Productionizing LLM Gateways: Architecture, Tradeoffs, and Hard Lessons from the Trenches

Official Schedule Context

As organizations scale their use of large language models, the biggest challenge is no longer

prompting, it’s productionizing. This session dives deep into building and operating an LLM gateway

that sits between applications and model providers, handling routing, observability, cost control,

reliability, and safety at scale. Drawing from real world experience, this talk breaks down the

architecture of a production LLM gateway, including model abstraction layers, request orchestration,

fallback strategies, caching, rate limiting, and evaluation pipelines. We’ll explore hard tradeoffs

such as latency vs. cost, quality vs. determinism, and vendor lock-in vs. flexibility. Attendees

will leave with concrete design patterns, failure modes to avoid, and a mental model for turning LLM

experiments into resilient, scalable systems.

No official session recording transcript was found by exact title match on the AI Engineer YouTube channel during this run.

Pending transcript synthesis when an official recording or confirmed matching video is available.