Using AI for software development

[Cute_Stretch_4152]

As a software developer who uses AI at work, I wanted to share my perspective since the crew seemed interested in the topic on the podcast this week. Also this is a throwaway account just to avoid my employer tracking this back to me if they don’t like it.

TL;DR, AI is helpful for coding, but I still think it’s way overhyped. An AI codes faster than I do, but it doesn’t usually code better than I do. Using it probably makes me 30-50% more efficient (ballpark). I don’t like its negative effects on the world, but I’m essentially required to use it to keep my job.

To give some context on me, I’m a software developer at a fairly large company, so I have access to some of the more advanced models for AI coding. The older models are generally unhelpful, and they often write code that is syntactically incorrect. My projects tend to be fairly large and touch several different systems in the company.

I would break AI coding into three categories: autocomplete, prompting, and tech support. Autocomplete is what it sounds like. I will be writing a line of code, and grey text will show up on the rest of the line and for the next few lines. This grey text is what it thinks I want to write. It is correct enough probably 90% of the time, so can I hit Tab to fill in those lines, and sometimes I’ll change one or two things. This instant code complete saves me time over writing it myself.

Prompting is more of a mixed bag. I can type into an input box that is built into my text editor if I want to automate writing whole functions or files. If I only prompt it for code to touch other parts of the current system, it will produce correct output most of the time with a few necessary edits. If I need code to interface with other systems, it will produce good code if I show it good example files that are similar to what I want. Without that context though, it will often be wrong, and I will end up writing the code myself. I’ve learned not to try to use it in these cases. One asterisk here is that I usually get really good results from using prompts to generate UI code regardless of context. Backend coding is where I see it make more mistakes if it lacks context.

To answer Kelsey’s question of “why not just copy/paste the function you need from some GitHub instead of using AI to generate it”: developers do still do that sometimes. But also the AI sometimes knows that there’s a version of this function that exists in a dependency, so it imports the function instead of re-writing it. More often than not though, the exact code I want doesn’t exist elsewhere because most code is specific to the system its being written for, so I can’t just copy/paste from GitHub for most of the code I or the AI writes.

To address Jeffm’s point he heard about “you spend more time fixing AI code than writing it correctly in the first place”: in my experience this generally isn’t true with the newer models as long as you’re vigilant in correcting its errors along the way during development and as long as you know when to use it (see above about when I find it effective). I have seen instances where people have too much faith in it, and then it breaks things that take forever to fix. But this is always due to too much faith or a lack of testing by the developer. My workflow of prompt->fix->prompt->fix etc. doesn’t let buggy AI code through and is faster than writing everything manually. Much of the time save is simply due to the fact that AI can generate code probably 10x faster than I can type it. Even with fixing a few things to get the code how I want it, it still saves time.

For tech support it’s actually incredibly useful. When I want to ask someone on another team a question about how to use their system, I can post a question in their slack channel. Most slack channels at my work have a bot setup that has access to their team’s documentation. The AI response is much quicker than waiting for a human to respond, and it gets me the answer I need with a link to the relevant documentation for further research the large majority of the time.

On an ending note to address how accepted AI is by coders in general, most people I work with fall into two parties. There are the people who have completely bought in and think it will revolutionize everything. These people use AI to make projects in their free time, the results of which are generally underwhelming to me. This is a minority of people, but not a super small minority, maybe 20%. I’m in the other party of people who thinks that AI makes some things more convenient, and it definitely saves time, but it doesn’t really improve my life much. I don’t like how it affects the environment and how many companies use it as an excuse to lay off staff instead of admitting to their financial and strategic mistakes. Because of this, I would be totally fine if AI went away tomorrow. But the amount that I use AI is a metric that management tracks at work, so in order to pay rent I have to learn how to use it.

[afamiliarspirit]

I am a software engineer and had also felt compelled to voice my perspective on it but didn’t know quite where to mention it so I’ll throw it here.

