She audited a whole Monday.com board in three weeks and found two hidden bugs
A full board audit delivered in three weeks, uncovering a bug that misrouted 13 of 16 subitems.
She took on a full audit of a Monday.com board in the middle of an event-planning crunch and delivered it in three weeks. By pairing Claude with careful screenshots of a live build, she found problems nobody had spotted. Her story shows how a sharp method and an AI partner can turn messy real work into clear answers.
Monday.com Board Audit and Recommendations
Before
She was mid-way through an event-planning crunch when the board audit landed on her plate. The board's automations were meant to route work cleanly, but what people did and what the system did had quietly drifted apart. Nobody had a clear picture of where things were going wrong.
“Screenshotted every step of a live event build, then compared her notes against the platform's actual automation configuration and activity logs to find where they diverged.”
In their own words
The turning point
She connected Claude directly to Monday.com and changed how she looked at the problem. She screenshotted every step of a live event build, then compared her notes against the platform's actual automation configuration and activity logs. The gaps between the two showed her exactly where to dig.
After
In three weeks she delivered a full audit and a set of recommendations. She found a hardcoded-assignee bug misrouting 13 of 16 subitems, and a duplication bug that re-fired a full 15-task cascade on any incidental edit. What had been invisible friction became a clear list of fixes.
What it lets people do
Her audit lets a team see how their board really behaves, not how they assume it does. Fixing the routing and duplication bugs means tasks reach the right people and stop multiplying with every small edit.
What they learned
She learned that watching real usage tells you more than asking about it. Her method let her see what people actually did, without interviews or permissions, so the diagnosis rested on evidence rather than memory.
“Could observe real usage patterns without interviewing anyone or asking permission, so the diagnostic reflected what people actually did, not what they said they did.”
In their own words
Monday.com Board Audit and Recommendations was built during AI Mastery.
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Written 9 August 2026 Submitted by the storyteller
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