Reflections are deeper dives into how law, technology, and innovation intersect. These longer form pieces analyze research and emerging trends — offering perspectives that help teams navigate what's coming next.
The intersection of AI agents and enterprise accountability fascinates me, particularly the challenge of building systems that can operate autonomously while maintaining complete audit trails and decision traceability.
NIST SP 800-63-4 updates digital identity guidelines to address AI-enhanced threats, requiring phishing-resistant authentication and risk-based approaches for secure identity verification amid AI risks
Product teams must architect agent-native security from day one rather than retrofitting traditional controls, implementing runtime monitoring, memory hygiene, and adaptive governance that can evolve alongside autonomous systems to avoid costly reactive security implementations.
"Agentic AI systems demand more comprehensive evaluation because their planning, reasoning, tool utilization, and autonomous capabilities create attack surfaces and failure modes that extend far beyond those present in standard LLM or generative AI models."
"Agent infrastructure: technical systems and shared protocols external to agents that are designed to mediate and influence their interactions with and impacts on their environments."
"Their ability to execute multi-step plans autonomously heightens the potential for abuse by lowering barriers to entry and costs involved in these activities."
Australian government procurement clauses require AI systems to include immediate shutdown capabilities accessible to buyers, establishing enforceable technical standards beyond governance principles.
Stanford's 2025 AI Index shows industry now produces 90% of notable AI models while training costs hit $170M per model, fundamentally reshaping competitive landscape.
