In this session, we explored how engineering leaders are using feature flags and experimentation to reduce risk during replatforming—without slowing teams down. Our speakers shared practical perspectives on: - Using feature flags as a control layer to migrate incrementally rather than relying on big-bang releases - Making clearer go / no-go decisions by measuring impact early and often in production - Detecting risk sooner through feature-level observability, not just system-level metrics - Treating feature flags as a lifecycle tool—designed to be rolled out, measured, and retired cleanly Beyond the Toggle eBook: https://www.harness.io/resources/beyond-the-toggle

This is a special episode, highlighting a session from ELC Annual 2025! Bill Coughran (Partner @ Sequoia Capital & former SVP of Engineering @ Google) and Bret Reckard (Talent Partner @ The General Partnership) deconstruct the evolving role of engineering leadership in an era dominated by AI hype. Bill is a legendary leader who joined Google right after the .com bubble and has seen every major industry shift since. Drawing on his experience scaling Google and advising world-class startups, Bill shares why the best leaders are "catastrophic thinkers," how to balance servant leadership with the need for decisive action, and why AI is forcing every leader to return to their technical roots. Plus they cover enduring companies and real value capture in the AI era, the nuances of organizational design, the "apprentice model" for mentorship and the dangers of over-layered hierarchies that stifle speed. Bill also provides a candid look at leadership transitions, offering a tactical guide for those moving from Big Tech to early-stage startups.

This is a special episode, highlighting a session from ELC Annual 2025! OpenAI evolved from a pure research lab into the fastest-growing product in history, scaling from 100 million to 700 million weekly users in record time. In this episode, we deconstruct the organizational design choices and cultural bets that enabled this unprecedented velocity. We explore what it means to hire "extreme generalists," how AI-native interns are redefining productivity, and the real-time trade-offs made during the world's largest product launches. Featuring Sulman Choudhry (Head of ChatGPT Engineering) and Samir Ahmed (Technical Lead), moderated by Lawrence Bruhmeller (Eng Management @ Sigma).

In this episode, Brian Balfour (Founder & CEO @ Reforge) deconstructs the two core, interconnected challenges leaders face in the AI age: deciding what to build and evolving the Engineering, Product, Design workflow to deliver it. We cover why you should avoid “the local maxima trap” and siphon off "skunkworks" teams to take high-risk, AI-native bets. Brian provides the blueprint for the "Great Distribution Shift," detailing how to reshape your product from the ground up to avoid being left behind as platforms close, and how to emerge as a winner in the new AI landscape. Plus, learn how to rethink what to build, avoid commoditization, compress product discovery from weeks to hours, scale feature variations & prototypes, evolve products to solve harder classes of problems and shift specialist roles from "inboxes" to system builders.

During this session, we discussed the importance of aligning technical strategy with business goals, the realistic impact of AI on productivity, and the need for cross-functional collaboration to keep roadmaps both flexible and realistic.

This is a special episode, highlighting a session from ELC Annual 2025! The true promise of AI isn’t in replicating human intelligence. It’s in developing entirely new forms of non-human intelligence that perceive and understand the world in fundamentally different ways. Jamie Lien (Co-Founder and Chief Scientist @ Archetype AI) and Rashi Agarwal (Head of AI Engineering @ GoodLeap) explore the emergence of "Physical AI" - machines that sense the world through modalities beyond human biology to form internal representations free from our biases and then translate that understanding back to us in human terms.

In an era where AI delivers answers instantly, leadership is shifting from output to awareness. This article explores how curiosity, clarity, and connection become essential skills for engineering leaders who want to stay grounded in their own judgment—rather than outsourcing confidence to the machine.