Facilitator Guide — Management (sessions 10–18)
Run these Lojik360 action sessions with a group — aligned to the three moves: delegate carefully, supervise rigorously, strengthen what stays human.
How to use this guide
This guide helps a facilitator, coach, trainer, or team lead run the 27 learner-action sessions. It is aligned to the improved learner guide and adds concept-teaching notes, guided action support, debrief questions, and learner artifact review criteria.
Facilitation principle. The facilitator should not lecture through the content. The facilitator's job is to help learners define concepts, act on real examples, protect sensitive information, review their artifacts, and leave with evidence of learning.
- Start each session by naming the learner artifact to be produced.
- Use the title concepts as a short warm-up before action begins.
- Keep learners working with their own real but safe examples.
- Use the guided action table to coach action, not to present slides.
- Use the review rubric to inspect artifacts before learners leave the session.
- Close each session with evidence, next action, and one open risk or question.
Learner version of these sessions: Management. Other facilitator volumes: Technology usage · Strengthen the human. Pick a session in the menu — one is shown at a time.
Session 10 — Publish a One-Page AI Usage Doctrine
Management · ⏱ 60 minutes · 🎯 Artifact: AI Usage Doctrine
Learner outcome. Managers can write a clear doctrine that tells teams what AI uses are encouraged, restricted, forbidden, and reviewable.
Core idea. A doctrine reduces improvisation. It gives people permission to learn while protecting data, quality, accountability, and trust.
Facilitator intent. Guide learners to produce a usable AI Usage Doctrine while applying the title concepts from the improved learner guide. The session should feel like coached practice, not a lecture about publish a one-page ai usage doctrine.
🧭 Domain note. Help leaders move from slogans to operating rules: owners, metrics, pilots, controls, and honest change conversations.
Watch for: Managers may speak in policy language. Push for examples, decision rights, stop rules, and visible feedback loops.
Watch for: Managers may speak in policy language. Push for examples, decision rights, stop rules, and visible feedback loops.
Title concepts to teach
Use this section to make the improved learner-guide title concepts practical before learners begin the worksheet. Keep this short and example-driven.
Publish — To publish is to make a rule, guide, or decision visible and usable by the people expected to follow it.
An AI rule that stays in someone's head does not guide behavior. Publishing creates shared expectations and a basis for review.
🏋 Try: Post the team AI rules where people actually work.Include examples of allowed and forbidden uses.
👩🏫 Ask learners to give one example from their own context and explain why the concept matters for their artifact.
An AI rule that stays in someone's head does not guide behavior. Publishing creates shared expectations and a basis for review.
🏋 Try: Post the team AI rules where people actually work.Include examples of allowed and forbidden uses.
👩🏫 Ask learners to give one example from their own context and explain why the concept matters for their artifact.
AI Usage — AI usage means the ways people apply AI systems to draft, summarize, analyze, recommend, classify, automate, or decide.
Different uses carry different risk. Drafting a low-risk email is not the same as recommending a benefit, diagnosis, loan, or disciplinary action.
🏋 Try: List every AI use your team already performs.Separate drafting, recommendation, and decision uses.
👩🏫 Ask learners to give one example from their own context and explain why the concept matters for their artifact.
Different uses carry different risk. Drafting a low-risk email is not the same as recommending a benefit, diagnosis, loan, or disciplinary action.
🏋 Try: List every AI use your team already performs.Separate drafting, recommendation, and decision uses.
👩🏫 Ask learners to give one example from their own context and explain why the concept matters for their artifact.
Doctrine — A doctrine is a short set of guiding rules that explains what is encouraged, restricted, forbidden, and escalated.
A doctrine is more practical than a long policy for daily behavior. It gives teams enough clarity to act while formal governance evolves.
🏋 Try: Write four zones: encouraged, review required, forbidden, and escalate.Add a review date so the doctrine evolves with tools and rules.
👩🏫 Ask learners to give one example from their own context and explain why the concept matters for their artifact.
A doctrine is more practical than a long policy for daily behavior. It gives teams enough clarity to act while formal governance evolves.
🏋 Try: Write four zones: encouraged, review required, forbidden, and escalate.Add a review date so the doctrine evolves with tools and rules.
👩🏫 Ask learners to give one example from their own context and explain why the concept matters for their artifact.
Before the session
- Review the matching learner-facing session before facilitating.
- Prepare a simple example of a completed AI Usage Doctrine that is safe to discuss.
- Remind learners not to paste confidential, personal, regulated, or sensitive information into public tools.
- Decide whether learners will work individually, in pairs, or in role-based groups.
- Prepare a visible timer so action time does not disappear into discussion.
Opening move
- Ask learners where this session topic already appears in their real work or life.
- Invite them to name one mistake that would be costly if they handled the topic casually.
- State that the goal is a concrete artifact, not agreement with the facilitator.
