The Indie Dev Edge in the Age of AI
AI can write you a thousand lines in seconds. Too bad it can’t read them for you. That’s still your job—and probably your superpower.
Everyone and their dog’s obsessed with writing code faster.
AI makes us 10x writers. 100x typists. Whatever.
But nobody’s talking about becoming a 10x reader.
And here’s the kicker — AI is vomiting out more code than ever. Which means you need to read and understand more code than ever. The bottleneck isn’t writing anymore. It’s comprehension, judgment, and knowing when to hit delete instead of commit.
Why this Matters More Now
The AI paradox
Claude can churn out 500 lines of backend logic in 30 seconds. But you still have to:
Check if it actually does what you asked
Notice the subtle bug hiding in error handling
Decide whether that abstraction will come back to bite you
Understand it well enough to fix it when the PM changes the requirements tomorrow
AI can write all the code in the world. It still can’t tell you if it’s good.
The reality
Juniors with AI now ship code at senior speed. The problem? They can’t tell good generated code from hot garbage. They move fast, break things… and then ask you to review it.
The unlock
Seniors with reading chops use AI without becoming its pet. They skim generated code like Neo reading the Matrix — “yeah, that’s an off-by-one bug right there.” Reading is the gate. Writing is just the noise.
The Code Reading Muscle
It’s not “reading comprehension.” It’s mental pattern recognition with caffeine.
Pattern recognition — You see if err != nil { return nil, err } and your brain whispers, “Go boilerplate, nothing to see here.”
Architecture intuition — You open a repo and know where the dead bodies are buried just from the folder structure.
Bug radar — That spidey-sense that tingles before you even scroll — something’s off. Usually missing validation, or someone “cleverly” sharing a global.
Context switching speed — You can hop from React component → API → database query → back again without losing the plot.
Abstraction unpacking — You see userService.authenticate() and immediately imagine the 12 files hiding behind that call.
That’s the muscle. Reading is pattern spotting at light speed.
Exercises That Actually Work
1. The 5-Minute Codebase Scan
Pick a random GitHub repo. Small, readable.
Set a 5-minute timer. Try to answer:
What does it do?
What’s the core abstraction?
Where would you add a new feature?
What’s the sketchiest piece of code?
You’ll probably be wrong the first few times. Perfect. You’re training intuition, not memorizing trivia.
Start with stacks you know. Then branch out. Eventually, try reading something alien — that’s where growth hides.
2. AI Code Review Roulette
Ask Claude or ChatGPT to write something — a rate limiter, a REST API, a React hook.
Now, don’t run it.
Read it like a detective:
What could break?
What smells?
What would you refactor?
Then run it and see how wrong (or right) you were.
Do this enough and you’ll develop a sixth sense for AI bugs — the kind that crash in production at 3 a.m.
Bonus: Ask two AIs the same thing. Which one’s code would you rather maintain? Why? That’s your taste muscle forming.
3. The Changelog Detective
Pick a library you use every day. Go to its GitHub releases. Read the commit diffs for a minor or patch bump.
Ask:
Why was this changed?
What broke?
What tradeoff did the maintainer choose?
You’ll start seeing the real engineering behind the facade. That’s where mastery lives.
4. Explain It to a Duck
Grab a gnarly function.
Now, explain it in plain English. No jargon.
If you can’t? You don’t actually understand it. Keep at it.
Bad: “It maps and filters the array.”
Good: “It finds active users in the last 30 days, sorted by login time.”
That’s real understanding. Not just parroting syntax.
5. The “No Running” Challenge
Write a small program. 50–100 lines. Don’t run it.
Read it twice and predict:
What will the output be?
Where will it break?
What edge case will it choke on?
Then run it. Reality check time.
This builds your internal compiler — the one that helps you debug production when the system’s on fire and kubectl exec isn’t helping.
How This Compounds Over Time
0–2 years:
You read slow. You write slow. You Google “Python for loop syntax” a lot.
AI enters:
Suddenly you write fast. But you still read like a confused tourist. You ship more bugs, faster.
2–5 years:
Now you read fast and write fast. You glance at AI output and see through it.
5+ years:
You can parachute into any repo and get the lay of the land in minutes. You’re debugging across services. Reading is 80% of your job. Writing is an afterthought.
Every project you touch sharpens the radar. Every bug you fix improves your mental models. Every codebase you inherit becomes easier to digest. That’s compounding.
Also: boring stacks help.
You read the same patterns — Postgres, Redis, Express — again and again until it’s second nature. No cognitive tax. Fancy tech makes you start from zero every time.
Daily Practice (a.k.a. the Boring Way That Works)
Morning ritual: Read one function before writing a line. Two minutes. That’s it.
PR reviews: Don’t just skim — ask why the author made those choices.
AI pair programming: Never accept AI code blindly. Read before you run. Especially when you’re in a rush.
Weekend deep dives: Pick one OSS project a month and read the core 200 lines.
Bug postmortems: After fixing something, read the surrounding code. Figure out why it broke in the first place.
That’s how you actually build the muscle. Quietly. Daily.
Don’t Fake It
Speed reading code to “feel productive” is fake progress.
If you can’t explain it, you don’t understand it.
Red flags:
Approving PRs faster than Slack loads
Forgetting what your own code does after a week
Acting surprised when it breaks exactly how it looks like it would
Slow down. Read with intent. Comprehension beats velocity every single time.
The Meta-Skill
AI will keep getting better at writing code. It’ll never understand why the code matters.
That’s your job.
The developer who can read code — fast, deeply, intuitively — will always win.
Start building the muscle. It ages like wine.
Do this today:
Pick one exercise. Do it now. Time yourself. Do it again next week. You’ll notice you’re faster — not at typing, but at thinking.
That’s the real 10x skill nobody’s bragging about on LinkedIn.