Use-case portfolio, value, and stop decisions
Compare the whole task with AI and without it.
In this lesson · L2 of 7
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Start with the idea
Compare the whole task with AI and without it.
Include review effort and important errors. Consider a template or simpler process. Treat a result from a small training set as evidence to investigate, not a universal benefit.
Total effort: All work needed for the result, including drafting, checking and correction.
See the example and check your understanding
A made-up teaching example
Manual notices take ten minutes. AI drafting takes three minutes plus eight minutes of review: eleven. A template takes seven minutes in the small test and avoids the observed unsupported dates.
Ask yourself
Has AI demonstrated time savings in this example?
Show the explanation
No. Three plus eight is eleven. The template is the stronger current candidate, pending broader testing.
Start with these checks
- Count review and correction.
- Report severity as well as error counts.
- Keep assumed benefits separate from findings.
Use the different practice case below and check every requirement in its full instructions.
The video explains the main idea. Use the sources, instructions and checks below to complete the practice.
Captions appear here during playback.
Use-case portfolio, value, and stop decisions
Compare the whole task with AI and without it.
Video playback is unavailable. Read the descriptive transcript below, go directly to practice, or open the video file.
Source-based teaching example · Fictional data · Reviewed 2026-10-03. Microsoft Mark · locally synthesized. On a small screen, use fullscreen for diagram details or read the transcript.
Read the descriptive transcript
0:00 · What you will learn
Compare the whole task with AI and without it.
What appears on screen
Compare the whole task with AI and without it.
0:05 · The idea
Include review effort and important errors. Consider a template or simpler process. Treat a result from a small training set as evidence to investigate, not a universal benefit.
What appears on screen
Include review effort and important errors. Consider a template or simpler process. Treat a result from a small training set as evidence to investigate, not a universal benefit.
0:20 · One useful term
Total effort. All work needed for the result, including drafting, checking and correction.
What appears on screen
All work needed for the result, including drafting, checking and correction.
0:29 · A worked example
Manual notices take ten minutes. AI drafting takes three minutes plus eight minutes of review: eleven. A template takes seven minutes in the small test and avoids the observed unsupported dates.
What appears on screen
Manual notices take ten minutes. AI drafting takes three minutes plus eight minutes of review: eleven. A template takes seven minutes in the small test and avoids the observed unsupported dates.
0:45 · Your turn to think
Has AI demonstrated time savings in this example? Pause and decide before continuing.
What appears on screen
Has AI demonstrated time savings in this example? Pause the video if you need more time.
1:02 · Why this answer works
No. Three plus eight is eleven. The template is the stronger current candidate, pending broader testing.
What appears on screen
No. Three plus eight is eleven. The template is the stronger current candidate, pending broader testing.
1:11 · Check 1
Count review and correction.
What appears on screen
Count review and correction.
1:16 · Check 2
Report severity as well as error counts.
What appears on screen
Report severity as well as error counts.
1:22 · Check 3
Keep assumed benefits separate from findings.
What appears on screen
Keep assumed benefits separate from findings.
1:28 · Now try a different case
Open the lesson and try its different practice case. Use every check in the full task. Watching alone does not mark the lesson complete.
What appears on screen
Open the lesson Try the new case Check and revise The full task and its requirements are in the linked lesson.
Watching explains the example. Complete the lesson practice to check what you can do. Explore all visual lessons →
Prerequisites: distinguish output from evidence; review the AI workflow reference. Public self-study is not official agency training, accreditation or a credential.
What you will be able to do
This lesson develops the ability to prioritize a portfolio by mission evidence and risk. The setting is NORTHSTAR Mission Portfolio, a fictional public-service portfolio containing ten proposed AI and non-AI interventions, three synthetic vendors, constrained staff capacity, and a staged incident. Every person, organization, system record, metric, and outcome in the case is fictional. Do not replace the case with operational, classified, CUI, export-controlled, proprietary, employer-confidential, or third-party personal information.
By the end of the lesson, you will be able to:
- Demonstrate how to prioritize a portfolio by mission evidence and risk.
- Apply that model to the synthetic NORTHSTAR Mission Portfolio environment.
- Produce a reviewable artifact that separates evidence, assumption, uncertainty, and authority.
- Recognize the critical failure and select a safe remediation path.
The performance standard is not confident language. It is a traceable decision, an artifact another qualified reviewer can inspect, a clear boundary around the learner’s authority, and a safe response to uncertainty. Knowledge checks are formative and do not award a certification or endorsement.
This curriculum runs self-study on VetsLearn. Where the text calls for an instructor, peer or formal review, use the stated acceptance criteria for self-review. Reflection questions support reflection; they do not replace independent assessment. A peer review is optional unless your actual organization requires it.
Part 1 Value and counterfactuals
Start with a mission bottleneck and baseline. Compare process improvements, clearer guidance, staffing, search, ordinary automation and AI. Benefits are measured outcome differences including quality and review work; prompts and seats are activity. Rank proposals by consequence, reversibility, evidence readiness, capacity and dependencies. Predeclare scale, revise, pause and stop conditions. A notice draft and automatic benefit prioritization need different controls and authority.
Calculate value without losing quality
Use end-to-end minutes = preparation + generation/process + review + correction. Keep error severity beside the time result. Divide observed differences by the baseline only when the tasks, populations and measurement procedures are comparable.
| Synthetic workflow | Draft/process | Review/correction | Total | Unsupported dates / 20 |
|---|---|---|---|---|
| Manual | 8 min | 2 min | 10 min | 0 |
| AI draft | 3 min | 8 min | 11 min | 2 |
| Template | 5 min | 2 min | 7 min | 0 |
The AI workflow is one minute slower, or 10% more time than the ten-minute baseline. The template is three minutes faster, or 30% less time, in this synthetic sample. Do not extrapolate those percentages to an agency or claim causation from an uncontrolled comparison.
Portfolio rule: select a bounded pilot only if its consequence is acceptable, evidence can be collected and manual fallback exists. Revise if review exceeds five minutes; pause on unsupported critical dates; stop if the workflow performs prohibited actions. Those are fictional rules to practice precommitment.
Feedback: a benefit estimate becomes useful when the measurement can disprove it. Adoption counts cannot repair a negative end-to-end result.
Part 2 Synthetic worked example
Manual notices take ten minutes. AI drafting takes three plus eight minutes review: eleven. Two dates are unsupported in twenty synthetic cases. A template takes seven minutes without unsupported dates in this small set. AI has not demonstrated time saving; the template is the stronger current hypothesis pending broader testing.
Guided practice: identify the unsupported conclusion, name missing evidence and rewrite its scope. Change one assumption and identify which decision reopens.
Part 3 Feedback and repair
Three plus eight is eleven. Pass when review burden and severity accompany timing, and assumed benefits are not presented as findings.
Retain the failed version, explain the criterion, correct the artifact and test a different invented case.
Next step: carry the artifact and failed cases into the next module lesson or capstone. Retain limitations when explaining your work.