In design work, you cannot simply ignore errors and hope they won’t become an issue later. They tend to remain unnoticed until the precise moment they become critical.
A well-known example of this is the positive scram effect in RBMK reactors. The shutdown system is intended to reduce reactivity, but under certain conditions, inserting the control rods temporarily increased reactivity instead. This phenomenon wasn’t unknown; however, it was left unaddressed, accepted, and worked around rather than fully resolved. The likelihood of such conditions arising was considered unrealistic, as it was believed that the power would never peak at the bottom 30 cm of the core.
On April 26, 1986, it did peak. This highlights the nature of design errors: they don’t have to be active all the time; they just need the right combination of circumstances to cause problems.
If something is wrong, do not just move on. You must isolate it, understand it, and fix it properly—even if it doesn’t seem strictly necessary at the time. Not because it will always lead to issues, but because one day it might.
Good engineering, in part, means refusing to leave loose ends unresolved.
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Engineers should still know how to use a slide rule, not out of nostalgia, but as a discipline.
I carried one for as long as I could. While a slide rule shouldn’t be an everyday tool, it should be a part of every engineer’s training.
Using a slide rule prevents you from hiding behind digits. You have to estimate the magnitude before you even begin your calculations. If you don’t know whether the answer is 30 or 3,000, you’re not ready to calculate.
This habit of estimating first could eliminate a surprising number of engineering errors.
A slide rule also encourages you to think in terms of relationships instead of just numbers. Multiplication, division, and powers are represented as distances on a scale. You begin to understand how different factors scale—such as flow versus pressure, temperature versus density, and power versus reactivity. That is where true understanding comes from.
Additionally, a slide rule enforces precision with three significant digits—no more. This constraint prompts you to evaluate whether the inputs or even the model justify anything beyond that. Most of the time, they don’t.
Modern tools can provide answers with twelve digits but rarely indicate whether those digits are meaningful.
Using a slide rule means you are involved in every step: choosing the scale, placing the decimal, and interpreting the result. You remain in control.
When the model deviates, when the system behaves unexpectedly, or when the numbers seem “fine” but something feels off, you revert to that mindset: estimate, perform a sanity check, and rebuild from first principles.
That’s engineering—not simply generating numbers, but knowing when those numbers make sense.
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The simpler it looks, the more design work it takes.
Simplification isn’t cutting corners - it’s designing better to get rid of excess complexity. Putting more effort into planning, not less.
Ideally, you don’t see any of the effort when looking at the final product. But it is there.
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Copying an idea is easy. Transplanting it, however, is not.
Every idea is built on a series of assumptions. These assumptions can relate to various factors, including physics, user behavior, constraints, and potential failure modes.
Many of these assumptions remain invisible, operating in the background to make the idea functional. When you attempt to copy an idea without fully understanding these underlying assumptions, you are not truly replicating the idea; you are merely copying its surface. And the surface is the least significant aspect.
An idea works because certain things are true. Change those, and it becomes something else.
Changing any of these factors can result in the idea behaving very differently. Sometimes it degrades, sometimes it fails, and at times it may even become dangerous.
Engineering history is filled with instances where a solution that was “proven” effective in one scenario failed when applied elsewhere. This often occurs not because the idea itself was flawed but because the original assumptions did not transfer successfully.
This tendency is particularly tempting with elegant solutions. When something appears clean, simple, and efficient, the instinct is to reuse it. However, elegance is often conditional, depending on a very specific environment where trade-offs were carefully balanced. Move that solution to a different context, and the balance can be disrupted.
To truly understand an idea, you must ask:
What must be true for this to work?
What underlying factors were silently relied upon?
What was intentionally overlooked?
What is likely to fail first if conditions change?
If you cannot answer these questions, you do not fully understand the idea. Without that understanding, you cannot safely reuse it. You are no longer engaging in engineering; you are simply hoping for success.
Good design is not about copying solutions. It is about comprehending why those solutions worked and then purposefully determining whether those reasons still apply in a new context.