At the Lance Developer Salon, Volcano Engine algorithm engineer Zeng Qian argued that a model being able to perform a task does not mean the business can use it. The last mile of AI productionization is blocked by three gaps—model capability, engineering pipelines, and output determinism. LAS uses more than 150 multimodal operators to package validation, execution, evaluation, and repair into stable contracts, while workflow orchestration carries business strategy into execution. The real...

Even when models can understand and generate text, images, audio, and video, why do many capabilities remain stuck in demo mode? Zeng Qian, an algorithm engineer at Volcano Engine's Data Intelligence Platform, offers an answer: businesses do not need something that works correctly once; they need it to run reliably thousands of times.

e divides usability into three stages: capability-ready means a single invocation succeeds; production-ready means the pipeline can deliver reliably; scale-ready means the same capabilities can be reused across business lines, and when the underlying model is upgraded, the upper-layer system does not need a full rewrite.

The distance from capability to delivery is the last mile of productionization. The key bottlenecks in scaled production can be summarized as three gaps: the model capability gap, the engineering pipeline