The techniques that boost your ideation, and make AI brainstorming better too
The one thing crazy 8s is missing
In the last post, we talked about the fundamentals of brainstorming, the principles that still matter, whether you’re using AI or not. In this one, we’ll get into practical techniques you can use to generate a lot of ideas. These same techniques can also make AI more useful when you bring it into the process.
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The advice to make ideation less intimidating, “don’t worry if your ideas aren’t great, just focus on quantity, let your creativity flow,” sounds good in theory. But honestly, it’s not always enough.
There’s something about a blank sheet of paper or a sticky note that can still feel paralyzing. The pressure is real.
Even well-known methods like Crazy 8s don’t always help.
You fold a piece of paper into 8 sections and sketch one idea per section in 8 minutes. 1 minute per idea. It’s just a gimmick after all. A nice way to say: produce a lot of ideas, fast. Go for quantity, don’t overthink. But still, I’ve seen empty sections. People say they feel stuck.
So, what actually helps?
For me, it’s scaffolding. It’s prompts, provocations, or guidance that help us think, reflect, and move away from our default patterns.
I tend to default to practical ideas that take the least effort to get the job done. Having scaffolds is helpful for me, they give me a stepping stone to push past that default. Think of them like a stool that helps you reach the top shelf, just enough lift to explore other ideas.
Here is one example, if you’re ideating solutions for a project on managing personal carbon offsets, a scaffold could be something like, ‘What ideas could I borrow from other fields, like finance or healthcare?’
Some of my other go-to scaffolds:
What if I flipped my thinking? What if the idea came from a complete opposite of my assumptions? If I assume a homepage needs to be compact and packed with immediate information, why not flip it? What if the home screen were spacious and expressive instead?
What other kind of value could this create? Or what if this weren’t about [x], but about [y]?” This kind of prompt helps me rethink what a solution is really for.
For example, what if managing personal carbon offsets wasn’t just about tracking your own impact? What if it could foster shared responsibility?
Scaffolding act like containers. They give you a frame to explore. They set boundaries for exploration without prescribing the ideas.
Use these scaffolds to generate ideas
Here are a few I keep coming back to:
Add constraints: How might we design this if the user could only use [e.g. one hand / no internet / one minute]?
Reframe value: What if this wasn’t about [x], but about [y]?
Flip the standard: What if we did the opposite of what’s standard here?
Borrow: Who’s solved a similar problem elsewhere and what could we learn or adapt?
Remix: What if we combined [x] with [y]?
Remove a default: What’s one idea if we couldn’t rely on [x]?
Focus on user state: What’s one idea that helps when the user is [ e.g. rushed / uncertain / overloaded]?
Most of the time, just one or two scaffolds is enough to help me diverge and open up new ideas.
Use your ideas as springboards to generate more ideas
Sometimes I use another technique where I treat the ideas I’ve already come up with as a starting point to go further, like:
SCAMPER
SCAMPER can help you come up with new ideas by changing something that already exists:
Substitute: What can I replace or swap out?
Combine: What ideas or elements could I merge?
Adapt: What can I tweak or borrow from a different context?
Modify: What if I exaggerate, minimize, or change part of it?
Put to another use: How else could this be used?
Eliminate: What can I remove or simplify?
Reverse: What if I flip the order or do the opposite?
Let’s try with an example. You have an idea for creating a carbon passport, a personal travel log that tracks your carbon emissions.
Combine → What if we include gamification, like badges, streaks, or levels?
Substitute → Substitute carbon units and logging with symbolic visuals, like stamps that reflect your impact or milestones.
Map into a spectrum or 2x2 matrix
Start with a specific idea, then abstract it. What’s the broader concept or principle behind it? From there, explore what lives on the opposite end. Stretch the idea by applying contrast or tension.
For example:
Passive tracking ↔ Active engagement
One end is passive tracking, a system that logs carbon data automatically.
The other end is manual input, where the user tags or logs each trip themselves.
When you come up with two spectrums, try combine them into a 2x2 matrix. Explore how two tensions interact and gives more interesting ideas.
Example axes:
Passive tracking ↔ Active engagement
Subtle feedback ↔ Loud recognition
They give you four distinct behaviors: Passive + Subtle, Active + Loud, Passive + Loud, and Active + Subtle. Try to think of at least one idea for each quadrant. For example: what might it look like if it tracks passively but delivers loud recognition?
Why these techniques make brainstorming with AI more effective
AI is truly promising to help us generate ideas, a lot and fast. Try it yourself: ask for 100 ideas, and it’ll deliver in seconds. There’s no way we can match that speed.
In fact, a study in Nature Human Behaviour showed that while ChatGPT can help generate ideas, it actually narrows the range of ideas.
In one experiment, people were asked to come up with a toy using just a brick and a fan. Those who used ChatGPT gave very similar answers, 94% of the ideas had the same core concept. Nine people even named their toy the same thing.
But people who used their own ideas, or looked things up on the web, came up with completely different and unique toys.
Across five different tests, the same thing happened. ChatGPT helped people come up with more ideas, but those ideas were often too similar to each other.
I saw this happen myself during a university project, my friend and I came up with similar ideas using ChatGPT. We hadn’t even told each other we were using AI. It felt like we were thinking along the same lines, but in reality, AI silently gave us the same generic ideas.
What we can do instead…
Mix human brainstorming with AI. Don’t rely on AI alone, start with your own ideas, then use AI to build on them, explore new directions, or the other way around.
Bring in multiple sources. Combine AI suggestions with web research and personal insights.
Use chain-of-thought prompting. Use AI step-by-step to generate ideas. Instead of prompting “What are 5 ideas for [x]?”, have multi-turn prompts, for example:
Chat 1 (Restating challenge): “I'm working on [insert context], and the core problem or goal is [insert goal]. Restate the challenge in your own words to clarify what’s truly at stake and why it matters.”
Chat 2 (Exploring options): “Let’s diverge: generate 25 distinct ideas I could explore around this challenge.”
Chat 3 (Expanding with structure): Pick one idea and ask follow-up prompt like, “Use SCAMPER to further diverge and expand on [this idea].”
In one experiment focused on generating low-cost product ideas for college students, Chain-of-Thought prompting led to a 27% increase in unique ideas compared to basic prompting. This step-by-step method also brought AI’s output significantly closer to the diversity level of ideas produced by real human groups.
This is where scaffolding techniques come in. Follow up with prompts that guide thinking, for example, ask “What ideas could I borrow from finance?” or apply SCAMPER to substitute, eliminate, or shift the angle. The goal is to mix in your own reasoning and steer the AI step by step using chain-of-thought prompting.
Do you have any techniques or prompts that you rely on for brainstorming, whether with AI or on your own?
Have you found that using AI narrows your ideas, or has it helped you discover something new?
I’d love to hear what works for you. Share your thoughts or your favorite brainstorming methods in the comments.
Until next week,
Thomas
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