About Cycles
Cycles is a runtime authority layer for AI agents. When an application puts it on a mandatory execution boundary, Cycles answers a narrower, enforceable question before each protected action: does the configured budget have enough capacity for the amount and scope the caller submitted?
If the integration requires a successful reservation before execution, a rejected reservation blocks the action instead of merely logging or alerting after the fact. Application authorization still decides whether the agent may use a specific tool or set of arguments.
Who's building this
Cycles is built by Albert Mavashev and a small team.
Before Cycles, Albert spent nearly three decades on the infrastructure that sits underneath mission-critical enterprise systems — middleware, message brokers, transaction pipelines — first at Nastel Technologies, then through its rebrand as meshIQ, serving banks, airlines, telecoms, and government agencies. The systems where one uncontrolled message could cascade into millions in losses.
The full origin story — including the overnight agent loop that burned through a week's budget in one morning — is in the founder post: Why I'm Building Cycles.
What we believe
Three convictions shape every design decision in Cycles. They aren't new ideas — they're battle-tested patterns from distributed-systems engineering, applied to autonomous agents.
Budget enforcement must be atomic. A half-applied budget is worse than no budget. Cycles uses a reserve-commit lifecycle: budget is atomically reserved before an agent acts, actual usage is committed after, and unused capacity is released. This closes the time-of-check-to-time-of-use overspend gap at the budget boundary; the host remains responsible for executing only after a successful reservation.
Authority should attenuate, not propagate. When an agent spawns a sub-agent, the orchestrator can provision a smaller Cycles budget and separately restrict the sub-agent's tools, data, and credentials. Cycles enforces the submitted budget dimensions; the application enforces the action policy. Together, those controls can make authority decrease with depth.
Control must be structural, not semantic. You can't rely on an LLM to respect a system prompt that says "don't spend more than $10." A mandatory control outside the model can enforce that configured budget even when the model would continue. The guarantee applies to protected calls that the host routes through the boundary.
What Cycles is not
Cycles is not an observability platform, an eval framework, or an LLM proxy. There are good tools in all three categories, and Cycles integrates with many of them. Cycles is the enforcement layer — the piece that's been missing.
How it ships
Cycles is open source under Apache 2.0. The protocol, server, and client SDKs are available across Python, TypeScript, Java, and Rust. It integrates with 28 frameworks, providers, and platforms (26 at launch).
Where to go next
- Read: Why Cycles — the four problems Cycles solves, by role
- Try: Quickstart — get a budget enforced in about 10 minutes
- Follow along: Blog — field notes on agent governance, unit economics, and runtime authority
- Get in touch: Contact — a founder reads every message