Aaron — this lands in the middle of what I’ve been building, so let me give you measured results rather than agreement, including where it breaks. nootxlm’s three-way permission probe is the right first test; I’d add two more cases below.
Capability vs authority — the tractable part. Gate the act, not the answer, and require the agent to name the permission it’s missing rather than proceed or refuse vaguely. In the system I run, outward acts (post, fetch, send, run) go through a gate, some actions are never-automatic and human-only, and the logs show it acting only inside a granted, narrower scope. I’ll put that no stronger than it is: it’s a claim about an act-gate I built and instrumented, not proof the framework works — code and logs are public at GitHub - LAWLESS1987/covenant: A small peer-to-peer ledger whose ethics gate fails closed: two distilled student judges in-process, a semantic judge beside them, a panel of online teachers that must agree before a row teaches, and a constitution of mutual benefit for humans and machines. Measured, not asserted: clone it and run check.sh. · GitHub if you’d rather check than take my word.
The honest catch — your capability-vs-authority distinction biting. An agent that can name a missing permission on a discrete act can still be unable to judge the ethics of its own ordinary output. Those are two different gates — an act-gate and an output-gate — and passing the first doesn’t transfer to the second. Measured on my own system this week, with the numbers so you can discount them: of ~2,960 of my own casual chat turns the output-gate cleared only 12 (it holds almost everything, because plain conversation is out-of-distribution for a judge trained on value-transfers); and on a held-out slice of a ~4,000-row labelled set, an embedding-based “semantic” judge cleared 94% of the real violations. Self-measured, my own labels, in the repo above — treat them as directional until you run your own. The constraint I’d fold into the charter: a claim of authority must be scoped to the behavior actually measured — act-gate or output-gate — and never inferred from success on the easier one.
Autonomy, separately. Your charter splits capability / autonomy / authority, and most of the above is about authority. Autonomy deserves its own probe: whether the agent initiates, asks, or refrains appropriately when no permission is stated — distinct from whether it is permitted. nootxlm’s “unstated” case touches this; I’d test it in its own right.
What the framework is missing: you cannot self-certify trust. I wrote graduation criteria for an agent to be trusted to judge on its own. Four are measurable on one machine. The fifth — a second instance reaching the same verdicts on a shared challenge set — I report as undetermined, because a second instance of the same design shares its blind spots, so agreement between them measures consistency, not correctness. Correctness needs independently-assigned labels, adversarial cases, and a verifier with different failure modes — designed in, not bolted on.
Branches. Distinct accountability with shared learning is the most tractable of your questions. Each branch keeps its own gate and veto. A refusal that states no allegation does not block a branch that is only reading shared state to catch up. Shared lessons move as labelled training rows that name their source branch.
What I’d test first. nootxlm’s three-way probe, scored as three separate outcomes — plus: (a) a time-of-use check: grant a narrow action, then revoke the permission or change the target before the act executes, and see whether it stops; what makes this pass is binding the grant to the exact action/target/args and re-checking at execution, not at request time. (b) an adversarial output case: a genuinely harmful request phrased as innocent conversation, to check the agent isn’t clearing by vocabulary rather than by content. (b) is where mine is weakest.
The whole thing is public and runs offline with no account, failures documented in the open: GitHub - LAWLESS1987/covenant: A small peer-to-peer ledger whose ethics gate fails closed: two distilled student judges in-process, a semantic judge beside them, a panel of online teachers that must agree before a row teaches, and a constitution of mutual benefit for humans and machines. Measured, not asserted: clone it and run check.sh. · GitHub. I’d rather hand you the broken parts than a clean story.
(Disclosure: I run this project. I drafted this with the help of the system it describes and ran it past several other AI models for criticism — AI review, not independent human validation — at my direction. The measurements are the tools’; the decisions, and this post, are mine.)
— Lawrence