Sarah-Jane Madden -- What AI means for AppSec

Sarah-Jane Madden joins Chris and Robert to ask what AI actually changes in software development—and what foundational practices still matter. Drawing on her OWASP Global AppSec EU keynote, she challenges the idea that AI makes the SDLC obsolete or turns every prompt into production-ready software. The conversation examines vibe coding, the difficulty of operationalizing AI-generated prototypes, skill atrophy, hallucinations, and the quality problems hidden by code that merely passes generated tests. Sarah-Jane argues for treating AI as a useful assistant rather than an unquestioned authority: engineers must preserve critical thinking, understand their systems, and verify the output. The episode closes with practical guidance for engineering leaders who want teams to gain efficiency from AI without surrendering judgment, accountability, or software quality.The Application Security Podcast is brought to you by Security Journey.About Security JourneyWe provide diverse training content and easy-to-digest lessons to meet individual learner needs.→ Learn more about Security JourneyConnect with Sarah-Jane Madden:→ Sarah-Jane Madden on LinkedIn→ Nemo Resideo keynote at OWASP Global AppSec EUMentioned in this episode:→ Nemo Resideo keynote at OWASP Global AppSec EU→ Sarah-Jane Madden — Threat Modeling to Established Teams→ GitHub CopilotFollow the Application Security Podcast:➜ Home➜ X➜ LinkedIn➜ YouTube➜ Instagram➜ FacebookChapters:00:00 Meet Sarah-Jane Madden: What AI Means for AppSec02:35 From an OWASP keynote to AI in software development04:59 The biggest misconception about AI-assisted development07:13 Why AI will not eliminate software development11:58 Vibe coding and the production-readiness gap15:46 Operationalizing AI-generated prototypes17:53 Where AI helps inside the SDLC23:58 Over-reliance, skill atrophy, and engineering judgment27:00 Using AI for grunt work without losing core skills29:38 Can developers trust large language model output?33:36 Practical guardrails for responsible AI use