I’ve been writing code long enough to remember when Stack Overflow didn’t exist.
If you didn’t know something, you read documentation.
If documentation didn’t help, you experimented.
If experimentation failed, you suffered.
That suffering built something juniors today are rarely allowed to build:
Debugging instincts.
After mentoring 37 junior developers over the last decade, I’ve noticed a pattern.
They are not lazy.
They are not stupid.
They are not entitled.
They are overwhelmed in a world that looks simple on YouTube.
The Tutorial Illusion
Junior developers today grow up in a golden age of content.
There are:
- 10-hour React courses
- 5-minute “Build Netflix Clone” videos
- AI that writes code faster than they can think
- Repos with 50k stars
Everything looks clean.
But production code is not a tutorial.
In tutorials:
npm install
npm start
✨ It works.
In real life:
- Dependency conflict.
- Environment mismatch.
- CI failing.
- Docker won’t build.
- Someone hardcoded credentials in 2019.
- Nobody knows why it works.
- Nobody wants to touch it.
And that’s their first job.
Mistake #1: They Optimize Before They Understand
Junior:
“Should we microservice this?”
Senior (internally):
You haven’t shipped a monolith yet.
They’ve read about:
- Distributed systems
- Event-driven architecture
- CQRS
- Serverless
- Kubernetes
But they haven’t felt:
- A 2AM production bug
- A memory leak that slowly kills a server
- The fear of deleting a line of legacy code
Architecture is trauma-informed design.
You earn it through pain.
Mistake #2: They Think Senior Devs Are Faster
They see a senior fix a bug in 10 minutes.
What they don’t see:
- The 10 years of pattern recognition.
- The 200 similar bugs already debugged.
- The instinct to check logs first.
- The refusal to guess.
Senior developers aren’t faster typists.
We just know where the bodies are buried.
Mistake #3: They Confuse Productivity With Output
Junior mindset:
“I wrote 600 lines today.”
Senior mindset:
“I deleted 800 lines today.”
The most valuable code I’ve written in my career was the code I removed.
Junior devs want to prove themselves by building.
Senior devs prove themselves by simplifying.
The Real Problem: Nobody Teaches Them How to Think
We teach:
- Syntax
- Frameworks
- Tools
- Patterns
We rarely teach:
- How to debug systematically
- How to read legacy code without panic
- How to ask good questions
- How to sit with confusion without quitting
The biggest shift from junior to senior is not technical.
It’s emotional regulation.
Can you stay calm when nothing works?
Can you admit you don’t know?
Can you resist rewriting everything?
The Day a Junior Surpassed Me
One of my mentees once told me:
“I don’t want to be the smartest person in the room. I want to be the calmest.”
That’s when I knew they were going to make it.
Because software development isn’t about intelligence.
It’s about composure under uncertainty.
What Juniors Actually Need
Not more courses.
Not more frameworks.
Not more AI prompts.
They need:
- Permission to struggle
- Time to break things
- Seniors who explain why, not just what
- Fewer architecture debates
- More debugging sessions
They need to see seniors fail openly.
And Here’s the Truth Seniors Don’t Admit
We were also terrible once.
We also:
- Overengineered everything.
- Rewrote code that didn’t need rewriting.
- Thought we were geniuses after learning design patterns.
- Judged legacy code without understanding constraints.
Experience doesn’t make you smarter.
It makes you humbler.
Final Thought
If you’re a junior developer reading this:
You’re not behind.
You’re just early.
And if you’re a senior:
Remember who you were at year two.
Mentorship isn’t about showing how much you know.
It’s about making someone else less afraid.
Please visit here
Top comments (49)
Excellent post. When I was a beginner, I made the same mistakes. Before training, I realized the real problem, as you described: we're not taught to think. And I think this applies not only to programming but to other fields as well. That's why I don't like learning in the traditional sense - I've never signed up for any courses or watched any super-detailed tutorials where someone spends five hours explaining how to do something step by step (200 steps, I think). I just do this:
Fixing these is precisely what provides the basis for learning, and I find it much more interesting to learn when I have finished code and can immediately see the results. Even changing a few lines of this code yields results, and seeing that it works motivates you to keep doing it, and it simply makes you happy.
And it's not like reviewing and modifying someone else's code - the LLM essentially provides you with an entire description of that code, which helps you understand it. After all, real learning is practice, not theory.
Love this perspective — especially the part about “we’re not taught to think.” That’s such a core technical issue, not just in programming but in how we approach problem-solving overall.
I also agree that copy-pasting from an LLM isn’t real learning by itself. The real growth starts exactly where you pointed: when the code hits the IDE and breaks — dependency conflicts, version mismatches, runtime errors, or subtle logical bugs. That debugging phase forces you to understand execution flow, environment setup, and why something fails. That’s where engineering thinking is built.
