STARWEST 2026 - Business Analyst
Customize your STARWEST 2026 experience with sessions for business analysts.
Thursday, September 24
Testing AI Systems That Learn in Production: From Static Test Cases to Continuous Validation
As organizations increasingly deploy AI and machine learning systems into production, testing practices built for static, rule-based software are no longer sufficient. Unlike traditional applications, AI systems learn from data, change behavior over time, and are sensitive to data drift, bias, and feedback loops, making defects harder to detect with conventional test cases. This session presents a practical, experience-driven approach to testing AI systems across the full lifecycle, from model development to live deployment. Drawing on real-world implementations and applied research, the...
Agentic Quality at Scale—Orchestrating a QA Swarm for Swift Delivery
As delivery cycles compress, single AI agents are not enough. The next leap is a coordinated swarm of specialized QA agents, each owning a slice of the quality lifecycle (requirements, test generation, execution intelligence, defect triage, and release decisions). This session shows how to design an agent operating model that scales across teams, products, and pipelines without losing trust, traceability, or control. This session will introduce a practical blueprint for deploying multiple cooperating AI agents across the SDLC, with clear boundaries, KPIs, and governance that align to...