Guided action support
Use the learner actions from the improved guide. Your job is to keep each action concrete, safe, and evidenced.
List the AI uses already happening or likely to happen in your team.
👉 Keep the learner working on a real case. Ask for a concrete sentence, example, or decision before moving on.
🔎 Evidence: A visible entry in the learner worksheet that another person can understand.
👉 Keep the learner working on a real case. Ask for a concrete sentence, example, or decision before moving on.
🔎 Evidence: A visible entry in the learner worksheet that another person can understand.
Sort them into four zones: encouraged, allowed with review, forbidden, and escalate immediately.
👉 Treat review as action. Ask who checks, what evidence they use, and what power they have to pause or change the result.
🔎 Evidence: A verification note showing source, reviewer, criteria, or correction.
👉 Treat review as action. Ask who checks, what evidence they use, and what power they have to pause or change the result.
🔎 Evidence: A verification note showing source, reviewer, criteria, or correction.
Define rules for data, verification, transparency, ownership, and incidents.
👉 Pause for data safety. Ask learners what information must not be shared and what can be safely fictionalized.
🔎 Evidence: A completed data note with allowed, forbidden, and unknown information clearly separated.
👉 Pause for data safety. Ask learners what information must not be shared and what can be safely fictionalized.
🔎 Evidence: A completed data note with allowed, forbidden, and unknown information clearly separated.
Write examples so the doctrine is concrete, not a vague principle statement.
👉 Ask for a short written output, then have learners underline the parts that are specific, checkable, and owned.
🔎 Evidence: A usable written sentence, rule, script, prompt, or brief.
👉 Ask for a short written output, then have learners underline the parts that are specific, checkable, and owned.
🔎 Evidence: A usable written sentence, rule, script, prompt, or brief.
Set a review date because tools, risks, and rules will change.
👉 Treat review as action. Ask who checks, what evidence they use, and what power they have to pause or change the result.
🔎 Evidence: A verification note showing source, reviewer, criteria, or correction.
👉 Treat review as action. Ask who checks, what evidence they use, and what power they have to pause or change the result.
🔎 Evidence: A verification note showing source, reviewer, criteria, or correction.
Learner worksheet guidance
Tell learners to fill these fields during the session. Do not let the worksheet become decoration; pause and inspect it.
- Team or project
- Encouraged uses
- Allowed with review
- Forbidden uses
- Escalation triggers
- Data rule
- Verification rule
- Review date
Choice path facilitation
Ask learners which option they would naturally choose before revealing the consequence. This surfaces habits and risk tolerance.
⚠️ Let everyone use judgment without written rules
Fragile. People may have different risk tolerance and hidden assumptions.
Fragile. People may have different risk tolerance and hidden assumptions.
✅ Write a short doctrine with examples and review points
Best choice. It gives permission and boundaries at the same time.
Best choice. It gives permission and boundaries at the same time.
⚠️ Ban all AI until leadership decides everything
Sometimes necessary for high-risk contexts, but often blocks useful low-risk learning.
Sometimes necessary for high-risk contexts, but often blocks useful low-risk learning.
Prompt safety and use
These learner prompts can be useful, but remind learners to use only information they are allowed to share.
Help me draft a one-page AI usage doctrine for [team]. Include encouraged uses, review-required uses, forbidden uses, escalation triggers, data rules, verification rules, and a review date.
Stress-test this doctrine. Give me ten realistic situations where people may misunderstand or bypass it.
Rewrite this doctrine in plain language for frontline staff while keeping the rules precise: [paste].
Mini-case bridge
An insurer discovers that teams use several assistants with different data practices. A one-page doctrine defines approved uses, prohibited data, owner responsibilities, and incident reporting. Experimentation continues, but the boundaries become visible.
👩🏫 Ask learners what the person or team in the mini-case did well, what risk remained, and what they would copy or change in their own context.
👩🏫 Ask learners what the person or team in the mini-case did well, what risk remained, and what they would copy or change in their own context.
Debrief questions
- What changed in your understanding of publish a one-page ai usage doctrine after building the AI Usage Doctrine?
- Where did you notice a temptation to skip a check, avoid a hard choice, or stay vague?
- What part of your work can you apply this to within the next seven days?
- What evidence would convince you that this session changed behavior, not only awareness?
Artifact review criteria
| Criterion | What good looks like | Red flag |
|---|---|---|
| Specificity | The AI Usage Doctrine names a real context, user, task, decision, or situation. | The artifact uses vague language such as 'improve work' or 'use AI better.' |
| Actionability | The next step is small, dated, and possible within seven days. | The learner ends with an aspiration but no action. |
| Human responsibility | The learner names who decides, reviews, verifies, or carries responsibility. | The tool, policy, or system appears to be responsible by itself. |
| Evidence | The learner saves proof: a baseline, example, draft, rule, message, map, or review note. | The learner leaves with only an opinion or intention. |
| Safety | Sensitive information is removed, fictionalized, or kept inside approved systems. | The learner exposes real data unnecessarily or cannot name the data boundary. |
Common mistakes to watch for
- Writing values without examples.
