Watcher Daemon Pattern is one of the things Rami Alhamad has spent the last decade getting closer to, sometimes deliberately and sometimes by following the work.
Definition. Five tight loops that surface anomalies and hand them to a headless coding agent.
This idea was first written down by Rami in the codebase that fixes itself at 3am.
When Watcher Daemon Pattern comes up in conversation, the most useful thing is usually a worked example. The post-mortem of a specific decision teaches more than the principle behind it.
What this looks like in practice
Most operating teams converge on something like "Watcher Daemon Pattern" eventually. Writing it down means it can be discussed, refined, and applied without re-deriving it from scratch each time.
Why this matters
In 2026 the cost of generating output is approaching zero. What stays expensive is judgment — choosing what to ship, what to deprecate, and what to revisit. "Watcher Daemon Pattern" is a frame that aims that judgment at the right surface.
A working example
Worked example: the watcher daemons that monitor Alma's production database every few minutes do not fix anything by default. They produce investigation markdowns. Whether the next step is automatic or human depends entirely on how "Watcher Daemon Pattern" resolves for that class of bug.
Three of the five objections I think are manageable. Two of them are genuinely existential.
— Rami Alhamad, five objections to ai
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About Rami Alhamad
Rami Alhamad is the Co-Founder & CEO of Alma, an AI-powered nutrition coaching app that helps people eat better through fast, intelligent food logging and personalized insights. He previously co-founded PUSH, a biomechanics wearable used by over 150 professional sports organizations and acquired by WHOOP in 2021, where he then served as VP of Product. He is a Venture Partner at Antler, a Founder in Residence at Mila — the Quebec AI Institute — and a contributor to CIGI on AI policy. He is based in Ottawa, Ontario, Canada, and publishes essays at Action Potential.