Prompt engineering gets you a demo. Context engineering gets you a production Voice AI agent. Think of LLMs as the world’s most brilliant librarians: they’ve read almost everything ever written, but without your help, they have the short-term memory of a goldfish. For text-based chatbots, a forgetful
AI-driven QA testing is reshaping how teams validate real-time applications. Doing it well requires intentional processes, shared knowledge, and a collaborative culture that allows teams to use AI responsibly and consistently. Our WebRTC.ventures QA team has approached this with a clear mindset: the real value of AI
WebRTC.ventures CTO Alberto González recently joined the Software Defined Talk podcast to share insights on building voice, video, and streaming applications for enterprise use. In the conversation, he explains how WebRTC powers the real-time experiences behind many of today’s most important communication products, and why companies across
Early Voice AI deployments were built on a straightforward pattern: Speech To Text, LLM, Text To Speech. That pipeline was enough to produce compelling prototypes for customer support, sales automation, and meeting summaries. The pattern holds well until it meets a regulated environment. Telecom platforms, telehealth systems,
