Summary
- AI can weaken your brain if overused
- The brain adapts to shortcuts: the more you delegate thinking, the less you do it
- Product skills like problem framing, discovery, and communication weaken without regular use
- Use AI as support, not a replacement
- Block time to think without tools
- Set team rules for responsible AI use
- Challenge your brain outside of work too
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Ever thought about the consequences AI could have on your brain?
A recent joint study by Microsoft and Carnegie Mellon found that people who use AI heavily are more likely to skip critical thinking. The more they trusted the tool, the less they questioned the output (Wang et al., 2025). Even more striking: according to an MIT research, people who relied on ChatGPT showed reduced activity in brain areas linked to reasoning when solving tasks (Lee et al., 2025).
This is becoming a real issue: when you start thinking with AI, your own muscles start to fade.
If you’re not intentional about how you use it, it can deteriorate the skills that make you valuable: critical thinking, creativity, or strategic vision.
How can product managers, designers, and product leaders protect their mental edge in the age of automation?
The product skills most at risk
Strategy and critical thinking
Good product strategy requires deep thinking, making informed decisions, comparing options, and understanding the underlying problems. But when AI gives you a ready-made strategy or suggests what to do next, it’s easy to just go with it without questioning it.
The result? You get a plan that looks fine, but you haven’t thought it through, dug into the problem, or explored different solutions. That’s where your thinking starts to weaken.
As Marty Cagan writes, “Product strategy is not about what you build, it’s about why you build.” And you can’t outsource the why.
“AI works well when you know what you want from it. It helps you go faster. But if you’re unclear, it won’t magically fix your thinking, it just speeds up the wrong work.” - Timoté Geimer, CEO @ dualoop
Problem framing is an excellent way to cultivate strategic and critical thinking. This initial phase involves crafting a clear problem statement, defining expected outcomes, delivering a minimal Product Initiative Document (PID), and identifying strategic fit and impacted metrics. Find our template here!
User research & discovery
While AI can summarise interview transcripts, cluster feedback, and more, it should never replace direct human interactions. Early customer conversations, especially, are critical for empathy, nuance, and to build real insights.
“Discovery is the practice of building insight, not collecting quotes.” - Timoté Geimer, CEO @ dualoop
AI is a generalisation mechanism which helps see patterns, but often loses the detail and nuance that make insights actionable.
Simply summarising feedback with AI isn’t the same as understanding it. AI can point you to common themes, but it hides the subtleties. If you don’t spend time in direct conversations, you lose the empathy and context that make discovery effective and you risk making decisions based on low signals.
We’ve put together a practical guide to structure interviews and get to what users really think! Grab your copy here.
Communication & collaboration
Product roles demand constant communication. AI tools might save time (writing emails, meeting notes, creating decks..), but they can also weaken your communication muscles.
If you never draft the message yourself, you never structure your thoughts. And in product work, that’s a key skill! You need to be able to convince people, align teams, and share a clear vision.
Design thinking & creativity
AI is great at generating ideas quickly and seamlessly. But if a team gets used to asking AI for design ideas or A/B test variations instead of brainstorming, it could short-circuit the creative process.
“One danger I see is jumping too fast into high-fidelity outputs using tools like Lovable or others. It skips the thinking. You may be testing usability when you think you’re testing value.” - Martin Crochelet, partner @ dualoop
Your creative muscles need practice to keep working correctly. Studies on earlier technologies illustrate this effect: for instance, heavy use of GPS navigation correlates with weakened spatial memory in drivers, and students who rely on autocorrect show poorer spelling and punctuation skills over time. More recently a 2025 MIT study recently warned of "semantic inertia," a phenomenon where users begin to rely on AI-suggested ideas rather than generating their own.
So sure, AI is convenient. But when technology does too much of the work, the brain adapts by doing less.
What cognitive offloading does to our brain
Science backs it up: when we get used to delegating the thinking part to external tools, our brains adapt by doing less. This is known as cognitive offloading, and even though it’s useful for simple tasks (like calculators), it becomes more problematic when we apply it to complex work.
The MIT study confirmed that using Chat GPT led to reduced activation in the brain’s fronto-parietal network, the very area linked to reasoning and problem-solving (Lee et al., 2025).
This is classic automation bias: our human tendency to trust a machine more than ourselves. In product work, it might look like blindly following an AI-generated A/B test insight, without asking whether it’s the right problem to solve from the start.
In the long term, the risk is deeper than just making bad decisions. Repeated offloading actually weakens the neural pathways we need for reasoning, judgment, and memory. If you stop using these mental muscles, they weaken, just like any other muscle.
“Use AI to challenge your thinking, not replace it. The real risk is not that AI gives you bad ideas, it’s that it makes you stop looking for better ones.” — Martin Crochelet, partner @ dualoop
5 practices to stay sharp with AI
The amazing news is that AI doesn’t need to make us less sharp. It can even be the best thought partner you’ve ever had when used right. But only if you stay in charge!
