Case Study: 8-10 Hours of Weekly Admin, Automated
André runs a solo SaaS business building AI automation tools. This is a documented breakdown of 8 automations he runs daily, what each one does, and the actual time savings.
No hypotheticals. These are real jobs running on real schedules.
The Automations
1. Morning Brief (7:00 AM daily)
A scheduled job pulls today's calendar events, local weather, filtered tech news, and generates a short priority list. The output arrives on Telegram before coffee.
What it replaced: Manually checking calendar, scanning news sites, reviewing the day's plan. About 15 minutes of scattered tab-hopping each morning.
Time recovered: ~15 min/day
2. Inbox Triage (7:05 AM daily)
Scans Gmail for the last 24 hours of email. Categorizes each message as urgent, informational, or promotional. Drafts replies for urgent items but never sends without explicit approval. Auto-unsubscribes from newsletters that haven't been opened in 30+ days.
What it replaced: Opening Gmail, scanning for urgency, deleting junk, writing routine replies. About 25 minutes of reactive email processing.
Key constraint: Draft-only mode. Nothing sends automatically. This is a hard rule.
Time recovered: ~25 min/day
3. Receipt Extraction (7:15 AM daily)
Finds receipt emails from the past 24 hours, extracts vendor, date, amount, and category, then appends rows to a Google Sheet. Sends a one-line summary with total spend and largest transaction.
What it replaced: Manually logging receipts (when remembered), scrambling at tax time to reconstruct expenses.
Time recovered: ~10 min/day
4. Heartbeat Monitoring (every 30 min, 7 AM to 11 PM)
Checks email for time-sensitive items, calendar for upcoming events in the next 2 hours, and server health via API. Only sends a notification if something needs attention. No "all clear" messages.
What it replaced: The mental overhead of constantly checking: is my server up? Did anything urgent come in? Do I have a meeting soon?
Time recovered: ~1 hr/week (eliminates compulsive checking)
5. System Maintenance (4:00 AM daily)
Updates platform packages, restarts services, reports what changed. Runs while André sleeps.
What it replaced: A weekly manual update routine that took about 30 minutes and was easy to forget.
Time recovered: ~30 min/week
6. Automated Backups (4:30 AM daily)
Backs up configuration files, task schedules, and workspace data to a private GitHub repo. Scans for leaked secrets and replaces them with placeholders before pushing.
What it replaced: Sporadic manual backups that happened when André remembered (which wasn't often enough).
Time recovered: ~1 hr/week
7. "On This Day" Display (5:30 AM daily)
Fetches historical events from Wikipedia, picks one, generates an AI illustration, and pushes it to a TRMNL e-ink display. No time saved. Just a daily thing that makes the morning more interesting.
8. Deep Research (on demand)
Launches parallel searches across Twitter/X, Reddit, Hacker News, YouTube, and the web. Each source gets its own search agent. Results are synthesized into a single document with executive summary, key themes, and source links.
What it replaced: Manually searching each platform one at a time.
Time recovered: 2-4 hours per research session (used a few times per week, varies)
The Math
| Automation | Frequency | Time Recovered |
|---|---|---|
| Morning Brief | Daily | ~15 min/day |
| Inbox Triage | Daily | ~25 min/day |
| Receipt Extraction | Daily | ~10 min/day |
| Heartbeat Monitoring | Every 30 min | ~1 hr/week |
| System Maintenance | Daily (4 AM) | ~30 min/week |
| Automated Backups | Daily (4:30 AM) | ~1 hr/week |
| On This Day | Daily (5:30 AM) | 0 (quality of life) |
| Deep Research | On demand | 2-4 hrs/session |
Daily automations (1-3): ~50 min/day, or about 5.8 hrs/week. Background automations (4-6): ~2.5 hrs/week. On-demand research: variable, not counted in the weekly total.
Conservative weekly total: ~8 hours. With 2-3 research sessions, it crosses 10.
What a Typical Day Looks Like
- 6:45 AM - TRMNL shows today's historical image.
- 7:00 AM - Morning brief arrives on Telegram during coffee.
- 7:05 AM - Inbox triage summary: 2 urgent emails flagged, 3 drafts ready.
- 7:15 AM - Expense summary for yesterday.
- 8:00 AM - Reviews drafts, approves what makes sense, starts deep work with full context.
- Throughout the day - Only gets interrupted if the heartbeat check finds something.
Design Principles Behind These Automations
- Schedule everything. If it needs to happen regularly, it should not depend on you remembering.
- Draft-only for anything high-stakes. Email replies need human approval before sending.
- Alert on exceptions, not on normalcy. No "all clear" messages. Only interrupt when there is something to act on.
- Back up automatically. You will forget. Your automation will not.
These automations run on a schedule with LLM-powered agents. Your setup and results will vary based on your tools and workflow.