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With AI tools writing code in seconds, everyone thinks projects should magically ship faster. Reality check:
AI is like a magic typewriter - it writes whatever you ask for, but won't tell you when you asked for the wrong thing.
? Where AI Shines
- First drafts (better than blank screens)
- Simple functions (when perfectly specified)
- Explaining code (mostly accurate)
What no one talks about:
- Prompt ping-pong:
- Try a prompt → Get wrong output → Reword → Repeat
- "Make it cleaner" → "Now it's too simple" → "But keep performance" → ??
- Reality checks:
- AI uses latest libraries → Your project uses older versions
- AI suggests "elegant" solutions → Your team's style guide says otherwise
- The polish phase:
- Fixing weird variable names
- Adding actual error handling
- Making it match the rest of your code
They notice:
"The AI wrote 100 lines instantly!"They miss:
The 4 hours spent making those lines actually work
The Hard Truths- Edge cases are your job: The happy path is easy. It's the other 97 paths you're paid to handle.
- Testing is still human work: AI won't write your e2e tests or debug that intermittent Friday 6:55 PM issue.
- Accountability stays with you: AI might write the code, but your name's on the commit - and your neck if prod goes down.
AI is here to stay. It's helping us write better code faster - and that's exciting. But let's not confuse:
- Code with product
- Generated with done
- First draft with production-ready
Building great software still takes time, effort, and thought. AI handles the first draft - humans do the hard parts:
- Thinking through trade-offs
- Deciding what actually matters
- Debugging the weird cases
- Caring about the result
Bottom line? AI is power steering for coding - helpful but you still need to drive.
(AI: giving developers more time to focus on the hard problems... and creating new ones.)
(Pro tip: When someone asks "Can't AI do this?" - smile, nod, and say: "Absolutely. Then we'll just need the rest of the week to make it actually work.")