Architecting High-Throughput AI Workflows for Enterprise Scale

Building autonomous execution engines requires rethinking traditional event-driven architectures. When AI agents execute multi-step tools, latency bottlenecks compound exponentially.

## The Challenge of Compounding Latency
Traditional synchronous queueing creates cascading stalls. By decoupling state snapshotting from step evaluation, Borna Engine v2 reduces overhead by 74%.

## Key Performance Innovations
- Zero-copy IPC queues
- Micro-batched vector queries
- Dynamic fallback route evaluation

## System Benchmarks
Testing under 100k concurrent requests demonstrates p99 latency under 1.8ms across macOS, Linux, and Windows nodes.