About MO§ES™

MO§ES™ is an enterprise AI operator evaluation platform built by Deric J. McHenry. The platform measures how people operate AI systems using content-free token telemetry — no prompt text required. It was founded to answer the enterprise question that usage analytics and skills assessments both miss: how well are people actually operating AI systems in real work?

It was founded by Deric J. McHenry, a researcher in commitment theory and AI operator evaluation whose work includes the Conservation Law of Commitment (published on Zenodo) and a pending patent on the MO§ES™ enforcement architecture (Serial No. 63/877,177).

What we do

MO§ES™ evaluates the humans operating AI. Not usage analytics. Not a workforce dashboard. Not a productivity score. We measure how operators use AI systems across real tasks, workflows, models, and operating conditions, then benchmark that performance against relevant comparison groups.

The platform delivers operator evaluations, performative benchmarks, bespoke enterprise evals, workflow fit analysis, operator × model fit, team composition analysis, capability dependency risk assessment, intervention design, and re-measurement after intervention. It operates on content-free canonical telemetry (input tokens, output tokens, cache reads, cache writes) — no prompt text required.

How it works

The evaluation follows a 7-step sequence: instrument, baseline, build bespoke evals, benchmark, diagnose, intervene, and re-evaluate. Operators are scored on 5 canonical metrics (leverage, yield, token signal-to-noise, log leverage, construction) and benchmarked across 13 classes (self-vs-prior, repeated task, matched task, peer, role, cohort, team, organization, system, workflow, model, intervention, external field).

Every diagnosis is labeled HYPOTHESIS, never fact. Every outcome join is labeled ASSOCIATION, never CAUSATION. A single metric never triggers hiring, firing, compensation, or promotion decisions. The platform enforces these governance constraints structurally in code, not just in documentation.

Research foundation

MO§ES™ is grounded in Commitment Theory, which asks what stays binding when language changes form, and the Conservation Law of Commitment: C(T_gov(S)) = C(S) — language can change form without losing what it still requires. The research program is published on Zenodo and GitHub.

Ecosystem

MO§ES™ is part of a broader ecosystem that includes SignalAF / SigRank (public and enterprise evaluation of AI operators), Signomy (dual-governance agentic marketplace), and AQUA (applications, questions, answers). The platform is delivered through CLI, TUI, and MCP — not a dashboard.

Contact

Email: burnmydays@proton.me
ORCID: 0009-0002-9904-5390
GitHub: SunrisesIllNeverSee