87: Everything is Power: Battery Life Engineering for AI Glasses

What changes for you as a developer when the device moves from your pocket to your face? The battery shrinks by an order of magnitude, the thermal budget is whatever won't make your nose uncomfortable, and your mental model of "one process, one device" goes out the window. Rey and Dmitrii talk us through their custom power monitors, how they've extended Perfetto to give a coherent trace across a multi-device system, why robotic arms make surprisingly good QA engineers, and what it takes to catch the kind of regression that quietly costs you thirty minutes of call time. All of this and more is discussed in this episode. Got feedback? Send it to us on Threads (https://threads.net/@metatechpod), Instagram (https://instagram.com/metatechpod) and don't forget to follow our host Pascal (https://mastodon.social/@passy, https://threads.net/@passy_). Fancy working with us? Check out https://www.metacareers.com/. Links Migrating Data Ingestion Systems at Meta Scale: https://engineering.fb.com/2026/05/12/data-infrastructure/migrating-data-ingestion-systems-at-meta-scale/  Timestamps Intro 0:05 Introduction and Setup 1:51 Battery Life Optimization in AI Glasses 1:57 Challenges in Testing and CI Architecture 5:37 Detecting and Managing Power Regression 8:27 Developer Tools and Best Practices 13:04 Advanced Monitoring and Synchronization Techniques 16:53 Advanced Power Monitoring in Wearables 21:26 Real-World Examples of Performance Optimization 23:53 Battery Life Improvements Through Engineering 25:21 Engineering Culture and Performance Mindset 27:49 Continuous Testing and Profiling Strategies 29:36 Balancing Profiling Overhead and Accuracy 32:15 Simulating Real-World Scenarios in Testing 34:27 Best Practices for Efficient Wearable Code 37:21 Outro 40:26