control-layer

Orka, an open-source control layer for AI agents in production, has been released.

The author built a runtime control layer to address the problem of AI agents failing silently in production environments.

Introduces RACL, a reasoning-agent control layer that improves metaheuristic optimization by learning to control internal search behavior from operational memory, showing cost improvements in vehicle routing tests.

The article discusses the problem of agent sprawl in teams using multiple AI agents with overlapping permissions and workflows. It proposes a basic control layer with owner, read/write systems, budget, stop rule, and four agent classes: readers, routers, operators, spenders.

Rain launches Agent Control Layer, a security layer for agentic payments in crypto and Web3.

AgentOS provides a unified control layer for managing AI agents, tasks, and workspaces.

The article discusses a shift in focus from AI agent capabilities to agent governance, highlighting recent product announcements from Microsoft, Noma, Netskope, Immuta, and Outreach that establish control layers for agent identity, permissions, and audit trails.

LuthorAI has spent most of its funding on building its control layer for regulated marketing, now supporting over $850B in assets under management and enterprise clients.

This paper argues that AI agent performance depends more on the harness (control layer) than on prompts alone, proposing natural-language agent harnesses to make design choices inspectable and portable.