Module 03 · 16 minutes
Context and Data Flow
Break a process into steps, then define context, data flow, tools, and human handoffs.
Written and edited by Cahyanto Arie Wibowo. Last reviewed · version 1.2.
How does the idea of “Context and Data Flow” change the decision we make?
In Applied AI, use Context and Data Flow to make the next step explicit and easier for another person to review. Ask two questions about Context and Data Flow. What is it, and which decision becomes clearer once you understand it? Afterward, it should be easier to separate evidence about Context and Data Flow from claims that have not been tested.
After this lesson
- In Applied AI, use Context and Data Flow to make the next step explicit and easier for another person to review.
- Use the idea of “Context and Data Flow” to interpret one realistic situation.
- Explain the limits of the concept and the information that still needs to be checked.
Start with the situation
Understand the situation first. The label can come later.
AI drafts a report, an analyst checks the figures, and the process owner approves the final recommendation. This lesson uses the idea of “Context and Data Flow” to examine that situation without treating a single term as the answer to every problem.
In Applied AI, use Context and Data Flow to make the next step explicit and easier for another person to review. Break a process into steps, then define context, data flow, tools, and human handoffs. Connect the term to a decision someone genuinely needs to make.
See how the decision unfolds
Move from the situation to a choice others can review.
01
Situation
AI drafts a report, an analyst checks the figures, and the process owner approves the final recommendation. This lesson uses the idea of “Context and Data Flow” to examine that situation without treating a single term as the answer to every problem.
02
Decision
AI drafts a report, an analyst checks the figures, and the process owner approves the final recommendation. Identify the part of the situation most closely connected to the idea of “Context and Data Flow”. Use the case as a thinking tool, not as proof that one solution fits every context.
03
Review
Automation without an owner makes errors harder to find and fix. This mistake often appears when a label is used before the problem is understood. Write down your assumptions so another person can review them.
Do not rush the choice
Two ways to look at Context and Data Flow
Useful when
- In Applied AI, use Context and Data Flow to make the next step explicit and easier for another person to review.
- Use the idea of “Context and Data Flow” to interpret one realistic situation.
- In Applied AI, use Context and Data Flow to make the next step explicit and easier for another person to review. Break a process into steps, then define context, data flow, tools, and human handoffs. Connect the term to a decision someone genuinely needs to make.
Pause and check
- Automation without an owner makes errors harder to find and fix. This mistake often appears when a label is used before the problem is understood. Write down your assumptions so another person can review them.
- Explain the limits of the concept and the information that still needs to be checked.
The stronger choice is the one whose evidence, owner, and limits can be explained, not simply the more sophisticated option.
Visual model
Map the parts before choosing what to do.
Read the diagram as a map of Context and Data Flow: begin with the context, follow the connections, and inspect the highlighted point before making a decision.
Pause for a moment
What evidence could change this decision?
Answer before opening the discussion. Name one fact and one assumption.
Open the discussion
In Applied AI, use Context and Data Flow to make the next step explicit and easier for another person to review. Ask two questions about Context and Data Flow. What is it, and which decision becomes clearer once you understand it? Afterward, it should be easier to separate evidence about Context and Data Flow from claims that have not been tested.
A tempting shortcut
A familiar term can still lead us to the wrong decision.
Why this can seem reasonable
Automation without an owner makes errors harder to find and fix. This mistake often appears when a label is used before the problem is understood. Write down your assumptions so another person can review them.
How to check it
Ask two questions about Context and Data Flow. What is it, and which decision becomes clearer once you understand it? Begin with what can be observed, then separate facts, assumptions, and open questions.
Try it on your work
Try it with one small piece of real work.
- Choose one real situation related to Context and Data Flow.
- Separate what you can observe from what you are assuming.
- Write one decision, its owner, and the evidence needed to review it.
- Name the signal that would make you stop or change direction.
Choose a task you know. List what is known, what is still an assumption, and what must be tested before using the idea of “Context and Data Flow”. The larger module activity is: Map the workflow before and after AI, including every human review point. Keep the first version small enough for another person to review in a few minutes.
Quick practice
Choose a task you know. List what is known, what is still an assumption, and what must be tested before using the idea of “Context and Data Flow”. The larger module activity is: Map the workflow before and after AI, including every human review point.
Summary
- In Applied AI, use Context and Data Flow to make the next step explicit and easier for another person to review.
- Use examples and evidence to test your understanding.
- Record the limits, risks, and conditions that should trigger another review.
Continue from here
- Tools and Handoffs: Continue the idea from Designing the Workflow with a closely related example.
- Model Capability: Connect this lesson to Product Thinking and test the idea in another context.
- Retrieval and Tools: See how the same decision changes when viewed through Prompting.
Sources and further reading
- People + AI Guidebook: Google PAIR · official-guidebook. Primary reference for the definition, evidence, or limits discussed in “Context and Data Flow”.
- AI Risk Management Framework Playbook: NIST · official-framework. Further evidence and context for checking the explanation in “Context and Data Flow”.
- Safety best practices: OpenAI · official-documentation. Further evidence and context for checking the explanation in “Context and Data Flow”.