If you have ever met me in person, you know that when you share an idea with me, I simplify it to its core and reflect it back to you, focusing on its essential parts.
I dissect each statement for precision. “What do you mean by this word?”

I have two decades of experience working with academics who overcomplicate everything. Humans are easily confused. A project proposal with ten moving parts and five objectives is overwhelming. Most people cannot think it through critically, which can lead to disaster.

By instinct, I simplify problems as my first step, reducing them to their “minimum viable product,” as they say in Silicon Valley.

Some people avoid simplicity to sound smarter. They won't admit it, maybe not even to themselves, but that's what they are thinking: “Oh no! I’m not doing this simple thing; my work is much more sophisticated.”

That’s a terrible idea. Even simple projects become challenging if you are ambitious. There is no need to complexify them. For example, seven years ago, we aimed to create a JSON parser faster than anything on the market—a simple idea. A senior colleague in computer science saw me at a campus coffee shop while I was working. He asked what I was busy doing... When I told him, “We’re writing a fast JSON parser,” he laughed. He would later admit that he thought I was joking: how could I work on something so mundane. I wasn’t kidding. The result was simdjson, a JSON parser four times faster than anything else at the time. By keeping our project conceptually simple, we made success easier.
Complexity is a burden, not a badge of pride.

Clear thinking demands precision.

People use emotionally charged words like “safe.” “My car is safe.” “My software is safe.” What does that mean? Define it precisely.

A graduate student of mine recently proposed reducing the cognitive load of agentic AI on developers. “Cognitive load” sounds great—thousands of papers discuss it—but what does it mean? How do measure it?

Take “AI” as another example. Nobody knows what AI is. Is a Google search AI? Is image search AI? Is an expert system AI? Or do you mean large language models? Clarify what you mean.
Too often, we accidentally hide behind overly abstract language. Not only does this harm how we think, but it also harms how we are perceived. People who avoid jargon are viewed as more honest, trustworthy and benevolent (Fick et al. 2025).
Your motivation should be clear from the start. Here is an example. I am often asked: “Should I go to graduate school?” What’s the motivation? Often, it’s to get a great job. Years ago, I had this conversation with a research assistant:

- Should I get a Master’s degree? Everyone with good grades does it.
- What is your objective?
- I want a good, well-paying job.

Given his exceptional technical skills, I told him he could already land that job soon. He did, and now he’s in a leadership role at one of Montreal’s top companies. He is outearning me by a wide margin, no doubt.

People often lose sight of their motivation and follow trends. Reconnect with your motivation and adjust your means accordingly.
To sum up, my advice for clear thinking:

- Simplify projects to their essentials early and often.
- Use precise language. Avoid jargon.
- Focus on your motivation first, then choose the appropriate means.
