AI-Assisted Work
A.
Appropriate Use
- 1.An AI assistant can be a legitimate first stop for understanding an unfamiliar general term, since this is exactly the kind of general knowledge an AI model is likely to represent accurately. For example, asking it to explain "user acceptance testing" in plain language.
- 2.It should not be treated as authoritative for anything organization-specific.
- 3.Whether this team calls a particular document a "requirements note" or a "business need statement," for instance, is not something an AI assistant can know - only a colleague or existing team documentation can confirm it.
- 4.A reliable habit is to use an AI assistant to get oriented on a general term, then confirm the organization-specific usage with a person.
I.
Applied Example — Learning to Ask Rather Than Guess
Scenario
- A.A new OFA 1 heard a colleague refer to "the RITE list" several times during a stand-up meeting for a stake technology rollout, and could not tell from context whether this was a system, a document, or a team.
- B.Rather than nodding along or guessing from context in a later conversation, the OFA asked directly after the meeting: "I heard 'the RITE list' a few times - could you tell me what that refers to?"
- C.It turned out to be the team's shorthand for a shared spreadsheet tracking Risks, Issues, Tasks, and Escalations for the rollout - a piece of vocabulary specific to this team that would not have appeared in any general glossary.
OFA Interpretation Questions
- D.What would have happened if the OFA had kept nodding along without asking?
- E.Why might team-specific vocabulary like this never appear in a general reference like Appendix A?
Stewardship Application
- F.Vocabulary is not always general-purpose; some of it is local shorthand invented by a specific team.
- G.An OFA who is comfortable asking "what does that mean?" in the moment, rather than waiting to be embarrassed by a later misunderstanding, builds trust faster than one who quietly hopes context will eventually clarify things.
II.
Applied Practice and Evaluation
Scenario Context
The learner attends, observes, or reviews a recording of a real team meeting (a stand-up, a requirements discussion, or a status update) for a project they are new to.
Required OFA Reasoning
Identify every term or process reference that was unfamiliar. Determine which can be resolved from Appendix A versus which require asking a colleague directly.
Required Output
A personal glossary entry for each unfamiliar term, noting the source of the definition (Appendix A, a colleague, or a general AI lookup later confirmed by a colleague).
Strong Performance Indicators
- A.Every unfamiliar term encountered is captured, not just the ones that stood out as obviously important.
- B.Team-specific terms are correctly distinguished from general industry terms.
- C.Definitions are confirmed against a source rather than inferred from context alone.
Weak Performance Indicators
- D.Only a few terms are captured; others are silently let go.
- E.A team-specific term is documented as if it were a general industry term, or vice versa.
- F.A definition is guessed at and recorded without confirmation.
III.
Business Case Applications
A.
Case 1 — Data Migration
- 1.Scenario
- a.The learner joins a kickoff meeting for a legacy ward record migration and hears several unfamiliar terms, including "field mapping" and "orphaned record."
- 2.Task
- a.Capture each unfamiliar term, resolve each against Appendix A or a colleague, and note which terms are general industry vocabulary versus specific to this migration project.
- 3.Deliverable
- a.A short personal glossary entry for each term.
- 4.Evaluation Notes
- a.The learner correctly identifies "field mapping" and "orphaned record" as general data migration vocabulary, likely to reappear on future projects, rather than assuming they are one-off jargon.
B.
Case 2 — Notification System Rollout
- 1.Scenario
- a.A new team the learner has just joined refers casually to "the opt-out flow" and "a soft bounce" during a planning meeting for a family activity reminder system.
- 2.Task
- a.Ask a colleague to clarify each term, and record the process implication of each (for example, what the team does differently when a message soft-bounces versus hard-bounces).
- 3.Deliverable
- a.A glossary entry for each term that includes not just a definition but the process action tied to it.
- 4.Evaluation Notes
- a.The entry captures the process action, not just a dictionary-style definition, since knowing what the team does about a soft bounce is more useful than a generic definition alone.
C.
Case 3 — System Integration
- 1.Scenario
- a.The learner moves from a project that captured requirements in a narrative Word document to a new project that captures them directly as structured work items in a tracking tool, and initially tries to draft requirements the old way.
- 2.Task
- a.Recognize that this team's requirements process differs from the previous project's, ask directly how requirements are captured here, and adjust accordingly.
- 3.Deliverable
- a.A short written note describing this team's requirements process, for the learner's own future reference.
- 4.Evaluation Notes
- a.The learner asks the question directly rather than assuming their prior project's process applies everywhere, and the resulting note is specific enough to be useful on a future assignment with this same team.