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nunezHNSource author
Lessons learnedExperience excerpt · English

This isn't too far off from what I was doing as a business analyst a little over 20 years ago (and …

… This isn't too far off from what I was doing as a business analyst a little over 20 years ago (and what some technical product managers do now for spikes/prototypes). I wrote FRDs [^0] describing what the software should do. Architects would create TRDs [^1] from those FRDs. These got sent off to developers to get developed, then to QA to get bugs hammered out, then back to my team for UAT. If agents existed back then, there would've been way fewer developers/QA in the middle. Architects would probably do a lot of what they would've done. I foresee that this is the direction we're heading in, but with agents powered by staff engineers/Enterprise Architects in the middle. > Edit: as an aside, I have learned plenty from reviewing coding agent generated implementations of various algorithms or methods. People learn differently. I (and others) learn from doing. Typing code from Stack Overflow/Expertsexchange/etc instead of pasting it, then modifying it is how I learned to code. Some can learn from reading alone. [^0]: https://www.modernanalyst.com/Resources/Articles/tabid/115/I...

Original discussionI Quit. The Clankers Won484 source comments · at import
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pfishermanHN

This is going to catch some heat, but what if the most important professional “developer skill” to learn or improve is how to effectively use coding agents? I saw something similar in ML when neural nets came around. The whole “stack moar layerz” thing is a meme, but it was a real sentiment about newer entrants into the field not learning anything about ML theory or best practices. As it turns out, neural nets “won” and using them effectively required development and acquisition of some new domain knowledge and best practices. And the kids are ok. The people who scoffed at neural nets and never got up to speed not so much. Edit: as an aside, I have learned plenty from reviewing coding agent generated implementations of various algorithms or methods.

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CamperBob2HN

Doing so will effectively force a (potentially unwanted) career change for many people and will lead to the end of software engineering (and software as a career), assuming AI continues to improve. If you expected things to stay the same forever, maybe software engineering wasn't the right career move for you. Even though it looked safe enough, given that we've spent 50 years writing the same old code the same old way, that was never guaranteed. I for one am glad to see something genuinely new come along. The last dozen or so "paradigm shifts" turned out to be disappointing variations on the same old paradigm. Not this one, though.

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zemHN

> This requires the ability to write well (or well enough to get what you want from the agent) and clearly communicate intent (in your language of choice, not code; very different IMO). I do not see why you can't write your spec in pseudocode if you really want to - communicating your intent to the LLM , for how the code should be developed is far closer to programming than writing skillwise.

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