Once OpenClaw is running and pointing at the local inference endpoint, the next step is giving it a way to receive messages. OpenClaw supports multiple messaging channels natively – Telegram, Signal, Discord, and others. This post covers Telegram : getting a bot token, connecting the channel, pairing it to your account, and trying it out.
Container 110 (Pi Coding Agent) and container 111 (OpenClaw) are both running. The question now is how OpenClaw routes a coding task to Pi and gets the result back.
Pi’s integration interface is RPC over stdin/stdout — it’s designed to be driven as a subprocess, not called over a network. OpenClaw lives in a separate container. Separate containers don’t share a process space, so “spawn Pi as a subprocess” doesn’t work out of the box.
At this point in the series, the inference layer is done. CT 100 is running llama-server on the RTX 5060 Ti at 26 T/s. CT 101 is running llama-server on the RX 6650 XT at 51 T/s. Both expose OpenAI-compatible endpoints on the local network.