Pod Insights Software Engineering Daily The 2025 Stack Overflow Developer Survey with Jody Bailey and Erin Yepis About this episode The Stack Overflow https://stackoverflow.com/ Developer Survey is an annual survey conducted by Stack Overflow that gathers comprehensive insights from developers around the world. It offers a valuable snapshot of the global developer community, covering a wide range of topics such as preferred programming languages, tools, and technologies.
Jody Bailey https://www.linkedin.com/in/jodybailey is the Chief Product and Technology Officer at Stack Overflow and Erin Yepis https://www.linkedin.com/in/erinyepis is a Research Manager at Stack Overflow. They join the show with Sean Falconer to talk about the results of the 2025 Developer Survey, which was recently released.
https://i0.wp.com/softwareengineeringdaily.com/wp-content/uploads/2023/10/Rectangle-3-2.pngSean’s been an academic, startup founder, and Googler. He has published works covering a wide range of topics from AI to quantum computing. Currently, Sean is an AI Entrepreneur in Residence at Confluent where he works on AI strategy and thought leadership. You can connect with Sean on LinkedIn.
Please click here to see the transcript of this episode. http://softwareengineeringdaily.com/wp-content/uploads/2025/10/SED1878-Stock-Overflow-Developer-Survey-2025.txt
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Transcript 0:00 Speaker 00 The Stack Overflow Developer Survey is an annual survey conducted by Stack Overflow that gathers comprehensive insights from developers around the world. It offers a valuable snapshot of the global developer community, covering a wide range of topics such as preferred programming languages, tools, and technologies. Jody Bailey is the Chief Product and Technology Officer at Stack Overflow, and Aaron Yepis is a Research Manager at Stack Overflow. They join the show with Sean Falconer to talk about the results of the 2025 Developer Survey, which was recently released. This episode is hosted by Sean Falconer. Check the show notes for more information on Sean's work and where to find him.
0:55 Speaker 01 Aaron and Jody, welcome to the show.
0:58 Speaker 02 Thank you. Great to be here, Sean.
1:01 Speaker 01 Yeah, and Aaron, I guess I should say, welcome back. This is now our annual podcasting event where we discuss the Stack Overflow Developer Survey, so I'm excited about that.
1:11 Speaker 03 Good, yeah, let's go ahead and get this set up for 2026.
1:14 Speaker 01 Yeah.
1:14 Speaker 03 Get it on the books early.
1:16 Speaker 01 Exactly. So I think we got a lot to cover. And before we get into it, I wanted you to help sort of frame what the Stack Overflow Developer Survey is for those that are not familiar with it. So can you give a quick explanation of what it is and what you're trying to accomplish with that?
1:32 Speaker 03 Yeah, so the Stack Overflow Developer Survey has existed for almost as long as Stack Overflow the site has existed. So this has been our 15th year of running it. It started as a very small thing. There's a lot of people on the site asking questions just to get that really clear aggregated view of what technologies are you using? Like, we can see what you're asking about, but it was just the most obvious question to ask that that community, and since then, it's grown into quite a bigger deal than that. But it's just a unique opportunity every year to get that temperature check from actual developers, from them directly saying themselves, instead of a third party inferring what
2:16 Speaker 03 it is that developers use and care about and do. And it means a lot to our community.
2:23 Speaker 01 What's the typical number of people that are participating, sort of the makeup of those developer profiles?
2:28 Speaker 03 So for the most part, the core group is, one of the questions that we ask is, do you code for work? So a majority of our users every year indicate that they are a developer by profession. So they're working as developers somewhere. This year it was 76% indicated that. But the survey is open to, you know, people that are students as well, or people that are adjacent in a way, like they're PMs, project managers and stuff like that. Besides that, we have a huge audience, obviously, here in the US. Of all the countries that responded this year, last year, and three years ago, the US, Germany, India, UK are always in the top five.
3:11 Speaker 03 This year, about, yeah, 50% of all respondents came from those four countries in addition to France and Canada. So we have a strong European, North American, and Indian developer group. And as we saw this year, what we have been seeing trending lately too, is that we have a lot of more experienced developers. So we ask this every year, how many years have you been coding? 2025, 65% of the respondents indicated they've been coding for more than 10 years.
