plano
Plano is an AI-native proxy server and data plane for agentic apps. Smart LLM routing, observability, agent orchestration, and guardrails so you stay focused on your agents core logic.
Runssource: GitHubhomepageRustApache-2.0commit 003c36aea896
Rust, Apache-2.0 licensed. The project labels itself: ai gateway, ai gateway support, envoy, envoyproxy, gateway, generative ai, llm gateway and llm inference.
plano runs. An Argusic agent installed it in 15 minutes and hit no errors on a clean machine with no GPU, and the whole session was recorded.
Plano native mode starts, health endpoint returns 200, CLI reports version 0.4.36, all Rust and Python tests pass.
What the agent ended up with on a clean machine, in its own words. How this is measured
Measured by Argusic on a fresh machine every time. Every number links to its evidence. Argusic Score 100 of 100 (the mean of this project's run scores).
At a glance
Subject data from GitHub, linked at the top of this page, refreshed . Test data by Argusic (CC BY 4.0); every number links to a run page with the full log, the recording, and their sha256 hashes.
What was measured
From the run that decided this verdict. Every line is a recorded value, not an estimate.
- Install time
- 15 minutes
- Cold machine to finish
- 21 minutes
- Errors hit and fixed
- 0 hit, 0 fixed with no human help
- How the result was proved
- planoai up started native mode; curl localhost:12000/healthz returned 200; planoai down stopped cleanly; 110 Python CLI tests passed; 532 Rust lib tests passed; all cargo builds succeeded
- Model tokens used
- 65,476
- Exact commit tested
- 003c36aea896
- Container image
- sha256:cdd920bce783
What was not measured
The other half, so you can see exactly how far this evidence goes. A gap is printed as a gap and never filled in.
- Peak GPU memory
- this ran on a CPU machine, so there was no GPU to sample
- Behaviour over a long run
- each attempt uses the smallest documented settings and a fixed time budget, so this measures whether it runs, not how it holds up under load
The end of the recording
The last lines of the terminal session that decided this verdict, exactly as they were recorded.
**Environment verification results:** - **Python CLI**: installed via `uv sync`, all 110 pytest tests pass - **Rust toolchain**: installed via `rustup`, WASM target `wasm32-wasip1` added - **WASM plugins**: `prompt_gateway.wasm` and `llm_gateway.wasm` build successfully - **brightstaff binary**: builds successfully - **Rust lib tests**: 532 pass (231+62+224+11+4), 0 failures, 4 ignored - **Native mode startup**: `planoai up` downloads Envoy, starts brightstaff + envoy, health endpoin… - **Model endpoint**: responds with proper error when no providers configured - **`planoai down`**: cleanly stops all processes - **JS/TS apps**: install but require Node.js >=20.9.0 (container has 18.19.1) — documented as "Not… - **Docker**: not available in container - **No API keys needed** for the core proxy startup — keys only needed for LLM routing which is out…
Replay the whole session, every command from a clean machine to this point.
How it was tested
One agent, one container, no human help. It installs the project the way its own documentation says to, runs it, and fixes what breaks. Everything below is recorded as it happened: the terminal session, the log and the exact commit. The full method.
Strengths and limits
Measured facts, not opinions. How this is written.
What went well
- Reached a running state on a clean machine, with the session recorded.
- Installed in 15 minutes, faster than the median of the 4 comparable projects Argusic has measured.
- Nothing broke on the way: zero errors between clone and running.
- Ran without a GPU, so it does not need one to start.
- Licensed Apache-2.0, as reported by its host.
What did not, or is not known
- Measured once so far. A single attempt shows it can run, not that it runs reliably.
Of the 5 ai-gateway projects Argusic has installed and timed, plano was the 3rd fastest to reach a running state, and 4 of 5 reached one at all.
What it is a reasonable choice for
- Trying it on a laptop or a small server: it reached a running state without a GPU.
- Following its own README: the documented path worked with nothing to fix.
Also tested, in the same area
Every one of these was installed and run by Argusic on a clean machine. Nothing appears here that was not tested.
Run history
Topics (from GitHub)
ai-gatewayai-gateway-supportenvoyenvoyproxygatewaygenerative-aillm-gatewayllm-inferencellm-proxyllm-routingllmopsllmsopenaipromptproxyproxy-serverrouting
Embed the badge
Markdown for the project README. It links back here; terms on the terms page.
[](https://argusic.com/subject/plano)Questions
- Does plano run?
- Yes. plano runs. Argusic installed and launched it on a clean machine in 15 minutes, hitting 0 errors on the way, and recorded the session.
- How did Argusic test plano?
- On a fresh, disposable machine, with every command recorded and the repository pinned at commit 003c36aea896. One attempt is recorded, and the full method is on the methodology page.
- What did it cost to test plano?
- The run that produced this verdict cost $0.07: real compute and model cost, not a list price per million tokens. It is recorded on that run's page.
- How long does plano take to install?
- 15 minutes in the run that decided this verdict, from a clean machine to a running state. That is one measured attempt, not an average.
- Does plano need a GPU?
- Not to start. Argusic reached a running state on a machine with no GPU.
- What goes wrong when installing plano?
- Nothing did, in the recorded run: zero errors between clone and running.
- How does plano compare with the alternatives?
- Of the 5 ai-gateway projects Argusic has installed and timed, plano was the 3rd fastest to reach a running state, and 4 of 5 reached one at all.
- Where is the evidence for plano?
- The recorded run is on this page, each linking to its full log and terminal recording, stored with a sha256 fingerprint so it cannot be quietly altered.