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Why building a system so you understand it means you're doing it wrong.

Featuring From the Weekly Meeting. Published July 11, 2026.

Michael Wacht explains a contrarian approach to organization: if you build your system primarily so that you can understand it, you’re building it incorrectly for an AI.

As we move toward AI-driven workflows, human readability becomes less important than machine readability. This clip explains why you need to change how you structure your data.

More from the Weekly Meeting

Why running local AI is like being a PC gamer.

  • Collin Thomas

Collin Thomas uses a vivid analogy, comparing the expertise needed to run local AI models to PC gamers overclocking their rigs.

Why you need to turn your training data off right now.

  • Michael Wacht

Michael Wacht gives a 17-second warning on why you should turn off training data sharing in your AI tools, and what companies retain if you don't.

Why you should build your organization system for the AI, not for yourself.

  • Jacob Brodsky
  • Collin Thomas
  • Michael Wacht
  • Matthew Sutherland

Jacob Brodsky, Collin Thomas, Michael Wacht, and Matthew Sutherland discuss why your current organization system will inevitably need to change. They explain why you should keep your core method stable while swapping the underlying parts, and why building structure for a machine to read is more important than building it for human readability.

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This clip comes from the AI for Life Weekly Meeting, live Wednesdays at 11 a.m. Eastern. Join the community to be in the room for the next one.