Theoretical knowledge from articles is insufficient for understanding AI models. True intuition is built through intensive, practical experimentation, such as feeding a model an entire codebase or extensive documentation. Pushing the AI to its limits is the fastest way to learn.
AI agents are becoming the dominant source of internet traffic, shifting the paradigm from human-centric UI to agent-friendly APIs. Developers optimizing for human users may be designing for a shrinking minority, as automated systems increasingly consume web services.
Formal, top-down AI integration protocols like MCP failed due to inefficiency and high context usage. The more successful approach was the bottom-up, community-driven emergence of 'Skills'—shareable, specific prompts that reflect how people were already organically using the technology.