AI Lao Pao: OpenAI quietly proved a harsh reality for enterprise AI: users will not change their browser or workflow for a shiny LLM interface. If your delivery plan still focuses on building a new AI portal, stop now.
Over the past year, I've helped system integrators and AI appliance channel partners complete more than 20 enterprise AI delivery projects across 10 industries. The #1 failure mode isn't model accuracy — it's pretending that a chat window or browser extension can wire into legacy ERP, policy DB, and government apps without DevOps rigor.
Real delivery means agent orchestration that reads existing APIs and handles failures gracefully, not a demo that breaks when the office moves to a WPS environment.
When deploying on-premises AI appliances (Kunpeng/Ascend, Hygon, etc.), the costliest mistake is skipping load-level monitoring and driver adaptation. Teams end up with ¥200K hardware that runs 3-second inference and overheats after 4 hours.
AI Lao Pao's delivery checklist requires: 48-hour stress testing, P99 latency under 6 seconds, Prometheus rules with auto-failover, and alerting integrated into existing DingTalk/Lark. No checklist, no acceptance.
An actionable audit starts small. If your AI project lacks an inter-system topology diagram or doesn't answer "what does the user see when a model node fails?", you're not ready for production. Reach out at william.yangshun@gmail.com or call +86 18800012501. We work project-based from ¥5,000 and deliver, not demo.
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AI Lao Pao / Yang Shun
AI Delivery Consultant | Architecture/DevOps/SRE/Localization
Enterprise AI is not a demo. It must be deliverable.
Capability site https://www.chinaase.com
Phone +86 18800012501
Business: william.yangshun@gmail.com
Project-based from 5000 CNY
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