AI features don't behave like static software. The prompt, model, or threshold that works today may not work tomorrow, and most teams have no way to change it without a full redeploy. Join us for a live demo of AI Configs, Harness's answer to controlling AI behavior with the same discipline you apply to feature releases: progressive rollout, experimentation, and kill switches, all governed by the same pipeline as the rest of your delivery process. What you'll take away: - Why hardcoded prompts and models create hidden release risk, and why AI behavior needs the same governance as any other production change - How to adjust AI behavior at runtime (prompts, models, routing) without a redeploy, and propagate that change globally in under a minute - How progressive rollout and experimentation let you validate AI behavior with real users before committing to it broadly - How kill switches and rollbacks give you an instant safety net when AI behavior drifts - How to close the governance gap between the code your teams ship and the AI they run, all through one pipeline

In this episode, Sergiy Nesterenko (CEO @ Quilter) joins the pod to share how he turned a personal technical challenge into his own company, even before the market caught up. He shares his unique journey from SpaceX to Quilter and addresses common eng leader / founder challenges, including taking critical feedback to solve tough technical problems, knowing when your most important role is educating the market / customers, and choosing the right customers. Sergiy and Jerry also dissect insights into principles around building circuit boards, and common misconceptions around hiring top-tier talent, finding investors, and procuring customers as an early-stage company. 

A quarterly signal map of what engineering leaders are noticing, questioning, and practicing - including both AI-driven change and the enduring organization, culture, and leadership work underneath it.

Vivek Raghunathan, SVP of Engineering @ Snowflake, joins the Engineering Leadership Community Podcast to discuss all things AI – most importantly, how Snowflake is utilizing AI internally to iterate faster with smaller, focused teams. Vivek shares how AI and lower coding costs ultimately help Snowflake implement tighter feedback loops between customer & eng teams to speed up product development rollout and how Snowflake empowers their orgs to upskill when it comes to AI. Jerry & Vivek also break down what quality leadership looks like across the board and the role of AI in shaping today’s eng leaders. 

Artificial intelligence is transforming how organizations prepare for, respond to, and recover from critical events. As AI capabilities continue to evolve, leaders are exploring how to harness its potential while maintaining the human oversight essential for effective decision making. This session will examine the practical role of AI in modern incident response, separating hype from reality. Attendees will learn where AI can provide meaningful value, including decision support, threat analysis, and reducing alert fatigue, as well as where human expertise remains indispensable. We will discuss the balance between machine generated recommendations and human judgment, explore real world use cases, and highlight best practices for integrating AI into critical event management workflows. Join us to discover how organizations can leverage AI to improve situational awareness, accelerate response times, and make more informed decisions during high pressure incidents while keeping people at the center of the process. Key Topics: - What AI can and cannot do during critical events - AI assisted decision support - Reducing alert fatigue - Human judgment vs. machine recommendations If you're interested in exploring moderizing your incident response, you can try xMatters https://www.xmatters.com/