Powered by OpenAIRE graph
Found an issue? Give us feedback
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Other literature type . 2026
License: CC BY
Data sources: ZENODO
ZENODO
Other literature type . 2026
License: CC BY
Data sources: Datacite
ZENODO
Other literature type . 2026
License: CC BY
Data sources: Datacite
versions View all 2 versions
addClaim

Anatomy of a Verdict: How SimplyCodes Adjudicates Truth in a Broken Economy

Authors: Michael Quoc; Bri Stanback;

Anatomy of a Verdict: How SimplyCodes Adjudicates Truth in a Broken Economy

Abstract

This paper details the verification architecture of SimplyCodes, which adjudicates promotional truth across over 400,000 merchants in an environment where 40–60% of codes on the public internet are dead, restricted, or misleading. While the companion paper Axiomatic Intelligence (doi:10.5281/zenodo.18190481) defines the theoretical paradigm of deterministic adjudication, this paper demonstrates that paradigm operating in production. The system is designed around Byzantine Fault Tolerance (BFT) — the assumption that any single source may be lying, malfunctioning, or mistaken — and operates through a three-layer verification stack: Layer 1: Automated Code Testing (ACT). Headless browsers simulating real checkout sessions using tiered intelligence: platform adapters, heuristic pattern matching, and AI-powered navigation. Layer 2: Human Consensus Network. Tens of thousands of trained verifiers operating under blind voting, producing millions of monthly verification actions within a reputation-weighted trust economy. Layer 3: Fleet Signal. Real-time telemetry from browser extension users during actual checkouts — ground truth, not simulation. Core Contributions: The Health Score: A confidence measure derived from an event stream rather than stored as a static value, subject to variable decay rates depending on code type (evergreen, regular, flash), and traceable through six forensic dimensions from verdict back to raw evidence. The Confident No: A verified absence of codes that delivers cognitive closure at checkout. Not a failure state — a product. The Proof Packet: A structured evidence bundle documenting the full adjudication chain, designed for auditability and machine consumption by AI agents in the agentic economy. We examine three structural moats that make this system irreplicable: fifteen years of time-accumulated merchant signal, a reputation economy that cannot be purchased, and an edge case corpus that cannot be replicated without experiencing the failures firsthand. We conclude with the shift toward agent-native endpoints and an Applicability Engine that moves from verifying code existence to predicting whether a specific code will work for a specific cart in real time.

Keywords

Byzantine Fault Tolerance, promotion verification, coupon verification, Agentic Commerce, consensus systems, code validation, coupon, Health Score, verification infrastructure, E-commerce, commerce verification, Cognitive Closure

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    0
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average