EPISODE · Feb 24, 2026 · 24 MIN
What's inside high-performing engineering teams | In conversation with VP, Engineering at ServiceNow
from Mala's Podcast · host Mala Ramakrishnan
Michael Avrahamov, VP of Engineering at ServiceNow, joins Mala Ramakrishnan to discuss what it really takes to lead large engineering teams in the age of AI.From early startup work building developer platforms to leadership roles at Siebel, Oracle, and now ServiceNow, Michael shares how he built a niche in observability and reliability engineering—and why falling in love with hard technical problems shaped his career.The conversation dives deep into AI-assisted coding, the risks of auto-generated code, IP concerns, and whether locking down engineers slows innovation. Michael also unpacks how ServiceNow infused AI into discovery, CMDB, and ITSM workflows—and what it means to scale responsibly with 170+ engineers.If you’re a founder, engineering leader, or developer navigating AI productivity tools, governance, and code quality, this episode is packed with practical insight.___________________________________________________________Timestamps00:00 Intro and Michael’s journey into tech01:00 Early startup days and developer platforms02:20 Discoverability, observability, and reliability focus03:40 From Siebel to Oracle to ServiceNow05:00 Reverse engineering the JVM and deep debugging06:40 ServiceNow’s early AI efforts before GenAI08:00 The ChatGPT pivot and accelerating product development09:30 Infusing AI as a co-pilot into product workflows10:50 Automating ITSM tickets with AI agents12:00 Managing a 170-engineer organization13:00 AI adoption vs locking down engineers14:30 Preparing internal systems for AI usefulness15:50 Where AI actually improved productivity17:00 The 2 million lines of AI-generated code problem18:30 Code quality, review discipline, and verification risks19:40 Should AI intentionally inject errors to test humans?20:30 Freedom vs governance in AI usage21:40 Prioritizing roadmap vs one-off customer demands23:00 Startup advice: protect focus and your moat24:00 Final thoughts on leadership in the AI era___________________________________________________________🔗 Connect with Michael Avrahamov → https://www.linkedin.com/in/michaelavr/🔗 Connect with Mala Ramakrishnan → https://www.linkedin.com/in/malaramakrishnan🎧 Subscribe to the podcastYoutube: https://www.youtube.com/channel/UCnL3D6aI60R-cCvypFIkh4ASpotify: https://open.spotify.com/show/1NIDE4cT5fuVjC3HaGbCDK?si=eoSTNmhqQNKHQl9d1Jx0UQApple Podcast: https://podcasts.apple.com/us/podcast/malas-podcast/id1848618438Visit our Website: www.malaramakrishnan.com | www.founderscreative.ai
What this episode covers
Michael Avrahamov, VP of Engineering at ServiceNow, joins Mala Ramakrishnan to discuss what it really takes to lead large engineering teams in the age of AI.From early startup work building developer platforms to leadership roles at Siebel, Oracle, and now ServiceNow, Michael shares how he built a niche in observability and reliability engineering—and why falling in love with hard technical problems shaped his career.The conversation dives deep into AI-assisted coding, the risks of auto-generated code, IP concerns, and whether locking down engineers slows innovation. Michael also unpacks how ServiceNow infused AI into discovery, CMDB, and ITSM workflows—and what it means to scale responsibly with 170+ engineers.If you’re a founder, engineering leader, or developer navigating AI productivity tools, governance, and code quality, this episode is packed with practical insight.___________________________________________________________Timestamps00:00 Intro and Michael’s journey into tech01:00 Early startup days and developer platforms02:20 Discoverability, observability, and reliability focus03:40 From Siebel to Oracle to ServiceNow05:00 Reverse engineering the JVM and deep debugging06:40 ServiceNow’s early AI efforts before GenAI08:00 The ChatGPT pivot and accelerating product development09:30 Infusing AI as a co-pilot into product workflows10:50 Automating ITSM tickets with AI agents12:00 Managing a 170-engineer organization13:00 AI adoption vs locking down engineers14:30 Preparing internal systems for AI usefulness15:50 Where AI actually improved productivity17:00 The 2 million lines of AI-generated code problem18:30 Code quality, review discipline, and verification risks19:40 Should AI intentionally inject errors to test humans?20:30 Freedom vs governance in AI usage21:40 Prioritizing roadmap vs one-off customer demands23:00 Startup advice: protect focus and your moat24:00 Final thoughts on leadership in the AI era___________________________________________________________🔗 Connect with Michael Avrahamov → https://www.linkedin.com/in/michaelavr/🔗 Connect with Mala Ramakrishnan → https://www.linkedin.com/in/malaramakrishnan🎧 Subscribe to the podcastYoutube: https://www.youtube.com/channel/UCnL3D6aI60R-cCvypFIkh4ASpotify: https://open.spotify.com/show/1NIDE4cT5fuVjC3HaGbCDK?si=eoSTNmhqQNKHQl9d1Jx0UQApple Podcast: https://podcasts.apple.com/us/podcast/malas-podcast/id1848618438Visit our Website: www.malaramakrishnan.com | www.founderscreative.ai
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What's inside high-performing engineering teams | In conversation with VP, Engineering at ServiceNow
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