(Current situation: I’m in Aruba for a week-long Mastermind Retreat, writing this poolside. We live and work in magical times, friends.)
Let’s call it: Automation is having a glow-up.
One minute, I was trying to channel my inner split personality for every social platform—writing snappy one-liners for Twitter, professional vibes for LinkedIn, and something vaguely inspirational for Instagram, all while muttering “I just want to write books” under my breath. I was basically a one-woman social media improv troupe. Exhausting.
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Then ChatGPT sauntered onto the scene, all cool and casual, and I thought: What if I didn’t have to do this the hard way? What if I could feed it one idea, and it could spit out platform-specific content without making me want to walk into the sea?
Naturally, I pushed the boundaries. Because of course I did.
One weekend (read: Tuesday morning when I was avoiding edits), I asked ChatGPT to plan my meals, give me a shopping list, and tell me where I’d find the ingredients in the store. And listen—it mostly worked. Some of the meals were Pinterest-worthy. Some were, uh, “experimental.” But the potential? Huge.
It was a lightbulb moment—not because it did the thing perfectly, but because it made starting feel less impossible.
Remember the “Just Chat” Era? This was the gateway drug for so many of us.
At first, it was small stuff.
“Hey ChatGPT, can you summarize this article?”
“Write a birthday message for my sister that’s funny but not too funny.”
“Give me five newsletter subject lines that sound clever but don’t scream I used AI for this .”
No integrations. No fancy workflows.
Just you, a blinking cursor, and a robot that somehow made Google Docs feel… obsolete.
And yet? It felt magical. Because for the first time, you weren’t just Googling things or copy-pasting templates. You were collaborating. This thing responded to you. It adapted. It remembered what you just said—kind of. (Let’s be honest: it remembered enough to fake it convincingly.)
Then came a little upgrade that changed the game:
Custom GPTs with memory.
Now you could train it. Give it your brand voice. Your preferences. Your audience. Even your weird little quirks (like “don’t ever use the word ‘journey’ unless we’re talking about the band”).
And suddenly? You weren’t starting from zero every time.
You started experimenting:
“Okay, write this caption like it’s for Instagram.”
“Now rewrite it for LinkedIn—with 30% more buzzwords and 100% fewer emojis.”
“Now make it sound like a snarky raccoon just woke up from a nap.”
(You laugh, but it nailed it.)
With memory in the mix, it didn’t just follow instructions—it understood context .
It stopped being a clever chatbot and started acting like a real creative partner.
Still not perfect. Still needs wrangling.
But it felt… different. Smarter. And more like something you could actually build a system around.
And it was enough to spark the big question:
What if this could do more than chat? What if it could take action?
That’s when we started looking for more.
And oh, did we find it.
Then Came Plugins: The Right Idea, Half Baked Ah, the plugin phase.
It looked like we were on the verge of something big.
ChatGPT with plugins? Suddenly, it wasn’t just a word machine—it could do things. You could tell it to send a task to Instacart. Pull data from Wolfram Alpha. Summon a chart. Even spin up a quick design in Canva like it was a digital art intern who never needed coffee breaks.
And in theory? It was brilliant.
I remember thinking, Okay, now we’re cookin’. It’s not just talking—it’s acting!
This time I asked it to plan my weekly meals, generate a grocery list, and toss it into Instacart.
And you know what? It tried. Bless its little digital heart.
Some ingredients went through. Some didn’t. The formatting was a little weird. I had to authenticate three times. And by the time it finished, I realized I probably could’ve just opened the Instacart app and done it myself in half the time.
But hey—the promise was there .
The idea that this thing could bridge across apps? That it could take your instructions and move beyond “chat” into execution ? That was a major vibe shift.
But here’s the thing nobody really said out loud:
It was still one plugin at a time. One command. One output.
It was like trying to throw a dinner party with a staff of butlers who each only know one sentence of English and refuse to speak to each other.
So yes, it felt like progress.
But it was still brittle. Still limited. Still you, playing traffic cop between apps that didn’t know how to coordinate without your constant supervision.
