As companies are adopting serverless architectures and moving away from monolithic and microservice-based deployments, they realise that the challenge lies not only in the rewrite of an old application, but also in the shift towards a new way of thinking. We see many serverless architecture patterns today, such as function chaining, function chaining with rollback (for transaction), ASync HTTP, fan-out and more. We also have a number of tools on the market that ease application development using serverless, of which Apache OpenWhisk (via action chaining or using function composites) and Amazon Step Functions are some of the more popular. In this talk, we will present a new alternative way of building serverless applications based on the orchestration of typed functions, using the probabilistic inference programing paradigm. Inference-based programming brings about the best of the current modelling approaches: the expressiveness and simplicity of decision trees, the high debugging capabilities of state machines, the scalability and flexibility of flow based programming and superior logic expressions to forward chaining approaches. The talk will include a live demo of how to use probabilistic inference programming for a complex IoT application.