Systems | Development | Analytics | API | Testing

AI-Powered Digital Front Door: How AI Improves Patient Access and Intake (2026)

The digital front door is moving beyond portals, online forms, and basic appointment booking. In 2026, AI is making patient access more responsive by helping patients find the right provider, schedule care, verify coverage, complete intake, and prepare for visits through connected digital workflows. The shift comes as healthcare organizations move AI from experimentation into real operations.

AI Literacy Starts at the Top

AI literacy across 60,000 people starts with the C-suite. In this clip from podcast, Bethany Miles, Chief AI Officer at Advantage Solutions, shares how she built enterprise-wide AI fluency, starting with 10+ hours of hands-on executive training and a CEO coding workshop. What you'll learn in the full episode:→ Why AI literacy has to start at the top before it can scale anywhere else→ How Advantage Solutions redesigned broken processes before automating them→ What to measure beyond adoption (service excellence and time-to-complete)

Cloud vs On-Premise Load Testing: 2026 Guide

Choosing between cloud-based and on-premise load testing solutions is a strategic decision in performance assurance. Picture cloud load testing as casting a wide net – covering broad territory and adapting to changing conditions. On-premise is more like fishing with a spear, offering precise control but with limited reach.

Self-Driving Regression Testing with AI Agents | Somu Suryanarayanan

This session looks at how agentic automation can take over web and mobile regression. We start with the regression tax: the slow 3-day cycle, the manual triage, and the flaky reruns nobody trusts. We then cover why scripted suites hit a wall and make the case for handing regression to agents instead. The core of the talk is how it actually works, with Appium MCP driving mobile and Playwright MCP driving web, interpreting intent rather than hard-coded steps and adapting when the UI shifts.

AI Is Changing How We Code - But What About the Data Behind It? | Innovation Blueprint

How is AI changing software development — and what happens when AI-generated code meets real-world data? In this clip from The Innovation Blueprint Podcast, Roman Havrylyuk from ORIL and Bob Frady, Co-Founder of PropertyLens, disscuss how AI is changing the way teams write code, work with data, and make business decisions — and why better AI capabilities don’t eliminate the need for strong engineering and data foundations.

Control how much autonomy your AI testing agents have | SmartBear BearQ

Can you trust AI agents to run your tests without losing control of your release process? In this video, you’ll learn how, with SmartBear BearQ’s agentic QA system, the answer is yes, because you decide exactly how much autonomy the agents get. This enables you to adapt QA to fast-moving AI codebases, all with human oversight.

Can AI Agents Safely Debug Production Node.js?

AI agents are getting remarkably good at fixing code. Give an agent a well-defined performance problem, enough runtime data, and access to the relevant codebase, and it can often trace the evidence back to a function, suggest an optimization, validate the change, and produce a useful patch. That workflow is no longer particularly difficult to imagine. In some cases, it is already practical. Production debugging, however, has never been only about fixing the code directly in front of you.

Why WebSockets beat SSE for AI streaming at scale

Picture a support agent mid-refund: it has pulled the order, flagged the tool call, and is one approval away from processing it. Then the user needs to approve it. On Server-Sent Events (SSE), there's no channel for that approval to reach the agent, because the connection only carries data one way - from server to client. A WebSocket keeps that connection open in both directions instead, so the approval could reach the agent the moment it's given.