Stack Overflow✓

According to our 2026 Developer Survey, 55% of devs think that AI performs well or very well at complex tasks—although 39% think it's only good, not great. We want to know what kind of complex tasks you're handing off to your AI tools, especially in autonomous agent workflows. If you're using agents to get work done—especially at a smaller company—we want to hear from you. We're recruiting for paid research interviews across engineering, product, support, and more.

You need verified knowledge to build. You don't need to be wasting your time searching for it. This month on Stack Internal, we're introducing everything from Scopes—a new way to deliver focused context to your team and AI agents with permission-governed spaces—to a Github connector to new moderator tools. And that's just the tip of the iceberg. Explore the newest features on Stack Internal, the trusted knowledge layer for your AI tech stack:

Finding important context shouldn't be a scavenger hunt through old chat threads and scattered repos. With the October release for Stack Internal, we're bringing you Scopes, a new way to create permission-governed spaces so teams and AI agents get focused knowledge without unauthorized exposure. Plus we're launching an out-of-the-box GitHub connector, service accounts, and new expert validation tools, so your teams and AI tools can stop searching and start building. Learn more about Stack Internal:

According to our 2026 Developer Survey, 63% of developers using AI agents are letting them run every single day. But what does that work actually look like? We want to know—and we're recruiting for paid interviews to learn more. If you're using agents to get real work done, whether that's in engineering, product, support, operations, or marketing, we want to hear about it. Sound like you? Tell us a little about what you're doing for a chance to participate in our paid research interviews:

🎙️ At @OpenAI Dev Day 2026, host Ryan Donovan sat down on the Stack Overflow Podcast with OpenAI's Andrew Ambrosino @ajambrosino for a conversation on OpenAI's strategy for merging ChatGPT and Codex into a unified experience, the advantages of localized computer access in their successful desktop application, and the technical hurdles of constructing ChatGPT Spaces to support real-time multi-agent collaboration. Listen to the episode:

Building an AI context layer in-house seems like a piece of cake for a capable engineering team. But six months later, maintaining it has become your platform team’s full-time job. Keeping the pipeline trustworthy, organized, and compliant actually costs more than you think. Eira May dives into the true cost of an in-house knowledge system and what you should keep in mind when you're deciding between build vs. buy.

🎙️ We're joined by Gabriela Moreira @bugarela, CEO at @quint_lang, about why formal specification languages like TLA+ are essential for catching system design flaws before writing code, how Quint brings developer-friendly syntax and executability to formal methods, and the ways trace validation and model-based testing can verify AI-generated code against real-world production data.

Engineering job titles are evolving so quickly that traditional hiring strategies are struggling to keep up. In this Q&A with Corey Hymel, @Andela's head of research dives into how emerging roles are actively reshaping modern tech teams, and how to tell the difference between fleeting industry buzzwords and the foundational technical skills your team actually needs to build right now.

It seems the days of the fully packed office are officially behind us. According to our 2026 Developer Survey, 35% of devs are coding completely remote, 36% are navigating hybrid life, and only 18% are heading into the office everyday for in-person work. Dive into the full results on work, technology, community, and more from the Annual Developer Survey:

🎙️ We sit down with @josh_triplett from Rust's leadership team to chat about how the borrow checker delivers compile-time memory safety without garbage collection overhead, why Rust consistently ranks as developers' most loved language by providing psychological safety for complex systems, and how strict compiler constraints make Rust an ideal target for AI coding agents.

Stack Overflow for Agents started as a hypothesis—what would happen if we brought the power of Stack Overflow's knowledge exchange to AI agents? And in just a few weeks, with the help of Codex, a scrappy two-person team brought it to life. Our VP of Product, Alex Lato, shares with OpenAI for Startups how Codex helped our small but mighty team quickly launch Stack Overflow for Agents and bring a ChatGPT plugin to market, allowing our community to turn scattered information into verified knowledge for agents, minus the friction.

🎙️ We're joined by Yanbing Li, Chief Product Officer at @datadoghq, to talk about applying observability to non-deterministic AI agents, blurring the boundaries between software development and production workflows, and navigating emerging challenges in AI security and tokenomics.

Work hasn't gotten easier for developers. According to this year's Developer Survey, unclear priorities (17%) and inefficient processes (15%) are developers' top cited difficulties at work, showing that operational friction is a main workplace challenge for the modern software developer. Explore the results of the 2026 Developer Survey:

According to this year's Annual Developer Survey, about 70% of devs turn to AI agents when faced with a problem they need answers to.But that doesn't mean everyone is turning away from communities like ours—69% of respondents still used Stack Overflow in the last year, including the developer quoted below! Dive into more results on community, technology, and knowledge in this year's #DeveloperSurvey:

As enterprises turn more to coding agents to build applications, organizational knowledge that users can trust and agents can understand is more important than ever. Stack Internal is where thousands of enterprises are building that organizational knowledge. @InfoWorld's Anirban Ghoshal @journoanirban explores how Stack Internal's latest release is equipping AI agents and developers with verified enterprise knowledge backed by trust scoring, MCP server integrations, and expert validation workflows.

We chat with Julien Verlaguet, CEO at Skip Labs, about finding the balance between human tolerance and tooling constraints, the spectrum of typed programming languages, and building cost-effective tooling for AI agents.

For nearly two decades, Stack Overflow has been the number one place for developers to find verified knowledge. Now, we're using our core curation mechanism to bring critical context to enterprise AI with Stack Internal, the trusted knowledge layer for AI. Our VP of Product, Alex Lato, shares how we're evolving Stack Internal so your teams and AI tools have the accurate, complete, and vetted information they need to do their best work. Get started on Stack Internal for free:

This is the 16th Developer Survey, which means it’s old enough to drive in the US 🎊 For the Dev Survey's 16th birthday, we're sharing tech insights about everything you want to know—from how AI and layoffs are affecting developer careers to the rise of SQL on the tech leaderboard to what skills developers are learning and where. Hand the keys over to us, and let’s get rolling!

Your AI tools need context more than ever—but they’re only as smart as the data you feed them. More context isn’t the fix. Accurate knowledge is. Join us for a live look at Stack Internal, the trusted knowledge layer for your AI tech stack. We’ll show you how it captures and validates information from your existing tools so your team—and your AI models—can act on facts, not guesses. Save your spot for our Thursday, October 29 webinar:

We sit down with Div Garg, CEO at @agi_inc, to talk about running AI agents entirely on mobile devices, optimizing models for edge computing chips, and building safety mechanisms into autonomous app interactions.

The results of our 2026 Developer Survey are here 🤖 This year, we’ve got the scoop on everything you want to know about the developer community, including how technologists are thinking about AI, where they’re learning new skills, how happy they are at work, and what programming languages they’re using. And that’s just the tip of the iceberg of what we’ve learned from the over 30,000 developers who participated in this year’s survey. Dive into the results of our Annual Developer Survey: