Alex Danilowicz, co-founder of Magic Patterns (YC W23), walks through the company's origin as an attempt to make design accessible to front-end engineers and non-designers, demos the new MagicOS canvas and its MCP integration with coding agents, and reviews several AI-built startup landing pages to explain what makes a site feel vibe coded and how to make AI-generated design more intentional.
Javier Garza's AI Security Engineer Foundations workshop walks through the OWASP LLM Top 10, shadow AI and AI Bills of Materials, AI threat modeling, securing agent skills and MCP servers, secure vibe coding, and offensive agent workflows. Throughout, he argues that AI systems break traditional security assumptions because they are probabilistic, reach external content, and act through tools, so defenses must combine least-privilege access, continuous inventory, automated scanning, human approval, and education that explains guardrails rather than merely imposing them.
Atlassian's Tamar Yehoshua explains what the AI builder era looks like for product managers in a company of more than 10,000 people. Using Confluence, RovoClaw, and Jira as examples, she covers when PMs should write code and prototypes, when they should steer the team instead, and how Atlassian is building AI fluency in its PM organization.
Katie Paxton-Fear explores the emerging security landscape of AI agents, moving beyond chatbots to autonomous, specialized entities. She details five critical vulnerabilities: social engineering, hacking frameworks, malicious agents, AI as accidental insiders (vibe coding), and the rise of hackbots. The talk concludes with a powerful call to action for security professionals to proactively engage and influence AI agent development, emphasizing that 'abstinence-only education doesn't work' when it comes to AI adoption.
This video explores how James Martin's 1991 Rapid Application Development (RAD) methodology, with its emphasis on rapid prototyping, iterative development, and user feedback, offers a robust framework for contemporary AI coding and "vibe coding" workflows. It highlights how AI agents accelerate prototyping but introduces new challenges regarding production readiness and security. The solution proposed is spec-driven development, where human expertise formalizes requirements and verifies AI-generated code based on insights gained from early prototypes, ensuring quality and mitigating risks.
Anna Gutowska explains the paradigm shift in software engineering towards "agentic engineering," where AI agents execute goals defined by developers. She differentiates this from traditional, AI-assisted, and vibe coding, highlighting the increased importance of human oversight, orchestration, and verification in a world of probabilistic AI systems, and how this redefines the developer's role.