I Stopped Buying SaaS for RevOps. I Built What I Needed on Harper Instead.

Reduce API latency under load with a caching alternative to Redis: an in-process cache that cut response time 100x without adding a new tier.

Harper 5.2 helps architecture and platform leaders improve performance, control infrastructure costs, secure production workloads, and reduce operational complexity by bringing faster data access, agentic capabilities, scheduling, backup, routing, and protection into one unified runtime.

Personalization is a data-delivery problem. Every architectural choice reduces to two distances: compute to user, and compute to fresh data. This piece maps five real architectures against both axes, scored on a concrete retailer workload where stale or slow data breaks the business.

Harper 5.1 adds int8 quantization, dropping index size by roughly 3x, search throughput improves roughly 5x, and p99 latency falls from ~9s to ~0.5s under load. The tradeoff is approximately 1% recall degradation before reranking.

Harper runs live, personalized apps 4–14x faster than Vercel by unifying data, logic, cache, and messaging in one runtime.

AI coding works in a sandbox because the environment is trivially narrow. Real systems have history, constraints, and blast radius. Coding agents make sound decisions only when the architecture is explicit and shared. Opinion isn't a constraint on agentic engineering, it's what makes it possible at scale.