Stream Blog

As agents become more commonplace, new protocols are being invented to simplify and standardize complex workflows. With so many emerging standards, it’s increasingly important to know which to use and how they fit together. This guide breaks down the most widely recognized AI agent protocols and explains how they interoperate, overlap, and complement each other.

Over the last few years, developers have gone from using language models for text-only chat to relying on them as general-purpose perception systems. You’re not only building chatbots; you’re building apps that use text, audio, and vision to understand and act on the world around them. GPT-4o is the most capable step yet: a single

B2B dashboards tend to evolve quietly. New features get added. New data appears. Navigation grows more complex over time. Eventually, what started as a focused interface becomes a dense surface area that’s difficult to extend, harder to learn, and increasingly fragile to change. At Stream, we recently rebuilt our dashboard from the ground up to

Telehealth is transforming the way patients and providers connect, offering faster access to care and reducing barriers caused by distance or scheduling. A critical part of this experience is enabling secure, real-time video consultations alongside features like chat messaging for sharing updates, questions, and follow-ups. With Stream’s healthcare chat solution, developers can build HIPAA-ready communication

Adding in-app chat is one of the most common (and underestimated) product decisions teams face. Today, AI has made it easier than ever to prototype messaging features quickly. A small team can scaffold a working chat experience in days, not months. But shipping a demo is not the same as running a production chat system.

You’re working in a warehouse when you see an automated forklift barreling towards a coworker. You whip out your phone and type "STOP!" into the app controlling the vehicle. You add another exclamation point to make sure it knows it’s an emergency. That’s not good enough, and it’s not how things have to be. AI

Vision Agents is our open source framework for quickly building low-latency video AI applications on the edge. It runs on Stream’s global edge network by default, supports any edge provider and integrates with 25+ leading voice and video AI models. To put the framework to the test, we built a real-time sports commentator using stock

Online communities rely on moderation to function, yet every moderation decision carries significant ethical implications.  The platforms that choose to remove, allow, promote, or downrank content directly shape culture, discourse, and safety. As AI systems take on more moderation responsibilities and regulatory scrutiny increases, the stakes continue to rise. Ethical moderation is no longer only