I got tired of running team operations by hand.
Our founding team's standups happened in a channel when people remembered. Our GTM tracking lived in spreadsheets nobody updated. Weekly reports took an hour to compile and were read by no one. And nobody could answer the simplest question: "Are we on track?"
So I built a company brain. It's an AI agent that lives in our Discord, runs daily standups, tracks our GTM numbers, and generates dashboards. We named it Dojo. It costs about $2-5 a month to run.
Here's what it does every day:
The weekly workflow reads those JSON files and generates a dashboard with charts: targets vs actuals, per-person contributions, trend lines. The monthly report adds channel breakdowns and strategic recommendations. The quarterly review checks the full-year trajectory against our revenue target.
The whole thing runs on:
The stack: a Hermes Agent instance with a dedicated profile, a SOUL.md identity file, 13 skills (workflows), and a data folder of JSON files. Everything is files and schedules — no magic, fully inspectable.
The idea came from Gumclaw, the agent that runs all of Gumroad's operations. If an agent can run a company's support and engineering, I figured it can at least run our standups. It was right.
Lessons after a month of running it:
If you're a founder still compiling standups by hand, clone it and run your first standup tomorrow. It takes an afternoon, not a quarter.
The line about a brain that silently dies being worse than none is the one that matters most here, and I would push it one step further. What happens when it does not die, but starts misparsing replies quietly? You said the parsing rules matter more than the model, which means drift in those rules is a real failure mode, not just uptime. Do you have anything watching for that, or would you only catch it when a dashboard number looks obviously wrong?
The part about people stopping replies after two weeks feels painfully familiar.
The self-learning piece is interesting too. Curious whether the team actually started relying on the generated summaries over time, or if the biggest value is still just keeping the daily workflow from falling apart.
The self-learning part is probably the most interesting piece here. Once the “company brain” starts updating itself, I imagine the harder problem becomes knowing when an old piece of information is no longer true.
How are you thinking about stale or superseded context? For example, if a project decision changes, does Dojo update the old knowledge, keep both versions, or rely on the latest information winning?