Practical writing on event instrumentation, data pipelines, LLM integration, offline-first React Native, and the messy reality of shipping analytics that actually get used.
Most analytics problems aren't measurement problems — they're architecture problems. Here are the seven patterns I see most often when auditing mobile data pipelines, and how to fix them before they cost you a sprint.
The model is the easy part. Instrumentation, latency budgets, failure modes, and cost management are where production LLM features actually break — and where most teams are completely unprepared.
Not every offline-first pattern survives contact with real field conditions. After building three production apps with hard offline requirements — basement inspections, rural property valuations, site surveys — here's the architecture that actually holds.
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5-Step Mobile Analytics Guide
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The most common gap I find: key user actions tracked in the app but never arriving clean. Step 2 in the guide shows exactly where.
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