- Forgetting to define who owns each AI system.
- Treating AI assistance, recommendation, and decision as the same thing.
- Never revisiting the doctrine after tools change.
Close the session
- Ask each learner to state the artifact they created and the next action they will take.
- Collect one unresolved question or risk from each learner or group.
- End by connecting the session back to Lojik360's three moves: delegate carefully, supervise rigorously, and strengthen what remains human.
Session 11 — Start Transformation From the Work Problem
Management · ⏱ 55 minutes · 🎯 Artifact: Work Problem Brief
Learner outcome. Managers can define the work problem, baseline measure, user group, and expected improvement before buying or deploying technology.
Core idea. Tool-first transformation creates theater. Problem-first transformation produces learning, measurement, and better decisions.
Facilitator intent. Guide learners to produce a usable Work Problem Brief while applying the title concepts from the improved learner guide. The session should feel like coached practice, not a lecture about start transformation from the work problem.
🧭 Domain note. Help leaders move from slogans to operating rules: owners, metrics, pilots, controls, and honest change conversations.
Watch for: Managers may speak in policy language. Push for examples, decision rights, stop rules, and visible feedback loops.
Watch for: Managers may speak in policy language. Push for examples, decision rights, stop rules, and visible feedback loops.
Title concepts to teach
Use this section to make the improved learner-guide title concepts practical before learners begin the worksheet. Keep this short and example-driven.
Transformation — Transformation is a meaningful change in how work creates value, not just the introduction of a new tool.
Real transformation changes roles, workflows, measures, skills, decisions, or customer experience.
🏋 Try: Describe what would change for the user if a project succeeded.Name which workflow, role, or decision will be different after the change.
👩🏫 Ask learners to give one example from their own context and explain why the concept matters for their artifact.
Real transformation changes roles, workflows, measures, skills, decisions, or customer experience.
🏋 Try: Describe what would change for the user if a project succeeded.Name which workflow, role, or decision will be different after the change.
👩🏫 Ask learners to give one example from their own context and explain why the concept matters for their artifact.
Work Problem — A work problem is a specific pain, delay, risk, error, cost, or unmet need in the way work is done.
A work problem should be observable and measurable. Vague goals like innovation or modernization are not enough.
🏋 Try: Write the painful moment in the workflow before naming a tool.Measure the current baseline for delay, rework, or frustration.
👩🏫 Ask learners to give one example from their own context and explain why the concept matters for their artifact.
A work problem should be observable and measurable. Vague goals like innovation or modernization are not enough.
🏋 Try: Write the painful moment in the workflow before naming a tool.Measure the current baseline for delay, rework, or frustration.
👩🏫 Ask learners to give one example from their own context and explain why the concept matters for their artifact.
Baseline — A baseline is the current measured state before a change is tested.
Without a baseline, you cannot tell whether the change improved anything or only felt new.
🏋 Try: Measure current turnaround time before piloting an AI assistant.Record current error types before changing a process.
👩🏫 Ask learners to give one example from their own context and explain why the concept matters for their artifact.
Without a baseline, you cannot tell whether the change improved anything or only felt new.
🏋 Try: Measure current turnaround time before piloting an AI assistant.Record current error types before changing a process.
👩🏫 Ask learners to give one example from their own context and explain why the concept matters for their artifact.
Before the session
- Review the matching learner-facing session before facilitating.
- Prepare a simple example of a completed Work Problem Brief that is safe to discuss.
- Remind learners not to paste confidential, personal, regulated, or sensitive information into public tools.
- Decide whether learners will work individually, in pairs, or in role-based groups.
- Prepare a visible timer so action time does not disappear into discussion.
Opening move
- Ask learners where this session topic already appears in their real work or life.
- Invite them to name one mistake that would be costly if they handled the topic casually.
- State that the goal is a concrete artifact, not agreement with the facilitator.
Guided action support
Use the learner actions from the improved guide. Your job is to keep each action concrete, safe, and evidenced.
Name the affected person or group. Be specific: customers, staff, managers, analysts, suppliers, trainees, or patients.
👉 Keep the learner working on a real case. Ask for a concrete sentence, example, or decision before moving on.
🔎 Evidence: A visible entry in the learner worksheet that another person can understand.
👉 Keep the learner working on a real case. Ask for a concrete sentence, example, or decision before moving on.
🔎 Evidence: A visible entry in the learner worksheet that another person can understand.
Describe the painful moment in the workflow, not the technology feature.
👉 Keep the learner working on a real case. Ask for a concrete sentence, example, or decision before moving on.
