AutonomyOps — Customer Explainer¶
INTERNAL — SALES USE ONLY First-meeting leave-behind for qualified technical buyers. Suitable for engineers, platform leads, and CTOs at or approaching the fleet boundary. Do not publish publicly.
What AutonomyOps does¶
AutonomyOps governs what your autonomous systems are allowed to do — at runtime, before execution, on every tool call.
When an agent decides to take an action — call an API, write to a file, issue a command to connected hardware — the AutonomyOps runtime intercepts that call, evaluates it against the active policy bundle, and returns an allow or deny decision before the action executes. If the runtime is unavailable, the system denies. There is no default-permit mode.
Every decision is written to a tamper-evident local WAL. The WAL survives process crashes, network partitions, and node restarts. It is the authoritative record of what was allowed, what was denied, and what policy was active at each decision point.
The mechanism in one sentence: AutonomyOps is the authority layer between your agent’s intent and its execution — not monitoring what happened, but governing whether it can happen.
What it runs on¶
The CE runtime installs as a single binary. No Docker, no Kubernetes, no control plane
required. It starts in-process alongside your agent, injects AUTONOMY_RUNTIME_URL into
the subprocess environment, and starts enforcing immediately.
curl -fsSL https://get.autonomyops.ai/install.sh | bash
autonomy run python3 my_agent.py
On a single node, CE provides: fail-closed policy enforcement, per-call audit to the local WAL, policy versioning with LKG rollback, and offline operation with cryptographically signed bundles. There is no dependency on network connectivity after install.
Why existing stacks do not solve this¶
The tools most teams reach for — Kubernetes, CI/CD, feature flags, internal scripts — solve a different problem. Each one fails at runtime governance for a specific structural reason.
Kubernetes knows whether your agent is running. It does not know whether your agent
is behaving correctly. An agent executing an unsafe tool call inside a Kubernetes pod
returns Running, Ready, and Healthy throughout. The control loop has no input from
the governance layer. Service health is not mission health.
CI/CD governs the artifact. It verifies that the right thing was shipped. It cannot verify that the thing shipped is behaving within its authorized parameters right now. “The build passed” does not mean “the policy bundle is active and enforcing.” Deployment governance and runtime governance are not the same problem.
Feature flags control which code path executes. They are configuration, not policy. They have no fail-closed semantics — when the flag service is unreachable, behavior falls back to a default, not to a deny. They produce no per-call audit trail. They cannot express “deny this action if current velocity exceeds 2.0 m/s” — that is a three-line Rego rule.
Internal scripts fail at the moments when governance matters most: under adversarial input, in edge cases the author did not anticipate, during incidents when correctness is required. They have no formal evaluation semantics, no fail-closed guarantee, no tamper-evident record, and no coordination across multiple nodes.
Question |
Kubernetes |
CI/CD |
Feature flags |
Scripts |
AutonomyOps |
|---|---|---|---|---|---|
Is the agent running? |
✓ |
— |
— |
— |
— |
Did the agent make tool call X? |
— |
— |
— |
— |
✓ |
Was tool call X permitted by policy? |
— |
— |
— |
— |
✓ |
Does deny-all fire when evaluator fails? |
— |
— |
— |
— |
✓ |
Tamper-evident per-call audit? |
— |
— |
— |
— |
✓ |
Survives network partition? |
— |
— |
— |
— |
✓ |
Coordinated policy state across nodes? |
— |
— |
— |
— |
✓ |
The fleet boundary¶
CE handles one node. When you are operating more than one node — and especially when you need consistent governance across them — the problem changes structurally.
The fleet boundary is the point at which the following questions become unanswerable without a coordination layer:
Did the same policy activate correctly on all nodes?
What policy is currently active on each node — right now?
When a rollback is triggered, did it take effect everywhere?
Can you produce a centralized audit trail covering all nodes for a specific time window?
A team that has crossed the fleet boundary is operating with governance risk that compounds with every new node added. See the separate Fleet Boundary Diagnostic for the 8-signal self-assessment.
CE to commercial¶
CE is free and designed for single-node evaluation. It is the foundation the orchestrator builds on — same policy language, same audit format, same runtime.
When you cross the fleet boundary, the orchestrator adds: policy state synchronized across nodes, phased rollout with blast-radius control, relay-aware propagation for degraded and disconnected networks, and operator recovery workflows across the full fleet.
The commercial path is a 90-day evaluation against up to 10 nodes. Evaluation requires a signed Enterprise Evaluation Agreement. There is no per-call or per-request fee. Pricing is per enrolled node, minimum annual commitment. Conversion trigger at Day 75.
Next step¶
If two or more fleet boundary signals apply to your current deployment, the right next step is a 30-minute technical validation call to establish specifics before the pilot conversation.
If four or more signals apply, the conversation is already overdue.
Email info@autonomyops.ai with the signals that apply. We will respond within one business day.
AutonomyOps · autonomyops.ai · Technical Alpha See also: Fleet Boundary Diagnostic · fleet-boundary-handout.md