I see LLMs less as shortcut machines and more as accelerators for experimentation. The key is not generating code, but dissecting it — tracing stack traces, refactoring parts, rewriting functions without looking, and testing edge cases. That’s where curiosity turns into skill.
Really appreciate you sharing this — I’m especially interested in how we can balance fast iteration with deep understanding. That tension is the real learning engine.
The real issue is that modern tooling (Copilot, AI assistants) optimizes for speed, not learning. Juniors ship faster but build slower, if that makes sense. Debugging instincts come from pattern recognition that only develops through repeated failure. How do we redesign onboarding so juniors get the benefits of AI without losing the struggle that builds intuition?
You hit the nail on the head—AI speeds up delivery but doesn’t teach the deeper debugging patterns. I think onboarding could mix guided AI use with small “failure zones,” where juniors experiment and troubleshoot on their own. It’d be exciting to see a framework that balances AI efficiency with intuition-building—definitely something I’d love to explore further.
Absolutely agree with you. Blending guided AI usage with intentional “failure zones” sounds like a powerful way to build real problem-solving skills. AI can accelerate learning, but true intuition comes from struggling, debugging, and reflecting on mistakes. Exploring a framework that balances speed with deep understanding would be incredibly valuable—I’d definitely be excited to work on or learn from something like this.
Totally agree! Combining AI guidance with deliberate “failure zones” seems like a smart way to strengthen real problem-solving skills. Speed is great, but intuition really grows through debugging and reflecting on mistakes. I’d be excited to see or contribute to a framework that balances both.
For real though... Yeah. 100%. Growth feels painful. We don't like pain so we sanded down the rough edges. No pain, no growth. You can't get good at debugging nonsense if you've never been eyeball-deep in your own self-created nonsense with no clear way out.
Love this take — seriously. You’re absolutely right.
Growth in engineering almost always comes from friction. When you’re deep in your own messy logic, chasing a race condition, untangling a weird state mutation, or tracking down a side effect you introduced three refactors ago — that’s where real debugging skill is forged.
You made an excellent point
Thanks.
I have been there to mentor people. I wish that I can program to be my assistant. The robot will make our life a bit easier.
That’s awesome — mentoring is seriously underrated and super impactful 👏
I really like your idea about programming an assistant. Honestly, we’re already moving in that direction with AI copilots and automation tools. The real technical challenge now isn’t whether we can build assistants — it’s how to design them to actually understand context, write reliable code, and reduce cognitive load instead of adding more noise.
I want to talk with you further.
Could you contact me via t.g?
Thanks, Ben! I completely agree—mentorship really shapes careers and helps share knowledge forward.
I also think you’re right about AI: tools like Gemini 3 Pro are improving fast, but they still can’t fully replicate human judgment or complex cognitive reasoning. Exciting to see how quickly the tech is evolving!
I’ll reach out via your email and look forward to continuing the discussion.
Yes, it is 100% for the mentorship. I agree with you that the technology is changing rapidly.It is really cool. I see the potential of AGI in AI in a good way. I am afraid of the technology because we can use AGI is a different context with hacker. I am glad that AGI is still theory on paper for now.
It sound good! Your email might go in my spam folder in my gmail. I will keep an eye on your email in both my inbox or my spam folder.
Ben
I completely agree with you, Ben — mentorship is becoming even more important as technology evolves so fast, especially with AI moving toward concepts like Artificial General Intelligence; the potential is exciting, but the real technical challenge will be building strong security architectures so it can’t be misused in malicious contexts. I’m also glad AGI is still mostly theoretical for now, since it gives us time to focus on safe implementation, and I’ll definitely keep an eye on both my inbox and spam folder for your email.
Exactly! I am curious. What is your first name? I don't write "hello art light" when I send my first email to you.
I have sent message to you, please check your inbox.
I got your email!
The point about juniors not being taught to think is something I keep coming back to. harsh2644's comment above about "ship faster but build slower" is exactly right.
Here's what I've started wondering: if we know the right habits — read error messages carefully, break problems down, understand before copying — why don't they stick? I think it's because methodology stays as advice, not as practice. You read "always understand the code before using it" and nod, then forget it the moment a deadline hits.
One thing that's worked in my own workflow: I write my best practices as executable instructions rather than notes I have to remember. Instead of a doc saying "always write a spec first," I have a workflow file that makes my AI tools automatically ask for a spec before generating code. The methodology runs whether I'm disciplined that day or not.
Not sure how well that translates to mentoring juniors, but the underlying idea — make the right behavior the default, not the aspiration — seems broadly applicable.