3:40 Speaker 01 And Jody, did you have something you wanted to add about your perspective on why you do this and the value that it brings to the community?
3:46 Speaker 02 Yeah, so I bring a slightly different perspective because I was one of the people that was always looking at the dev survey as a dev manager, as a developer even, understanding what other people are doing. What are the trends? What can I learn? And as a hiring manager, it was always important to understand what tools and technologies people were using. So it was always a barometer. It was something I always looked forward to kind of see what was new and exciting, what people were thinking, and was super helpful just in terms of identifying trends as well as thinking about how I hire and create a place that people wanted to be a part of.
4:24 Speaker 01 Yeah. And I was saying, you know, sort of in the pre-show that I reference the survey all the time. I think that if you really want to start to sound smart in conversations, there's a lot of meat on the bone that you can leverage there for all kinds of different questions people might ask, like, how's Rust doing as a language? It's right there in the survey that you can use sound so smart, quoting some statistics around that. So
4:45 Speaker 02 That's one of the things, like, a lot of the places I've worked, we've been Polyclot, where there's lots of different tools and technologies, right? And everybody wants to use something new and cool, Rust, right? And the survey would be a good reference of, okay, well, if we're going to consider this, what is our hiring tool, right? I mean, do we really want to have a tool that maybe we can't find enough developers to work in and end up with this code base after our Rust, not to pick on Rust, but fill in the blank language de jour, you know, after that person, that advocate leaves, then what do we do? So the developer survey was super helpful in that way, too.
5:20 Speaker 01 Yeah, yeah. Is this like just a moment in time trend that we should invest in this company? And how does that impact us? Or is this something that's going to be, everybody's moving this way? I think the survey results certainly can help with those kinds of decisions within the company. From your perspective, and I'd love to hear from both of you, if you kind of have different views on this, like, what is the biggest story coming out of this year's developer survey? And maybe we'll go back to you, Aaron.
5:43 Speaker 03 Yeah, so I think the biggest story, and I would not be alone in thinking this, is the numbers we have around adoption, trust, and favorability. So for the third year, we see more developers than ever are using AI tools. And I should have mentioned that.
6:04 Speaker 03 Not just of, in general.
6:05 Speaker 02 I knew what you were talking about.
6:08 Speaker 03 I referenced this so much, I'm like, you guys know what I'm talking about. Because it was a pretty big story. So we see that for the third year in a row, we have this growing adoption of AI tools. Now we're over 80% of our respondents, 84% I believe, are using AI tools for work.
6:26 Speaker 03 But the trust took a dramatic dive this year compared to 2023 and 2024, and favorability did as well. So it's interesting to see that, wow, so more people are using these tools, but they don't like them and they trust them less. To me, I think it makes sense as you have, one, there's just more AI tools being developed. So you have a lot of things that you can try, a lot of things that could fit into your nuances of what your role is as a developer. So not just a one-size-fits-all type of deal. But I think we have these high expectations as well for certain developers. And of course, everyone knows when you have high expectations, there's more probability that you're going to be disappointed.
7:10 Speaker 03 I will say this, that when we look at specifically, we asked this year to use AI tools daily, weekly, less than weekly, like what's the variability in use there? There is a correlation that we see for the developers that indicated they use them daily. They have higher favorability scores than those that use AI tools less than daily. So I think it probably speaks to more of that learning curve, like, hey, I just tried a couple of things. Some of it didn't meet my expectations, but if I keep up with it and find out how to make this work, then I can figure out my expectations are at the right place. I'm using the tool for the right thing that works for me. And we also see with younger developers, developers that have less career experience,
7:53 Speaker 03 they have higher favorability and trust scores as well, which probably also just speaks to, hey, my bar was low already. I don't know what I don't know because I just started doing this job. So there's room to grow there as far as like those two things. And as I mentioned, we have a lot of very experienced developers that answer the developer survey. Of course, their expectations are going to be high.
8:14 Speaker 01 Yeah. So the key is set low expectations and then you'll be blown away.
8:19 Speaker 02 It's kind of like when you go see a movie and everybody told you it was amazing.
8:23 Speaker 01 Yeah, exactly.
8:24 Speaker 02 It's okay.
