(and why sticking with one model is often not enough)
I think I’ll long remember the lightbulb moment when it dawned on me that there was probably a better way I could use AI, and the magic of combining multiple AI models. Now, well it seems such a simple concept, I’m wondering why the penny hadn’t dropped earlier!
There I was, wrestling with a blog post that just wouldn’t cooperate. You know the type, a real stubborn bastard!
I’d been feeding the same prompt into ChatGPT for the fourth time, seeking inspiration and a starting point, tweaking words here and there, hoping for something… anything… that didn’t sound like it was written by an overly enthusiastic instruction manual.
Then, almost on a whim, I copied that same prompt into Claude. And the result? Completely different.
Not just slightly different. Fundamentally different in tone, structure, and approach.
That’s when it really clicked: you just can’t treat AI like a vending machine. Insert prompt, receive output, accept whatever tumbles out. It’s what I see so many people still doing.
But there’s a clear-as-day reality nobody tells you when you’re starting out with AI content creation…. different models think differently.
They have distinct personalities, strengths, and blind spots. And the magic often happens when you stop expecting one tool to do everything and start building a toolkit instead.
The “One AI Fits All” Myth That’s Holding You Back
Here’s a simple analogy that might ruffle some feathers: sticking to just one AI model is like owning a kitchen with only a microwave. Sure, you can heat things up. You can even get creative with what you make. But you’re missing out on what magic can happen when you have the right tool for each job.
Recent research backs this up. A study from MIT Sloan found that only half of performance gains from using a more advanced AI model come from the model itself, and the other half? Well, it comes from how users adapt their approach. Simple translation – yes, the tool matters, but your strategy matters just as much.
Different AI models are trained on different data, built with different priorities, and excel at different tasks. ChatGPT tends to be conversational and versatile. Claude often produces more nuanced, naturally flowing prose. Gemini integrates beautifully with Google’s ecosystem. Perplexity excels at research with real-time citations. DeepSeek offers surprisingly strong results for technical tasks.
Same prompt. Different brains. Wildly different outputs.
But Won’t Using Multiple AIs Make Me Even MORE Overwhelmed?
I hear this concern constantly from small business owners, and honestly? It’s valid.
The AI landscape ecosystem feels like drinking from a fire hose. The last thing you need is another five tabs open, another three subscriptions to manage, and yet another learning curve to climb.
Here’s something to ponder, though. Using multiple AI models strategically isn’t about doing more. It’s about doing smarter. It’s about spending less time coaxing mediocre output from one tool and more time selecting brilliant output from several.
Think of it like this: you wouldn’t ask your accountant to design your logo. You wouldn’t ask your web developer to write your sales copy, and I hope you wouldn’t ask me to service your car (well, you might, but you’d regret it). Each expert brings something different to the table. AI models work the same way.
The trick isn’t to use every AI tool available. It’s to understand which tools complement each other and build a simple system that doesn’t require a PhD in prompt engineering to operate.
5 Ways You Can Use Multiple AI Models Without Losing Your Mind
1. Start With Your “Home Base” Model—Then Branch Out Intentionally
Pick one AI as your primary tool. This is your go-to, your daily driver, the one you know inside and out. For most small business owners, this is ChatGPT or Claude, simply because they’re accessible and capable.
But where it gets interesting once you’ve got your home base established, is identifying one or two specific scenarios where you’ll deliberately seek a second opinion. Maybe that’s whenever you’re writing something high-stakes (a pitch, a sales page, an important email). Maybe it’s when your primary AI gives you something that feels… off.
You’re not abandoning your main tool. You’re just building in strategic checkpoints where the fresh perspective of a different model genuinely adds value.
2. Assign Models to Their Strengths (Like Building a Dream Team)
Each AI has a personality. Once you recognise this, you can stop fighting against it and start leveraging it.
Based on extensive testing and real-world use, here’s a rough guide:
For capturing conversational, human-sounding brand voice: Claude tends to excel here. It picks up on subtle tone cues and produces prose that reads less like AI and more like a thoughtful human wrote it.
For structured tasks, lists, and technical explanations: ChatGPT handles these brilliantly. It follows instructions precisely and organises information logically.
For research-heavy content with citations: Perplexity pulls real-time information from the web and shows you exactly where it came from. Invaluable for fact-checking or content that needs current data.
For brainstorming and creative ideation: Try multiple models with the same prompt and cherry-pick the best ideas from each. This is where the “ensemble approach” genuinely shines.
You don’t need to memorise this list. Just notice patterns over time. Which AI consistently gives you results you love for which types of tasks? That’s your data. Use it.
Disclaimer: with models constantly releasing new versions, these aren’t ‘set and forget’ suggestions. If you’re serious about making the most of AI, my advice is to never stop playing and experimenting.
3. Use the “Blend and Polish” Method
This technique has transformed how I think about content creation, and it’s beautifully simple.
Start by generating a first draft from your primary AI. Then take the sections that feel weak, generic, or off-brand and feed them (along with specific guidance about what’s not working for you) into a second model.
For example: “This paragraph feels too formal for my brand voice. Can you rewrite it to sound warmer, more conversational, like you’re chatting with a friend over coffee?”
The second AI isn’t starting from scratch. It’s polishing. It’s adding what was missing. And because different models have different default “voices,” you’ll often get suggestions that genuinely surprise you.
The result? Content that’s stronger than what either AI would have produced alone.
4. Create a Simple “Which AI When” Cheat Sheet
Overwhelm often comes from decision fatigue. You’re staring at your screen, prompt half-written, wondering which of six AI tools you should paste it into.
Eliminate this friction by making a decision in advance. Create a simple reference document, nothing fancy needed, even a sticky note works, to map your regular tasks to specific tools.
Blog first drafts: Claude Email subject line variations: ChatGPT Social media captions: Try both, pick best Fact-checking statistics: Perplexity Rewriting something that sounds robotic: Claude
Your list will look different from mine. That’s the point.
Build it based on your experience, update it as you learn, and stop making the same decision fifty times a week.
5. Set a “Good Enough” Threshold (And Stick To It)
Here’s where perfectionism can derail you. The temptation with multiple AI models is to keep testing, keep comparing, keep searching for the perfect output.
It doesn’t exist. And chasing it will eat your time faster than any efficiency you’ve gained.
Instead, define what “good enough to edit” looks like for you. Maybe that’s content that captures 80% of your intended tone and gets the core message right. Maybe it’s output that needs fewer than 15 minutes of human polishing.
When you hit that threshold, from whichever AI model that gets you there, STOP prompting and START editing. The human layer is where your content becomes truly yours anyway. AI gets you to the starting line faster. You still run the race.
The Real Secret: You’re Still in Charge
Multiple AI models aren’t a complication. They’re options. And options, when you know how to use them, are power.
The overwhelm most people feel doesn’t come from having too many tools. It comes from not having a system. Follow the above five principles, and you’ll have the foundation of a flexible, practical approach that makes AI work harder so you don’t have to.
One AI might be enough for getting started. But if you want content that genuinely sounds like you, resonates with your audience, and doesn’t require three hours of rewriting? Building a small, strategic toolkit is the move.
Your brand voice is worth it. Your time is worth it. And honestly? Once you see what’s possible when different AI “brains” collaborate under your direction, you’ll wonder why you ever tried to make one tool do everything.
Ready to Build Your AI Toolkit?
If you’re tired of generic AI output and want content that actually sounds like your brand, I can help. Explore the Prompt Playbooks, they can be used to make every AI tool work harder for your business.
