Any devs actually getting a leg up using AI tools?

There is a lengthy debate, over 400 posts on reddit as of this writing, on the topic of usefulness of AI in software development on Experienced Developers reddit. I read and analyzed all of them, so you don’t have to, and because this topic is near and dear to my heart. The software developer productivity is what my company does, so being in tune with developers’ attitude towards AI tools is very important to me. I’ve noticed general skepticism on twitter/bluesky about AI – and from people who’ve really tried it. Also, I’ve seen thought leadership pieces from VCs like Sequoia who go on to clam we’d be better of educating the next billion developers, then working on AI tools. But let’s dig in the current reddit debate as it is quite good. The Original Post is copied below – verbatim. Below it you will find a more complete analysis on the good and not-so-good use cases for AI in software development. Overall, the consensus of the thread is that AI works best as an assistant rather than an autonomous coder. Even as an assistant it must be kept a close eye on. While some people seem bullish on AI tooling, there is very strong skepticism towards AI tools but, surprisingly so, sometimes even the skeptics acknowledge AI tooling usefulness in specific scenarios One of the Big Bosses at the company I work for sent an email out recently saying every engineer must use AI tools to develop and analyze code. The implication being, if you don't, you are operating at a suboptimal level of performance. Or whatever. I do use ChatGPT sometimes and find it moderately useful, but I think this email is specifically emphasizing in-editor code assist tools like Gitlab Duo (which we use) provides. I have tried these tools; they take a long time to generate code, and when they do the generated code is often wrong and seems to lack contextual awareness. If it does suggest something good, it's often so dead simple that I might as well have written it myself. I actually view reliance on these tools, in their current form, as a huge risk. Not only is the code generated of consistently poor quality, I worry this is training developers to turn off their brains and not reason about the impact of code they write. But, I do accept the possibility that I'm not using the tools right (or not using the right tools). So, I'm curious if anyone here is actually getting a huge productivity bump from these tools? And if so, which ones and how do you use them? Most Frequent Use Cases Where Developers Found AI Helpful Boilerplate Code Generation (Writing YAML files, API route patterns, class structures, and basic CRUD operations. Generating repetitive code like adapter methods, constructors, and ORM models.) This one user seems to have hit them all!

Feb 21, 2025 - 18:57

Any devs actually getting a leg up using AI tools?

There is a lengthy debate, over 400 posts on reddit as of this writing, on the topic of usefulness of AI in software development on Experienced Developers reddit.

I read and analyzed all of them, so you don’t have to, and because this topic is near and dear to my heart. The software developer productivity is what my company does, so being in tune with developers’ attitude towards AI tools is very important to me.

I’ve noticed general skepticism on twitter/bluesky about AI – and from people who’ve really tried it. Also, I’ve seen thought leadership pieces from VCs like Sequoia who go on to clam we’d be better of educating the next billion developers, then working on AI tools.

But let’s dig in the current reddit debate as it is quite good. The Original Post is copied below – verbatim. Below it you will find a more complete analysis on the good and not-so-good use cases for AI in software development.

Overall, the consensus of the thread is that AI works best as an assistant rather than an autonomous coder. Even as an assistant it must be kept a close eye on. While some people seem bullish on AI tooling, there is very strong skepticism towards AI tools but, surprisingly so, sometimes even the skeptics acknowledge AI tooling usefulness in specific scenarios

One of the Big Bosses at the company I work for sent an email out recently saying every engineer must use AI tools to develop and analyze code. The implication being, if you don't, you are operating at a suboptimal level of performance. Or whatever.
I do use ChatGPT sometimes and find it moderately useful, but I think this email is specifically emphasizing in-editor code assist tools like Gitlab Duo (which we use) provides. I have tried these tools; they take a long time to generate code, and when they do the generated code is often wrong and seems to lack contextual awareness. If it does suggest something good, it's often so dead simple that I might as well have written it myself. I actually view reliance on these tools, in their current form, as a huge risk. Not only is the code generated of consistently poor quality, I worry this is training developers to turn off their brains and not reason about the impact of code they write.
But, I do accept the possibility that I'm not using the tools right (or not using the right tools). So, I'm curious if anyone here is actually getting a huge productivity bump from these tools? And if so, which ones and how do you use them?

Most Frequent Use Cases Where Developers Found AI Helpful

Boilerplate Code Generation (Writing YAML files, API route patterns, class structures, and basic CRUD operations. Generating repetitive code like adapter methods, constructors, and ORM models.)

This one user seems to have hit them all!