I used to think building AI automation meant hiring a developer, learning to code, or waiting until I magically had a spare month to figure it out. So I did the manual thing instead. For way too long.
Then I came across this post from an AI professional who breaks down automation so simply that I actually felt a little silly for waiting. The original poster makes one point stick: automating your work does not require an engineering team, a Python course, or a computer science degree. It requires understanding three moving parts. That’s it.
I was genuinely surprised at how clear this is once you strip away the jargon. So I’m breaking down the creator’s full framework for you, step by step, the way they’d hand it to a brand new hire on day one.
The big idea: automation is 3 things stacked
Here’s the mental model the author leans on. Every automation, no matter how fancy it looks, is really just:
- A trigger: the thing that kicks it off
- A decision: AI figures out what should happen
- An action: the system does the thing for you
That’s the whole system. As the expert puts it, no engineering degree required. Once I saw it framed this way, a dozen manual tasks I’d been grinding through suddenly looked automatable.
Why it matters: the founders who understand this early are already several steps ahead. While one person automates a task in an afternoon and moves on, everyone else keeps doing the manual version for another quarter.
The exact flow the creator hands a new hire
This is the part I loved. It’s a clean, repeatable process you can run on almost any workflow. Here’s the step by step, straight from the original poster, with the reasoning behind each move.
- Pick a trigger. A new email, a new lead, a payment received, a form submitted. This is your starting gun. Choose something that already happens in your business regularly.
- Feed it to AI. Summarise it, extract the details, classify it, and let it decide what happens next. This is where the smart part lives, so the work doesn’t land on a human.
- Take the action. Update a CRM, send a Slack message, generate a document, book a meeting. The AI’s decision turns into a real result.
- Add rules on top. High priority lead? Notify sales. Payment received? Send the receipt. Rules keep the automation behaving the way you actually want.
- Test every single step before it ever touches a real customer. This is the guardrail that saves you from embarrassing mistakes at scale.
- Turn it on and let it run in the background. Now it works while you sleep.
What I appreciate about this creator’s framing is that each step has a clear reason. It’s not “do this because I said so.” It’s a logic chain anyone can follow.
You don’t have to build the plumbing yourself
This part surprised me the most. The expert points out that you no longer have to wire everything together by hand. The connections already exist.
- Tools that plug straight in: Gmail, Notion, Slack, Stripe, Airtable, and Calendly
- No-code platforms that handle the wiring: n8n, Make, Zapier, and Gumloop
So the technical heavy lifting is basically solved for you. You’re assembling pieces, not building an engine from scratch.
Hard-won lessons the author learned by getting them wrong first
This is the section I’d tape to my monitor. The creator is refreshingly honest that these came from mistakes, not theory.
- Start with one workflow, not ten at once. Momentum beats ambition here.
- Be painfully specific. A vague prompt gets you a vague result, every time.
- Never skip testing just because the workflow feels obvious.
- Don’t let AI touch sensitive data without a human checking first.
- Keep every workflow simple enough that you could explain it in one sentence.
- Monitor it after launch. Automations drift if nobody’s watching.
That last one hit home for me. I always assumed “set it and forget it” was the goal. The original poster reframes it: set it, then keep an eye on it, because systems quietly wander off course.
The skills that actually matter
Here’s the reassuring truth the author drives home. The skills that make automation work aren’t technical at all:
- Prompt writing
- Workflow design
- Logical thinking
- Knowing what “done” looks like
And to be crystal clear, the expert spells out what you do not need: you do not need Python, you do not need JavaScript, and you do not need SQL. If you can think through a process clearly, you can build this.
My honest takeaway
The reason I wanted to share this contributor’s breakdown is that it removes the biggest excuse most of us hide behind: “I’m not technical enough.” The three-part model of trigger, decision, action is something you can literally sketch on a napkin. Then the no-code tools do the rest.
If you’ve been putting off automating that one annoying manual task, this framework is your permission slip to start small this week.
Go read the full LinkedIn post for the complete walkthrough and the creator’s attached infographic. And here’s a question worth sitting with: what’s the first thing you’d automate if it only took an afternoon?