Coding
Krutika P. B.
Feb, 2026
If Coding Advice Worked, We’d Have Fewer Bad Codebases.
The internet is full of coding advice.
“Always do X.”
“Never do Y.”
“Best practices you must follow.”
“Clean code rules every developer should know.”
And yet…
Codebases are fragile
Bugs keep repeating
Projects slow down as they grow
Developers feel stuck despite “doing everything right”
So here’s the uncomfortable truth:
Most coding advice is not wrong because it’s false.
It’s wrong because it’s incomplete.
Most popular coding advice has three problems:
Advice is often given as absolute rules, while software lives in trade-offs.
What works for:
A side project
A tutorial
A startup MVP
Can break horribly in:
Large teams
Long-lived systems
High-traffic applications
Context decides correctness — not rules.
Advice is simplified to be teachable:
Short examples
Clean scenarios
No legacy constraints
No deadlines
No business pressure
Real systems are messy.
Advice that works only in ideal conditions is theoretical, not practical.
Patterns are tools, not commandments.
But advice turns them into dogma:
“Always use microservices”
“Never repeat code”
“Always abstract early”
Engineering is about judgment, not obedience.
When developers follow advice without thinking:
They cargo-cult patterns
They add unnecessary abstractions
They optimize prematurely
They fear breaking “rules”
They stop reasoning independently
The result?
Code that looks “correct” but behaves poorly.
Duplication is sometimes cheaper than coupling.
Removing duplication too early often creates:
Hard-to-change abstractions
Shared code nobody fully understands
Ignoring performance completely is also a mistake.
Good engineers:
Design with performance in mind
Measure before optimizing
Avoid architectures that block scaling
New ≠ better for your problem.
Stability, team skill, ecosystem, and longevity matter more than hype.
Senior developers break rules consciously.
Junior developers break rules accidentally.
The difference is understanding consequences.
Good advice isn’t about what to do —
It’s about why it exists.
Instead of memorizing rules, engineers use:
Trade-off analysis
System thinking
Failure prediction
Change tolerance
Human readability
Mental models scale. Advice doesn’t.
Treat advice as:
A starting hypothesis
Not a final answer
Always ask:
What problem was this advice solving?
Does that problem exist here?
What does it cost me in this context?
Engineering begins where advice ends.
Bad software isn’t caused by ignoring advice.
It’s caused by following advice without thinking.
The goal isn’t to write rule-compliant code.
The goal is to build systems that survive change.