Writing

Documentation turns tacit knowledge into a strategic asset that scales communication, preserves institutional memory, and becomes the training data powering custom AI solutions. By making it context-fit, concise, visual, skimmable, current, and discoverable—and extending its depth for AI-native use—organizations convert unique insights into lasting competitive advantages.

This post examines how growing organizations can devolve into bureaucratic labyrinths that stifle innovation, drawing on insights from Olson’s theory to Conway's Law. It highlights real-world examples and strategies for streamlining processes, ensuring that the structures meant to ensure efficiency don’t ultimately hinder creativity.

Engineers know that 3D printing works best as part of a larger material system—not as a standalone solution. This principle of "borrowing tolerances" from steel, silicon, and other materials reveals a useful analogy for AI development. Like the PLA filament in thoughtful engineering designs, AI delivers its best value when integrated within robust technical systems that leverage each component's unique strengths.

Technological breakthroughs have historically shifted from engineering challenges to marketing battles, as seen with personal computing, the internet, search engines, and electric vehicles. Now, the real test for autonomous vehicles is convincing consumers and regulators, raising the question: who will lead this marketing revolution?

AI is not the harbinger of low-quality content, but a catalyst for an influx of high-caliber material on the web. As AI models favor authoritative inputs, organizations will shift towards creating more valuable content to influence AI-driven decision-making.

Don't let SaaS solutions train on your unique competitive advantage and protect your company's unique IP by building your own custom AI.