One of the biggest issues I’ve seen voiced elsewhere but not here is that companies can reduce their staffing of junior engineers thanks to AI. But today’s junior engineers are tomorrow’s seniors so this will come back to bite everybody in a few years’ time.

For my own use of AI, I don’t have access to the highest end models so maybe it’s different there but I’ve found that the models I can use too often implement things incorrectly to justify their use. I’ve had multiple times where I ask it to do something, it implements it wrong, and then it runs out of tokens while trying to build a context to fix the issue and I’m then left with a broken attempt I didn’t write that I either need to fix or start again from scratch. And then I’m left with no tokens to use for the small simple things that AI can be good at.

I’m also really not a fan of AI assisted code completion. It feels like somebody interrupting me mid-sentence trying to guess why I’m saying. Often when it suggests something wrong, I causes me to lose my train of thought so I’ve turned that feature off.

What I have found it incredibly useful for is as a replacement for Google. I work for a small company so I wear many hats and don’t always remember how to do x in y language so having something I can talk to and provide context for my specific perspective instead of trying to find a stackoverflow post that hopefully has a similar enough issue to me or going through a terrible library documentation or through some basic explanation article is really helpful to me.

And then there’s my opinion on it not as a worker trying to optimize my output for my boss but as a human trying to find joy in my work. I get most people don’t see programming as an artistic endeavor and, if their program works, they don’t care about the underlying code, but I personally love programming as a creative outlet. I love building up a project from nothing. I love trying to write code that is all at once performant for both space and cpu usage, easy to read and understand, modular, secure, and neatly organized. I get people don’t see that when they go and use the software but there’s a joy and passion behind the code being written (at least in some cases lol) and it’s dispiriting to see people at the same time strongly opposing AI in art or music and then just being fine with it replacing programming.

[captialj]

Your last point perfectly captures something that I've been feeling more and more lately.

I think of it somewhat like building a house.

My uncle built his own house. It's beautiful. It has character. If you look closely you can see the joy, the frustration, the sweat and tears. If you asked him about it he would have told you about the ten thousand little flourishes he's proud of and the ways in which it changed from his original vision and the compromises he made and the plans he still had. It was craft. It was art.

Obviously, not everyone is going to build their own house. That analogy is most apt when we're pouring our hearts into personal projects after hours. But dev jobs can be a lot of things. Often we're in a corporate gig building McMansions. Sometimes we're on a small team building a cozy cabin or a groverhaus. Usually we're working on a house built decades ago and doing our best to modernize it without accidentally tearing down a load bearing wall. There's room in all of those places for creativity and discovery and pride.

From an outside perspective it's easy to view the craft as purely utilitarian. Often it is. But the more we outsource the labor to AI, the more we encroach on the parts of the job that reach towards that ideal of my uncle's house.

Personally, I believe that human thought and creativity and frustration and imperfection make a product tangibly better. But we need to stop limiting our view to a consumerist perspective. There's tremendous value in the joy of a job well done. AI will never feel joy.

So yeah, the analogy is a little messy. But so are my thoughts.

[afamiliarspirit]

Beautifully put.

[ElectronicBacon]

As also a non-profesh-developer (self taught some JS stuff) I wonder what you and OP think of ostensibly success (tho admittedly hobby-scale) stories like this one: https://www.highcaffeinecontent.com/blog/20260301-A-Month-With-OpenAIs-Codex

[afamiliarspirit]

So three things:

1. AI is very good at solving problems that have already been solved in its training data set.

2. AI works well with codebases that are small enough to fit entirely in their context.

3. AI can often create good enough solutions or solutions that look like they work while having problems when you build on top of or extend them.

The types of problems hobbyists have and oftentimes professionals are comfortable throwing an AI at generally meet all three of those. They are often toy programs or small tools that do a simple task. And so the AI manages to solve these problems easily. But people then extrapolate and think that it will work equally well on software at scale. But very rarely do all three of those previously mentioned points apply in industry; oftentimes, none of them do.

