What the Dev? is a podcast by the SD Times editorial team. We cover the biggest and newest topics in software and technology.
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330: Code quality + security shouldn't be separate concerns (with Aikido Security's Khachatur Virabyan)
In this episode, Jenna interviews Khachatur Virabyan, head of code quality at Aikido Security, about why code quality and security should be addressed together.They discuss:The differences in definitions for code quality and securityHow clean code could still have vulnerabilitiesThe impact AI coding will have on code quality and security
329: The impact of AI on ASPM (with ArmorCode's Mark Lambert)
In this episode, Dave interviews Mark Lambert, chief product officer of ArmorCode, about how AI is influencing Application Security Posture Management (ASPM).They discuss:How AI-generated code has more vulnerabilities than human-generated codeThe risks of slowing down innovation while trying to govern AI-assisted developmentUsing AI agents for automated testing and security vulnerability detection
328: What you should know about Shai-Hulud and its impact on npm (with Chainguard's Dan Lorenc)
In this episode, Jenna interviews Dan Lorenc, CEO of Chainguard, about the Shai-Hulud worm that has made its way through the npm ecosystem.They discuss:What Shai-Hulud is and why it's so badSecurity measures GitHub plans to implement in npm Best practices to follow to mitigate risk
327: Failure is a key part of AI experimentation (with Planview's Alan Manuel)
In this episode, Dave interviews Alan Manuel, group VP of product management for platform and AI at Planview.They discuss: Why AI requires a different mindset than other technology adoptionSetting realistic expectations for AIWhy it's important to focus on the outcome, not the features
326: Using AI to modernize legacy code (with R Systems' Neeraj Abhyankar)
In this episode, Dave interviews Neeraj Abhyankar, vice president and practice head of Data, Analytics, and Generative AI at R Systems.They discuss: The role of AI in modernizationThe evolution of AI throughout technology historyThe importance of "human in the loop" when working with AI
325: The impact of AI on digital transformation (with Google's Andi Gutmans)
In this episode, Dave interviews Andi Gutmans, VP and general manager of Data Cloud at Google.They discuss:How AI can help with data managementHow AI tools have matured and are now more accessible for late adoptersThe work Google is doing with AI This episode originally aired 7/31/2025 on Get With IT.
324: QA management in an AI world (with Sembi's Judy Bossi)
In this episode, Dave interviews Judy Bossi, VP of product management at Sembi, about the importance of QA in AI integration.They discuss: Predictions for how QA will evolve alongside AIEnsuring executives see the business value in QAThe challenges in ensuring security and safety when integrating AI into the software development life cycle
323: AI agents need transparency and trust to be successful (with Creatio's Burley Kawasaki)
In this episode, Dave interviews Burley Kawasaki, global VP of product marketing and strategy at no-code CRM platform Creatio.They discuss: The cautious adoption of AI in the workplace due to trust issuesThe need for transparency and visibility into AI decision-making processesHow to balance innovation with security and compliance
322: What to consider before selecting AI tooling (with Instabase's Anant Bhardwaj)
In this episode, Jenna interviews Anant Bhardwaj, CEO and founder of Instabase, about what factors to consider before purchasing an AI tool.They discuss:Why it's important to start with the problem you have and work backwardsMaking sure agentic AI fits in with the rest of the existing systemsPlanning for long-term use
321: Bridging the gap between AI tools and Kubernetes with kagent (with solo.io's Idit Levine)
In this episode originally published on Get With IT, Dave interviews Idit Levine, founder and CEO of solo.io, about kagent, a framework for running agents in Kubernetes. They discuss:Why kagent was createdWhat led solo.io to open source the project and donate it to the CNCFDifficulties with deploying AI agents in large organizations
320: Creating a culture for AI experimentation (with LaunchDarkly's Jenn Wei)
In this episode, Dave interviews Jenn Wei, senior vice president of product at LaunchDarkly.They discuss:The importance of creating a culture for AI experimentationNeeding to shift from building features to managing dynamic learning systemsThe role of leadership in driving innovation
319: Rules and guardrails for AI coding assistants (with Continue's Brian Douglas)
In this episode, Dave interviews Brian Douglas, head of developer experience at Continue, about the importance of rules for AI tools.They discuss: How to implement rules for AI assistantsUsing rules to replace lengthy promptsPreventing technical debt when using AI-generated code
318: How developer advocacy fuels product growth (with DigitalOcean's Wade Wegner)
In this episode, Jenna interviews Wade Wegner, chief ecosystem and growth officer at DigitalOcean, about the importance of developer advocacy.They discuss:The relationship among developer advocacy, developer relations, and technology evangelismEffective strategies for engaging with developersMetrics to track to know that advocacy is contributing to product growth
317: Using HOPrS to verify that images and videos are real and unedited (with OpenOrigins' Manny Ahmed)
In this episode, Jenna interviews Dr. Manny Ahmed, co-founder and CEO of OpenOrigins, the company behind Human-Oriented Proof System (HOPrS), which can be used to determine if an image or video has been altered or is AI-generated.They discuss:How it works and how it differs from other tools that try to do thisHow it can be used to address concerns around AI-generated contentIts recent acceptance into the Linux Foundation Decentralized Trust Lab
316: The benefits of specialized language models (with OpenText's Justin Cantrall)
In this episode, Dave interviews Justin Cantrall, AI engineer and architect at OpenText, about specialized language models.They discuss:The difference between specialized language models and large language modelsThe benefits and disadvantages of choosing specialized language modelsOpen weight models