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👋 The 12 practical software engineering concepts that will make you a better developer
Software jargon causing confusion? Learn 12 key engineering terms to boost understanding, improve team communication, & prevent project pitfalls.
FRAN SOTO
JUN 22

 




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Software engineering is full of jargon: quirky phrases, metaphors, and shorthand terms that carry deep meaning for those in the know.

While they make communication faster among engineers, they can also become a wall between teams when misunderstood.

This disconnect can cause confusion between engineers and nontechnical stakeholders, leading to misaligned expectations, missed risks, and wasted effort.

In this post, you’ll learn 12 terms frequently used by software engineers. Let me know how many did you know already!

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🧠 #1 Premature optimization

Premature optimization is the act of trying to make code faster or more efficient before the actual bottlenecks are known.

Premature optimization is the root of all evil, so to start this project I'd better come up with a system that can determine whether a possible optimization is premature or not.
Why it matters: It leads to wasted time and complexity in areas that might not even be performance-sensitive.

Practical explanation: A developer might write complicated logic to optimize disk I/O before knowing if disk access is even a bottleneck.

Optimizing too early adds code that’s harder to read and maintain. It slows the team down when actual performance issues appear.

🪣 #2 Yak shaving

Yak shaving is doing a chain of small, seemingly unrelated tasks that are needed to reach your main goal.

What is yak shaving and what does it mean example: someone looks on confused as another explains the convoluted story which led to them sitting there shaving a yak, just like solving problems in software development
Why it matters: It can waste hours if you lose sight of your original goal while chasing dependent problems.

Practical explanation: You try to fix a CSS bug, but first you update dependencies, which breaks a build, which leads you to a new CI setup.

Yak shaving hides real progress. It makes task estimates unreliable and leads to frustration.

🧽 #3 Rubber duck debugging

Rubber duck debugging is the process of explaining your code to someone else or even an inanimate object to help yourself understand it better.


source
Why it matters: It helps catch bugs and improve understanding by forcing clarity.

Practical explanation: A developer talks through a function line by line and suddenly sees a condition that never gets triggered.

This technique works because most bugs are logic errors that reveal themselves when you slow down and articulate your assumptions.

🧱 #4 Technical debt

Technical debt is the extra cost of choosing easier, short-term solutions instead of better, long-term ones.

Tech Debt
source
Why it matters: It makes future changes harder, slower, and riskier.

Practical explanation: Skipping test coverage or hardcoding values to ship faster can later require painful refactors.

When unmanaged, technical debt compounds. It reduces a team's ability to move fast.

🧩 #5 Scope creep

Scope creep is the uncontrolled expansion of a project's goals or features over time.


source
Why it matters: It delays delivery, burns out teams, and makes products harder to maintain.

Practical explanation: A client asks for “just one more feature” every sprint, eventually doubling the original scope.

Clear requirements and versioning help avoid this problem. Without them, teams keep building without knowing when they're done.

🔥 #6 Shotgun debugging

Shotgun debugging is trying many random changes to fix a bug without understanding its cause.

Debugging | code-memes, debugging-memes, bug-memes, debug-memes | ProgrammerHumor.io
source
Why it matters: It leads to fragile fixes that often break in new ways.

Practical explanation: You comment out blocks of code until the crash goes away, then hope the app still works.

It’s reactive and can cause hidden side effects. This is especially true in complex systems.

🚌 #7 Bus factor

The bus factor is the number of people who need to disappear, for example by getting hit by a bus, before a project is in serious trouble.

The bus factor summary - A poor soul squashed by a bus lamented because they were the only one who knew the password
source
Why it matters: Low bus factors mean critical knowledge is siloed. That’s a serious risk.

Practical explanation: If one person owns deploys and they go on vacation, releases stop.

Documentation, pairing, and rotation raise the bus factor. They reduce operational risk.

🧰 #8 Gold plating

Gold plating is adding features or polish that weren’t asked for and don’t add value.

Communicate and approve with the client before making changes
source
Why it matters: It wastes time and adds risk without user benefit.

Practical explanation: An engineer builds a settings page with animations and themes when users just needed toggles.

Polishing things no one requested can create bugs. It also complicates maintenance.

🌊 #9 Boiling the ocean

Boiling the ocean is trying to solve a massive, vague problem all at once.


Why it matters: These efforts rarely finish. Teams burn time with little to show.

Practical explanation: A team tries to fix the whole analytics stack instead of solving one reporting issue.

Focusing on small, valuable wins keeps momentum. It builds confidence and delivers value.

🧪 #10 Cargo cult programming

Cargo cult programming is copying code or patterns without understanding why they work.

The Arcane Art Of Copy-Paste Programming
source
Why it matters: It leads to brittle, bloated systems full of unnecessary abstractions.

Practical explanation: A junior engineer copies a Redux setup into a simple form app because that’s what good apps do.

It creates confusion, slows debugging, and misuses tools.

🛠 #11 Trunk-based development

Trunk-based development is a strategy where all engineers commit to the main branch frequently.


source
Why it matters: It reduces merge conflicts and keeps integration issues small.

Practical explanation: A team commits code multiple times a day behind feature flags and runs automated tests on every push.

It works best with CI pipelines. It encourages small, reversible changes.

💣 #12 Second-system effect

The second-system effect is the tendency to overengineer the second version of a system.

Image
Source: The mythical man month
Why it matters: It wastes effort and builds complexity based on ambition, not needs.

Practical explanation: The first version of a chat app was simple and successful. The second tries to add video, payments, and bots from day one.

The result is often a bloated, delayed system. It loses the simplicity users liked.

🎯 Conclusion

Understanding this jargon isn’t about sounding smart, but about speaking the same language.

Whether you’re an engineer trying to explain trade-offs or a product manager trying to follow technical conversations, these terms help surface real engineering challenges quickly.

Knowing them means better teamwork, faster decisions, and fewer surprises down the road.

How many did you know already?

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👏 Weekly applause

These are some great articles I’ve read last week:

Why Perfectionism Isn't Perfect by Daniil Shykhov. It's important for engineers to recognize the difference between striving for excellence and being paralyzed by perfectionism, as the latter can hinder productivity and mental well-being.
Key Topics to Learn API Development by Saurabh Dashora . Learning API development is essential for modern software engineers, covering fundamentals, requests/responses, security, design, testing, and deployment.
How Dropbox Optimizes Search by Byte-Sized Design . Understanding how Dropbox optimizes search across various media types provides good insights into building efficient indexing and retrieval systems in software engineering.
Ace Your Next JavaScript Interview: this, new, Prototypes, Classes (Part 3) ✨ by Petar Ivanov. Understanding the nuances of this, the new keyword, prototypes, and classes in JavaScript is crucial for acing interviews and improving your coding skills.
Concurrency Is Not Parallelism 🔥 by Neo Kim . Concurrency is about structuring tasks to enable parallelism, enhancing system efficiency and responsiveness.

🙏 One last thing before you go:

I am always working to make this newsletter even better.

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See you in the next email,

Fran.
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