1. Adopt a stewardship mindset
“I try to own the outcome first, whether it’s the message, the problem, or the solution. Then I use AI to expand on it. In the past, I did it the other way around, and it led to bland, generic answers I couldn’t build on.” - Martin Crochelet, partner @ dualoop
AI should never be treated as the final voice in your work. Think of it as a junior collaborator that still needs your oversight. You’re the editor responsible for making sure that its work makes sense.
When AI gives you any output, review it and ask yourself: What assumptions are built into this? What’s missing from the reasoning? What would I change or challenge if this came from a colleague?
This simple mindset shift keeps your brain active, and pushes you to stay engaged with the thinking part rather than only the formatting.
💡 Ask the AI to challenge its own recommendation, then challenge it yourself. If you both spot the same weaknesses, that’s great. If you find things it didn’t, even better.
2. Block time to think without AI
Set aside time each week to solve a problem without using AI. It could be something simple, like sketching a roadmap on a whiteboard, manually analysing user feedback, or drafting a strategy document from scratch.
MIT researchers call this “cognitive resistance:” actively choosing not to rely on AI even when it’s available, to protect your judgment over time .
Like any skill, your ability to think needs regular training. For example, pilots are required to fly manually from time to time so they don’t forget the core mechanics of flying. The same principle applies to product managers: if you always lean on AI, your core PM skills will become weaker over time.
As Shreyas Doshi puts it, “The best PMs aren’t the ones who delegate fastest, they’re the ones who still know how to think.” And this kind of thinking can only stay sharp if you practise it!
💡 Tip: write the structure first, by hand or in bullet points. Once you’re clear on the thinking part, bring in AI to refine it. That way, you’re keeping your brain at the centre of the process.
3. Strengthen the way you think
Even if AI can give you answers, your added value is still the understanding you built by learning your domain, going deep into customer behaviour, mastering what you do, and reflecting on your own experience.
The more context and expertise you bring to the table, the more value you’ll get from AI, and the better you’ll spot gaps, inaccuracies, or incorrect thinking in the outputs. Reading industry frameworks, studying past product decisions, talking to users regularly, and running experiments allow you to build what AI can’t replace.
💡 Tip: every time AI gives you an output, pause and ask yourself, “Would I have arrived at the same conclusion on my own? If not, why?” Let that gap guide what you still need to learn.
4. Create AI guidelines
If you’re not careful, AI use can quickly become invisible and everyone stops asking how they’re used or what standards should apply.
To avoid this, teams can create clear guidelines to define how and when AI is used. What kind of work can be AI-assisted? What always needs a human in the loop? What outputs must be reviewed, validated, or cross-checked ?
AI will amplify whatever system you already have. If your teams already lack focus or clear goals, AI won’t fix it, but will just produce more clutter, and faster. That’s why AI guidelines only work when paired with clear product practices and leadership alignment.
At dualoop, we regularly coach teams to implement norms as part of broader product transformations, aligning discovery, strategy, and delivery practices. 👉 Learn more about how we can help
5. Bonus: Keep your brain active outside of work
Your brain needs variety and challenge. Activities like reading books, learning a new language, playing strategy games, or even doing mental math are mental workouts that help strengthen focus, memory, and problem-solving.
These habits are essential when a big part of your day involves AI-assisted tasks. They balance it out by forcing your brain to stay active and engaged.
According to Dr. Ann McKee’s research on aging brains, those who regularly challenge their minds can build up a “reserve” that helps them stay sharp longer, even as they age. In other words, every time you choose to think for yourself when it’d be easier not to, you’re investing in your brain’s long-term vitality.
Conclusion: Stay sharp to stay in control
AI is a powerful tool, but only if you use it intentionally. Product work takes mental effort! If you let AI do all the work for you, you lose the habit of doing it yourself and your valuable skills might fade. So use AI, but make sure to build the right habits to protect your judgment and creativity.
This means:
- Thinking before prompting
- Challenging what AI gives you
- Practicing deep thinking
- Learning your craft continuously
- Creating clear rules for AI use
- Keeping your brain challenged outside of work
So stay intentional, curious, and most of all, stay sharp!
Whether you’re scaling your product org or redefining how teams work with AI, we can help. 👉 Let’s talk
References & sources
Wang, Y. et al. (2025) – The Impact of Generative AI on Critical Thinking. Microsoft Research & Carnegie Mellon University
Lee, H. et al. (2025) – Your Brain on ChatGPT: Accumulation of Cognitive Debt when Using an AI Assistant for Essay Writing Task. MIT
Dr. Ann McKee – Cognitive Reserve Research
Interviews with Martin Crochelet & Timoté Geimer
Marty Cagan – Empowered and Inspired
Shreyas Doshi – @shreyas on X
dualoop training material and frameworks
