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Using more AI does not automatically make you a better developer.
We may be creating a strange new productivity metric in software development:
“How much AI did you use today?”
More prompts.
More generated code.
More automated tasks.
But more AI usage does not always mean more productivity.
A developer who generates 1,000 lines of code with AI may still create more complexity than someone who:
→ rejects an unnecessary feature
→ removes 100 lines of code
→ chooses a simpler architecture
→ catches a bad assumption early
→ solves the problem without adding another dependency
That’s the part I think we sometimes miss.
AI is extremely useful, but it should be a tool for reducing unnecessary work, not a reason to create more of it.
Atlassian’s 2026 developer research found that 41% of developers said they use AI more than necessary because they feel expected to, while only 28% reported noticeably less day-to-day friction.
That gap is interesting.
Because the goal of AI in development shouldn’t be:
“How much code can we generate?”
It should be:
“How much unnecessary effort can we remove while still building the right thing?”
Good engineering has never been about producing the most code.
Sometimes the best technical decision is to write less, remove more, or not build something at all.
So maybe the real productivity metric in the AI era isn’t AI usage.
It’s better decisions, simpler systems, and better outcomes.
The goal isn’t to use more AI.
The goal is to produce better software with less unnecessary work.
What do you think, is AI actually reducing your workload, or just helping you produce more output?
#AI #SoftwareEngineering #Developers #AICoding #Productivity #Engineering #FutureOfWork
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Designed an AI research workspace where the agent plans the work and fills a sheet with cited sources as it goes.
Same screen, two modes. Which one would you work in all day? 👀
13 voted
72%
5 voted
28%
18 votes
Closed
Keeping the research plan and cited results side by side is a useful way to make the agent’s work easier to inspect. I’d lean toward light mode for reading the table in daylight. How do you distinguish a verified source from one that still needs review?
I didn't agree with you fully because there are ways to remove the ai slope, I think a human skill + ai is a killer combo 💀...
But in short AI has given us the speed of 10x even sometimes its 100x, so the thing you have to learn is the basics process:
(Input -> Process -> Output)
and then you have to guide the ai and it will slay it off like a pro🔥
Trust me bros its true 🙌
Manual work is always better than ai slop you can use ai for some clips but full video made with ai is unprofessional and a waste of money and resources
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When a CRM-to-database sync fails halfway, how do you handle it: idempotent retries, or a reconciliation pass afterward? That's usually where integrations start to drift.