Imagine two versions of a fire suppression system. The first version, when it detects heat above a threshold, activates the sprinklers – every time, without exception. The second version analyzes the heat pattern, consults a learned model, and usually activates the sprinklers – but sometimes decides it was probably just Read more
Security engineers often talk about “defense in depth” – the idea that no single control should be the only thing standing between an attacker and damage. coding-ethos and Ethosure apply this principle through a clean architectural separation between two layers with different jobs: the control plane decides whether an action Read more
One of the most important words in AI governance right now is “deterministic.” It means: given the same input, the system produces the same output, every time, without exception. A coin flip is not deterministic. A weather forecast is not deterministic. A fire suppression system is – and that is Read more
Most organizations have no shortage of written rules. There are security policies, coding standards, compliance frameworks, architectural principles, and onboarding guides. The problem is that written rules are only as good as the people – or agents – reading them. When an AI coding agent writes a thousand lines of Read more
Every company deploying AI coding agents faces the same uncomfortable question: how do you know what the agent actually did, whether it followed your rules, and whether the evidence would hold up to a regulator’s scrutiny? Ethosure’s answer rests on an open-source project called coding-ethos, built and owned by one Read more
This document describes a scoped six-to-eight-week design-partner pilot with Ethosure. The goal is to take one AI agent already running in your environment, instrument it with Ethosure’s enforcement layer, and produce an auditor-ready evidence pack. Three objectives drive the pilot: (1) validate technical fit – confirm the enforcement layer integrates Read more
The hardest part of AI agent governance is not writing a policy document. It is building infrastructure that enforces the policy – at runtime, deterministically, on every action, without being bypassable – and producing a tamper-evident record while doing it. Most organizations trying to solve the AI governance problem discover Read more
Governance claims are easy to make. The interesting question is: what actually happens, mechanically, when an agent takes an action? Where does the control sit? Who or what evaluates it? What runs if the action is approved? And what record is produced? Ethosure’s architecture answers all of those questions with Read more