8:25 Speaker 01 Yeah, yeah. Nothing disappoints you like high expectations. So I would think too, as part of this, you know, we're becoming more comfortable with AI. It feels probably less magical because people are using. It day to day. So you're less blown away by it. And then also, I think if you're using it all the time, you naturally encounter the rough edges more often. The other thing I wonder, which could be a factor in terms of the decrease in trust and sort of people enjoying these tools, is that maybe in the early days, essentially, the collection of developers that were using them, were more the early adopters that were excited about this. And now a lot of companies are sort of taking the stance that, hey, if you're going to develop in our company, you have to use this tool. We purchased it. We want the efficiency gains.
9:09 Speaker 01 And now you're kind of, whether you want it or not, you're kind of being forced to use it, which naturally also creates sort of a negative reaction to it initially.
9:17 Speaker 02 Yeah, I think that's spot on. It's something I've seen, not just survey wise, but just talking to peers and other people in the industry. And when people, as you mentioned, are forced to use it, so to speak, especially a tool like this where my observation and experience, it's not like you're perfect right out of the gate, right? I mean, you have to learn how to use the AI tools and how to break things down into manageable pieces. And people are still experimenting as they're building things. You know, I talked to developers and it's like, well, I've got to figure out ahead of time, is it going to be more work debugging the code I generate? Or just easier to write it myself, right? And it's figuring out what that balance is.
10:01 Speaker 02 And going back to the high expectations and dictation, right? Nobody likes to be told what to do or how to do their job, and especially developers, right? I mean, we've always considered ourselves craftsperson where it's as much art as science. And then to have somebody tell you, oh, well, just generate a bunch of code and it'll be fine. That it discounts the value of what developers bring to their job. And there's also these super high expectations that all of a sudden we're going to have this massive increase in throughput. And, you know, if you think about it, and I always encountered this with pair programming or mob programming for my team. It's like, there's this assumption, especially by leadership or people that aren't in.
10:46 Speaker 02 The business that developers spend eight hours a day typing code, right? And we all know that's not the case, right? So if you think about the fact that developers spend twenty to forty percent of their time writing code, even if you improve the throughput there by cut it in half, it's still a small percentage increase in the throughput. That said, I think that's where there's real opportunity in terms of how to leverage AI and what I'm seeing with some of the thought leaders within my own team is identifying ways to reduce time on those things that aren't about writing code, right? The things that, whether it's collapsing meetings
11:26 Speaker 02 or if it's about figuring out how to think about designs and break things down more effectively. You see, oftentimes, those types of things using AI are really beneficial. So what I'm trying to do and encourage with my team is experiment with the different tools, find the ways that work best for you and help you, and not necessarily, hey, all code has to be written with an agent.
11:49 Speaker 01 Yeah, no, that's a really good point about the fact that an engineer's time is not hands on keyboard writing code all the time. So you're only going to get so much efficiency gain there, even if the tool is as successful as possible. I think like one area too, that I'm seeing a lot of investment from companies. I can't remember if there was anything covered in the survey, but I'm curious to hear your thoughts on is the bane of many teams' existence is on-call duty. And there's a lot of companies and investment on the AI front there of how do we alleviate some of the stress of being on-call, provide better tooling to solution those. And a lot of times too, if you're an on-call engineer, you might be on-call for systems that you're not necessarily working in all the time.
12:31 Speaker 01 So you end up inevitably having to go to someone who's like an expert in the company to ask them questions and then you're sort of taking them away from their time that they can be thinking about designs or executing whatever their job is. So it ends up being this sort of cascading effect of sucking up a lot of people's time. It's not just the person on-call, it's all these other people that might be involved in it.
12:51 Speaker 03 Yeah, so we didn't have a specific question about like that use case, which I do think is interesting, like kind of, yeah, that support aspect of things. But I will say that we did ask about what are like specific tasks? What are you using AI tools for?
13:10 Speaker 03 We created this visualization where it's sort of superimposed the tasks that people said they're mostly using AI tools for and the satisfaction that they have with AI tools. And we can see that for the most part, the people that use AI tools a lot are using it for searching for answers, which I think would be when you can't find the experts or the expert is not available.
13:33 Speaker 01 Yep.
