Blog
Analysis, practical guides, and perspectives on AI governance.
Agentic Drift: The Silent Risk of AI Systems in Production
Behavioral drift in AI agents is not a bug. It is an emergent property of stochastic systems in open environments. Understanding the phenomenon is the prerequisite for controlling it.
Steve P.
Zero-Trust for AI Agents: Beyond the Network Perimeter
Zero-trust architecture applied to multi-agent systems requires rethinking identity, authorization, and continuous verification. Classic network models are no longer sufficient.
Steve P.
Executive Order 14110: Operational Impact on AI Deployments
Executive Order 14110, signed in October 2023, restructures the US federal framework for AI. Its implications extend beyond US territory and affect any organization deploying AI systems at scale.
Steve P.
Multi-Agent Observability: Beyond Technical Metrics
Observability tools designed for microservices fail to capture emergent properties of multi-agent systems. A new observation paradigm is needed.
How to prepare your organisation for the EU AI Act
The EU AI Act is being progressively enforced. Here are the concrete steps to bring your organisation into compliance before the first penalties.
Building an AI governance framework in 8 weeks
AI governance isn't about policies on paper. Here's how to implement an operational framework that actually works, in 8 weeks.
Why every AI system needs a Kill Switch
A Kill Switch isn't an admission of weakness. It's proof that you control your agents, not the other way around.
AI audit trail: mandatory in 2027, essential today
In 2027, audit trails will be a legal requirement for high-risk AI systems in Europe. But companies implementing them today are already finding major operational advantages.
Model-agnostic architecture: why it's non-negotiable
Depending on a single AI provider is a strategic risk. Here's why your governance layer must be independent of the underlying model.
CISO Guide: securing your AI agents in production
A practical guide for security directors who need to govern AI agent deployments without blocking innovation.