Operations | Monitoring | ITSM | DevOps | Cloud

Building reliable embedded devices means embracing the unexpected. At Pebble, we deliberately crashed our watches to capture core dumps and debug issues—especially with Bluetooth. From loud beta build notifications to shipping asserts in production, these strategies helped us create a rock-solid product.

After years in the field, Pebble watches started failing—resources wouldn’t load, watch faces went blank, and support requests piled up. The culprit? A subtle timing issue with NOR flash wear that only surfaced as devices aged.

Pebble wasn’t built by industry veterans, it was built by hackers figuring it out as they went. Memfault founders François Baldassari and Chris Coleman, alongside Brad Murray of Beeper, dive into how Pebble’s startup culture led to a unique approach in firmware development.

A single unprotected region holding fonts changed everything. Memfault founders François Baldassari and Chris Coleman, along with Brad Murray of Beeper, discuss one of the most clever security bugs discovered through Pebble’s WhiteHat program.

Join the Founders of Memfault as they dive into this trend alongside special guest Alexander Samuelsson, CTO and Co-Founder of Imagimob (an Infineon Technologies company). This conversation on The Future of Edge AI and What It Means for Device Makers will explore how advancements in Edge AI are reshaping the embedded landscape, from hardware design to edge AI model development.

When Pebble launched its SDK in 2012, it started as a pile of Python scripts. That was just the beginning. Memfault founders, François Baldassari and Chris Coleman, along with Brad Murray of Beeper, discuss the evolution of Pebble’s app sandbox, the challenges of early firmware development, and how a passionate developer community helped shape the platform.

IoT margins are already tight—why make it worse? Many companies are throwing away money on preventable costs like unnecessary RMAs, bloated customer support, and costly technician visits. But there’s a better way: Observability and OTA updates can help reduce churn, cut support costs, and eliminate waste. We just watched a customer slash support tickets by 30% and RMAs by 50% using Memfault’s observability data. These are real numbers, real savings, and real impact.

Big tech has the resources, but startups have the real advantage in AI wearables: speed, agility, and the freedom to take risks. Right now, the AI wearable market is in the wildcard phase—no dominant device, no set form factor, and no clear winner. That’s a massive opportunity for smaller teams that can move fast, test in the field, and refine in real time. Unlike big tech, startups don’t need a five-year roadmap. They can launch quickly, experiment aggressively, and pivot without worrying about shareholders.

Meta is making a massive push into AI wearables, with at least six new devices launching in 2025. But here’s the catch—this wasn’t originally about AI. Meta built its hardware for the metaverse, only to find itself at the center of the AI revolution. With over 1 million Ray-Ban smart glasses already sold (and a goal of 5 million in 2025), it’s clear there’s demand. But can Meta actually scale this initiative from within, or will they lean on brand partnerships like Oakley to expand?