I Got Called Out by My Senior — and It Taught Me the Real Cost of "AI-First" Coding

Kumaresan — Fri, 21 Aug 2026 11:07:08 +0000

For a while now, I've been quietly embarrassed about something, and I think a lot of junior devs are quietly dealing with the same thing — so let's talk about it instead of hiding it.

The Pattern

More times than I'd like to admit, I've walked into a task without fully understanding it. Not "I understood 80% and figured out the rest" — I mean genuinely unclear on what was being asked, why it mattered, or what the actual requirement was. And instead of stopping to figure that out, I'd jump straight to producing a solution — often leaning heavily on AI to generate something that looked right.

It worked, on the surface. Code got written. PRs got opened. Things moved.

Until my senior asked me one simple question during a task walkthrough:

"Why did you do it this way? What does this actually mean?"

And I froze. Not because the code was wrong — but because I couldn't explain the reasoning behind it. I hadn't built it. I had assembled it.

That moment was more educational than any tutorial I've ever done.

The Real Problem Wasn't AI

It's tempting to say "AI made me lazy" and leave it there. But that's not quite accurate. The real issue was using AI to skip the understanding step instead of to support it.

When you don't fully get a task, there's a natural discomfort — a "wait, I don't actually know what I'm doing" feeling. That discomfort is useful. It's supposed to push you to ask questions, dig into the requirements, or slow down. But AI can resolve that discomfort artificially — it gives you a plausible answer instantly, so the uneasy feeling goes away without the actual understanding ever happening.

The output looks complete. Your understanding isn't.

What I'm Changing

Here's what I've started doing differently, and it's already made a visible difference in how I approach tasks:

Restate the task in my own words before touching any code or any AI tool. If I can't write 2–3 sentences explaining what's being asked and why it matters, I don't understand it yet — full stop. No amount of code will fix that gap.
Ask clarifying questions before starting, not after getting stuck. Seniors respect a "before" question far more than an "after" one. It signals you're thinking, not scrambling.
Draft my own rough approach first, then bring AI in as a reviewer — not an author. Even a messy first attempt in my own words is worth more than a polished AI-generated one I can't defend. This flips the relationship: I'm reviewing AI's suggestions critically instead of consuming them blindly.
Run a 30-second self-interview before presenting any solution. Why did I choose this approach? What would break it? What's the alternative? If I can't answer these, I'm not ready to show the work yet.
When I genuinely don't know the "why," I say so — instead of guessing. "I don't have a solid reason yet, let me think it through and get back to you" rebuilds far more trust than a shaky, made-up justification ever will. ## Why I'm Sharing This

I think a lot of us who ramped up fast using AI tools are quietly in the same spot — good at producing output, shakier on the reasoning behind it. It's an easy trap because the output looks like progress. But the gap shows up eventually, usually in front of the person whose opinion matters most in that moment.

Getting called out was uncomfortable. But it was also the fastest feedback loop I've had in a while, and it forced a change I probably needed anyway.

If you've caught yourself in the same pattern — reaching for AI to resolve the discomfort of not understanding something, rather than to help you understand it — you're not alone. The fix isn't dropping AI. It's changing what step you use it at.

Curious how others have navigated this, especially those a few years further into their careers. What helped you build that "why" muscle?

Recent grad on an AWS backend team — how do I actually get good, fast?

Kumaresan — Mon, 17 Aug 2026 10:07:43 +0000

Hey folks 👋

I graduated a few months back and landed my first "real" SWE job, working mostly on AWS backend stuff. Stack so far:

Node.js/TypeScript on Lambda, sitting behind API Gateway
Postgres + Drizzle ORM
Cognito for auth, plus the usual encryption fundamentals (AES-256-GCM, HMAC)
Serverless Framework, some SAM/CloudFormation, Docker for local dev

I can ship features and I'm not drowning, which is nice. But I keep noticing the gap between "I got the ticket done" and "I actually understand why the system is built this way." I don't want to spend year one just closing Jira tickets and calling it growth — I want the growth to actually compound.

So, genuine question for anyone who's mentored juniors or remembers their own first year clearly:

1. What actually separates someone who "gets" backend architecture from someone who's just wiring up endpoints? Is it a specific set of concepts, or more of a habit of asking different questions?

2. Past Lambda/API Gateway — what's actually worth digging into next? I keep seeing SQS/SNS event-driven patterns, ElastiCache/Redis caching, and observability come up as "the next level" for serverless folks. Curious what you'd prioritize and why, versus what's a distraction this early.

3. How do you build technical credibility on a team without turning into "that junior who won't stop talking in standup"? Genuinely trying to be useful and visible without overstepping into territory I haven't earned yet.

4. What's a trap you (or juniors you've mentored) fell into that a senior had to catch in review? Doesn't matter if it's cost blowups, connection pooling gone wrong, IAM permissions sprawling out of control, swallowed errors, whatever — I'd rather hear it from you than learn it the expensive way in prod.

5. If you had to pick one book, mental model, or daily habit that paid off the most in your first year — what would it be?

Even a single sentence helps. Appreciate anyone who takes the time 🙏

DEV Community: Kumaresan

I Got Called Out by My Senior — and It Taught Me the Real Cost of "AI-First" Coding

The Pattern

The Real Problem Wasn't AI

What I'm Changing

Recent grad on an AWS backend team — how do I actually get good, fast?