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description: A developer reflects on how AI now writes most of their code and reframes their own role around five practices: writing precise prompts as specs, reviewing AI...
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# AI Writes My Code Now. Here’s What I Actually Do With My Time.

**[Medium](https://daily.dev/sources/medium_js)** · 4 min read · 26 upvotes · 8 comments

## Summary

A developer reflects on how AI now writes most of their code and reframes their own role around five practices: writing precise prompts as specs, reviewing AI output critically like a junior dev's PR, supplying real-world user context AI lacks, owning system architecture, and testing for chaotic edge cases. The core argument is that coding was never the real job — thinking, judgment, and problem framing were always the actual value a developer provides.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://blog.stackademic.com/ai-writes-my-code-now-heres-what-i-actually-do-with-my-time-a7387fd82e75>

## Community discussion

Top comments from developers on daily.dev.

**@elmarchavez** · 1 upvotes

> Good points. I hope people are doing these steps responsibly. If not, well we already know what could happen.

**@ahmetozel** · 1 upvotes

> Writing precise prompts as specs and reviewing output like a junior's PR are doing quite different work, and the first is the harder skill. A spec precise enough to generate from is precise enough to test, which is why that practice pays off even when you end up writing the code yourself.
>
>
> The part I would push on is the junior-PR analogy. A junior's mistakes correlate with their experience, so you learn where to look. Model mistakes do not correlate that way: it can nail the concurrency and then invent a config key. Review has to stay uniformly suspicious rather than targeted, which is...

**@ahmetozel** · 1 upvotes

> Writing precise prompts as specs and reviewing output like a junior's PR are doing quite different work, and the first is the harder skill. A spec precise enough to generate from is precise enough to test, which is why it pays off even when you end up writing the code yourself. The part I would push on is the junior-PR analogy: a junior's mistakes correlate with their experience, so you learn where to look, while model mistakes do not correlate that way. It can nail the concurrency and then invent a config key, so review stays uniformly suspicious instead of targeted.

**@agustinbarrientos** · 0 upvotes

> The login spec should say what happens when guest data conflicts with an existing account. I'd ask the product owner which copy to keep. Then I'd put that exact case in the acceptance tests.

**@fabooy961** · 0 upvotes

> has anyone tried maintaining an OF account while ai does the coding?
>
> ![GIF](https://static.klipy.com/ii/4493325008d34b7bf8cd6813cd5c1619/5a/f2/3vCsKGQMYb3RQCR.gif)

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---

Tags: [#architecture](https://daily.dev/tags/architecture), [#productivity](https://daily.dev/tags/productivity), [#ai-coding](https://daily.dev/tags/ai-coding), [#code-review](https://daily.dev/tags/code-review)

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