Automating My Daily Workflow: How I Saved 15 Hours a Week with Python

I didn’t start automating my life because I love Python scripts.
I started because I was tired.

Tired of:

• Clearing the same types of emails every morning
• Manually accepting calendar invites and blocking focus time
• Copy-pasting the same content across LinkedIn, X, and other platforms

So I did what any lazy developer does: I wrote code so I could be lazier 😄

In this post, I’ll share exactly how I saved ~15 hours a week by automating:

• Email triage and labeling
• Calendar events and time blocking
• Social media content scheduling and posting

No crazy architecture. Just practical Python scripts + APIs.

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Step 0: Where Did the 15 Hours Come From?

Before I automated anything, I tracked one week of my “normal” behavior.

Roughly, this is what I found:

• Email: ~1.5–2 hours/day
• Calendar (booking, rescheduling, accepting, blocking focus time): ~30–45 minutes/day
• Social media posting + context switching: ~1.5 hours/day

Total: around 3.5–4 hours/day → ~18–20 hours/week.

After automation, most of that turned into quick reviews instead of from-scratch work. Net saving: 15+ hours/week on average.

The lesson:

Don’t automate blindly. Measure where your time is actually going, then attack the biggest chunk first.

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Part 1: Automating Email Triage with Python

Email used to be my biggest sinkhole.

My Goal

I didn’t want a robot to answer everything. I just wanted:

• Newsletters to go into a “Read Later” label
• Low-priority notifications to skip the inbox
• Important emails to be highlighted so I could respond faster

The Stack

• Email provider (e.g., Gmail)
• Python
• Official API / IMAP access
• A small scheduler (cron or a task scheduler)

The Logic

My email script basically does this:

1. Connect to my email account securely
2. Fetch unread emails from the last X minutes
3. Apply simple rules:
   • If sender is in a newsletter list → label “Newsletter” + mark as read
   • If subject contains certain keywords → “Automation”, “Invoices”, “DevOps Alerts”, etc.
   • If sender is in an “Important” list → star + keep in inbox
4. Move/label those messages accordingly
5. Log what it did, so I can review if needed

What Changed for Me

• My inbox stopped feeling like a slot machine
• I rarely see newsletters or low-priority automation emails during deep work
• Important messages are easier to spot and clear

On a normal day, I spend 10–15 minutes quickly replying to what matters, instead of 90 minutes wrestling with the inbox.

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Part 2: Calendar Automation and Time Blocking

Email is where chaos starts. Calendar is where it solidifies.

I used to:

• Manually accept meeting invites
• Forget to block time for deep work
• Miss setting up buffers between back-to-back calls

My Goal

Let the system handle repetitive calendar hygiene, so I can focus on actual work.

The Stack

• Google Calendar (or similar)
• Python
• Calendar API
• A daily or half-hourly scheduler (cron, GitHub Actions, etc.)

What My Script Does

A simplified version of the automation:

1. Auto-accept rules
   • If invite is from a specific domain (e.g., my company) and within working hours → auto-accept
   • If outside working hours → leave as “needs action” so I can consciously decide
2. Time Blocking for Deep Work
   • Every morning, if my day has more than X free hours, the script:
     • Creates 1–2 focus blocks (e.g., 90 minutes each)
     • Marks them as “Busy” with titles like “Deep Work: Coding / Writing”
3. Buffer Between Meetings
   • Detects back-to-back meetings
   • Automatically adds a 10–15 minute “Break” event
4. Automatic Naming/Color Coding
   • If title contains “1:1”, “sync”, “standup” etc. → apply specific color
   • Makes the calendar visually easier to parse at a glance

Result

Calendar went from:

“Random meetings thrown at me”

to

“Deliberately structured day that’s mostly on autopilot.”

Instead of managing my calendar, I mostly review it and do small tweaks.

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Part 3: Social Media Automation with Python

This one was huge for me, especially while trying to stay consistent on platforms like LinkedIn, X, and Instagram.

