Agentic AI Foundation urges workflow reuse over agents

The author argues that as agentic AI workflows mature, routine multi-step tasks should be identified as "desire paths" and formalized into reusable skills, workflows, and code. By capturing repeated agent interactions as artifacts, users can achieve consistency, accumulate feedback, and optimize execution by offloading tasks to smaller models and code scripts. However, the author warns that a lack of interoperable harnesses threatens to lock users into proprietary tools and hinder routine discovery. Open article →