Stack Overflow

🎙️ We welcome McLaren Stanley, Senior Principal Engineer for Amazon Stores, to discuss what it actually takes to make teams AI native, why agentic engineering is shifting code bottlenecks downstream to testing and deployment, and why robust validation is essential to build trust and enable “fearless commits.” https://lnkd.in/gesRqV6W

For engineering teams who can build their own AI knowledge system, an in-house build seems like a no-brainer. But just because you can build it yourself doesn't mean you should—especially when you don't know how much it'll really cost you. In this article, we dive into what it takes to build your own production-grade knowledge pipeline, how much it'll actually cost your team to create and maintain, and why building a context infrastructure yourself might be the wrong decision for your business. https://lnkd.in/gN-MeVCm

Stack Overflow was everywhere at #Ai42026—from the floor to the stage. Our very own Ryan Donovan took the stage with PayPal's Srini Venkatesan for a fireside chat on closing the gap between AI capabilities and impact, while Stackers on the expo floor spoke with attendees about how we're building the trust layer for enterprise AI with Stack Internal. Learn how Stack Internal turns your existing foundation of knowledge into enterprise memory that your people, teams, and AI agents can act on: https://lnkd.in/gUfRmCgJ

🎙️ We welcome Anurag Goel, CEO and co-founder of Render, to discuss why most startups shouldn’t start by managing their Kubernetes and cloud infrastructure, why we're heading to a future where your application itself may allocate its own compute, and why DevOps jobs aren’t going anywhere. https://lnkd.in/gAu8dC7f

When it comes to AI-augmented engineering teams, it can be easy to focus solely on the one or two engineers who are suddenly operating at a different scale. But real impact isn’t about individual heroics. In this Leaders of Code companion piece, Eira May dives into the explorer vs. exploiter binary, the myth of the 100x engineer, and what steps leaders can take from how Snowflake's Vivek Raghunathan built a successful AI-assisted engineering organization. https://lnkd.in/gGcGv37H

Your semantic layer doesn't eliminate data risk. But it does change the economics of data risk. In this Dispatch from O'Reilly, Blue Yonder's Jeremy Arendt explores the semantic layer as a risk mitigation strategy and why a single source of truth is the best way for organizations to tackle the practical, operational risks that come from bad data management. https://lnkd.in/gws7TW_w

🎙️ We welcome WP Engine CTO Ramadass Prabhakar to the show to chat about what happens—and what we should do—when agents start acting like humans online, how our internet is evolving to serve both human and agentic experiences from the same interface, and what we can do to differentiate and protect human actions online from malicious bot activity. https://lnkd.in/gAEuge4p

Your unique organizational knowledge makes the work you do possible—but it's being spread thin across platforms and tools. When your AI agents can't reliably access up-to-date information, they start to make historical mistakes at machine speed. That's why you need Stack Internal. Our latest release turns your existing foundation of knowledge into enterprise memory that your people, teams, and AI agents can act on. Learn about Stack Internal's new capabilities and how we’re building the trust layer for enterprise AI: https://lnkd.in/edjiNWYA

Prompts sent, tokens spent, and lines of code generated can seem like good metrics when tracking your AI productivity. But they fail to answer one important question: did your software get any better? Our VP of Product Alexandra Lato shares with HackerNoon the real cost of only measuring AI productivity, and why engineering leaders should be focusing on outcomes and developer satisfaction instead. https://lnkd.in/gdC8vqjr

If your favorite kitchen knife kept changing shape, you’d probably stop using it. The same goes for our dev tools, which we love because of their predictability and trustworthiness. But what happens when agentic coding fundamentally changes the nature and stability of these tools? Ryan Donovan dives into how our dev tools build trustworthy processes, the ways that tool changes highlight but can’t fix broken processes, and where tooling and culture can work together to build new trust. https://lnkd.in/dr5tMDTw