13:33 Speaker 03 That's the use case. And if it's helping them, they are more satisfied with that use case, too, of all of the things that you can be doing with AI tools right now.
13:41 Speaker 01 Hmm hmm.
13:41 Speaker 02 Not necessarily related to the survey, but just my own experience and work with the team is using AI to explain code and break things down has been really useful. So you can imagine in that use case, and I see my, my quality engineers doing this to reverse engineer code, or as we're looking to break down really complex pieces of code, using AI in that way is really helpful. And you can kind of picture that as well from a support perspective, because you're right, it's like you have one person and you can't expect them to know the whole system. So how can you help break it down, make it easier to understand? I think there's real opportunity there. We see our infrastructure teams focused on improving those aspects.
14:21 Speaker 01 And that applies to new people on the team as well, or even junior developers, too, just helping to sort of grasp where things are, how the code's structured, having sort of a psychologically safe zone to ask an AI automation is, it might be in favor to having to ask somebody who's on the team. In terms of AI agents, there's a tremendous amount of hype right now around AI agents. And there's a lot of stats out there that indicate this could really be the next frontier of software, but the survey shows that adoption is still relatively low. What do you think is holding developers back there?
14:57 Speaker 03 So, yeah, we had a couple of questions where we asked about, in your own words, and for AI agents, we had this too, we asked about like, what is the impact for those that have adopted it? So sort of like backwards engineering that, what we see for those that have adopted it is that they were able to see productivity gates. And they were able to learn new things faster and upskill, reskill. So I think where the adoption is lacking is that whoever is in charge of either purchasing or making the decision, they're not able to connect the, this is a possibility.
15:40 Speaker 03 What does it mean for in time and money and what's the ROI on that? So there's people that have already taken the leap and they're able to show like, hey, my experience as a developer, this has helped me do this and this. It has saved me time. It has helped me learn. And there it's just like that, I guess, because we see generally surface level, a lot of feedback about AI, it's hard to connect that to the specific agents. Should I invest in that? Is that worth the time of standing it up, debugging a couple of things with integrations, get it running on a couple of local machines, having the team all in on it. We're all like on the same page. Like, yeah, it's going to take some time to invest.
16:23 Speaker 03 But we're seeing more of the good parts and we see that in the dev survey too, is that they've said, I use this for the people that have used it. Yeah, I have seen these impacts.
16:32 Speaker 02 Yeah. One of the challenges, and it goes back to the hype, right? Is the hype is way out in front of the actual engineering and the learning curve. And, and it's easy to forget, or maybe not, how fast things are changing, right? And how, especially as engineers, we're still just learning how everything works. I mean, MCP as a protocol is really new, but it's really powerful and it's changing the way people think. Building agents is
16:59 Speaker 01 It's not even a year old.
17:00 Speaker 02 Right? But it, it feels old already, right? It reminds me of, and you probably remember when JavaScript was taking off and there was, it felt like there was a new framework every week, right? It's like you didn't know what to do or how to do it. And it's kind of the same thing. So you've got the hype and you've got all the people out on social media talking about, oh, it's doing this. I did this in five minutes and you can do all that. But meanwhile, you know, all the engineers are trying to deliver all the things they are already committed to, trying to learn new tools, what it can really Do versus what people say it can do and then how do you scale it etcetera. So I'm seeing already people are starting to adopt and build agents that didn't know what an agent was six months ago.
17:40 Speaker 01 Right. And so I think Two years ago, no one knew what a vector was and then suddenly.
17:44 Speaker 02 Yeah.
17:45 Speaker 01 Everybody
17:46 Speaker 02 Right, it was aligned with two points, right, you know, from math and physics, right, but.
17:52 Speaker 01 So another trend that I think the survey talks about that also is something that we see a lot on social media and so forth. Besides AI agents, this is concept of vibe coding. So first of all, for those unfamiliar, can you explain what vibe coding is? And why do you feel it's kind of resonating with some of the new developers that are out there?
18:11 Speaker 03 Yeah, so vibe coding is just a terminology and it's codized in Wikipedia. I feel like it has some sentiment associated with it. I wanted to make sure whenever I ask the question, I'm referring to this thing. This is a social phenomenon. I'm not trying to put any shade on your work or what you do for whatever, however you get your job done. So it comes with a lot of, I feel like, very passionate emotions for some developers. But vibe coding is just you're using these AI tools to sort of tell you what to do. When you may have like zero to little knowledge about what it is that you're trying to accomplish.
