Resources

Reading and reference material

PCS Labs internal materials and selected external context for understanding the AI stability and governance infrastructure space.

PCS Labs materials

The core problem framing: why AI capability is advancing faster than stability infrastructure, and what that means for the systems being built today.

How PCS Labs conceptualises the four-layer abstraction for stability infrastructure: represent, track, detect, recover.

The eight design principles that govern how PCS Labs approaches its research and infrastructure design.

Current state of the PCS Labs research program, active workstreams, and engagement context.

The full PCS Labs strategic memorandum — available on request to qualified investors, academic partners, and design collaborators.

External context

Background reading

Selected external resources for understanding the AI stability and governance space. Links open external sites.

McKinsey Global Institute overview of how AI agents are shifting from tools to autonomous actors in enterprise workflows.

Official summary of the EU Artificial Intelligence Act, including requirements for high-risk AI systems and transparency obligations.

Anthropic's published research on AI safety, alignment, and the challenge of making AI systems reliably beneficial.

The US National Institute of Standards and Technology framework for managing risks to individuals, organisations, and society from AI systems.

Annual research report covering capability advances, safety research, industry dynamics, and policy developments in AI.