Discover how Harper successfully transitioned to a sustainable commercial open source platform. Ethan Arrowood details their split core licensing strategy, engineering velocity, and practical framework for building true community trust.
End-to-end latency in real-time pipelines comes from coordination across systems, not from any single component. Four common workloads, tested two ways, show where multi-hop architectures compound delays and where collapsing storage, messaging, and compute into one runtime changes the math.
Most teams treat a cache as a black box: URL-keyed blobs with a TTL, useful for speed and nothing else. In Harper, cached data lands in a real table inside the same query engine. That means filtering, joining, real-time subscriptions, and vector search all work against it.
Deserializing entire records to read one field is a bottleneck at scale. Structon stores objects in a binary format where any field is reachable by byte offset, with lazy getters that never allocate until you access a property. It's the encoding Harper has used internally for years, now a standalone package.
Production agents spend 56–74% of their time waiting on tool calls and infrastructure, not the model. Microservices were the right answer for the web era; agentic workloads need the stack pulled back into a single unified runtime.
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