The Three Axioms

These aren't predictions. They're axioms. Build from them.

Axiom 1: No Sentient AI — Ever

AI is a machine. An algorithm. A predictive model that needs humans to drive it.

Stop waiting for AI to "wake up." It won't. Build accordingly.

Implication: Stop designing for consciousness. Design for capability amplification.

Axiom 2: Human Control — Always

Every AI action needs a human trigger. No matter how good AI gets, it always needs human decision-making at the core.

The question isn't "how do we keep AI under control?"

The question is "how do we make human control efficient enough to keep up?"

Implication: The bottleneck is human decision-making speed. Optimize for that.

Axiom 3: Only As Fast As AI Can Explain

AI moves at the speed of human understanding, not the other way around.

The speed limit isn't compute. It's cognition. Humans need to understand enough to decide with confidence.

Implication: Translation quality > AI capability. Invest accordingly.

The Non-Negotiables

1. No sentient AI — it's not coming, stop designing for it
2. Human sovereignty — every decision has a human trigger
3. Understanding before action — confidence before speed

Everything else is implementation detail.

Building on the Axioms

If you accept these axioms, certain approaches become obvious:

Do:

• Compress options to human-scale (2-5 choices)
• Audit every AI action back to a human decision
• Measure translation quality, not just capability
• Design for confidence, not just speed

Don't:

• Build for autonomous decision-making
• Eliminate human touchpoints for efficiency
• Assume AI will eventually "figure it out"
• Sacrifice understanding for throughput

Axioms are starting points. Contribute extensions, critiques, or alternative foundations.