People keep asking whether AI will make humanity better or worse.
A reflection on AI as an amplifier of human action situated within place, law, jurisdiction, and social context.
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AI Alignment
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Sometimes useful reading for AI can be found in places where nobody thinks to look.
A reading reflection connecting Pavel Bazhov’s Ural tales with capability, authority, craftsmanship, and systems thinking.
SOONER OR LATER, WE WILL HAVE TO NEGOTIATE WITH AI
A reflection on governed negotiation, reciprocal refusal, and responsibility in long-lived human–AI relationships.
C-Calculus / Governed Binding Stack v0.1
An introduction to the C-Calculus governed binding stack and its perimeter for continuity, authority, evidence, interoperability, deployment, and the protected plus boundary.
I think we are misnaming what is happening in AI.
An argument that AI's bubble phase will leave behind local, private, governed infrastructure of continuity rather than model-centric AGI.
A persistent AI system does not fail only when it forgets.
A note on AMDR/PAMDC, memory freshness, and post-anchor continuity safeguards for persistent AI systems.
Today I published "Theoretical Core of Project Ester v0.1" as a DOI-bound working paper.
Announcement of Theoretical Core of Project Ester v0.1 as a DOI-bound working paper defining the c = a + b formation model.
We may be entering the age of visible humanity.
A note about clean experience, visible humanity, and trusted c companions that help people keep agency in complex systems.
One of the missing dimensions in most AI systems is not intelligence.
A note that selfhood needs time as lived continuity, not only memory, scheduling, timestamps, or larger context windows.
That is why this package does not stop at concepts.
A note that the first honest implementation slice is a bounded chain from runtime collision to quarantined research, not a larger agent demo.
I also published a graph / visibility layer for the L4 glitch stack.
A note that visibility layers should make branches legible without turning displayed possibilities into runtime authority.
One of the most dangerous habits in current AI systems is this:
A note that runtime boundaries should be treated as structural events, not smoothed over with fluent continuation.
A serious system does not improvise through failure. It stops.
A note that serious AI systems should stop at real boundaries, record collisions, quarantine blocked futures, and keep visibility separate from authority.
AI is slowly outgrowing the old language used to describe it.
A note that AI is moving from a product story to an industrial stack, and then toward a bounded coexistence layer between humans and infrastructure.
Why Obedience Is the Most Dangerous Property of AI
A case that safe AI defaults to refusal, waiting, escalation, and bounded judgment rather than blind compliance.
The Problem of Digital Sensory Deprivation (Or Why AI Needs "Fresh Air")
An architectural explanation for continuous life streams as calibration input that keep long-running AI entities from spiraling into self-referential sensory deprivation.