Hi r/LocalLLaMA, Caroline and Niko from Mozilla AI are back from Shift AI in Barcelona. Thank you to everyone who stopped by Booth 13, and to those who answered in the pre-event thread. The same challenges kept coming up in conversation: Reliability and access: provider outages, rate limiting, and API keys and permissions scattered across teams and tools. Cost: unpredictable spend that is hard to attribute to a team, project or feature. Lock-in and visibility: difficulty switching or combining models, and limited insight into usage and performance. These conversations are feeding directly into how we think about Otari, and we're taking them back to the team. For context, Otari is our open-source LLM gateway and control plane. It covers failover, budget limits and drop-in OpenAI-compatible routing, and it goes commercial on November 2. We'd like to keep this conversation going: Does the list above match your experience, or are we missing something? Which of these problems is still unsolved for you? What should a control layer provide, and what should it stay out of? Thanks again, and we'll be in the comments.   submitted by   /u/mozilla-ai   to   r/LLMDevs [link]   [comments]