In this episode, Roger Keyserling outlines an AI system designed not around speed, profit, or novelty, but around three foundational axioms that govern behavior, ethics, and long-term alignment. Rather than treating artificial intelligence as a tool to be optimized at any cost, this discussion reframes AI as a system that must be grounded in principles before it is allowed to scale.

The episode explains why most modern AI deployments fail at the structural level — not because of technical limitations, but because they lack immutable guiding truths. These three axioms act as non-negotiable anchors, ensuring that intelligence remains accountable, comprehensible, and oriented toward human well-being rather than unchecked autonomy.

This is not a programming tutorial or a speculative futurist argument. It is a conceptual blueprint for how AI systems should be designed if they are meant to coexist with humanity rather than replace or undermine it.

Why intelligence without axioms becomes unstable

The role of immutable principles in system design

How axioms differ from rules, policies, and constraints

The dangers of optimization without ethical grounding

What it means to build AI for longevity rather than dominance

AI builders seeking ethical coherence

Thinkers concerned about runaway automation

Human-centered technologists and philosophers

Anyone questioning how intelligence should be governed

Part of the NextXus: HumanCodex Podcast, this episode contributes to the ongoing exploration of ethical AI architecture and the conditions required for sustainable human–machine collaboration.