Helpful? Sure.
Efficient? Meh.
Revolutionary? Not yet.
Because you still had to be the glue holding it all together.
You still had to remember what needed to happen, in what order, and how to recover when something broke halfway through.
And that’s when the real shift began.
When we stopped asking, “Can it do this task for me?”
And started wondering…
“What if I didn’t give it a list of chores—what if I gave it a goal ?”
Enter the No-Code Era: Tools With “I Got This” Energy This is where things got real.
Tools like Zapier and Make.com entered the scene like your cool older siblings—
the ones who’d already read the manuals, color-coded their calendars, and had a spreadsheet for their spreadsheets.
They didn’t just promise automation.
They handed you the keys and said, “Go ahead, build it yourself. We’ll handle the wiring.”
Suddenly, you didn’t need to know how to code to make your tools talk to each other.
You didn’t have to wait for some tech team to build the perfect app.
You could just… drag, drop, and launch.
These platforms made workflows visual. Logical. Yours.
You weren’t duct-taping plugins together anymore—you were building legit systems. And yes, it felt powerful. Like, “I-might-start-charging-consulting-fees” powerful.
Here’s one of my favorite setups—my personal pride and productivity joy:
Google Doc links live in Airtable —each one tagged, sorted, and primed for publishing.
Make.com grabs the content , plugs it into ChatGPT , and tailors the caption for every platform (because no, we do not post the same thing to TikTok and LinkedIn, thank you very much).
It pulls a relevant stock image from Pexels , based on the post’s vibe or keywords.
Then? It packages the whole thing up and hands it off to Vista Social , which schedules the post across platforms—with no need for me to lift a finger.
From one Airtable row to a month’s worth of content , scheduled, polished, and platform-perfect.
No tab juggling.
No copy-paste chaos.
No hand cramps from retyping the same keywords 47 times in slightly different ways.
It wasn’t just automation anymore.
It was delegation .
I wasn’t the one doing the tasks—I was the one giving the instructions and watching them get done.
And yeah, I definitely had a moment where I leaned back in my chair and whispered, “Wait… am I a wizard now?”
But even with all that firepower, this setup had limits.
It could follow instructions.
It could handle logic.
It could even run loops and filters and branching paths like a flowchart on caffeine.
But it didn’t think.
It didn’t analyze results or make new suggestions.
It didn’t learn from what worked last time.
And it definitely didn’t say, “Hey, this post style flopped—want to try something different?”
It was still a really smart assistant.
But it wasn’t a strategist. Not yet.
Which brings us to the next evolution.
The one that does think.
The one that doesn’t wait for orders—because it already knows the mission.
Agents.
Agents: When Your Automation Grows a Brain Here’s where things get spicy.
Up until now, automation has been like hiring a really enthusiastic assistant who follows instructions to the letter.
You say, “If I publish a blog post, share it on Twitter.”
And it does. Faithfully. Predictably. No questions asked.
But agents?
Agents are like hiring someone who doesn’t just follow the script—they read the room, look at your calendar, check the weather, and go, “Actually, I’ve got a better idea.”
Instead of “do this task,” you give them a goal .
Something like: “Keep my social media audience growing at 3% per month and my CTR on posts at 4%.”
And they figure out the how —often better than you would’ve.
Here’s the leap:
A regular workflow posts your content.
An agent posts your content and reviews past performance.
It checks what time your audience actually interacts.
It pulls trending hashtags from today’s feeds—not last week’s.
It adjusts the tone if engagement’s been flat lately.
It skips over platforms where your last few posts flopped.
And it emails you: “Hey, this new format is working better—want me to test it again next week?”
It’s not just doing. It’s deciding .
Enter my favorite tool: n8n? Think of n8n (pronounced “nate-en”) as your automation HQ—but with way more brainpower.
If Zapier is a magic wand that casts a spell when you wave it, n8n is a whole spellbook that lets you write your own incantations, chain them together, and summon actual results.
