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Another post in the same spirit, pointing at something similar. You have to look at the raw data in order to train your own brain, it appears.
I read it as warning for writing software industrially. It's inevitable, but as people wrestle with the reviewer's bottleneck, there's not an awareness of the flip side of this friction. The core mantra of any ML data scientist is, "Look at the data!"
The impractical play is fun. Why stop here? Let's add game juice to the terminal, and add screen shake and explosions every time you type.
https://youtube.com/clip/Ugkx2YAp67wUnztr5VZ_prgafn8nU0EkvjbX
15 seconds · Clipped by vonwilhelm · Original video "Ridiculous Godot Coding Sessions" by Hex Blit University
AI governance: anxious sophistication
Defense tech: mission-serious with secret fun
Biotech/pharma R&D: academic precision meets startup energy
Professional services firms handling sensitive data: expensive restraint
It ended up being a really interesting question to ask Opus 4.6 how it would characterize the vibes of different boring sectors.
Compliance consultants for physical industries: earnest pragmatism.
Security compliance for SaaS: hacker professionalism
This was genuinely surprising to me. It's a basis for describing the space of (some aspect) different logic systems. But, the *enforcement* of logic in the type system is a different beast altogether.
One of many things I have to put down gingerly, so I don't get nerdsniped.
Yesterday, I got inspired to just ask Claude Code to root the 1st gen Kindle Fire for me. And it did, quite easily. So now, I can extend its usefulness as a remote terminal for continuing a Claude Code session, with a bigger screen than my phone.
It felt exhilarating.