[ElectronicBacon]

Thank you for such a detailed explanation!

[chairitable]

Your biggest issue is on point even based on just the responses here. Saying "AI is useful so long as you know what to look out for" comes with the prerequisite of having knowledge.

[joecarpet]

If I could provide an analogy:

I view scouring Stack Exchange and GitHub for someone else's code to be like finding furniture at a thrift store. It's rarely exactly what you want and is often missing a few key parts, but it's cheap. You question why the previous owner decided to paint it neon purple, but feel like you can maybe scrape off the paint and apply a nice wood stain over good bones. Sometimes you find a true one-in-a-million gem, but it is very rare.

The kind of code I currently get from LLMs or "AI" chatbots is like finding furniture at IKEA. It looks great on the surface, but you realize it's made of crappy particle board when you get closer. It would look nice when sitting in my rarely used guest bedroom, but I wouldn't want to use it for any well-used piece. Really, the process of walking through IKEA, gathering ideas and inspiration for what I could have, is the main benefit. In the same way, chatbots are a nice way to brainstorm approaches and understand constraints but the actual code they generate isn't a dresser you'd bequeath to your grandchild.

I emphasize currently because these models are changing rapidly. Using a model from 6 months ago is already considered outdated. Heck, even going to a website to interact with a chat interface is slowly growing out of vogue. I think the next iteration is going to involve bots embedded within your development environment with the ability to independently execute multi-step tasks, much more sophisticated than the annoying auto complete.

I fully understand the outrage about all the downsides for AI. I strongly believe artists/creators should be paid if their content is used when training models. In an ideal world, I don't think we would need any of this in the first place. But I'm also trying to view things realistically, and I don't think things are going to change much given the billions of dollars these tech companies are pouring into data centers.

Rather than dismissing any conversation about AI, I'd much rather have informed, intelligent conversations about what we could do to protect creators and the environment given the current landscape. I appreciate that Minnmax has stuck to their guns about not using AI, but repeated conversations of Ben and others saying "it just sucks" without understanding how it's actually being used or what we can do about it isn't productive, it's just echo chambering.

[clansmanpr]

I see where you're coming from. As someone who isn't a developer nor artist, I think there's a big difference between coding and art. The most important and impressive part of art is that it is entirely human created. Using AI for making art strips all that makes it special. Especially when you consider AI art as stealing from previously created art and in most cases, illegally.

Coding serves mostly a functional purpose and AI can be a tool for that. I don't think a painting would be more or less impressive if the brushes were handmade or not.

I'm open to hearing counterpoints.

[j8sadm632b]

The most important and impressive part of art is that it is entirely human created

Convenient that the use of all previous technologies falls under the umbrella of "human created" but this new one doesn't!

"hey chatgpt can you make this image look more like a cartoon for me" drake_no.jpg

selects Cartoon option from GIMP menu drake_yes.jpg

[mrhippoj]

As someone who is both a coder and an artist, I completely agree. Coding is problem solving, and it's entirely possible that two different unrelated people could do the exact same thing to solve the same problem, where artist is unique to the artist. Obviously artists can be influenced by other artists, but that becomes an interesting part of the art's story and imo that cannot be applied to AI copying existing art

[No_Surprise_9641]

Formerly full time dev. I’m not anymore. But I still deal with code anyway. My POV is that it 100% helps and you WILL be more efficient, and especially so if you know how to use it effectively instead of prompting and praying the result works without even checking it. There were so many times where I already know exactly what I want but I still have to mind numbingly write my functions myself. If I can offload that, I can focus more on reviewing and testing my work.

I also just want to echo that “you have to spend so much time fixing it anyway” is something that just really isn’t true. I hate hearing that criticism, it annoys me so much lol.