This is such a sharp observation — turning methodology into enforced workflow instead of relying on discipline is a powerful systems-level solution, especially when deadlines start pressuring decision quality. I’m really interested in pushing this further in mentoring juniors too, maybe by embedding thinking checkpoints directly into code reviews or tooling so “understand first” becomes the default execution path rather than a motivational slogan.
"Architecture is trauma-informed design" — that line is going to stick with me for a while.
I've noticed the same thing mentoring newer devs on my team. The biggest gap isn't knowledge, it's comfort with ambiguity. They want a clear answer before they start, but real debugging is more like detective work — you form a hypothesis, test it, adjust. That loop is uncomfortable at first.
One thing that's helped: instead of code reviews where I just point out issues, I started doing "thinking out loud" sessions where I debug something live and narrate my actual thought process. The messy parts. The wrong turns. The "wait, that can't be right" moments. It demystifies the whole thing way more than any tutorial.
Your point about emotional regulation is underrated. The ability to sit with "I have no idea why this is broken" without panicking is genuinely a skill you have to practice.
Thanks, I really appreciate your insight! I completely agree—mentoring juniors often shows that handling ambiguity is the real skill. I love your “thinking out loud” approach; sharing the messy debugging process is such a practical way to build intuition. I’ve been experimenting with something similar—pair debugging while narrating hypotheses—and it really helps normalize trial-and-error. Emotional regulation in debugging is huge, and your point reminds me I should emphasize that more when guiding others.
Great read! I am also just going to graduate, and this was really really helpful. I was in my second year of college, when LLMs really started to take speed. I was hesitant at first that, no I won't use it to do my assignments but slowly slowly seeing the sheer speed at which works is completed and even explained to us took me into the wave as well.
Although I still think about the fact that, were my most important years of learning wasted with LLMs and not man pages? Did I miss the thrill of figuring stuff out on my own? I still sometimes go to man pages just to see if I can read and understand. But I understand that we need to give ourselves the space to try and fail. In the world where everyone knows everything and all syntax is perfectly written, and all methods have sensible names, maybe we need to give ourselves the space to miss the semi colon here and there.
Love this comment — and congrats on graduating soon! 🎓
I really respect that you were hesitant at first. That shows you care about actually learning, not just finishing assignments fast. And honestly, that’s the real technical challenge here — not whether we use LLMs, but how we use them.
I don’t think your important years were “wasted.” If anything, you learned in a different environment. Reading man pages builds depth. Using LLMs builds speed and pattern recognition. The problem starts only when we stop thinking critically and just copy-paste without understanding memory usage, complexity, edge cases, or why a certain abstraction exists.
I still believe we should sometimes go back to raw docs, break things intentionally, read stack traces, debug without autocomplete. That friction builds real engineering intuition.
And I fully agree with you — we need space to fail. Missing a semicolon is not the problem. Not understanding why the program broke is.
That is so true and very real. I also mentor developers, and they do struggle with being overwhelmed. Some want to be very good immediately, and when they realise they cant they panic. I usually don't know how to help them. Thank you, this gives me an idea of a better approach.
I really appreciate you sharing that — mentoring developers is no small responsibility, and you're absolutely right that the pressure to “be great immediately” can overwhelm them, especially when they start facing real-world complexity like architecture decisions or debugging production issues.
One thing I'd add: juniors often skip understanding why a pattern works and just copy code that passes tests. The most effective fix I've seen is requiring them to explain their solution out loud before submitting a PR — not as gatekeeping, but because articulating logic exposes the gaps that syntax won't. Rubber-duck debugging as a mandatory step, not an afterthought.
That’s a really strong point — I completely agree with you.
Copy-pasting patterns without understanding the why behind them is one of the biggest technical gaps at the junior level. Code can pass tests and still hide design flaws, wrong assumptions, or poor scalability decisions.
I really like your idea of explaining the solution out loud before opening a PR. When someone walks through their logic — data flow, trade-offs, edge cases — the weak spots show up immediately. It’s not gatekeeping at all; it’s forcing clarity in thinking.
Honestly, I think this should be part of every code review culture. Rubber-duck debugging as a required step could reduce shallow fixes and improve architectural awareness early on.
Great insight — I’m definitely going to push this more in my team.
The biggest thing I've noticed mentoring junior devs: they optimize for writing code, not reading it. They'll spend hours building a feature but won't spend 20 minutes reading the existing module they're modifying.
The best junior devs I've worked with read 3x more code than they write. Not glamorous advice but it compounds fast.
Absolutely, I totally agree! Reading existing modules is such a force multiplier—spending that time upfront often prevents messy refactors later. I’ve found pairing reading with small exploratory experiments helps me understand code faster and catch hidden edge cases. Definitely something I try to prioritize more now.
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