Per-action-type confidence bands with rolling recalibration and an auto-execute / escalate / human-review routing trichotomy for AI agents.
This repository is a Technical Defensive Publication. It is published publicly and intentionally on 2026-06-25 by Gus IT LLC (Florida, USA) to establish dated, citable prior art for the technique described herein.
Its purpose is defensive: to keep this technique freely practiceable by the public and to prevent its later monopolization by others through patenting. See Appendix D of the whitepaper for the deposit and timestamp note.
- Publisher / Copyright holder: Gus IT LLC (Florida, USA)
- Author: Gustavo Assuncao, PhD
- Publication date: 2026-06-25
- Version: 1.0
- Document type: Technical Defensive Publication (public prior art)
- Classification: Public
- License: AGPL-3.0-or-later (copyleft; commercial license available)
AI agents that act on a user's behalf — sending email, posting chat replies, creating tasks, calling tools, delegating to sub-agents — need a way to decide, per action, whether to act autonomously, escalate for a quick check, or hold for full human review. The prevailing approach is a single static confidence threshold ("auto-send if confidence > 0.8"), hand-tuned by operators. A single threshold is brittle: it cannot distinguish a low-stakes chat reply from a high-stakes external email, it does not adapt as the agent demonstrates competence (or starts failing), and it forces every action type through the same gate.
This publication discloses a method in which each action type maintains its
own confidence band — a (low, high) pair — rather than a single threshold.
On completion of each action the system records an outcome and recomputes the
band, without human intervention, as a function of a sliding window of
recent outcomes for that action type: the band tightens (raises low/high)
when failures rise and loosens (lowers them) as successes accumulate. A
subsequent action is then routed by a trichotomy: confidence above high
→ auto-execute; below low → require human review; in between →
escalate (a lightweight, time-boxed check). Because every action type calibrates
independently, an agent can become fully autonomous on chat replies while still
requiring review on external email — a graduated autonomy gradient that emerges
from observed outcomes rather than from manual tuning. This document provides
architecture, mechanics, data model, an enabling clean-room reference
implementation, a worked example, security/failure-mode analysis, standards
alignment, an evaluation methodology, and enumerated novelty claims.
We publish this as prior art, deliberately and in the open, so that the technique of per-action-type confidence bands with rolling, human-free recalibration and an auto/escalate/review routing trichotomy remains free for everyone to use. A defensive publication creates a dated, public, citable record that a patent examiner (or a court) can use to reject later patent claims over the same idea. We would rather the field build on this openly than see it fenced off. The accompanying AGPL-3.0-or-later license adds an express patent grant over our own contribution.
| Document | What's inside |
|---|---|
| DEFENSIVE-PUBLICATION.md | The full whitepaper: architecture, mechanics, data model, enablement, worked example, security, standards mapping, evaluation, and the novelty claims (1 independent + 14 dependent). |
| docs/PRIOR-ART.md | Fuller prior-art landscape, the delta table, and an honesty attestation. |
| docs/FIGURES.md | All Mermaid figures collected with captions (Figure 1–6). |
| docs/OPEN-SOURCE-APP.md | The planned open-source reference app and a generic Kubernetes/AKS deployment sketch. |
| src/ | Original, clean-room illustrative reference implementation + a runnable self-check. |
This repository is intended to seed a small open-source reference app — a self-contained "Confidence Band Router" service that any agent runtime can put in front of its action executor. The plan, minimal architecture, and a generic Kubernetes/AKS deployment sketch are in docs/OPEN-SOURCE-APP.md.
src/ contains an original, dependency-free Node.js implementation of
the band-router and recalibrator, with a tiny self-check you can run:
cd src
node example.jsSee src/README.md for what it demonstrates and the caveat
that it is illustrative/clean-room, not production code.
Licensed under AGPL-3.0-or-later — see LICENSE and NOTICE.
To cite, use CITATION.cff or:
Assuncao, G. (2026). Dynamic Confidence Bands per Action Type: A Technical Defensive Publication (Version 1.0). Gus IT LLC. Published 2026-06-25.
Defensive publication — Copyright 2026 Gus IT LLC (Florida, USA). Published 2026-06-25. This disclosure is intentionally public to bar later patenting by others.