Subvolts take AI writes code faster than we can test it, creating hidden risks. Listen to learn how to ensure application integrity. Apr 14, 2026 - Developers
- Learn about new risks in AI-generated code and how to ensure your applications function reliably.
- Business
- Understand how the speed of AI development creates hidden risks and the importance of application integrity for your products.
This interview addresses a critical, underappreciated risk in AI development: the gap between AI-generated code speed and software validation.
#332 Dan Faulkner: The Code Is Clean. The App Is Broken. Why AI Development Has an Integrity Problem
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From Subvolts
Summary and analysis by Subvolts editorial, AI-assisted.
This episode of Eye on AI features Dan Faulkner discussing the integrity problem in AI development. As AI generates code rapidly, testing systems lag behind. Faulkner argues that clean code passing tests does not guarantee a working application, introducing the concept of "application integrity" to ensure software functions as intended and avoids unintended behaviors. He highlights emerging risks from agentic AI and SmartBear's solutions.
Imagine AI writing computer instructions incredibly fast. This episode explains that just because the instructions look good, it doesn't mean the program will work correctly. It covers new ways AI can break software and how to build tools to check that software actually does what it's supposed to.
This episode is crucial for engineering leaders and developers grappling with the speed of AI-driven coding. Faulkner explains how current validation methods fail to keep pace with AI-generated code, creating hidden risks. He introduces "application integrity" as a necessary framework for ensuring software reliability. The discussion on agentic AI failure modes like slop squatting and instruction inversion is particularly relevant as labs like Google Gemini and Anthropic deploy more autonomous systems. SmartBear's BearQ offers a glimpse into AI-augmented developer tools.
- HostCraig S. Smith
- GuestDan FaulknerCEO, SmartBear
- Episode Title: Dan Faulkner: The Code Is Clean. The App Is Broken. Why AI Development Has an Integrity Problem
- Show: Eye on AI
- Guest: Dan Faulkner, CEO of SmartBear
- Length: 55 minutes
- AI Coding Tools Mentioned: Claude Code, Codex
- SmartBear Product: BearQ
What happens when AI writes code faster than anyone can test it?
In this episode of Eye on AI, Craig Smith sits down with Dan Faulkner, CEO of SmartBear, to explore one of the most underappreciated risks of the AI coding boom. As tools like Claude Code and Codex push software development to unprecedented speed, the systems built to validate that software are being left behind. Dan makes a distinction that every engineering leader needs to hear: clean code passing unit tests is not the same as an application that actually works.
Dan introduces the concept of application integrity, continuous and measurable assurance that your software does everything it was intended to do and nothing it was not. He explains why the gap between what AI builds and what teams actually validate is already creating hidden risk in production, and why that risk compounds the faster you ship.
We also get into the new failure modes that agentic AI is introducing. Slop squatting, instruction inversion, cascading errors. These are not theoretical. They are happening now, at scale, in codebases that no human has fully read.
Dan also walks through SmartBear's autonomy ladder framework and their newest product BearQ, a team of AI agents that explores your application, builds a knowledge graph, authors tests, runs them, and updates everything as your app evolves. The key distinction: it is built to augment human teams, not replace them.
Finally, Dan shares his honest take on the future of software engineering. The fallacy was always that coding was the hard part. The hard part is knowing what to build. That skill is not going anywhere.
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(00:00) Introduction and Dan Faulkner's Background
(01:05) What SmartBear Does: Testing and API Lifecycle Management
(03:27) AI Is Outpacing Application Testing
(07:51) Slop Squatting, Instruction Inversion and New AI Failure Modes
(17:31) Black Boxes, Technical Debt and the Expertise Crisis
(22:00) How to Avoid Self-Validating AI Systems
(24:11) The Autonomy Ladder and BearQ
(31:30) Why Testing Must Be Continuous and Everywhere
(36:31) Infrastructure Risk and Automation Bias
(44:11) The Future of QA and New Specialist Roles
(50:44) How Teams Use SmartBear Tools Today
(58:57) The Future of Software Engineering and Human Roles
- application integrity
- Dan Faulkner
- making sure software works correctly and does only what it's supposed to.
- agentic AI
- Dan Faulkner
- AI that can act on its own to perform tasks.
- slop squatting
- Dan Faulkner
- a new type of software failure caused by AI.
- instruction inversion
- Dan Faulkner
- a new type of software failure caused by AI.
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WithAndrii Hrytseniuk
Questions people ask
- What is application integrity?
- Application integrity is the continuous and measurable assurance that software does everything it was intended to do and nothing it was not, even as AI rapidly generates code.
- What are new failure modes of agentic AI?
- New failure modes include slop squatting, instruction inversion, and cascading errors, occurring in codebases that humans have not fully reviewed.
Page generated Oct 19, 2026. Summaries are Subvolts' own; the audio, artwork and notes belong to Craig S. Smith.