectations. When a company makes bold claims at launch and then fails to deliver, trust takes a long-lasting hit. The Echo Show 15 is still a functional device: the screen is handy, basic commands work, and the integration with Amazon services hasn't gone anywhere. But Alexa+ as a symbol of a new generation of AI is, for now, more a marketing pitch than a reality.

Amazon has the resources to fix this. The company has invested billions in Anthropic and has access to cutting-edge language models. The question isn't capability but execution and priorities. Until Alexa+ learns to hold context, understand intent, and handle everyday requests decently, it will remain a reminder of how hard it is to catch up with the leaders at a time when the bar for user expectations has risen to a fundamentally new level.