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5 AI Automations I Built This Month That Save Me 10 Hours a Week
Copy these exact setups. None of them required coding.
Hey there,
Last month I got obsessed with one question: what is the most boring, repetitive thing I do every week that a machine could do instead? I made a list. Then I automated everything on it.
The result: I got back roughly 10 hours every single week. Not by working harder. Not by hiring anyone. Just by setting up five automations using tools that already exist, most of them free or close to it.
I am going to walk you through each one. The exact tools, the exact setup, and the exact time it saves me per week. You can copy all of these this weekend.
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The Numbers
What These 5 Automations Actually Save
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Let us get into it.
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AI Email Inbox Sorting — 2.5 hrs saved/week |
I used to spend 30-40 minutes every morning just triaging my inbox. Deciding what needed a reply, what was noise, what needed action. It felt productive. It was not. It was just email anxiety dressed up as work.
Now I use a combination of Gmail filters and a ChatGPT-powered sorting system. Every morning my inbox is pre-sorted into three buckets: Reply Today, Read Later, and Archive. I open my email once, spend 10 minutes, and I am done.
How To Set It Up
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AI Content Repurposing Pipeline — 3 hrs saved/week |
Every newsletter I write used to stay as just a newsletter. Turning it into tweets, LinkedIn posts, and short-form content meant sitting down for another two hours after already finishing the main piece. I stopped doing it because it was exhausting. Which meant I was leaving reach on the table every single week.
Now the moment I finish a newsletter draft, one prompt does the repurposing for me. I get five tweets, a LinkedIn post, and a short-form hook — all in under three minutes.
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The Exact Prompt
Paste This Into ChatGPT After Every Newsletter
Tools used: ChatGPT + Buffer for scheduling. Total setup time: 20 minutes. Time saved per week: 3 hours. |
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AI Research Summarizer — 2 hrs saved/week |
Writing a good newsletter means staying sharp on what is happening in your niche. I used to spend two hours every week reading articles, scanning Reddit threads, watching YouTube summaries just to find two or three ideas worth writing about. Most of that reading produced nothing useful.
Now I use a Make (formerly Integromat) workflow that pulls RSS feeds from my top ten sources every Monday morning, summarizes each article using AI, and drops a clean digest into a Notion page. I spend 20 minutes reading summaries instead of two hours reading full articles.
How To Build This
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AI Reply Drafts for DMs — 1.5 hrs saved/week |
If you run a newsletter or create content, DMs and reply emails pile up fast. Most of them are variations of the same five questions. "How do I start a newsletter?" "What tool do you use?" "Can we collaborate?" I was spending 90 minutes a week typing out the same answers in slightly different words.
I built a simple ChatGPT custom instruction set that drafts replies in my voice. I paste the incoming message, get a draft back in seconds, tweak one or two lines, and send. The reply still sounds like me. It just takes 30 seconds instead of 5 minutes.
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My ChatGPT Custom Instructions for DM Replies
Takes 2 minutes to set up in ChatGPT's custom instructions. Saves 90 minutes every week. |
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AI Weekly Analytics Report — 1 hr saved/week |
Every Friday I used to manually pull numbers from Beehiiv, Twitter analytics, and Gumroad, drop them into a spreadsheet, and try to figure out what they meant. It took an hour and the insights I got were usually shallow because I was too tired from the data collection to think clearly about it.
Now I paste my weekly numbers into one ChatGPT prompt and get back a plain-English summary with three specific action items. Takes five minutes instead of sixty.
The Weekly Analytics Prompt
The insights this produces in 10 seconds are genuinely better than what I used to produce manually in an hour. Pattern recognition is where AI earns its keep. |
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All 5 Automations at a Glance
Total: About 2.5 hours of setup. About 10 hours saved every week after that. |
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The Bigger Point
None of these automations are impressive on their own. No one is going to write a case study about sorting email labels or repurposing tweets. But that is exactly the point. The most valuable AI use cases are not the dramatic ones. They are the boring, repetitive tasks you do on autopilot every week that quietly drain your best hours before you ever get to the work that actually matters.
Ten hours a week is 520 hours a year. That is thirteen full work weeks handed back to you. You can spend that time building something, thinking clearly, or just not being exhausted. All three are good options.
Start with one. Pick the automation that matches the task you hate most. Get it working. Then build the next one. By the end of the month you will have a system that works for you around the clock without asking for anything in return.
Which of these five are you building first? Hit reply and let me know. I read every one.
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Until Next Time, AI Spotlight |
Arnold Schwarzenegger has a newsletter.
Yeah. That Arnold Schwarzenegger.
So do Codie Sanchez, Scott Galloway, Colin & Samir, Shaan Puri, and Jay Shetty. And none of them are doing it for fun. They're doing it because a list you own compounds in ways that social media never will.
beehiiv is where they built it. You can start yours for 30% off your first 3 months with code PLATFORM30. Start building today.