🔎 Evidence: A visible entry in the learner worksheet that another person can understand.
👉 Keep the learner working on a real case. Ask for a concrete sentence, example, or decision before moving on.
🔎 Evidence: A visible entry in the learner worksheet that another person can understand.
Measure the current baseline: delay, error, cost, rework, frustration, risk, or missed opportunity.
👉 Insist on a real baseline. If learners cannot measure exactly, ask for a reasonable proxy and a date to improve it.
🔎 Evidence: A number, proxy, or observation that can be compared after the test.
👉 Insist on a real baseline. If learners cannot measure exactly, ask for a reasonable proxy and a date to improve it.
🔎 Evidence: A number, proxy, or observation that can be compared after the test.
Write the improvement you want in observable terms.
👉 Ask for a short written output, then have learners underline the parts that are specific, checkable, and owned.
🔎 Evidence: A usable written sentence, rule, script, prompt, or brief.
👉 Ask for a short written output, then have learners underline the parts that are specific, checkable, and owned.
🔎 Evidence: A usable written sentence, rule, script, prompt, or brief.
Only then list possible solutions, including non-AI changes.
👉 Keep the learner working on a real case. Ask for a concrete sentence, example, or decision before moving on.
🔎 Evidence: A visible entry in the learner worksheet that another person can understand.
👉 Keep the learner working on a real case. Ask for a concrete sentence, example, or decision before moving on.
🔎 Evidence: A visible entry in the learner worksheet that another person can understand.
Learner worksheet guidance
Tell learners to fill these fields during the session. Do not let the worksheet become decoration; pause and inspect it.
- Affected group
- Painful moment
- Current baseline
- Root cause hypothesis
- Desired improvement
- Constraints
- Possible solutions
- First test
Choice path facilitation
Ask learners which option they would naturally choose before revealing the consequence. This surfaces habits and risk tolerance.
⚠️ Buy or copy the tool because others are using it
Tool-first change can create cost without solving the work problem.
Tool-first change can create cost without solving the work problem.
✅ Define the problem, baseline, and user before selecting tools
Best choice. It turns transformation into measurable learning.
Best choice. It turns transformation into measurable learning.
⚠️ Wait until the problem is perfectly understood
Too slow. A clear first problem statement is enough to start a limited test.
Too slow. A clear first problem statement is enough to start a limited test.
Prompt safety and use
These learner prompts can be useful, but remind learners to use only information they are allowed to share.
Convert this tool idea into a work problem brief: [tool idea]. Ask who is affected, what pain occurs, what baseline proves it, and what improvement matters.
Challenge this problem statement. Is it a real work problem, a symptom, a preference, or a technology wish?
Suggest non-AI, low-tech, AI-assisted, and fully automated options for this problem. Explain what evidence would select between them.
Mini-case bridge
A department wants a chatbot because competitors have one. Interviews show that the real pain is delayed escalation for emotional customer cases. The solution becomes a triage and handoff redesign, not just a chatbot.
👩🏫 Ask learners what the person or team in the mini-case did well, what risk remained, and what they would copy or change in their own context.
👩🏫 Ask learners what the person or team in the mini-case did well, what risk remained, and what they would copy or change in their own context.
Debrief questions
- What changed in your understanding of start transformation from the work problem after building the Work Problem Brief?
- Where did you notice a temptation to skip a check, avoid a hard choice, or stay vague?
- What part of your work can you apply this to within the next seven days?
- What evidence would convince you that this session changed behavior, not only awareness?
Artifact review criteria
| Criterion | What good looks like | Red flag |
|---|---|---|
| Specificity | The Work Problem Brief names a real context, user, task, decision, or situation. | The artifact uses vague language such as 'improve work' or 'use AI better.' |
| Actionability | The next step is small, dated, and possible within seven days. | The learner ends with an aspiration but no action. |
| Human responsibility | The learner names who decides, reviews, verifies, or carries responsibility. | The tool, policy, or system appears to be responsible by itself. |
| Evidence | The learner saves proof: a baseline, example, draft, rule, message, map, or review note. | The learner leaves with only an opinion or intention. |
| Safety | Sensitive information is removed, fictionalized, or kept inside approved systems. | The learner exposes real data unnecessarily or cannot name the data boundary. |
Common mistakes to watch for
- Starting with features instead of user pain.
- Using vague goals like 'modernize' or 'be efficient.'
- Forgetting to measure the current baseline.
- Ignoring simpler process fixes.
Close the session
- Ask each learner to state the artifact they created and the next action they will take.
- Collect one unresolved question or risk from each learner or group.
- End by connecting the session back to Lojik360's three moves: delegate carefully, supervise rigorously, and strengthen what remains human.
Session 12 — Run a Limited Pilot With Balanced Metrics
Management · ⏱ 70 minutes · 🎯 Artifact: Pilot Board
Learner outcome. Managers can design a pilot with scope, guardrails, support, stop rules, and metrics for quality, speed, cost, risk, and experience.
