Rather than writing detailed specifications, Felix Lee demonstrated that a high-level FigJam flowchart can serve as the sole input for an AI to generate a complete, playable game like Flappy Bird. The AI interprets the user flow and game logic to build the application with animations and scoring in minutes.

Creating rich, interactive 3D worlds is currently so expensive it's reserved for AAA games with mass appeal. Generative spatial AI dramatically reduces this cost, paving the way for hyper-personalized 3D media for niche applications—like education or training—that were previously economically unviable.

Instead of a complex 3D modeling process for Comet's onboarding animation, the designer used Perplexity Labs. By describing a "spinning orb" and providing a texture, she generated a 360-degree video that was cropped and shipped directly, showcasing how AI tools can quickly create high-fidelity, hacky production assets.

Creating custom "playground" tools for design exploration no longer requires advanced coding. You can simply describe the interface and the controls you want (e.g., "a grid with sliders for rows and opacity") in a natural language prompt to an AI, which will generate a functional tool.

Large language models are insufficient for tasks requiring real-world interaction and spatial understanding, like robotics or disaster response. World models provide this missing piece by generating interactive, reason-able 3D environments. They represent a foundational shift from language-based AI to a more holistic, spatially intelligent AI.

Modern coding agents can now execute entire data analysis workflows in a single request. This includes scraping public data via custom queries, performing analysis, and generating publication-ready visualizations based on provided style guides and theoretical principles, collapsing a multi-day task into minutes.

Coding agents are becoming powerful tools for general knowledge work. A non-technical user was able to point Claude Code at a data file and have it autonomously produce five complete, well-designed HTML dashboards and analysis reports.

Claude Code can take a high-level goal, ask clarifying questions, and then independently work for over an hour to generate code and deploy a working website. This signals a shift from AI as a simple tool to AI as an autonomous agent capable of complex, multi-step projects.

Use Claude's "Artifacts" feature to generate interactive, LLM-powered application prototypes directly from a prompt. This allows product managers to test the feel and flow of a conversational AI, including latency and response length, without needing API keys or engineering support, bridging the gap between a static mock and a coded MVP.