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As AI applications transition from experimental prototypes to production systems, the gap between success and failure often hinges on prompt management. Organizations deploying large language models (LLMs) face a critical challenge: how do you systematically track, test, and deploy prompt changes without introducing regressions that impact thousands of users? Without

TLDR Key Takeaways: * LLM gateways solve critical production challenges, including provider lock-in, reliability issues, cost management, and operational complexity * Bifrost by Maxim AI leads the market with 50x faster performance than LiteLLM, adding less than 100µs overhead at 5,000 RPS * Enterprise features like automatic failover, semantic caching, and unified

TLDR AI agent observability has become a critical infrastructure for production deployments in 2025. The top five platforms each serve distinct needs: * Maxim AI provides comprehensive agent simulation, evaluation, and observability with enterprise-grade features and cross-functional collaboration * Langfuse offers open-source flexibility with self-hosting capabilities and a generous free tier * LangSmith