Core idea. A pilot should not be a public relations demo. It is a disciplined learning device with permission to stop, adapt, or scale.
Facilitator intent. Guide learners to produce a usable Pilot Board while applying the title concepts from the improved learner guide. The session should feel like coached practice, not a lecture about run a limited pilot with balanced metrics.
🧭 Domain note. Help leaders move from slogans to operating rules: owners, metrics, pilots, controls, and honest change conversations.
Watch for: Managers may speak in policy language. Push for examples, decision rights, stop rules, and visible feedback loops.
Watch for: Managers may speak in policy language. Push for examples, decision rights, stop rules, and visible feedback loops.
Title concepts to teach
Use this section to make the improved learner-guide title concepts practical before learners begin the worksheet. Keep this short and example-driven.
Limited Pilot — A limited pilot is a small, bounded test of a change before broader adoption.
The purpose of a pilot is learning. It should have scope, duration, users, data, metrics, support, and stop rules.
🏋 Try: Test one request type with one team for two weeks.Exclude high-risk cases until the control method is proven.
👩🏫 Ask learners to give one example from their own context and explain why the concept matters for their artifact.
The purpose of a pilot is learning. It should have scope, duration, users, data, metrics, support, and stop rules.
🏋 Try: Test one request type with one team for two weeks.Exclude high-risk cases until the control method is proven.
👩🏫 Ask learners to give one example from their own context and explain why the concept matters for their artifact.
Balanced Metrics — Balanced metrics measure more than speed, including quality, cost, rework, satisfaction, mental load, incidents, and trust.
A tool can make work faster and worse at the same time. Balanced measures reveal tradeoffs.
🏋 Try: Track time saved and customer callbacks together.Measure review effort and user stress during the pilot.
👩🏫 Ask learners to give one example from their own context and explain why the concept matters for their artifact.
A tool can make work faster and worse at the same time. Balanced measures reveal tradeoffs.
🏋 Try: Track time saved and customer callbacks together.Measure review effort and user stress during the pilot.
👩🏫 Ask learners to give one example from their own context and explain why the concept matters for their artifact.
Stop Rules — Stop rules define conditions that pause, redesign, or end a pilot.
Stop rules prevent momentum from carrying a weak or harmful system into full deployment.
🏋 Try: Stop if error severity exceeds the agreed threshold.Pause if users cannot verify outputs within the available time.
👩🏫 Ask learners to give one example from their own context and explain why the concept matters for their artifact.
Stop rules prevent momentum from carrying a weak or harmful system into full deployment.
🏋 Try: Stop if error severity exceeds the agreed threshold.Pause if users cannot verify outputs within the available time.
👩🏫 Ask learners to give one example from their own context and explain why the concept matters for their artifact.
Before the session
- Review the matching learner-facing session before facilitating.
- Prepare a simple example of a completed Pilot Board that is safe to discuss.
- Remind learners not to paste confidential, personal, regulated, or sensitive information into public tools.
- Decide whether learners will work individually, in pairs, or in role-based groups.
- Prepare a visible timer so action time does not disappear into discussion.
Opening move
- Ask learners where this session topic already appears in their real work or life.
- Invite them to name one mistake that would be costly if they handled the topic casually.
- State that the goal is a concrete artifact, not agreement with the facilitator.
Guided action support
Use the learner actions from the improved guide. Your job is to keep each action concrete, safe, and evidenced.
Write one hypothesis: if we use this tool for this task, this measurable result should improve.
👉 Ask for a short written output, then have learners underline the parts that are specific, checkable, and owned.
🔎 Evidence: A usable written sentence, rule, script, prompt, or brief.
👉 Ask for a short written output, then have learners underline the parts that are specific, checkable, and owned.
🔎 Evidence: A usable written sentence, rule, script, prompt, or brief.
Define the pilot boundary: users, data, cases, duration, support, and excluded situations.
👉 Pause for data safety. Ask learners what information must not be shared and what can be safely fictionalized.
🔎 Evidence: A completed data note with allowed, forbidden, and unknown information clearly separated.
👉 Pause for data safety. Ask learners what information must not be shared and what can be safely fictionalized.
🔎 Evidence: A completed data note with allowed, forbidden, and unknown information clearly separated.
Choose balanced metrics: time, quality, rework, satisfaction, mental load, cost, incidents, and escalation quality.
👉 Insist on a real baseline. If learners cannot measure exactly, ask for a reasonable proxy and a date to improve it.
🔎 Evidence: A selected option with one sentence explaining why it is the best safe next step.
👉 Insist on a real baseline. If learners cannot measure exactly, ask for a reasonable proxy and a date to improve it.
🔎 Evidence: A selected option with one sentence explaining why it is the best safe next step.
