OpenOPC's performance and token consumption for AI-native application development.

This issue highlights critical performance and cost challenges for OpenOPC, an AI-native platform. The frontend experiences severe bottlenecks, rendering it unusable and requiring service restarts. Simultaneously, token consumption is excessively high (64M output, 1.8M input), directly impacting operational costs and scalability. For a product positioned as 'Self-Run,' these issues undermine its core value proposition. Developers face immediate operational hurdles and significant financial overhead, hindering adoption and demonstrating fundamental instability in the underlying AI orchestration or resource management. Market implications include reduced trust in AI-native solutions that fail to manage resource efficiency and deliver consistent performance, potentially limiting enterprise-scale deployment.