The building blocks of an AI workflow
Every workflow, from a bedtime story to a research report, is built from the same few blocks. The AI step sends a prompt to a model and gets back text, an image, a voice, music or a video. Knowledge blocks bring in facts with their sources. Quality blocks check the work, and a human approval waits for you. Logic blocks shape the flow with branches and loops. Output blocks join everything into one video and save the result.
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Every workflow, from a bedtime story to a research report, is built from the same few blocks. Let's go through them. The main block is the AI step. It sends a prompt to an AI model and gets back text, an image, a voice, music or a video. Every call is billed on its own.
Knowledge blocks bring in facts: a web search, a search through your own files, and a citation step that formats the sources an answer used.
Quality blocks check the work. A quality gate scores a step's output and sends it back for another try if it falls short. A human approval pauses the run until you've had a look. Logic blocks shape the flow.
A branch follows the arrow whose condition matches. A loop repeats its steps for every item in a list. And output blocks finish the job: a media step joins images, voice and music into
one video, and a save step stores the result. Every template is made of these blocks. Open any of them in the editor, and you'll see exactly how it's built. Workflows, on ToRun.