Stop Looking for the Right Answer—Find the ‘Minimally Wrong’ One
Engineers love optimization. We want the best solution—the one that scales beautifully, never fails, and earns us nods of approval from the smartest people in the room.
Let me guess: You’re stuck on a decision. Maybe it’s about picking the right architecture for a new service. Maybe it’s about whether to refactor that godforsaken legacy system or leave it alone. Maybe it’s about your own career—should you jump to that shiny new role or stay put?
And here you are, looking for the right answer.
Here’s the bad news: You won’t find it. Because it doesn’t exist.
The Myth of the Right Answer
Engineers love optimization. We want the best solution—the one that scales beautifully, never fails, and earns us nods of approval from the smartest people in the room. But here’s the thing: in complex systems (and in life), the perfectanswer is an illusion.
The world doesn’t give you binary outcomes like “correct” and “incorrect.” It gives you trade-offs. Every decision is a balancing act between constraints, risks, and unknowns. And while you’re waiting for the right answer to reveal itself, someone else is making progress with a good enough answer.
This obsession with perfection has a hidden cost: delayed execution. The longer you sit in analysis paralysis, the more opportunities you lose. Meanwhile, the person who made a decision—flawed as it might be—is already iterating, learning, and improving.
The Power of Being ‘Minimally Wrong’
Instead of hunting for the best choice, shift your mindset: Your goal isn’t to be right. Your goal is to be the least wrong.
Think about it. The best decisions aren’t about nailing perfection; they’re about making the choice that is the least painful, the least disruptive, and the easiest to correct if things go sideways.
Can’t decide between two database solutions? Pick the one that’s easiest to migrate away from.
Debating between speed and reliability? Choose the one that leaves you an escape hatch if reliability becomes an issue.
Wondering if you should leave your job? Which option has the lowest downside if you’re wrong?
This is how experienced engineers, great leaders, and successful investors think. They don’t obsess over getting things right—they focus on limiting how wrong they could be.
This mindset shift is critical because the biggest risk in decision-making isn’t being wrong—it’s being too slow to realize it. When you optimize for being minimally wrong, you create decisions that allow for adjustments. You move forward knowing that if things don’t work out, you can pivot quickly.
Why This Works in Real Life
Let’s take an example. Say you’re tasked with building a new service that needs to handle high throughput. You’re debating whether to go all-in on a fancy new distributed system or keep things simple with a monolith.
The engineer searching for the right answer will get stuck. They’ll spend weeks reading whitepapers, debating pros and cons, and waiting for some epiphany.
The engineer aiming to be minimally wrong? They’ll ask:
What’s the worst thing that happens if we go monolith and later regret it?
What’s the worst thing that happens if we go distributed and later regret it?
Which decision has a more reversible failure mode?
Maybe they realize that starting with a monolith and extracting services later is the least painful path. Not because it’s right, but because it’s the easiest to course-correct.
This doesn’t just apply to technical decisions—it applies to careers, product strategies, and even hiring decisions.
A Mental Model: Option Value
A useful framework for making decisions this way is option value. In finance, options are valuable because they allow you to make a choice later without committing everything upfront. The same applies to engineering and career decisions.
When choosing a technology stack, prioritize flexibility over the newest trend. Future-proofing is about adaptability, not clairvoyance.
When structuring a team, keep roles fluid. A rigid org chart might look good on paper but will break under real-world pressure.
When negotiating a job offer, optimize for leverage—such as remote flexibility, growth opportunities, or an escape route—rather than just salary.
The more optionality you build into your choices, the more room you have to be less wrong in the long run.
Applying ‘Minimally Wrong’ Thinking to Your Job Search
Many engineers overthink job changes, waiting for the perfect opportunity that checks every box. The problem? It doesn’t exist.
If you treat your career decisions like picking the “right” technology stack, you’ll get stuck endlessly comparing options while others make moves, gain experience, and open doors you never even considered.
Instead, apply the minimally wrong mindset:
Should you stay or go? Ask which option has a lower downside. If you leave and it doesn’t work out, can you recover easily? If you stay, are you missing out on learning opportunities?
Picking between two offers? Instead of agonizing over every detail, ask: Which job keeps my options open? A role that expands your skills and network is often better than one with just a slightly better salary.
Worried about a job title mismatch? Focus on what it enables, not just what it is. A step sideways or even down on paper can lead to a much bigger leap in a year or two.
Not sure about a company’s future? Join if it gives you high agency and visibility. The worst-case scenario isn’t failure—it’s stagnation.
Most bad career decisions aren’t irreversible. The real risk is standing still while others make imperfect but directional moves.
The Takeaway: Bias Toward Action
The biggest trap in decision-making is paralysis—getting stuck because you’re afraid of making the wrong choice. The trick is to recognize that every choice is wrong to some degree. Your job is to pick the one that’s easiest to survive.
So the next time you’re debating a decision, stop asking “What’s right?” and start asking “What’s the least wrong move I can make right now?”
You’ll move faster. You’ll learn more. And you’ll make better decisions—not because you got them right, but because you left yourself room to be wrong.
And that’s how you actually win.