FAQ
Answers to the questions first-time visitors ask before reading any of the detailed pages. Each answer links to where the topic is covered in full.
What is AI Agent Assembly, in one sentence?
It is a governance layer for AI agents: it sits between your agents and the outside world and enforces policy, tracks cost, and intercepts unsafe actions before they run. See the Introduction and Why AI Agent Assembly?.
Do I have to change my agent’s code?
Not necessarily. Three interception mechanisms exist, they are deployed independently rather than as an ordered pipeline, and you can pick how invasive to be:
- The SDK layer needs a small amount of instrumentation in your code and is the fastest path.
- The sidecar proxy (
aa-proxy) governs an agent’s network traffic without modifying the agent’s own source, on traffic that is routed to it and trusts its CA. - The eBPF sensor (
aa-ebpf, Linux only) observes activity at the kernel level and reports it. It is observe-only: it returns no verdict and blocks nothing.
See the interception mechanisms in the Introduction.
Does it work with my LLM / framework?
Yes — it is provider-agnostic. It governs agents regardless of which model provider you use, and ships SDKs for Python, TypeScript/Node, and Go, with framework examples (LangChain, LlamaIndex, bare OpenAI, and more) in the examples repository.
Is it free? What is open source vs. paid?
The enforcement core — the interception mechanisms, policy engine, SDKs, and CLI — is open source under Apache-2.0. Enterprise operations (SSO, SCIM, tamper-evident audit, dedicated regions, SLAs) are commercial and delivered on paid SaaS tiers. See the Open core boundary.
Can I self-host it?
You can self-host a limited-function stack from the open-source crates (using the published Docker Compose example) for local evaluation and development. The complete feature set is delivered through the AI Agent Assembly cloud (SaaS). See the Open core boundary.
How does it actually block an unsafe action?
Before an agent action runs, the gateway evaluates your policy and returns an allow or deny decision; a deny stops the action. Budgets are enforced the same way — once a team is over budget, further calls are denied. See the Policy reference.
How is it different from an observability / tracing tool?
Observability tools record what an agent did, after the fact. AI Agent Assembly makes a binding allow/deny decision before the action executes. The comparison page maps this against other tools.
Where do I get started right now?
Clone the examples repository and run a governed agent end to end — that is the path you can run today. The managed service is planned and not available.
What do the acronyms mean (eBPF, SCIM, mTLS, STRIDE…)?
See the Glossary, which defines every recurring term and acronym in plain language.
Last updated: 2026-09-07 by AI Agent Assembly Team