Constrain and inspect agent actions
People need explicit limits or inspectable records around what an agent does.
Dedicated disposable machines isolate execution. Approval gates, policy checks, scoped tools and spending caps restrict actions. Repository contracts, issue-linked diagnoses and visual action displays expose what ran and what it produced; these mechanisms operate at different layers.
- What brings them together
- An explicit isolation boundary, action approval or authority check, spending cap, execution-proof contract or inspectable agent-action trail.
- Outside this wave
- Agent hosting alone, cloud tools without stated controls, messaging, shared knowledge, scaffolding and generic incident automation.
Enterprise infrastructure for governed AI execution.
CollieOpen-source desktop AI assistant that executes approved task plans.
FoveaMac interface for coordinating work across AI agents.
McpifexMarketplace and gateway for MCP servers.
NoBurnPre-request spending controls for LLM APIs.
OtaRepository execution-contract tooling for people, CI and AI agents.
PolyShared workspace for teams building with AI.
Sandbox as a ServiceDedicated virtual-machine sandboxes for agents.
SentinelSCAExecution-governance layer for consequential AI-agent actions.
TermiLive 3D observation workspace for AI coding agents.
ThermiteSelf-hosted error tracker that hands issues to a user's coding agent.