Create support and reporting channels so users can raise problems quickly.
👉 Keep the learner working on a real case. Ask for a concrete sentence, example, or decision before moving on.
🔎 Evidence: A visible entry in the learner worksheet that another person can understand.
👉 Keep the learner working on a real case. Ask for a concrete sentence, example, or decision before moving on.
🔎 Evidence: A visible entry in the learner worksheet that another person can understand.
Write stop, adjust, and scale criteria before the pilot starts.
👉 Ask for a short written output, then have learners underline the parts that are specific, checkable, and owned.
🔎 Evidence: A usable written sentence, rule, script, prompt, or brief.
👉 Ask for a short written output, then have learners underline the parts that are specific, checkable, and owned.
🔎 Evidence: A usable written sentence, rule, script, prompt, or brief.
Learner worksheet guidance
Tell learners to fill these fields during the session. Do not let the worksheet become decoration; pause and inspect it.
- Hypothesis
- Pilot users
- Included cases
- Excluded cases
- Baseline
- Metrics
- Support path
- Stop criteria
- Scale criteria
Choice path facilitation
Ask learners which option they would naturally choose before revealing the consequence. This surfaces habits and risk tolerance.
⚠️ Call it a pilot but deploy broadly
That is a rollout without the discipline of learning.
That is a rollout without the discipline of learning.
✅ Run a narrow pilot with balanced measures and stop rules
Best choice. You can learn without locking in a bad system.
Best choice. You can learn without locking in a bad system.
⚠️ Pilot only with enthusiasts
Risky. Enthusiasts may hide usability, trust, or workload problems that others will face.
Risky. Enthusiasts may hide usability, trust, or workload problems that others will face.
Prompt safety and use
These learner prompts can be useful, but remind learners to use only information they are allowed to share.
Design a pilot board for this AI use: [use case]. Include hypothesis, scope, data, users, duration, metrics, guardrails, support, stop criteria, and scale criteria.
Review this pilot plan and identify where it could accidentally become an uncontrolled rollout: [paste].
Create a balanced metric set for this pilot. Include at least one measure for speed, quality, human experience, risk, and customer or stakeholder outcome.
Mini-case bridge
A contact center tests an AI response assistant on one low-risk request type. It measures net time, error rate, rework, satisfaction, mental load, and escalation quality before widening the scope.
👩🏫 Ask learners what the person or team in the mini-case did well, what risk remained, and what they would copy or change in their own context.
👩🏫 Ask learners what the person or team in the mini-case did well, what risk remained, and what they would copy or change in their own context.
Debrief questions
- What changed in your understanding of run a limited pilot with balanced metrics after building the Pilot Board?
- Where did you notice a temptation to skip a check, avoid a hard choice, or stay vague?
- What part of your work can you apply this to within the next seven days?
- What evidence would convince you that this session changed behavior, not only awareness?
Artifact review criteria
| Criterion | What good looks like | Red flag |
|---|---|---|
| Specificity | The Pilot Board names a real context, user, task, decision, or situation. | The artifact uses vague language such as 'improve work' or 'use AI better.' |
| Actionability | The next step is small, dated, and possible within seven days. | The learner ends with an aspiration but no action. |
| Human responsibility | The learner names who decides, reviews, verifies, or carries responsibility. | The tool, policy, or system appears to be responsible by itself. |
| Evidence | The learner saves proof: a baseline, example, draft, rule, message, map, or review note. | The learner leaves with only an opinion or intention. |
| Safety | Sensitive information is removed, fictionalized, or kept inside approved systems. | The learner exposes real data unnecessarily or cannot name the data boundary. |
Common mistakes to watch for
- Measuring speed but not quality.
- Ignoring the workload of review and correction.
- Not giving users a safe way to report problems.
- Scaling because the demo impressed people, not because the pilot proved value.
Close the session
- Ask each learner to state the artifact they created and the next action they will take.
- Collect one unresolved question or risk from each learner or group.
- End by connecting the session back to Lojik360's three moves: delegate carefully, supervise rigorously, and strengthen what remains human.
Session 13 — Redesign Roles After Automation
Management · ⏱ 65 minutes · 🎯 Artifact: Role Redesign Map
Learner outcome. Managers can redesign a role so automation improves the job instead of leaving people only with stressful exceptions.
Core idea. Removing tasks is not the same as redesigning work. A good redesign preserves learning, ownership, relationship, and meaningful responsibility.
Facilitator intent. Guide learners to produce a usable Role Redesign Map while applying the title concepts from the improved learner guide. The session should feel like coached practice, not a lecture about redesign roles after automation.
🧭 Domain note. Help leaders move from slogans to operating rules: owners, metrics, pilots, controls, and honest change conversations.
Watch for: Managers may speak in policy language. Push for examples, decision rights, stop rules, and visible feedback loops.