It’s open-source, which means you can host it yourself. You control the data. No surprise fees. No worrying about who’s peeking at your workflows behind the scenes.
And because it’s so customizable, you can add in logic, loops, external data, APIs, even full decision trees. It’s like a LEGO set for your business—except instead of tiny plastic bricks, it’s made of powerful automations you can tweak any way you like.
And what about MCP? MCP (Modular Coordination Protocol) is where things get real nerdy—in the best way.
It’s like giving each of your agents their own walkie-talkie so they can talk to each other.
Imagine this:
One agent’s job is to monitor Google Trends.
Another watches your Instagram analytics.
A third one manages your content calendar.
With MCP, they’re not just working in parallel. They’re collaborating.
They’re sharing info in real-time.
They’re making decisions together —without you being the middleman.
It’s less “run this zap” and more “build a team of bots that manage themselves.”
You set the mission.
They execute it.
And if something unexpected happens (like a post going viral, or a trend suddenly spiking), they adjust—on the fly.
But Wait—Don’t Panic.
Now—deep breath, friend —if you’re somewhere between “ChatGPT is neat” and “What in the flowchart hell is n8n?”…
Take a breath.
You don’t have to jump into agents tomorrow.
Zapier and Make are still wildly powerful. And they’re not going anywhere.
You can build amazing, business-saving, creativity-unlocking automations without ever touching an agent.
You can stay in the no-code playground forever, if that’s your jam.
And if you’re ready for more, I’ll be here to show you the path. I’m putting together some webinars now, because I can’t just talk about this stuff – I need to show you.
The Privacy Piece (Because It Matters ) Let me be very real with you for a second:
I trust these tools with my brand voice—but I don’t blindly trust them with my data.
That’s why I host my own systems.
That’s why I use open-source alternatives when I can.
That’s why I pay attention to what’s happening with large language models and where our information goes when we use them.
This newsletter will always point out the privacy concerns, the fine print, and the “read this before you connect your life to the cloud” stuff.
What’s Coming Next (And Why We’re Starting Here) I know—we just walked through some pretty wild possibilities. But before we start wiring up book launch bots and merch-triggering workflows…
We’re backing up.
Because starting at the beginning?
It’s not just practical—it’s a very fine place to start.
Things in the automation and AI space are moving fast .
Like, whiplash-fast.
And while that’s exciting, it also means we all need to pause and ask better questions:
What tools actually make sense for your business?
How do you choose between LLMs, especially when some are ethically murky and others are built with creators in mind?
What’s worth automating now—and what’s still best handled by a human (you know, the one with the coffee and intuition)?
Over the next few issues, I’m going to lay it all out:
Which LLMs are best for what (and which ones are paying attention to licensing, data privacy, and creative ownership)
What tools like Zapier and Make.com can actually do —and how to use them without needing a tech translator
A peek into what’s possible now—and what’s coming next (so you’re not caught off guard by the future knocking on your inbox)
This is your foundation.
Your orientation.
Your “what the hell is happening and how do I not get buried in tools I don’t need” starter kit.
We’re building clarity before complexity.
So if you’ve ever looked at automation and thought, “That sounds amazing but… also terrifying?” —you’re in the right place.
And if you’ve been feeling like the tech is outpacing your to-do list—or like every week there’s a new tool you’re “supposed” to be using but haven’t even had time to Google—take a breath.
We’re not rushing. We’re building.
Intentionally. Strategically. And with plenty of coffee breaks.
Because automation shouldn’t feel like another overwhelming project.
It should feel like relief. Like momentum. Like finally getting some breathing room.
So that’s where we’re headed—step by step.
If you’re already a subscriber, buckle up. Next week, we’re diving into the real-world basics of automation—no fluff, no jargon. Just clear, doable ways to start reclaiming your time.
And if you’re new here?
Subscribe now so you don’t miss what’s next.
Because this ride’s just getting started—and trust me, it’s worth it.
Until then—
Build smart. Automate smarter.
And yes, take the nap.
—Chelle
Author Automations is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.