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The gap between having an idea and showing it has collapsed. In this post, I document the 9 Google specific AI workflows I demonstrated in my SCU Product Management class. From generating full-stack prototypes in seconds with Gemini Canvas to building custom strategy tools with Opal, this guide covers how to research, build, and validate at the speed of thought. Whether you are a student or a seasoned PM, these tools will supercharge your velocity.

The whispers have solidified into code. GPT-5 has arrived, and it's not another incremental update—it's a seismic shift. We're moving beyond mere assistance to genuine cognitive partnership. What does it mean when an AI can synthesize an entire book, generate an application from a "vibe," and curtail hallucinations to become a reliable partner? It means the landscape has fundamentally changed. This post dissects the architecture of our new reality.

Ever wish your AI could remember what you said or work seamlessly with other tools and agents? Enter Model Context Protocol (MCP), an open-source framework that gives AI shared memory and universal access to tools, data, and prompts. MCP transforms isolated models into collaborative, context-aware systems, enabling real-time insights, personalization, and multi-agent orchestration. It is the backbone of a smarter, more connected AI future.

For years, the Application Programming Interface (API) economy has been the silent engine of the digital world, enabling seamless connections between disparate software systems. From integrating payment gateways to embedding mapping services, APIs have fostered a modular, reusable, and incredibly efficient way to build and scale products. But as Artificial Intelligence rapidly matures and its capabilities become increasingly sophisticated, a powerful new synergy is emerging: