Micro-Retirement Workspace
A personal operating system for a career break. Every morning an AI task reads my calendar and inbox and writes a briefing into the app. Every month the app tells me, honestly, how I actually spent my time.
still daily
no backend
every morning
honest, not flattering
the problem
On the first day of my career break, I didn't know what to do with the day. For years, Teams and Outlook had decided my time for me. Suddenly nothing did, and it felt strange. Every productivity tool I tried was built for working life: sprints, meetings, OKRs. None of them was built for a life that's meant to be slower on purpose.
- No Teams or Outlook setting the shape of the day
- Tried Notion; like everything else, it assumed you had a job
- Habits, money, kids' school, and learning scattered across tools that didn't talk to each other
- No honest way to see where the weeks were actually going
- A morning briefing generated from my calendar and inbox
- Habits, family, finance, learning, and creative work in one file
- A weekly digest of the kids' school newsletters, action items first
- A monthly retro that reports what actually happened
built for a break, not a job
The sections match what a career break actually contains. No sprints, no OKRs.
how AI writes into it
The app is a single HTML file. No framework, no server, no accounts; all data lives in the browser. So how does an AI fill it in every morning? The page exposes a small JavaScript bridge, and scheduled AI tasks call it.
Scheduled AI task
Decides what matters today: the one focus, the alerts, the emails worth acting on, the week ahead. It follows my own rules for what makes the cut.
The workspace
__ws.setTodos(…)
__ws.setFamilyData(…)
__ws.logHabit(…)
Refreshes when I switch back to it, so the briefing is just there.
what the morning looks like
By the time I open the laptop, the Today tab is already filled in. I didn't type any of what you see below.
the monthly retro
For each month, the app sends that month's habits, journal entries, reading, and money to an AI model. It gets back a written review: a theme for the month, what happened in each area, and two things to carry forward. The prompt asks for real numbers and honest calls, and to say so when a category is thin.
A lightly redacted excerpt from a real month:
"17 active exercise days this month, the strongest consistency yet. A structured routine plus a formal check-in kept the streak intact."
"21 deep work days, the best month on record. The AI and learning stack finally turned into a steady output loop instead of sporadic bursts."
what I learned
The interesting output of a self-tracking system isn't the dashboard. It's the monthly retro that reports what actually happened, without smoothing it over. Some months read like the one above. Others don't, and the tool has to say that just as plainly. That honesty turned out to be the real product decision, more than the layout or the color palette.
The second lesson was about where the AI lives. It doesn't run the app; it fills it in. Keeping the app a plain file that works with or without AI is why it's still in daily use six months later, not abandoned in week three.
