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408 posts on AI agents, the laws and asymmetries that shape how we build, and lunch-break physics. Search, filter by tag, or start with a series.
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2026
- Content Provenance Is Growing Up: What Anthropic's Watermark Really Signals
TL;DR: Text from Claudeās newer models carries an imperceptible statistical watermark, and its generated files carry a cryptographically signed C2PA provenance manifest where the platform supports it.ā¦
- AI Moved Into the Database. I've Spent 25 Years Getting Logic Out of It.
TL;DR: SQL Server 2025 (and Amazon RDSās managed version of it) can now store vectors natively and call Amazon Bedrock straight from T-SQL. Half of that is genuinely good: vectors are data, and data bā¦
- The Beach Test: Why Big Neural Networks Stop Getting Stuck
TL;DR: Dry sand flows; densely packed, confined sand jams into a rigid pile - and the jamming transition that describes that rigidity is, in the work of physicist Matthieu Wyart, analogous to a transiā¦
- Laws & Disorder #5 ā Goodhart's Law: The Goal You Specify Is the Only One You Get
TL;DR: Goodhartās Law says that when a measure becomes a target, it stops being a good measure. People optimize the number and quietly drop every goal you had in mind but never expressed. I once watchā¦
- The AI That Only Watches
TL;DR: The whole industry is racing to give AI more permissions: more tools, more autonomy, more write access. I went the other way this month and noticed something uncomfortable: the assistant that oā¦
- Self-Consistency Is Just Probability Amplification
TL;DR: āSelf-consistencyā, ask a model the same question several times at a non-zero temperature and take the answer they most agree on (a plurality vote), gives large accuracy gains over greedy decodā¦
- Laws & Disorder #4 ā Gall's Law: Great Systems Are Built From Small Bricks, Not Big Plans
TL;DR: Gallās Law says a complex system that works is invariably found to have evolved from a simple system that worked, and that a complex system designed from scratch never works. There are two readā¦
- Understanding Is the New Bottleneck ā and Your AI Agent Can Fix It
TL;DR: In AI coding the hard part is no longer writing the code, it is understanding the code the agent wrote well enough to keep steering. Geoffrey Littās framing is that the human job shifts from veā¦
- Generate-and-Verify: What P vs NP Teaches Us About AI Reasoning
TL;DR: The defining feature of the complexity class NP is polynomial-time verifiability: a candidate answer is cheap to check. The asymmetry that matters shows up in its hardest members, the NP-compleā¦
- Laws & Disorder #3 ā Tesler's Law: You Can't Delete Complexity, Only Choose Who Owns It
TL;DR: Teslerās Law, the conservation of complexity, says a system has an inherent amount of complexity that can be reallocated between owners but not simply deleted, and the boundary condition is thaā¦
