I'm the creator of the Dapr CNCF project, happy to answer any questions.

One pattern we've seen while building AI agents is that developers often have to make a frustrating choice between agent frameworks and workflow engines.

Frameworks like LangGraph, Strands, CrewAI, ADK, etc. already implement reasoning loops, tool execution, retries, and memory. But they typically don't provide durable execution—if the process crashes, the agent will restart from scratch. Some have very basic checkpoint systems that leave failure detection and resumption to the user, which is essentially the hard problem workflow engines solve.

The problem with workflow engines is they handle durability well but require developers to rewrite their agent logic inside the workflow system, which means rebuilding the agent framework from scratch.

This work aims to remove that tradeoff by allowing existing agent frameworks to get all the benefits of a durable workflow orchestrator without rewriting any part of their code.

Thank you! :) (Dapr maintainer here)

Hi everyone, I performed a deep analysis of the code, runtime behavior and architecture of many popular agent frameworks and decided to publish a post with some initial findings on what I perceive to be critical gaps when it comes to guaranteed execution in real world scenarios, that shift the hardest problems to the users. Happy to discuss further

This is a way to give developers and semi-technical people a way to generate and run code-first workflows using a visual language, be it UML or otherwise. We will be expanding support for text prompts in the future

Very much so, and in next iterations we will be expanding the scope both in what the generated code does as well as the ways to prompt

Definitely fair feedback, we will look into it

1. A user can always go into the generated code and make changes to it. The code generated includes explanations for what each step in the workflow does

2. Dapr has 9 APIs, one of which is Workflows which indeed competes with Temporal. Dapr Workflows isn't DAG based, it's code-first. This tool allows you to start with an external representation

Great point. Our tool does UML/BPMN as well as regular drawn diagrams without a specific notation, and will soon expand into regular prompts

Dapr is a code-first workflow engine that doesn't require a DSL language and includes many other integration points like pub/sub, service discovery and more. It also runs and deploys natively on K8s

So for workflows it's like Airflow, Brigade or hatchet or ...? How do workflows integrate with k8s (ressources, ...)? Camunda can also deploy natively on k8s. However you still develop apps for Camunda and it seems like dapr is no different there? Why is it in CNCF if it doesn't provide a way to build a workflow out of k8s-native artifacts (PVs, Deployments, Jobs, ...)?