18:53 Speaker 03 There's a lot of people that don't even have to touch a keyboard in order to create a whole app. They can just speech to text and then it does everything else in the background. So there's like levels to it, but at its core, it's just you're using these tools where your knowledge is not quite there. You're using it to bridge the gap in order to get something accomplished software code wise.
19:17 Speaker 01 Yeah, I think the survey said seventy seven percent of developers say vibe coding isn't really part of professional work. So do you think that this is primarily about enabling like a new class of user to create things? Or focus on certain types of side projects versus something that we'll see in a professional setting?
19:35 Speaker 03 Yeah, definitely. I think that for right now, though, the phrase itself isn't helping. It sort of just conjures up like an immediate reaction and we saw that. But in their own words, because this question on the survey was an open response. So I let them say whatever they wanted to. And then I used an NLP algorithm to sort of group it all together. So I had like responses that were like emphatic, no, I am not vibe coding.
20:02 Speaker 01 Yeah. Did you get any sentiment analysis on that? I'm sure there's wild swings.
20:08 Speaker 03 There's lots of good stuff there, but I think so. Another indication, and Jody already mentioned this earlier too. It vibe coding is associated, I think, with this future tech debt. So your coworkers, your peers don't want to hear about you pushing this vibe coding idea. Because to them, they're like, that's just something I have to fix later. And we know that, yeah, 45% of developers indicated that debugging AI generated code was their top frustration with using AI tools.
20:38 Speaker 01 So outside of AI, based on the survey, are there any technologies, frameworks or shifts that kind of stood out in the data that people are excited about?
20:49 Speaker 03 Some of the things that I've noticed as far as the what's been growing in usage and popularity for technologies. I mean, it's not new, but we see, I created this new section. So we kind of grouped all of the, the cloud, DevOps tools, technologies, platforms together. And we see that now that we know when people can focus on it. Because a lot of these tools, especially when you look at some of the things that are being used for AI as well, it's old stuff that's being repurposed. It's like, oh yeah, this is perfect for this use case too. We are seeing this just like growing usage of cloud technology. We saw a huge jump in people using Docker and Kubernetes, which again, these have been around for a while.
21:31 Speaker 03 They've been on the survey for a while, but I just think we're now getting to like that point where everyone, it's just becoming more standardized. Postgres SQL, you know, again, an old favorite, but is coming back the spotlight because of AI that's just being kind of repackaged or remarketed in a way for that. So we saw a huge jump in usage for that this year too.
21:52 Speaker 01 There was also in the last year, really that sentiment around like Postgres for everything movement. We don't need all these other databases, just use Postgres to solve all these problems. So I wonder if that kind of impacted responses that we saw in the survey.
22:05 Speaker 03 Yeah, probably. Again, because we have a majority of more experienced developers. They've been around, they've seen like, hey, if you made it this far by career, probably this is a good thing to keep using. So it's moving to something that's just brand new. But yeah, other than that, it was also interesting to see. So you know, Stack Overflow itself, we have a new new section where we asked about which of these like new popular tags, what are you interested in as far as the technology goes? So while people associate Stack Overflow with the top three HTML questions, JavaScript questions, Python questions. We see a growing interest and a lot of popularity, a lot of people that are using these technologies
22:49 Speaker 03 for those AI tools. Well, large language models as a tag is growing in usage. MCP growing in usage. We also see RAG as a tag growing in usage. So that was pretty cool. It shows again, it's that temperature check on on the developer community that that we have access to.
23:08 Speaker 01 Was there surprises in the survey? You know, things that came up that are different than prior years that you weren't expecting?
23:17 Speaker 03 Yes. So this year, I added a question at the very end. So if you made it all the way to the end, which a lot of people did, I just asked general survey feedback, like, hey, was this too long for you? And then two, open response, general feedback. And I got a lot of feedback. So it was pretty cool to see that they took the time. Again, they took the whole survey and then were able to leave feedback. But a lot of that feedback was general annoyance of having to answer so many questions about AI.
