Lateral Thinking

I have always liked people who can look at a problem from a different perspective.

Not because they are trying to be clever or impress anyone. But because sometimes the obvious path is not hard because the problem is difficult. It is hard because we are stuck in the habit of looking at it the same way.

That is what lateral thinking feels like to me. It is not random brainstorming, and it is not just “thinking outside the box,” which has become one of those phrases people use when they want to sound creative without saying anything useful. Lateral thinking is what happens when you stop asking, “How do I solve this?” and start asking, “Am I even looking at the right problem?”

Edward de Bono, who popularized the term, put it well: “It is not the ideas we do not have that block our thinking but the ideas we already have.” I think that is exactly right.

The real enemy is not ignorance. It is the first decent answer that makes us stop looking.

There is an old concept in psychology called the Einstellung effect. The idea is simple: once you have seen one solution work, your brain wants to keep reusing it, even when a better or simpler solution is sitting right there. Abraham Luchins showed this in the 1940s with his famous water jar experiments. People learned a more complicated method to solve a series of problems, and then kept using it even when later problems could be solved much more easily.

That feels uncomfortably familiar.

You see it in engineering all the time. A team solves a scaling problem with a queue, so now every problem somehow becomes a queue problem. Somebody had success with microservices, so now even a toy internal tool needs service discovery, tracing, retries, and a small religion around it. Or the reverse: a company got burned by too much architecture once, and now refuses to separate anything ever again. Same pattern. Old answer, new question.

And of course this happens outside software too. In management, relationships, health, parenting, money, and life in general, people often keep applying a once-useful pattern long after the context has changed.

This is why lateral thinking matters. It gives you a chance to escape your own momentum.

I do not think lateral thinking means rejecting logic. It means delaying commitment. It means resisting the urge to lock onto the first plausible frame. Sometimes the useful move is not more analysis. Sometimes it is a forced change in perspective.

A good example is analogical thinking. Some of the best ideas do not come from drilling deeper into the same domain, but from importing a pattern from somewhere else entirely. That is one reason broad curiosity pays off. If you only read one kind of thing, work on one kind of system, and talk to one kind of person, your idea graph gets pretty small.

There is some interesting research here too. The classic work by Gick and Holyoak showed that people often fail to apply a useful analogy unless they are nudged to notice the structural similarity. More recently, a 2025 paper in the Journal of Sleep Research found that a short afternoon nap improved analogical transfer in problem solving. The nap group became better at seeing the hidden commonality between previously learned source problems and new target problems. That is fascinating. Sometimes the brain needs less forcing and more space.

That also matches my experience. I have had more than a few situations where the answer only became obvious after I stopped attacking the problem head-on. Go for a walk. Take a shower. Sleep on it. Work on something else. Then suddenly the problem changes shape.

That does not mean the answer came from magic. It probably means my brain finally stopped hammering the same groove.

Another thing I find interesting is that constraints often help lateral thinking instead of hurting it. That sounds backwards at first. We usually imagine creativity as infinite freedom. But total freedom often produces mush. A constraint gives your brain something to push against.

No budget. No new headcount. No third-party services. No new dependencies. Must be understandable by a non-technical audience. Must fit on one screen. Must work with what we already have.

Those kinds of limits can force better questions. If the obvious solution is no longer available, you are more likely to find a different one.

This is one of the reasons I enjoy working with AI coding agents right now. They are useful not just because they can write code quickly, but because they are willing to explore paths I might not have considered. If I tell the model exactly what to do, I usually get a competent implementation of my current thinking. If instead I ask, “What are three completely different ways to solve this?” I sometimes get something better.

Not always, of course. Models can be bland, overcomplicated, or confidently wrong. But they are very good at one thing: producing alternative framings cheaply. That is surprisingly valuable.

It is almost like having a machine whose main job is to help you escape the Einstellung effect.

Almost.

The real trick is not outsourcing thinking. It is using the tool to widen the search space before you collapse it again.

This is also why I think good questions matter so much. Lateral thinking is often less about generating exotic answers and more about generating better questions:

• What if the opposite were true?
• What would this look like if it had to be ten times simpler?
• What if we removed the feature instead of improving it?
• What if the real customer is not who we think it is?
• What if the bottleneck is social, not technical?
• What if the thing we are optimizing should not exist at all?

That last one is one of my favorites.

A lot of smart people are very good at optimizing within a frame they never should have accepted in the first place. They become world-class at digging the wrong hole.

De Bono had another line I like: “The mind can only see what it is prepared to see.” That is both the problem and the opportunity. If you want better answers, you sometimes need to prepare your mind to notice different categories of answer.

Read outside your field. Talk to people who solve different kinds of problems. Ask for more than one approach. Introduce artificial constraints. Leave things unresolved for a while. Be suspicious of the first answer that feels satisfying.

And maybe most importantly: notice when your expertise is turning into a trap.

Experience is useful, obviously. I am not arguing for naive novelty. But expertise has a dark side. Once you have solved enough problems, it becomes very easy to assume you already know what kind of problem this is.

Sometimes you do.

Sometimes you really, really do not.

That, to me, is the point of lateral thinking. Not being quirky. Not being contrarian for sport. Just staying flexible long enough to let a better path appear.

Because every now and then, the best way forward is sideways.