World's Most Expensive Serializer

We’ve built the worst serialization library in computing history, and we’re scaling it across every company with an AI first goal.

Let’s sketch this out: A human has a thought. Let’s say: “We should ship this feature faster.” Instead of saying that in a meeting, they open Claude and ask it to write a strategy document. Claude serializes the thought into 2,000 words of corporate prose—complete with “key stakeholders,” “strategic alignment,” and a section on “driving synergies.”

The document gets sent to three other humans.

None of them read it.

Instead, they paste it into ChatGPT and ask for a summary. ChatGPT deserializes the prose back into: “Ship the feature faster.”

Net result: We went from thought → expensive token round-trip → same thought and nobody read (needed?) the middle part.

Corporate Comfort & Tool Shaped Objects

Because the tools exist. Because the document isn’t for reading—it’s for having been written. The summary isn’t for understanding—it’s for having been processed.

Both parties can now point to artifacts. “I sent the comprehensive strategy doc.” “I reviewed the materials.” Actual information transferred: nearly zero. Appearance of productive process: flawless.

We’ve built tool-shaped objects—things that look like work, smell like work, and generate the same Jira tickets as work, but don’t actually do the thing we pretend they do.

The AI isn’t the problem. The AI is just doing what we asked: making it easier to produce artifacts. We’ve automated the performance of work while carefully preserving all the inefficiency of the actual work.

And somehow, we’re calling it productivity.