Project Components

Many AI portfolio projects start the same way: a notebook or script that runs correctly on the developer's own machine, using the developer's own data. The code may be well written and the model may perform impressively on the test split, yet the project can still show very little about whether the work mattered to anyone. IJK TEC Academy uses the term production AI workflow for the stronger kind of project, one that is actually being used in the real world. Recognizing one, and describing your own work in those terms, is the first step toward a portfolio that tells a clear story.

This sentence is the central test in the definition. The other elements of the definition, which are real users, real data, and a before/after story with a measurable outcome, support it. The source explains the logic directly: if someone other than you depends on the workflow, the users, data, and outcome are usually already present. Dependence is the signal that the work has moved beyond the developer's own environment.

The source is flexible about who the users are. They may be external customers, internal colleagues, or friends who run small businesses. A personal use case is also allowed, as long as it is clearly named and is a workflow you actually use in a real situation. The category of user matters less than the fact that someone other than you is genuinely using the project, and that you can describe its impact in one sentence.

Read the flowchart as a sequence. The first check is always whether someone other than you depends on the workflow. If the answer is no, the project is not yet in production, regardless of how polished the code is. If the answer is yes, the second check asks whether you can state the impact in one sentence with a measurable change. The source notes that a project may still lack a measurable outcome, or the developer may not yet know what the outcome is. In that case the project is in use but is not yet fully described as a production workflow.

The definition names three ingredients. Each one rules out a common imitation of real production work. Together they describe what a production workflow looks like once the central test is passed. The diagram below shows how the three ingredients sit together and how the central test supports them.

The source gives a concrete before/after sentence: before this tool, the office spent most of Monday sorting scanned forms by hand, and now the forms are sorted in minutes. Trace the state of the office's work across the change, one element at a time. The before state contains a manual task with a large time cost. The after state contains the same inputs handled by the tool, with a much shorter time cost. The measurable outcome is the change in time, and it appears in the difference between the two states.

Notice what did not change. The input is the same kind of scanned form in both columns. The step that changed is the sorting, and the time it takes is the measurable outcome. If you can point to a step that changed and a quantity that moved, your before/after story is concrete enough to check.

The source requires that you can describe a project's impact in one sentence. This discipline forces the before/after story into a compact form. A good impact statement contains a before state, an after state, and an outcome that can be checked. If you cannot write such a sentence, the project may still lack a measurable outcome, or you may not yet know what the outcome is.