Join LISUG for a practical, high-signal evening with Pascal Polverini on two subjects that are quickly becoming inseparable: modern software testing and AI-assisted development. As delivery speed increases, teams need better ways to measure risk, prove quality, and keep change under control. This event connects the business case for automation with the engineering discipline required to use AI responsibly.

Pre-Session: ROI of Software Testing: Manual Versus Automated
Software testing is a critical phase in the software development lifecycle. It ensures that software is reliable, functional, and aligned with requirements. This session explores the return on investment of automated testing compared with manual testing, with a clear focus on the metrics leaders and practitioners actually care about: time delays, efficiency loss, bug fixing, downtime, human resources, trust and credibility, regulatory compliance, and overall ROI comparison.

Main Session: Small Steps, Automated Proofs: A New Programming Paradigm with AI
Artificial Intelligence is not replacing programmers; it is redefining their role. AI can generate large amounts of code at unprecedented speed, but that speed introduces risk. AI-generated code can be incomplete, subtly incorrect, or misaligned with real-world constraints. This session shows why the programmer's role is shifting from writing every line to directing, constraining, and validating AI output. Pascal will walk through a safer methodology built on strict supervision, tight feedback loops, and comprehensive automated testing, where AI is guided through small, incremental steps that are fully understood, reviewed, tested, and reversible before teams move forward.

If your team is trying to increase delivery speed without sacrificing confidence, this event will give you a sharper framework for making automation measurable and AI output trustworthy. Expect practical takeaways you can apply immediately to testing strategy, engineering workflow, and modernization planning.