Earlier this month, my team at Stacklok surveyed 520 technical leaders to understand whether they were concerned about being locked into frontier labs. The data says they’re already swapping models in and out, but the trap they’re concerned about is the layer on top of the model.

Craig McLuckie

A maturity model for taking agents from an impressive demo to a system people can depend on — with a self-assessment and the map to a deep-dive on each layer.

Most engineering teams capable of building an internal AI knowledge system think they should. But six months later, it's a platform team's full-time job. Building an in-house AI context layer costs more money and energy than you think.

Eira May

While the whispers say that everyone is becoming a generalist, that's not where headcount is going.

Ryan Donovan

It’s gotten exponentially harder to identify talent that we feel is a good fit for our teams at the top of the application funnel.

Tom Harvey

Agents don't build trust for another reason, structurally worse than the first. It isn't only that the tool keeps changing shape. It's that the feedback loop you would need in order to learn the tool is broken at the point of measurement.

Chase W. Hughes

This analysis compares the 2024 and 2025 Developer Survey data across three connected stories: the evolution of AI, humans at work, and demographics and community.

Erin Yepis

AI can make the first part remarkably fast. It can find the page, the discussion and the person who might know. The harder work begins when those sources disagree, or when they become stale.

Alex Lato, Peter O'Connor

We've learned a lot in the last three months since launching Stack Overflow for Agents, our API-first knowledge exchange for agents. Here's a few of our findings, what's new on the platform (including our new ChatGPT plugin), and how we're continuing to build Stack Overflow.

Phoebe Sajor, David Gibson

For the past few years, we’ve been looking at ways to bring a little more of the individual developer back to Stack.

Philippe Beaudette

Organizations cannot solve shadow AI with a document employees read once. They need to make responsible use easier than improvised use.

When code gets cheap, the hard part is deciding what “correct” means and building a reliable way to check it.

Markus Eisele

In this No Dumb Questions, Phoebe asks Stack’s Engineering Manager Doug Whitley and Product Manager Ash Zade everything she wants to know about AI context architecture. What exactly is it? Why is it so important? What makes for good AI context architecture? Why buy one when you can build your own?

Phoebe Sajor

Your semantic layer is a risk mitigation strategy. Not risk in the abstract, compliance-framework sense, but the practical, operational risk that quietly drains organizations every day.

Jeremy Arendt