Watch for: Managers may speak in policy language. Push for examples, decision rights, stop rules, and visible feedback loops.
Title concepts to teach
Use this section to make the improved learner-guide title concepts practical before learners begin the worksheet. Keep this short and example-driven.
Redesign — To redesign is to intentionally reshape a role, process, or system so it works better under new conditions.
Redesign is not simply removing tasks. It creates a healthier, more complete role around outcomes, learning, and decision rights.
🏋 Try: Replace repetitive data entry with quality review and exception analysis.Add coaching duties when routine beginner tasks are automated.
👩🏫 Ask learners to give one example from their own context and explain why the concept matters for their artifact.
Redesign is not simply removing tasks. It creates a healthier, more complete role around outcomes, learning, and decision rights.
🏋 Try: Replace repetitive data entry with quality review and exception analysis.Add coaching duties when routine beginner tasks are automated.
👩🏫 Ask learners to give one example from their own context and explain why the concept matters for their artifact.
Roles — Roles are bundles of responsibilities, relationships, decisions, skills, and expected outcomes.
A role is more than a task list. It includes identity, learning, trust, workload, and contribution.
🏋 Try: Map a role by outcomes, not just tasks.Name which decision rights must change if responsibility changes.
👩🏫 Ask learners to give one example from their own context and explain why the concept matters for their artifact.
A role is more than a task list. It includes identity, learning, trust, workload, and contribution.
🏋 Try: Map a role by outcomes, not just tasks.Name which decision rights must change if responsibility changes.
👩🏫 Ask learners to give one example from their own context and explain why the concept matters for their artifact.
Automation — Automation is the use of systems to perform work with less direct human effort.
Automation changes what humans do next. If the role is not redesigned, people may inherit only difficult exceptions.
🏋 Try: After automation, add improvement work instead of only monitoring.Check whether junior staff still have a path to learn the basics.
👩🏫 Ask learners to give one example from their own context and explain why the concept matters for their artifact.
Automation changes what humans do next. If the role is not redesigned, people may inherit only difficult exceptions.
🏋 Try: After automation, add improvement work instead of only monitoring.Check whether junior staff still have a path to learn the basics.
👩🏫 Ask learners to give one example from their own context and explain why the concept matters for their artifact.
Before the session
- Review the matching learner-facing session before facilitating.
- Prepare a simple example of a completed Role Redesign Map that is safe to discuss.
- Remind learners not to paste confidential, personal, regulated, or sensitive information into public tools.
- Decide whether learners will work individually, in pairs, or in role-based groups.
- Prepare a visible timer so action time does not disappear into discussion.
Opening move
- Ask learners where this session topic already appears in their real work or life.
- Invite them to name one mistake that would be costly if they handled the topic casually.
- State that the goal is a concrete artifact, not agreement with the facilitator.
Guided action support
Use the learner actions from the improved guide. Your job is to keep each action concrete, safe, and evidenced.
Map the current role by outcomes, tasks, relationships, decisions, and learning moments.
👉 Turn this into a real conversation. Ask learners to prepare the exact question or message they will use.
🔎 Evidence: A prepared question, message, interview note, or feedback pattern.
👉 Turn this into a real conversation. Ask learners to prepare the exact question or message they will use.
🔎 Evidence: A prepared question, message, interview note, or feedback pattern.
Mark which tasks may be automated, augmented, preserved, or expanded.
👉 Turn this into a real conversation. Ask learners to prepare the exact question or message they will use.
🔎 Evidence: A prepared question, message, interview note, or feedback pattern.
👉 Turn this into a real conversation. Ask learners to prepare the exact question or message they will use.
🔎 Evidence: A prepared question, message, interview note, or feedback pattern.
Identify what learning would disappear if all routine tasks vanished.
👉 Turn this into a real conversation. Ask learners to prepare the exact question or message they will use.
🔎 Evidence: A prepared question, message, interview note, or feedback pattern.
👉 Turn this into a real conversation. Ask learners to prepare the exact question or message they will use.
🔎 Evidence: A prepared question, message, interview note, or feedback pattern.
Design new responsibilities that create full contribution: quality review, improvement, client insight, exception analysis, training, or coordination.
👉 Treat review as action. Ask who checks, what evidence they use, and what power they have to pause or change the result.
🔎 Evidence: A verification note showing source, reviewer, criteria, or correction.
👉 Treat review as action. Ask who checks, what evidence they use, and what power they have to pause or change the result.
🔎 Evidence: A verification note showing source, reviewer, criteria, or correction.
Check workload fairness so the person is not left only with high-pressure edge cases.
👉 Treat review as action. Ask who checks, what evidence they use, and what power they have to pause or change the result.
🔎 Evidence: A verification note showing source, reviewer, criteria, or correction.
👉 Treat review as action. Ask who checks, what evidence they use, and what power they have to pause or change the result.
