Uncover the hidden risks of AI-coded software
AI coding is changing how organizations build software. As adoption grows, technology leaders need to ensure that speed and innovation go hand in hand with quality, security, and reliability.
Join our free 30-minute session to learn what to watch for and how to keep AI-generated software reliable and secure.
For CTOs, engineering leaders, and AI decision-makers overseeing AI coding across their organizations.
Save a spot
Registration is free and includes the AI-Coded Applications Risk Catalog, the research behind this session.
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Recording and slides go to everyone who joins live.
What we'll cover
From the 33 risks documented in the catalog, JD and Mariano selected six that require more than a quick fix and where experienced judgment makes a difference.
Injection attacks
How vulnerable code and hidden instructions can open applications to attack or hijack AI coding agents.
Security erosion over iterations
Why repeated AI-generated changes can weaken security, increase technical debt, and compromise software architecture.
Sensitive data exposure
How AI-built applications can unintentionally expose customer information, credentials, or internal data.
Destructive agent actions
What happens when AI agents have excessive permissions, and which controls can limit the damage.
Rubber-stamp reviews
Why the growing volume of AI-generated code can turn human oversight into a routine approval process.
Lost system knowledge
How teams can lose track of the decisions behind their software, making future changes and maintenance more difficult.
Lessons from real projects
JD and Mariano help companies build and adopt AI-enabled software. In this live session, they'll draw on documented incidents and their own client work to explain what can go wrong, what teams often overlook, and how to address it.
Stay after the 30-minute session for an open Q&A with JD and Mariano.
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Where AI-coding risks show up
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Safeguards that catch and contain them
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How they apply to your projects
Speakers
With nearly 20 years of experience in software engineering and architecture, JD has spent more than a decade at Making Sense designing complex systems and helping organizations adopt emerging technologies.
A Claude Certified Architect and the author of the AI-Coded Applications Risk Catalog, his work focuses on AI architecture, agentic systems, and the engineering practices needed to make them reliable in production.
Mariano brings more than a decade of experience developing digital products for U.S. mid-market and PE-backed companies.
With a Chief Product Officer specialization in AI Applied to Digital Transformation from MIT Professional Education, he connects technology and product strategy with business needs.
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