Don't feel pressured to label every AI-powered enhancement as an "AI feature." For example, using AI to generate CSS for a new dark mode is simply a better way to build. The focus should be on the user benefit (dark mode), not the underlying technology, making AI an invisible, powerful tool.

Integrating generative AI into Alexa was complex due to its massive scale: hundreds of millions of users, diverse devices, and millions of existing functions. The challenge was weaving the new tech into this landscape without disrupting the user experience, not just adding an LLM.

Amazon's product development philosophy has evolved. To be released, a device must first be excellent as a standalone product, delivering perfectly on its core function. Secondly, it must seamlessly integrate with the broader ecosystem (e.g., Alexa) to create an interconnected experience greater than the sum of its parts.

MCP shouldn't be thought of as just another developer API like REST. Its true purpose is to enable seamless, consumer-focused pluggability. In a successful future, a user's mom wouldn't know what MCP is; her AI application would just connect to the right services automatically to get tasks done.

A truly "AI-native" product isn't one with AI features tacked on. Its core user experience originates from an AI interaction, like a natural language prompt that generates a structured output. The product is fundamentally built around the capabilities of the underlying models, making AI the primary value driver.

The best agentic UX isn't a generic chat overlay. Instead, identify where users struggle with complex inputs like formulas or code. Replace these friction points with a native, natural language interface that directly integrates the AI into the core product workflow, making it feel seamless and powerful.

The most effective application of AI isn't a visible chatbot feature. It's an invisible layer that intelligently removes friction from existing user workflows. Instead of creating new work for users (like prompt engineering), AI should simplify experiences, like automatically surfacing a 'pay bill' link without the user ever consciously 'using AI.'

To get mainstream users to adopt AI, you can't ask them to learn a new workflow. The key is to integrate AI capabilities directly into the tools and processes they already use. AI should augment their current job, not feel like a separate, new task they have to perform.

Alexa's architecture is a model-agnostic system using over 70 different models. This allows them to use the best tool for any given task, focusing on the customer's goal rather than the underlying model brand, which is what most competitors focus on.