

Manuel Vivo
Senior Staff Mobile Engineer
Super Technologies

Manuel Vivo is a Staff Mobile Architect and seasoned Android engineer with experience at leading companies including Capital One, Google, Bumble Inc., and Super Technologies. Beyond his technical expertise, Manuel is a dedicated mentor, accomplished public speaker, and prolific writer.
Fundamentals of Mobile System Design
Session
Mobile apps are no longer just thin clients that passively render API responses. Modern apps are expected to cache, sync, stream, retry, paginate, prefetch, observe, and recover. They must seamlessly adapt to unreliable networks, strict background execution limits, and volatile device resources.
In this talk, we’ll break down the foundations of mobile system design and the critical questions senior engineers must answer before writing code: What data survives offline? How do we balance data freshness against battery and memory constraints?
Using a concrete example, we’ll explore the real-world trade-offs behind feed orchestration, infinite pagination, client caching, state synchronization, etc. without spoiling the full blueprint.
You’ll walk away with a practical mental model for approaching complex mobile architecture, whether you’re prepping for senior/staff interviews, mentoring your team, or making critical design choices in production iOS and Android apps.
Degrease your Android app: stripping bloat for low-end devices
Session
Low-end Android devices expose performance problems that flagship phones often hide. Small inefficiencies in startup, memory usage, caching, or background work can quickly turn into ANRs and a frustrating user experience at scale.
In this talk, I’ll walk through how we approached a performance overhaul at Super, from local profiling to production telemetry. We’ll use memory dumps, Perfetto traces, flamegraphs, Macrobenchmark, and microbenchmarks to identify CPU and memory bottlenecks, then look at the trade-offs behind architectural choices such as on-disk caching, in-memory caching, and memory-efficient data structures. We’ll also cover how to ship risky performance changes safely using feature flags, and how to validate their real-world impact with production observability.
By the end, you’ll have a practical blueprint for finding Android performance bloat, reducing ANRs on constrained devices, and proving that your optimizations actually work in production.