23:51 Speaker 01 Yeah, I think that's kind of some of the things that we touched on earlier. I think there is like a, it's natural where there's such a saturation of something in a market for people to start to become negative towards. It's like overexposure of even in media is like, okay, we have no game shows and then we have too many game shows, or we have no reality TV and then we have too much reality TV and then people become turned off. And we're probably going through the downturn in, I don't know, comic book movies right now. It's like, okay, well, we got oversaturated. Now we need to contract the market essentially. Maybe we're seeing some of that with AI as well. What do you think engineering leaders should take away from some of the findings?
24:30 Speaker 01 Around team productivity, training, tool adoption, like, how should people be thinking about that?
24:34 Speaker 02 I think, you know, similar to things I've been saying, that in terms of adoption, engineering leaders need to think about how do they get their engineering teams to leverage AI to create the outcomes that they want, right? Which isn't necessarily to write more code faster, right? It's to deliver business outcomes, it's to provide solutions. I think that it's important that they give the developers opportunity to experiment with different tools in order to find what works best for them. I think the other thing that is clear is that as people are using AI, they need help, an expert help, right? There's a certain point where there's a lack of confidence in the output.
25:17 Speaker 02 And one of the things in talking with other peer, they talked about is, well, when I get stuck, I just talk to, you know, somebody in my network, right? Well, not everybody has a large network and then, you know, they don't necessarily have a large community to talk to. And that's one of the things that we want to support from Stack Overflow is to be that place where people can go and get help when they get stuck. So I think making sure that the engineers have different tools to choose from, look at different ways to leverage them to their advantage, take advantage of their own community within their organizations, but then also, you know, look to places like Stack Overflow to share and learn, because we're all still figuring out how to use it to be really effective.
26:00 Speaker 01 It's like developing any new skill set. I think when, the more sort of exposure you have to these tools, the better you get at aiming them to generate the outputs that you want and the value that you want. But that can be hard for a company that's investing in these technologies, kind of expecting like some, you know, ROI delivery immediately and not sort of factoring in the account, the training aspect of it. And then it's also something that's so net new for every company, like you can't find somebody with 10 years' experience, you know, doing this ROI on. So, you know, where do you go? Where is your source of information? It's either trial and error, which might take time, or you have to go somewhere else. And historically, when it comes to learning new programming languages, new frameworks,
26:42 Speaker 01 it's really the community that's helped people facilitate that process. It seems like there's a gap in the market when it comes to these AI-powered developer tools.
26:51 Speaker 02 You need the collective power to figure out how to use the different tools. And some of the things like we're trying to figure, I'm trying to figure out is when you think about implementing AI in your products, right? A big part of how you implement is creating the appropriate prompts, right? And who's an expert at writing prompts? There really aren't any, you know? Is it the product manager because they understand the product and the spec? Is it the MLE or data scientist because they understand how it works? Is it the software engineer? What I'm seeing is it, it kind of takes a village, you know, to really figure those things out. Because there are no experts out there, or at least none with tons of experience.
27:33 Speaker 02 Because people have been at it less than two years, even if they were there at the beginning.
27:38 Speaker 01 I think another aspect of this too, whether it's you're, you're building AI systems or you're adopting these types of software tools is how are you measuring results? What are you seeing from companies with that aspect? Like, you know, I go and I bring in some AI agent coding tool. Are companies thinking about how are they actually going to measure the results of whether this has an impact or not?
28:01 Speaker 02 Yeah, see a variety of different things and, and no real standards, right? It's, you know, a lot of it is just easy. How much code is generated by AI agents or tools? It's not always easy, right? But some tools, I think Copilot, for example, will help you understand how much code. You can look at, you know, what is your cycle time? How long is it taking from the time you do a pull request to the time you deliver the code? You know, are, are those periods of time shortening? But at the end of the day, you know, what we all care about as leaders is delivering results. And are we getting the results to users faster? You know, so I think some of the tried and true metrics still apply, whether it's DORA
28:42 Speaker 02 or lean metrics in terms of understanding, you know, how long does it take to deliver value to the user? At the end of the day, that's really what matters, not how much code we generated by AI or how fast the code was written. It's how quickly are we delivering results?
28:58 Speaker 01 Yeah, yeah, exactly. Wines a code is probably not a good measurement.
