Formalizing AI Workflows with Mathematics and Python

Distinguish variables, constants, parameters, and outputs in a description of an AI workflow.

Assign symbols and units to quantities such as token count, cost, latency, branching factor, and success rate.

Translate one deterministic workflow step from plain language into an algebraic expression.

Interpret and evaluate function notation as an input-output mapping.

Use summation and product notation to represent repeated operations in a workflow.

Draw a dependency graph from a set of equations and compute its outputs in a valid order.

Run and modify short Python expressions that reproduce a mathematical calculation performed by hand.