You've read eleven lessons. You know the patterns. You've got types, domains, events, quality gates, and documentation.
Now let's talk about the five ways developers sabotage all of it — usually with the best intentions.
Trap 1: Premature abstraction
You see similar code in two places and immediately extract a shared utility. The DRY principle, right?
Wrong timing. Wait for the third occurrence. The first two examples rarely share as much as you think. You end up with an abstraction that sort of fits both cases but perfectly fits neither — and now you have to maintain a shared utility that's harder to change than the duplication it replaced.
Three lines of duplicate code is better than the wrong abstraction.
The Rule of Three exists for a reason. By the third time you see a pattern, you understand it well enough to extract correctly. Before that, you're guessing at the interface.
Trap 2: Blind AI trust
AI generates clean, well-formatted, confidently written code. It reads like it was written by someone who knows what they're doing. That confidence is exactly the problem.
AI doesn't know your business rules. It doesn't know that "archived" projects should still appear in usage reports. It doesn't know that your European users expect dates in DD/MM format. It generates what looks right based on patterns, not what is right based on your domain.
The fix: Review every generated function like you would a junior developer's pull request. Ask three questions:
- Does it do what I asked? (Not what it assumed I asked)
- Does it follow our patterns? (Not its own invented patterns)
- Could it fail silently? (The most dangerous bugs are the ones that don't crash)
Trap 3: Big-bang refactoring
"Let's take two weeks and clean everything up."
This sounds responsible. In practice, here's what happens: the team stops shipping features for two weeks. They introduce 40+ bugs through large-scale changes. The refactoring takes three weeks instead of two. Feature requests pile up. When they finally resume shipping, the codebase starts getting messy again within a month.
The fix: Continuous small improvements beat planned rewrites. The Boy Scout Rule (leave every file a bit cleaner) compounds over time. You've seen the data — 40 features shipped with only 45 hours of refactoring spread across 6 months.
Trap 4: Skipping documentation
"I'll document it later."
You won't. Nobody does. And every day without documentation, your AI partner is guessing instead of following patterns. You're throwing away the single highest-leverage investment you can make.
Ninety minutes to build your .claude/ directory. That's it. AI accuracy jumps from 40% to 90%. Prompt length drops from 500 words to 50. You'll make that time back within the first day.
The fix: Write the docs before you need them. Five files, 90 minutes. Do it today.
Trap 5: Perfection paralysis
The code works. Tests pass. But you keep tweaking. That variable name could be better. This function could be cleaner. Maybe if you restructured this one more time...
Meanwhile, nobody is using the feature. Zero users are getting value. Your perfect code is sitting in a branch, being perfect for an audience of one.
The fix: Time-box improvements. Phase 2 gets 30 minutes. When the timer rings, ship what you have. It's good enough. "Good enough, deployed" beats "perfect, in a branch" every single time.
That's the full system
Architecture First isn't a philosophy. It's a practice. Start with the .claude/ directory. Add types. Draw domain boundaries. The first feature will be 5x faster. By the fifth, you'll wonder how you worked any other way.
The developers who thrive with AI aren't the fastest coders. They're the clearest thinkers. They make the architectural decisions that turn AI from a fancy autocomplete into a genuine force multiplier.
Now go build something.