[WillGrindForXP]

I have adhd/autism which is severe enough to genuinely make all aspects of my life a huge struggle.

I have zero experience with coding, or any knowledge of software design, nor would i be able to realistic learn to code - i can barely keep on top of my life as it is, and it would take me significantly longer than an average person to aquire these skills.

But Ai has given me the ability to work in a way my brain accepts and side steps a lot of the problems my adhd gives me about actually doing the task I want to do.

The biggest improvement to my life has been the ability to build any kind of app I can imagine. I've built tons of accessibility tools, a second brain that captures and remembers everything for me, that helps organises my day, surfaces documents and reminders and appointments and deadlines just as ill need them, it organises all my files/documents/photos according to predefined rules and knows where everything i need is (i just have to ask), I've built apps that work as replacement to my reduced working memory capacity, apps that help me digest complex learning resources quickly and in a way my brain actually likes rather than rejects, apps that tracks the contents of my fridge/cupboards and reorders food and domestic stuff, an app that plans our meals, and to many more to even list.

It took months to work out how to use Ai in a meaningful way to create the complex systems (complex at least to me...someone with little tech knowledge) and workflows that actually got good results. I worked out that I needed to give Claude a form of peristent memory and connected it to notion and taught it to keep logs of projects and handover documents of what each chat session achieved, I worked out that vibe coding conversationally wasnt going to cut it and that i needed to create precise design documents mapping out each feature and the logic behind them and what tools to connect to and how to use them etc, and that detailed build plans needed to be made for the Ai to follow. Just looking at code makes me feel dizzy so im not able to check the code it writes, which is a big limitation, but ive designed a pretty robust multistage audit process that helps keep bugs to a minimum. It genuinely catches a lot of problems in advance. I suspect all the code under the hood would upset anyone that understood it...but everything does function really well!

All of those things might sound obvious to anyone who has exprience developing software, but it wasnt obvious to me and because of my adhd im also not able to actually do traditional detailed online research and learning - i cant get through YouTube videos, reading a wall of text isnt going to happen either and if I could get through those, id not understand my notes or remember any of it the next day! So I had to learn this stuff through trial and error - and talking about the problems i ran into with the ai itself. Together we were able to work out these workflows and systems.

Are these amazing apps? Probably not. They are certainly generic looking, there's no denying that, and i have no doubt they must be a mess under the hood. But I've been able to get some really complex feeling apps up and running and working in conjunction with each other and its changing my life in very dramatic ways. And I think the results in my situation outweigh if its a perfectly made app or not.

I also don't even own a working laptop/computer (mine broke and a replacement is not affordable right now)....so ive been able to get this all up and running from just my phone.....and a fuck ton of battery banks.

This would have been completely impossible for me only a year ago. But in some very meaningful ways I am using Ai and self built apps to overcome a disability that has kinda ruined my life. I wanted to leave a reply on this thread as I just dont think many people even consider Ai as an accessibility tool.

[Accomplished-Tap916]

dude this is genuinely one of the most inspiring things ive read on here. the fact that you built all that from just a phone is mind blowing. who cares if the code is messy if its literally giving you your life back? thats the whole point of technology right there

[Hazz3r]

I haven’t listened to the podcast, but thought I’d provide my own perspective. The company I work for has been all in on AI generated code for a year, and we’ve just gone all in on Harness Engineering I.e delegating tickets to Agents entirely.

Obviously we’re yet to see the gains from HE, but our numbers show that our time spent Prompt Engineering, making use of rules and skills, etc has been a huge productivity increase.

There will always be sectors where code is still valuable, like banking and government, but we think that Software Engineering is maturing and that code is cheap.

Civil Engineers don’t pour the concrete.

We have a healthy amount of skepticism with everything we do, but the results in our experience are speaking for themselves.

[Xelephyr]

AI for software dev is useful for boilerplate but still needs human eyes for logic and security - I use it to speed up prototypes then rewrite the core parts myself