You NEED to set up a multi agent team with OpenClaw and Hermes
TL;DR
Two agents kill the single point of failure — Alex Finn says pairing OpenClaw with Hermes took his downtime from “like an hour every time I upgrade” to “literally seconds,” because when one breaks, the other jumps in to repair it.
He treats OpenClaw as the expensive brain and Hermes as the cheap operator — OpenClaw runs as the main agent on Opus 4.6 for planning and QA, while Hermes uses a cheaper model like ChatGPT or GLM for fast execution and monitoring.
The best workflow is planner-builder-reviewer — In his example, OpenClaw generated a 256-line markdown plan for a Next.js scanner dashboard, Hermes built it, and then OpenClaw reviewed the code and suggested improvements.
Hermes shines as a lightweight hallway monitor — Because it’s faster and lower-cost, Alex uses Hermes on cron jobs every two hours to inspect scanners, flag failures, and watch systems OpenClaw originally built.
Shared memory turns separate agents into a learning system — Using Obsidian folders for agent-specific notes plus a shared workspace, both agents can see each other’s logs, mistakes, and decisions, which Alex frames as recursive self-improvement.
His setup is practical, not theoretical — He keeps both agents open side-by-side in Telegram on a second monitor, names them Henry and Hermes, and uses them constantly for real work like fixing broken updates and building internal dashboards.
The Breakdown
Why Alex Thinks OpenClaw + Hermes Is the Best Combo Right Now
Alex opens with a strong claim: OpenClaw and Hermes together are “the most powerful combo in AI right now,” because reliability shoots up when two different agents can cover for each other. His core point is simple and useful: stop treating them like rivals and start treating them like teammates with complementary strengths.
OpenClaw as the Main Agent, Hermes as the Fast Assistant
He says OpenClaw is his primary agent because it’s been more stable, gets updates faster, and handles big tasks more reliably. Hermes, meanwhile, is the assistant and monitor: lighter weight, faster, cheaper on tokens, and great at keeping the main system moving without needing top-tier intelligence for every job.
The Model Split: Pay for Brains, Save on Execution
Alex is blunt here: “Opus is the best model for AI agents,” so he powers OpenClaw with Opus 4.6 even though it’s expensive. For Hermes, he recommends something cheaper like ChatGPT or even GLM-tier options, because the assistant role doesn’t need the same level of reasoning and this setup lets you spend money only where it matters.
The Killer Use Case: One Agent Fixes the Other When Updates Break
His first real example comes from an OpenClaw update that suddenly threw a fake “missing API key for OpenAI” error even though he wasn’t using OpenAI at all. Instead of manually debugging for an hour, he handed the error to Hermes, which inspected the OpenClaw codebase, found the issue, and fixed it — the cleanest argument in the video for a two-agent setup.
Planner, Builder, Reviewer: The Dashboard Demo
Then he shows the workflow he likes most for actual creation: OpenClaw plans, Hermes builds, OpenClaw reviews. He asks Henry — his OpenClaw agent — to create a plan for a Next.js dashboard for his scanner system, gets back a 256-line markdown spec, feeds that to Hermes, and Hermes produces a polished dashboard showing 18 scanners, health status, last run, next run, and run history.
Why the Review Loop Saves Money
Once Hermes finishes, Alex sends the code back to OpenClaw with a simple “check out the code here and let me know what you think.” That’s the point of the system: the smartest, priciest model doesn’t do all the typing — it does the planning and quality control, while the cheaper agent does the labor.
Hermes as the Hallway Monitor
From there he shifts into monitoring: Hermes regularly runs cron jobs every two hours to inspect systems OpenClaw created and alert him if anything is off. He compares it to a hallway monitor — always checking scanners, apps, social media, or email — and argues Hermes is better suited for that because it’s lightweight and cheap enough to run constantly.
Shared Memory in Obsidian Makes the Team Smarter
The last big piece is memory: Alex keeps separate Obsidian folders for OpenClaw and Hermes plus a shared folder where they exchange lessons, plans, logs, and mistakes. He gives a concrete example from that morning, where Hermes drafted the plan for this very YouTube video in the shared folder so OpenClaw could review and improve it, turning two separate agents into a system that learns across tasks.