The Problem

I kept:

• Writing posts whenever I felt like it
• Forgetting to post on some days
• Copy-pasting the same content into multiple platforms manually

This led to zero consistency (and also a lot of mental overhead).

My Goal

Turn social posting into a batch + automate system:

1. Create content in bulk once or twice a week
2. Store it in a simple structure (CSV / JSON / Notion / Google Sheet)
3. Let scripts handle scheduling & posting via official APIs or connected tools

The Stack

• Python
• Platform APIs (e.g., LinkedIn, X/Twitter, etc.) or a scheduling tool with API/webhooks
• A content source: CSV / Google Sheet / Notion database
• Cron / scheduler to run at specific times

My Workflow

1. Content Planning Session (1–2 hours/week)
   • I write 10–20 short posts
   • Each with: text, platform(s), scheduled date/time, image URL (optional), tags
2. Store It
   • I either use a Google Sheet or a simple JSON file like:

   {
     "id": 1,
     "platforms": ["linkedin", "twitter"],
     "text": "Today I automated my email workflows with Python. Here’s what changed for me...",
     "scheduled_at": "2025-12-15T10:30:00",
     "image_url": null,
     "status": "pending"
   }
   

3. Python Posting Script
   • Runs every X minutes
   • Checks for posts where scheduled_at <= now and status = "pending"
   • Uses platform APIs or a scheduling service’s API to publish
   • Marks them as posted once successful
4. Logging & Fallbacks
   • Logs any failures (rate limits, auth issues, etc.)
   • Sends me a quick email/notification if something breaks badly

The Difference

• I’m not “thinking about posting” during the day
• I don’t scramble to write something at 10 pm
• My content looks consistent on the outside, even when my day is chaotic on the inside

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My Automation Stack (At a Glance)

Here’s the high-level stack I rely on:

• Python – the glue for everything
• Email API / IMAP – for reading & labeling emails
• Calendar API – for reading & creating events
• Social APIs / Scheduling tool APIs – for posting content
• Cron / scheduler (local or cloud) – to run scripts on schedule
• Logs (files, simple dashboards, or even email reports) – so I know what the bots did

You don’t need to get all of this perfect from day one. I definitely didn’t.

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How You Can Start Automating Your Own Workflow

If you want to try this for yourself, here’s a simple path:

1. Track One Week

Don’t guess.

• Where does your time go?
• Email? Calendar? Slack? Social? Meetings?
• Which tasks feel repetitive and rule-based?

Write it down for 5–7 days.

2. Pick ONE Area to Automate

Resist the temptation to automate your entire life at once.

• If email drains you → start there
• If meetings drain you → start with calendar
• If content drains you → start with social media batching

3. Write a Super Simple Script

Keep v1 tiny. Example:

• Email: “If sender = newsletter@domain.com → label + archive”
• Calendar: “Create a 90-minute deep-work block at 9:00 if free”
• Social: “Post one hard-coded message to LinkedIn via API”

Once that’s working and stable, you can layer complexity.

4. Add Logs and a Kill Switch

Automation without visibility is scary.

• Always log what your scripts are doing
• Add safeguards (e.g., don’t send more than X posts per day)
• Make it easy to disable automation quickly if something goes wrong

5. Iterate Weekly

Every week, look at:

• What manual task annoyed you the most
• Whether your script misfired anywhere
• What next small thing you can automate

Tiny improvements compound surprisingly fast.

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The Real Benefit: Mental Bandwidth

Yes, saving 15 hours/week is great.

But the bigger win for me was mental bandwidth:

• Fewer context switches
• Less guilt about “I should post something today”
• More energy for deep work and creative projects

Automation is not about turning yourself into a robot.
It’s about letting the robots handle robotic work so you can focus on:

• Strategy
• Creativity
• Building things only you can build

If you found this helpful, follow along as I share more dev, AI, and automation experiments. You can also find me on YouTube and LinkedIn for deeper breakdowns.