Systems | Development | Analytics | API | Testing

This session takes a practical look inside LLM context windows and token consumption, exploring what happens when context enters a model - from tokenization, embeddings, attention, QKV, prefill, and decode to KV caching. It also examines how context windows are allocated and why simply increasing context length doesn’t always lead to better model performance.

Rovo, Atlassian’s AI assistant, can help you generate test cases directly inside Jira through the SmartBear Zephyr Agent for Rovo. This demo offers a practical look at AI-powered testing with Rovo in Jira, from requirements to reviewed test cases, all within the Jira experience, without switching tools.

AI writes code faster than any team can check it. Diego Molina thought he had a tooling problem. He didn't. In 37 minutes he shows the workflow mistake most engineering teams are making right now, the one bottleneck that decides whether AI speeds you up or buries you, and the principles that drive his own workflow scale without the noise. Chapters Learn more at saucelabs.com.

When a performance test run goes wrong, the real work begins, which means hours of manual analysis, digging through metrics, and trying to prioritize what to fix first. Agentic Performance Testing (APT) in NeoLoad changes that. In this demo, see how APT's specialized AI agents automatically analyze a failed test complete with a full, stakeholder-ready report, surfacing an executive summary, SLA compliance breakdown, trend analysis. critical findings, a prioritized action plan, and more, all without leaving NeoLoad.