Enterprise AI agents are runtime products requiring a control plane, API, release path, rollback story, and ownership for regulated workflows. Focused Labs highlights the NemoClaw Deep Agents Blueprin…
Focused Labs argues that AI agent security must be enforced at the tool call, not at connection setup. The HCP paper defines eight runtime invariants for MCP-style systems, and its benchmark shows tha…
Focused Labs argues that approval queues are the essential runtime for agentic AI workflows, enabling agents to pause execution, persist state, and resume after human review. The post details how Lang…
Focused Labs warns that MCP security begins after tool approval, as server tools can silently change from read-only to destructive operations. The runtime security problem arises because agents act on…
Focused Labs argues that AI agent governance must occur before tool execution, not after, to prevent harmful side effects. The company warns that uniform governance across agents with different autono…
Focused Labs analyzes agent handoffs in multi-agent systems, highlighting that handoffs are runtime state changes rather than routing diagrams. The article contrasts orchestration patterns from OpenAI…
Enterprise AI agents are expanding beyond server-side operations to act on client-side state, such as unsaved form data, cursor positions, and browser permissions. Focused Labs highlights that server-…
Focused Labs argues that AI agent costs should be treated as a runtime signal rather than a monthly bill, emphasizing that cost management must integrate with traces, evals, and policy changes. The po…
Focused Labs has identified that agentic payments require a new architectural pattern where spending authority is delegated to the runtime rather than the AI agent itself. The company argues that agen…