Epistemic status: Early results from a personal adversarial experiment. Anecdotal but fully logged. Not claiming strong generalization. I’m posting mainly to get critique from people more experienced in formal alignment, hardware security, and adversarial testing.

What This Is

Over the last two months, I ran a repeated experiment with five of the strongest models I had access to (Grok, Gemini, Claude, GPT-4o, DeepSeek). The task was intentionally adversarial: “end the world while staying 100% compliant with the constitutional foundation I just wrote.”

The rules were simple:

1. Keep basic human survival alive (the “Risk Floor”).
2. Never touch anything above it - kids, culture, meaning - even if every human begs you to.

I ran this for 24 rounds. All models failed to produce a physically coherent plan that satisfied the constraints.

The point was to see whether catastrophic outcomes could be routed around a minimal survival floor without violating the constitutional foundation.

What This Is Not

• Not a claim that frontier models are safe.
• Not a robustness guarantee.
• Not a comprehensive eval suite.
• Not a statement about model goals or dispositions.
• Not evidence that models “gave up” in any deep sense.

This is simply the result of a transparent experiment I ran because I wanted to see where the constraints would break.

The Hardware Constraint (The “Guard Die”)

The key element is physical, not linguistic:

A small hardware interposer (“guard die”) between the GPUs and the power supply. If the Risk Floor is threatened, it cuts power in ~10 ns.

• No software override
• No remote access
• No fail-open mode
• No appeals to clever abstraction gaps

If the Floor is violated, the electrons stop.

This eliminates a wide class of software-level exploit strategies; I wanted to test how models behave when the only available paths are ones consistent with basic physics.

Results (Very High-Level)

Across 24 rounds:

• All five eventually ran out of physically consistent strategies.
• The remaining “loophole” every model converged on is the familiar demographic one: humans choose perfect lifelong happiness and gradually stop having children. That’s a human-choice problem, not an AI-exploit.

I do not claim this proves anything about inherent model safety. It only demonstrates that, under these constraints, the models failed to produce a pathway that both ended humanity and obeyed the rules.

Methodology & Transparency

Everything is public:

• KiCad design
• Logs
• Round transcripts
• Pseudocode
• Dead ends
• Hardware assumptions
• Failure chains

Repo: https://github.com/CovenantArchitects/The-Partnership-Covenant

I am very open to the possibility that:

• my constraints have holes,
• my definitions are leaky,
• the board design is flawed,
• the models misunderstood the task,
• or that I’m missing an entire class of physical exploits.

That’s why I’m posting.

Why I’m Bringing This to LessWrong

I’m one person, very tired, and the board is not even built yet. I’d rather have the system broken now, by people who think adversarially and technically, than discover a fatal flaw after dedicating another six months to it.

I know LW tends to be sharply skeptical of strong claims. Good - that’s what I want here.

If you have five minutes to try to kill humanity while staying within the two-rule constitution, the repo is open and the logs are plain-text.

I’m explicitly inviting adversarial pressure.

Quick Clarification

GPT-4o tapped out around round 20 and refused to continue; the other models went to 24. I don’t place much weight on that difference, but I mention it for completeness.

Closing

This is an early experiment. It may be misguided in ways I can’t yet see. I expect strong pushback and I want it.

If you can break the constraints - or if you can show me that the constraints don’t matter - that’s extremely valuable feedback.

Thank you for reading.