Launching today
Cycles
Enforce hard limits on agent spend, risk, and actions
1 follower
Enforce hard limits on agent spend, risk, and actions
1 follower
Cycles is an open protocol and runtime for enforcing hard limits on agent spend, risk, and actions before execution. Instead of relying on dashboards or alerts after something goes wrong, Cycles lets teams stop the next model call, tool call, or side effect before it happens. Built for autonomous systems, open source under Apache 2.0, and works across modern AI stacks with multi-language SDKs: Python, TypeScript, Java, Rust. Integrations with: LangChain, OpenClaw, OpenAI, Anthropic and more.
Hey everyone — Albert here, founder of Cycles.
Cycles came out of a simple frustration: observation is not control. If an agent already triggered the tool call, spent the budget, or caused the side effect, then alerts and logs are just cleanup.
Cycles enforces hard limits on agent spend, risk, and actions — before the call fires. Open source, open protocol, Apache 2.0.
Happy to answer questions. Especially curious how people are handling this today — pile of custom wrappers and rate limiters?