Systems | Development | Analytics | API | Testing

10x faster coding. Same QA. Until now. You're coding faster with AI. But if your agents are siloed and disconnected, those gains aren’t yet showing up in your quality or delivery – it's getting lost in the handoffs. Join SmartBear for a live demonstration of the connected agentic SDLC. See how BearQ extends beyond creating tests to coordinating quality work across Jira, GitHub, and AI-powered workflows – detecting issues, triggering the right next action, and carrying context from one agent to the next.

AI may make coding faster, but can your safety, security, and verification practices keep pace? In this webinar, Perforce Director of Product Steve Howard examines how the emerging AI Development Lifecycle (AIDLC) could reshape embedded software development and specifically V&V processes. You'll also learn where AI can help, where its limitations remain, and what organizations should consider as they prepare for AI-driven development.

Going from a written requirement to an executable test usually means writing the steps and data yourself, then mapping each one to the application by hand. Pair Tricentis AI Workspace's requirement analysis with Tosca's agentic automation to go from a Jira ticket to a running, reusable test case for your SAP Fiori applications. In this walkthrough, you will see how to generate a test case from a requirement, map it to the Fiori UI, and save it for regression.

One developer burned through 300 million AI tokens in a single week. The payoff was far less impressive. For Todd Trevillion, it's a striking example of what can happen when AI adoption outpaces the controls needed to manage it. And with autonomous AI agents beginning to make decisions on behalf of businesses, the stakes are getting higher.

Agents are easy to build and hard to measure. When your company runs hundreds or thousands of them, hand-written evals can’t keep up, and it’s unclear which agents are correct, efficient, and ready for users. In this conversation, Ryan Yackel, SVP of Product Marketing, and Andrew Demers, Product Manager for Agent Score at Tricentis Labs, explain how to measure agent quality, score agents automatically, and trace issues back to behavior.

Before building an AI-powered real estate product, understand the data that will power it. In this episode of The Innovation Blueprint Podcast, Roman Havrylyuk of ORIL and David Lovins, CEO of The Warren Group, explore why understanding your data — where it comes from, how it’s structured, and how different datasets connect — should come before building AI solutions. The better you understand your data, the better equipped you are to build technology that delivers reliable, meaningful results.

Secure AI starts with securing the APIs underneath it. This session breaks down why APIs and MCPs are the control plane for AI apps and agents, where unmanaged API risk hides, and how security and platform teams can improve visibility, posture, runtime protection, and governance across production environments. KEY TAKEAWAYS TIMESTAMPS.