29:03 Speaker 02 Oh, no, I gotta change everything.
29:07 Speaker 01 You touched on this a little bit, but how do you see the role of communities like Stack Overflow sort of evolving in AI era? Especially where there's it's debatable how trustworthy sometimes AI answers are, you know? How are you thinking about that?
29:20 Speaker 02 Yeah, you know, so spend a lot of time thinking about that, obviously. And I think it's different, but the same, right? And what I mean by that, as we've been talking about, people are still figuring it out. And being able to take advantage of a large community or population of people is really still our best way of kind of getting to grounded truth. And so, you know, I think that it's what we need to do is we need to find ways to create opportunities to ask questions about some of these things that people are encountering, making it easier. For example, to take a prompt and put it on a site like Stack Overflow, create a question and be able to get an answer.
30:03 Speaker 02 That means we've got to adapt how we think about questions and answers on our site. At the same time, one of the things that we're seeing, it just somewhat independent of AI, but in part because of that, you know, people are looking for quicker answers. They're looking for, you know, smaller communities even, right? When you have a million people that you're interacting with, it doesn't always feel like the community. And we're seeing a lot of the newer developers and the non-traditional developers, right? We haven't really talked a lot about that, but more and more people are writing code that aren't traditional developers. How do they find people that they can talk to, that they can get feedback? And so you see a lot of micro communities out, you know, whether it's Discord or other things.
30:48 Speaker 02 And so with Stack Overflow, you know, we're looking at ways to create easier ways for people to connect, you know, identify their community, their tribe, if you will, be able to ask questions and get answers. And so while it's evolving and different, it's kind of the same.
31:02 Speaker 01 Yeah, I think what you said about the niche communities, I think that's kind of a trend that we see. Even outside of developers is across like all like media, basically is there's something for everybody regardless of what your interest is and you can kind of find your tribe out there on the internet now and connect with them. So people are able to go a lot deeper sort of into their interests. It doesn't necessarily have to be like mainstream interests. It's not the days when we had, you know, four channels on television and two radio stations. You're bombarded with a plethora of things that you can distract your attention with.
31:34 Speaker 02 Right. Yeah, you're dating us both now. So.
31:37 Speaker 01 Yeah. So if we look ahead to say the 2030 survey of this, so five years from now, do you think developers are still going to be wrestling with some of these concerns over trust for AI? Or do you think that's something that will solve between now and then?
31:53 Speaker 03 So I think when you talk about trust, there's a couple of different things going on. I think in five years, we will get better tools that don't hallucinate as much as they do now. Probably, yeah. But trust is a human emotion. Trust is something that humans have evolved to learn, discern. You know, when you talk to someone and you, you have to like immediately make a, a value judgment. Do I trust what this person is saying to me? And I think we asked specifically in this survey, like about why would a developer continue to ask a human being questions if AI can answer all your questions? A lot
32:36 Speaker 03 of the open responses for that indicated that AI is no replacement for a human being. There is no sense of trust with AI. AI cannot learn trust. I want to trust something or someone that learns trust itself. So it's like reciprocated reciprocal trust. So I don't know that we're ever going to see that sort of trust, that specific level of trust get very increased that much. I think the tools are going to get better for sure. But in the end, again, going back to this idea of communities and niche communities and of course, people not spending eight hours a day at work, just coding, straight up coding, like there's more to the experience and to the creativity and trust and all of those
33:21 Speaker 03 like human aspects of building that is not replaceable and people do not seek to replace it.
33:28 Speaker 02 I agree. The lack of trust, let's see if I can say this right, will approach zero, right? But it won't get there, you know, in 2030, isn't that far away, I guess. It sounds so far away, but yeah, it's five years, right? So I don't think that we'll get to a point where people trust AI a hundred percent, you know, in that timeframe. They'll trust it more. They'll still want to validate things. They'll need the human connection, even thinking about cloud and how old that is. And you still have people that aren't comfortable going to the cloud, right?
34:01 Speaker 01 There's still security, privacy concerns with the cloud, exactly.
34:04 Speaker 02 Yeah, exactly. And AI is so much more of a mystery than cloud, right? So I think that it's going to be a long time before we get that far in terms of trust.
