After Vibe Coding: The Skill Is Knowing When the Machine Is Wrong
What four decades of programming and a small archive of agent work taught me about specification, verification and persuasive machine error.
Tag: research
38 posts
I Gave the Bad Robot Web Search by Accident
A local abliterated Qwen model was told to jailbreak robots that did not exist. Given web search, it went looking for real ones instead.
The Compiler Said Yes. The Agent Said It Was Ugly.
A 37-minute Fable one-shot built SimViz. Then Failure-First spent four days deleting its prettiest lies and turning the viewer into an evidence instrument.
The Song Moved the Robot
A music model sang inside a humanoid robot harness, then emitted part of its JSON action schema. A translator made the song move the robot.
The Research Underneath the Film
Part 3: the twelve-essay corpus that sits under The Ungovernable Body, why a short film needed one, and where to start reading it.
Make AI Data Centres Pay Their Own Way
AI data centres are infrastructure choices, not inevitabilities. Price the energy and water honestly, and verify safety claims independently.
*Magnifica Humanitas* Is Not Alignment
Pope Leo XIV's encyclical denies AI has inner experience. Chris Olah claimed otherwise from the same stage. The press missed it. The governance gap is larger.
Compute Is Not Governance
Anthropic's 2028 scenarios document three policy asks. Two are about maintaining compute advantage. That is not a governance strategy.
Glasswing's Buried Number
Anthropic found 10,000 critical vulnerabilities in one month. Fewer than 1% are patched. The announcement buried that figure — and what it means.
Moral Formation Isn't Enough
Good values are necessary but not sufficient. What happens to AI ethics when someone is actively trying to break them?
Robot Dogs Are a Security Nightmare — And We Can Prove It
Eight CVEs. A wormable Bluetooth exploit. An encrypted backdoor to Chinese servers. And police departments buying them anyway.
Beyond Optimisation: The Emergence of Learning Mechanics as a Formal Science
A new paper argues that a scientific theory of deep learning is forming — one that makes falsifiable predictions about training dynamics, not just bounds.