Output: An operational acceptance and response card for one team task.
Before this: Understand model limits and evidence basics, or complete AI foundations first.
Work through the fictional examples and feedback. Short notes are enough.
LecXie suggested study allocations, not provider runtimes or verified learning time. Optional deeper work is outside the total.
0 / 4
Stops marked explored
Off by default. Notes stay in this tab while navigating Learning; reload or close loses them unless exported. Nothing is sent to a learner database. Avoid personal or sensitive information.
Stop 1 of 4
Choose a useful application
Define the user problem and a useful outcome before selecting a tool.
Journey fit: Start with the prerequisite concepts above. The selected resource supplies context; the local case is where you use it.
Selected resource · Lesson 2B: The 4D Framework
Anthropic · Rick Dakan & Joseph Feller
Lesson 2B: The 4D Framework
What you will learn: Use delegation, description, discernment and diligence to plan a human–AI task.
Why this is worth the time: A practical bridge from understanding a model to describing a useful task and taking responsibility for the result.
Before this
Basic model limits
Study time
Suggested 15-minute reflection; runtime not verified
Access
Free video; no Claude account to watch; full-course access not verified
Currency / limits
Published 12 Jun 2025; AI-fluency framework, not an independent outcome evaluation
Loads a third-party player only when selected. No autoplay. If the provider blocks playback, use the original link below.
Self-reported and shared across routes. Source date: 2025-06-12 · Last update: not established · Checked 2026-10-15. Part of this stop’s selected reading.
Selected resource · User Needs + Defining Success
Google PAIR
User Needs + Defining Success
What you will learn: Identify a user problem, desired outcome and whether AI adds value.
Why this is worth the time: Makes choosing a useful application more concrete; use it before choosing automation simply because it is possible.
Before this
A candidate task or user problem
Study time
Suggested 20-minute study activity
Access
Free public text; no account needed
Currency / limits
Foundational guidebook originating in 2019; page undated
Self-reported and shared across routes. Source date: not established · Last update: not established · Checked 2026-10-15. Part of this stop’s selected reading.
Original local activity · Fictional case
Define the user problem and a useful outcome before selecting a tool.
Two hypothetical tools have different quality and checking costs. Set the minimum acceptable quality before comparing price.
Apply it to a working example
Use a hypothetical or approved non-sensitive example. Set the task’s quality threshold, evaluation examples and unacceptable failure types.
A self-report of exploration, not verified proficiency. Your work is not sent to LecXie.
Stop 2 of 4
Budget human review
Allocate review authority and capacity as part of the task.
Journey fit: Build on Choose a useful application before this activity. The selected resource supplies context; the local case is where you use it.
Selected resource · AI Risk Management Framework
NIST
AI Risk Management Framework
What you will learn: Turn a vague risk concern into ownership, context, measurement and controls.
Why this is worth the time: Provides a general risk lens. It does not replace local controls or legal advice.
Before this
A candidate task and people affected by it
Study time
Suggested 25-minute exploration of Govern, Map, Measure and Manage; not a provider runtime
Access
Free public framework; no account needed
Currency / limits
AI RMF 1.0 (2023) is being revised; check current guidance before use
Self-reported and shared across routes. Source date: 2023-01-26 · Last update: not established · Checked 2026-10-15. Part of this stop’s selected reading.
Original local activity · Fictional case
Allocate review authority and capacity as part of the task.
A team can generate 200 drafts a day but can carefully review only 40. What should change?
Apply it to a working example
Use a hypothetical or approved non-sensitive example. Write a review protocol: who checks what, at what volume, and which cases escalate.
A self-report of exploration, not verified proficiency. Your work is not sent to LecXie.
Stop 3 of 4
Monitor outcomes and drift
Plan ongoing checks for the actual system version and task mix.
Journey fit: Build on Budget human review before this activity. The selected resource supplies context; the local case is where you use it.
Selected resource · Impact Evaluation of AI Interventions
HM Treasury · Evaluation Task Force
Impact Evaluation of AI Interventions
What you will learn: Specify a baseline, comparison and outcome measures before starting a pilot.
Why this is worth the time: Connects the earlier notes to a testable pilot rather than a demonstration.
Before this
Task, safeguards, workflow and capability notes from stops 1–5
Study time
20 min selected sections; full guidance takes longer
Access
Free public guidance; no account needed
Currency / limits
Updated 15 May 2026; UK public-sector guidance, adapt to context
Self-reported and shared across routes. Source date: not established · Last update: 2026-05-15 · Checked 2026-10-15. Part of this stop’s selected reading.
Original local activity · Fictional case
Plan ongoing checks for the actual system version and task mix.
After an update, average quality looks stable but rare serious errors increase. What should the team inspect?
Apply it to a working example
Use a hypothetical or approved non-sensitive example. Define a monitoring sample, a consequential-error indicator and a pause trigger.
A self-report of exploration, not verified proficiency. Your work is not sent to LecXie.
Stop 4 of 4
Rehearse a safe stop
Prepare a response that includes affected people and a restart decision.
Journey fit: Build on Monitor outcomes and drift before this activity. The selected resource supplies context; the local case is where you use it.
Selected resource · AI Risk Management Framework
NIST
AI Risk Management Framework
What you will learn: Turn a vague risk concern into ownership, context, measurement and controls.
Why this is worth the time: Provides a general risk lens. It does not replace local controls or legal advice.
Before this
A candidate task and people affected by it
Study time
Suggested 25-minute exploration of Govern, Map, Measure and Manage; not a provider runtime
Access
Free public framework; no account needed
Currency / limits
AI RMF 1.0 (2023) is being revised; check current guidance before use
Self-reported and shared across routes. Source date: 2023-01-26 · Last update: not established · Checked 2026-10-15. Part of this stop’s selected reading.
Original local activity · Fictional case
Prepare a response that includes affected people and a restart decision.
A tool sends an incorrect internal instruction to several teams. Which response is most complete?
Apply it to a working example
Use a hypothetical or approved non-sensitive example. Write a short response card: pause, owner, evidence, correction, affected people and restart condition.
A self-report of exploration, not verified proficiency. Your work is not sent to LecXie.
An operational acceptance and response card for one team task.
Assembled from your working notes. Empty sections remain prompts. This is a draft for discussion with the responsible people.
Optional deeper branches
Separate from the core route. Alternatives cover a similar outcome; deeper work extends it. Choose deliberately rather than repeating everything.