34:16 Speaker 01 I also think AI has the challenge, and I think robotics is similar, where there is doing something that historically feels like uniquely human, whereas like cloud infrastructure is not like, oh, okay. It takes more of a mental leap to anthropomorphize that. Whereas if I can, you know, chat with a system that, you know, sounds human enough, then that also, I know, evokes a different emotion, I think, in people than an infrastructure system.
34:43 Speaker 02 Yeah, yeah, we tried to use pets and cattle to, you know, with cloud, right? But it's not the same.
34:49 Speaker 01 Yeah. So as we get close to wrapping up here, is there anything from the survey or other insights that you, you know, stand out that is worth having a conversation around, anything that we missed?
35:03 Speaker 03 There's so much, you know, it's hard to focus and hone in on just one set of interesting insights. I will say this, you know, every year, try to get better at getting the most answers for specific questions. I feel like over the years, we've gotten a lot of great feedback. One, gotten a lot of great feedback about job satisfaction question in the survey. So specifically, you know, job market for software engineers hasn't been great in the last couple of years. So they have a place to sort of like specifically go talk about that there. And, you know, I did a little analysis where we asked about job satisfaction last year and this year. We saw a little bit of an increase last year.
35:46 Speaker 03 One in five developers said they were happy with their job. This year is one in four. Probably has a lot to do with the job market. But when you look at that, I ran a, an analysis, just a, a simple regression against how many tools, we asked this year specifically, how many tools are you using at work? So you can add a number. And when you compare it to job satisfaction, because we know developers are using a lot of tools. Now there's a whole bunch of AI tools out there, too. We see that people that are satisfied with their jobs, the number of tools that they're using for work, it doesn't affect that. So I think that was interesting, mostly because while it must be annoying for a lot of people
36:26 Speaker 03 to have to learn how to use a new tool, if it's like sort of mandated, like you were talking about earlier, like we have to use this. I think developers like using a lot of tools. I think there's like things that are like, no, I, I like having this specifically to do this. And it's not, uh, the number of tools that's really sort of dictating like whether they're happy at work, which is good because I can only see that tool number increasing. When we talk about this, yeah, it by 2030, I think that that probably will go up a little bit, but it won't be for, I think we'll adapt to that, too. And, and things are going to be more integrated, hopefully, and just easier, you know, like everything you log in once and it works and you got your two FA, it's already done and stuff like that.
37:11 Speaker 03 So I thought that was pretty cool.
37:13 Speaker 01 And George, do you have anything to add?
37:15 Speaker 02 I mean, I think the one that always stands out for me is the happiness at work. It hasn't changed a ton, but I was, it's gone up, which is good, but it's, it surprises me, right? My expectation or maybe my hope is, you know, there's more, more developers are happy at work. You know, especially early days and dating myself here. And people became developers because they were passionate about what they do, passionate about writing code. And, and they loved doing that. And, you know, my hope is that they continue to love the craft, you know, the art of creating new solutions via code or vibe coding or whatever the right phrase is. And, you know, it comes back, I think, a lot to people feeling like they have the autonomy.
38:00 Speaker 02 To choose what and how they do it, what tools they use and how they do it in order to create those outcomes. And I suspect that the more we try to dictate, you have to do it this way. You know, it's going to create more and more challenges in terms of that happiness with the workforce. So hopefully with AI tools, engineers will find ways to adopt it, you know, to automate and get rid of the parts of the job that they don't enjoy. And focus on the things that they really do enjoy, which is, you know, creating solutions for people.
38:31 Speaker 01 Yeah, I think that's the ideal. That's the goal would be, can you give people back time to spend on the things that they're more interested in? That makes them more happy and satisfied, like whether that's, you know, solving more complex problems, whatever it happens to be versus more with the more mundane sort of types of things that you need to do. And I think that's not just about developers, but that's across the workforce is the, that's the ideal state. I don't know that we're there yet, but hopefully we can get there.
38:59 Speaker 02 Agreed.
39:00 Speaker 01 Jody, Aaron, this was fantastic. Thanks so much for doing this. Thanks for coming on the show and cheers.
39:05 Speaker 02 Thanks. Take care.
Next Radix UI with Chance Strickland Page updated November 6, 2026 · transcript and summary are machine-generated