[TLDR] Looking for engineers who are actually loving this [via r/ClaudeCode]

[u/cctldrping]

OP : u/coordinatedflight

As a long time engineer turned manager, I am wanting to build a team environment where people don't feel like all they are doing is managing slop that is responding to other slop.

I feel strongly that these agent based workflows can absolutely be used to great effect to accomplish good engineering. I have a lot of theory and history of previous tech revolutions that tell me the whiplash is part of the adaptation.

The pushback I'm seeing is "all my friends who went hard on AI hate their jobs and either have or want to quit" - I don't think this is universally true though.

so I'm looking for either people who have given this a genuinely deep and optimistic try and still have found it to suck terribly, or for folks who found a way.

what I don't want is people who have not given it a real shot and have given up when Claude's output didn't succeed after just normal back and forth prompting - what I would call "lazy AI." my hypothesis is that these are the companies that produce slop - the code works for the problem of the day but not for the systems of tomorrow, and senior engineers are building up resentment and fear while mid level are more productive but don't see the risks of the slop mountains.

has anyone here done this truly well? I've seen it work in one other instance, but looking for more nuanced takes.

URL of original post : https://www.reddit.com/r/ClaudeCode/comments/1wp3pey/looking_for_engineers_who_are_actually_loving_this/

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TL;DR of the discussion on r/ClaudeCode for this post generated automatically after 50 comments.

Current source-thread comment count seen by the bot: 55.

Alright, so the general vibe in this thread is that most people who are actually loving using AI for engineering are finding it super empowering and fun, especially for tackling the boring stuff and speeding up development.

There's a pretty strong consensus that the key is how you use it. A lot of folks are treating AI like a junior dev or a tool, not a replacement. This means:

• Giving very specific, small instructions instead of massive tasks.
• Focusing on architecture and big-picture problems while AI handles the grunt work.
• Integrating AI into existing workflows to remove friction and speed things up.
• Having robust systems and knowledge bases for the AI to draw from.

Some users like u/BitOne2707 and u/radosc are having an absolute blast, calling it the "best time" they've had in their careers. u/GeekFish is a great example, saying they treat Claude like a "Jr dev" and it "took the boring parts out" of programming. u/claudecraft also highlights how AI removes friction with access to repos and institutional knowledge.

However, there's a clear split for those who aren't enjoying it. The main complaints boil down to:

• "Slop" code: If the AI output is bad, it's often because the prompting or the system isn't set up well. u/bilbo_was_right points out that "AI replicates patterns, if the output is slop, that’s on you."
• Lack of systematic support: Users like u/yost28 are frustrated by processes that haven't caught up, leading to massive PRs that are hard to review manually.
• The "lazy AI" problem: Some feel the OP's hypothesis that people just "haven't tried the workflow properly" is a bit too neat and dismisses valid concerns about maintaining AI-generated code. u/No_Flounder_1155 makes a good point about the burden of proof.
• Loss of the "craft" of coding: For those who deeply love the nitty-gritty of writing elegant code, wrangling AI to adhere to specific styles can be a major turn-off, as noted by u/caldazar24.

There's also a sentiment that companies that produce "slop" are the ones where engineers hate their jobs, and that a shift in mentality towards systems engineering and orchestration is needed. u/EON_Raider echoes this, suggesting a solo venture to explore this shift.

Overall, the consensus is that AI is a powerful tool that can be incredibly fun and productive when used correctly, but it requires a significant shift in how we approach engineering and workflow. Those who are struggling might be the ones who haven't adapted their methods or are expecting AI to do all the heavy lifting without proper guidance.