RIP StackOverflow? In July 2023 we talked about the impact of ChatGPT and Copilot: This was then disputed by StackOverflow, who pointed out (very fairly so) that there were privacy-related changes in their analytics instrumentation in 2022. StackOverflow no longer reports traffic, but based on StackOverflow’s continuing transparency we can see that organic declines have continued throughout 2023.

Retool’s report comes over a year after those changes and has some self reported samples from users: * 57.6% of people said they have used StackOverflow less; almost all of them replaced it with ChatGPT and Copilot. * 10.2% said they no longer use StackOverflow. We also saw a lot more tools being released in the dev tools space such as (one of our oldest pod friends) Codeium (which just raised a $65M Series B), SourceGraph (and their newly released Cody), Codium AI (just released AlphaCodium which was picked up by Karpathy), Phind (which beat GPT-4 with OSS models), and Cursor, one of the most beloved products in the dev community at the moment. Intelligence is getting closer and closer to the IDE, and the trend doesn’t seem to be reverting. We already said that “You are not too old (to pivot into AI)“, and the advice still stands. When asked to rate “Preference for hiring engineers effective at using ChatGPT/Copilot for coding” on a scale of 1 to 10, where 10 is “Much more likely”, ~40% of companies voted 8-10. Having an AI Engineer skillset is extremely important. 45% of companies between 1,000-4,999 employees said that they increased the difficulty of technical interviews to compensate for these new tools, so the gap between users and non-users will keep widening. Crossing the AI in Production Chasm Geoffrey Moore’s “Crossing the Chasm” is one of the most quoted business frameworks. Every market has an initial group of Innovators and Early Adopters, who are willing to suffer through the rough edges of products initially, and eventually crosses into the Early Majority, which expects a full product. In the AI world, ChatGPT and Midjourney / DALL-E have crossed the chasm in the consumer space. Copilot is probably the only tool that did it in the enterprise, having crossed 1M paid users. ~$50B were invested in AI in 2023, and we still only have According to the survey, only 25% of companies had real production usage, but 77.1% said their company is making efforts to adopt more. Closing that gap could triple AI adoption in one year. The report also broke down adoption by use case. 66% of companies use it internally, while only 43% do so in customer-facing use cases. Internal usage of AI is much more varied than customer-facing one as well: One point that David made in the podcast is that this number isn’t a knock on AI as a tool, but rather about the demographics of businesses outside of our Silicon Valley bubble: We all work in Silicon Valley, right? We all work at businesses, basically, that sell software as a business. And that's why all the software engineers that we hire basically work on external facing software, which makes sense with most software companies. But if you look at most companies in the world, most companies in the world are actually not software companies. […] Most of the [work of] software engineers in the world actually goes towards these internal facing applications. Beyond code models, it’s clear that the big winners of the first wave of AI adoption are vector stores and RAG. Knowledge base Q&A, customer chatbots, recommendation systems, etc are all based on them. Retool even rolled out their own with Retool Vectors. Expect the battlefield to get even hotter in these areas, with Mongo and Chroma leading the charge on a NPS/popularity basis. It’s also clear that OpenAI won the first campaign in the AI models war, by far. Hopefully Mistral and LLaMA3 will shake up this chart when we look back at it in 2025: TLDR: We’re really early. If you want to build in AI, there’s a ton of work to be done, and a lot of problems to be solved. You can find the full report here to dive through all the numbers. Video podcast Watch along on our snazzy YouTube! Show Notes Companies and Projects: * Retool * State of AI Report * Retool AI * Retool Workflows * Raising less money at lower valuations * Paul Graham's "playing house" essay * Gödel, Escher, Bach (GEB) Timestamps * [00:00:00] Introduction * [00:02:43] Retool's founding story and decision not to present at YC demo day initially * [00:09:08] Philosophy on fundraising - raising less money at lower valuations * [00:12:53] Overview of what Retool is * [00:15:41] Origin story of Retool AI product * [00:19:59] Decision to use open source vector database PG Vector * [00:21:29] Most underrated AI use cases * [00:25:56] Retool's AI UX and workflows * [00:30:38] Zapier vs Retool * [00:32:54] Updates from Retool's 2023 State of AI survey * [00:35:21] Who is adopting AI first? * [00:37:40] Evolving engineering hiring practices in the age of Copilot/ChatGPT * [00:40:02] Retool's views on internal vs external AI adoption * [00:41:50] OSS models vs OpenAI in production * [00:44:46] Additional survey questions to ask in 2024 * [00:47:04] Balancing enterprise sales vs bottom-up adoption * [00:51:54] Philosophical thoughts on AGI and intentionality Transcript Alessio [00:00:00]: Hey everyone, welcome to the Latent Space podcast. This is Alessio, partner and CTO in Residence at Decibel Partners, and I'm joined by my co-host Swyx, founder of Smol.ai. Swyx [00:00:16]: And today we are in the studio with David Hsu from Retool. Welcome. David [00:00:20]: Thanks. Excited to be here. Swyx [00:00:23]: We like to give a little bit of intro from what little we can get about you and then have you talk about something personal. You got your degree in philosophy and CS from Oxford. I wasn't aware that they did double degrees. Is that what you got? David [00:00:35]: It's actually a single degree, which is really cool. So basically you study content, you study philosophy, and you study intersection. Intersection is basically AI, actually, and sort of computers think, or computers be smart. What does it mean for a computer to be smart? As well as logic. It's also another intersection, which is really fun too. Swyx [00:00:51]: In Stanford, it might be symbolic systems or whatever. It's always hard to classify these things when we don't really have a word for it. Now I guess everything's just called AI. Five years ago, you launched Retool. You were in YC at winter 17 and just been a straight line up from there, right? David [00:01:09]: I wish. Swyx [00:01:10]: What's something on your LinkedIn that people should know about you? Maybe on their personal hobby or, you know, let's just say something you're very passionate about. David [00:01:17]: Yeah, sure. I read quite a bit. I probably read like two books a week around about. So it's a lot of fun. I love biking. It's also quite a bit of fun. So yeah. Swyx [00:01:25]: Do you use Retool to read? David [00:01:27]: No, I don't use Retool to read. No, that'd be funny. Swyx [00:01:30]: What do you read? How do you choose what you read? Any recommendations? David [00:01:35]: I'm mostly reading fiction nowadays. So fiction is a lot of fun. I think it helps me be more empathetic, if you will. I think it's a lot of fun. I actually just want to see what it's like to be in someone else's shoes. That's what I really good about philosophy as well. I find philosophy just so interesting, especially logic. We can talk more about that for probably hours if you want. Swyx [00:01:50]: So yeah, I have a casual interest in epistemology. And I think that any time you, you know, you're trying to figure out a way to solve a problem, you're going to have to figure out a way to solve it. David [00:02:05]: Yeah, totally. What does it mean to know? Alessio [00:02:13]: That's its own podcast. We should do a special edition about