Thousands of emails, all marked read except the ones that matter
Ronald runs a company of 35 people and, by his own description, keeps "everything" in his Gmail — "a thousand emails and maybe a few thousand per day." His existing habit was already a kind of manual triage: "everything is marked read except what I want" to come back to. He'd built a filter for himself by hand, one email at a time, long before automating any of it.
"I don't read them all, but ChatGPT reads them"
Describing how he actually handles the volume now, on a recent xTiles call: "I don't read them all, but ChatGPT reads them — he tells me if something is critical." That's not ignoring the inbox. It's delegating the reading, so what actually reaches him is a short list of things that were already judged to matter.
Built on top of a system he'd already built himself
Before this call, Ronald had already taught ChatGPT his own priorities directly, through its memory: "I told him in his memory what to do, and I tag xTiles, he knows what to do." He'd asked ChatGPT outright whether he needed anything more, and gotten a direct answer back: "at this moment, I don't see why — because I know you better." Connecting xTiles didn't replace that personal setup. It gave the same review a structured place to land instead of staying locked inside one long-running chat.
Not just email — Teams, meetings, and the day as a whole
The same review extends past his inbox. His company uses Microsoft Teams rather than Slack, and the same daily pattern covers it: overdue tasks moved forward automatically, important Teams threads surfaced instead of scrolled past, meeting-note follow-ups pulled in so a promise made on a call doesn't quietly disappear. By the end of the day, the same review turns into a short recap of what actually happened — not a read requirement, just something to glance at.
The number that made the case: another CEO, four hours to 45 minutes
During the call, one detail landed harder than the feature list: a CEO at a different, roughly 50-person company had been spending about four hours a day manually pulling information together from every tool she used — tasks, email, calendar, team chat — just to figure out what needed her attention. With the same kind of automation in place, that dropped to about 45 minutes.
That's not Ronald's own number. It's the comparison that made the shape of the problem — and the plausible size of the fix — concrete enough to act on.
His actual verdict
Asked to compare it to what he already had running in ChatGPT, his answer was measured, not a sales pitch: "probably similar possibilities but better organized, maybe quicker, and better overview." He subscribed on the call: "I'll take subscription now and see how it works for me. I think it will be okay."