🔎 Evidence: A verification note showing source, reviewer, criteria, or correction.
Learner worksheet guidance
Tell learners to fill these fields during the session. Do not let the worksheet become decoration; pause and inspect it.
- Role
- Current outcomes
- Tasks changing
- Learning moments at risk
- New responsibilities
- Decision rights
- Support needed
- Workload risk
Choice path facilitation
Ask learners which option they would naturally choose before revealing the consequence. This surfaces habits and risk tolerance.
⚠️ Remove automated tasks and leave the rest unchanged
Incomplete. The role may become narrower, more stressful, and less developmental.
Incomplete. The role may become narrower, more stressful, and less developmental.
✅ Redesign the role around outcomes, learning, and decision rights
Best choice. Technology improves the work rather than hollowing it out.
Best choice. Technology improves the work rather than hollowing it out.
⚠️ Keep old tasks for everyone even if tools help
May protect learning briefly but can waste capacity if not redesigned intentionally.
May protect learning briefly but can waste capacity if not redesigned intentionally.
Prompt safety and use
These learner prompts can be useful, but remind learners to use only information they are allowed to share.
Help me redesign this role after automation: [describe role]. Map outcomes, tasks, relationships, decision rights, learning moments, and risks if routine tasks disappear.
What new responsibilities could make this role more valuable and humane after these tasks are automated: [tasks]?
Act as an employee advocate. Review this role redesign for stress, fairness, learning, autonomy, and recognition.
Mini-case bridge
An automated quality system reduces repetitive visual inspection. The plant manager adds root-cause analysis, improvement suggestions, and rotating supervision duties so operators gain capability instead of inheriting only difficult anomalies.
👩🏫 Ask learners what the person or team in the mini-case did well, what risk remained, and what they would copy or change in their own context.
👩🏫 Ask learners what the person or team in the mini-case did well, what risk remained, and what they would copy or change in their own context.
Debrief questions
- What changed in your understanding of redesign roles after automation after building the Role Redesign Map?
- Where did you notice a temptation to skip a check, avoid a hard choice, or stay vague?
- What part of your work can you apply this to within the next seven days?
- What evidence would convince you that this session changed behavior, not only awareness?
Artifact review criteria
| Criterion | What good looks like | Red flag |
|---|---|---|
| Specificity | The Role Redesign Map names a real context, user, task, decision, or situation. | The artifact uses vague language such as 'improve work' or 'use AI better.' |
| Actionability | The next step is small, dated, and possible within seven days. | The learner ends with an aspiration but no action. |
| Human responsibility | The learner names who decides, reviews, verifies, or carries responsibility. | The tool, policy, or system appears to be responsible by itself. |
| Evidence | The learner saves proof: a baseline, example, draft, rule, message, map, or review note. | The learner leaves with only an opinion or intention. |
| Safety | Sensitive information is removed, fictionalized, or kept inside approved systems. | The learner exposes real data unnecessarily or cannot name the data boundary. |
Common mistakes to watch for
- Treating people as task leftovers.
- Forgetting junior learning pathways.
- Giving responsibility without decision rights.
- Measuring only output while ignoring stress and development.
Close the session
- Ask each learner to state the artifact they created and the next action they will take.
- Collect one unresolved question or risk from each learner or group.
- End by connecting the session back to Lojik360's three moves: delegate carefully, supervise rigorously, and strengthen what remains human.
Session 14 — Build the Human-in-the-Loop Control System
Management · ⏱ 75 minutes · 🎯 Artifact: Control Rule
Learner outcome. Managers can place human review where it actually detects errors, rather than using review as a symbolic final approval.
Core idea. Human control works only when the reviewer has criteria, time, evidence, authority, and a clear place in the workflow.
Facilitator intent. Guide learners to produce a usable Control Rule while applying the title concepts from the improved learner guide. The session should feel like coached practice, not a lecture about build the human-in-the-loop control system.
🧭 Domain note. Help leaders move from slogans to operating rules: owners, metrics, pilots, controls, and honest change conversations.
Watch for: Managers may speak in policy language. Push for examples, decision rights, stop rules, and visible feedback loops.
Watch for: Managers may speak in policy language. Push for examples, decision rights, stop rules, and visible feedback loops.
Title concepts to teach
Use this section to make the improved learner-guide title concepts practical before learners begin the worksheet. Keep this short and example-driven.
Human-in-the-Loop — Human-in-the-loop means a person is intentionally placed in a workflow to review, decide, correct, or stop an AI-supported action.
The human must have evidence, time, criteria, authority, and accountability. A symbolic final approval is not enough.
🏋 Try: Require a specialist to review sensitive cases before response is sent.Let the reviewer see the source document, not only the AI summary.
👩🏫 Ask learners to give one example from their own context and explain why the concept matters for their artifact.
The human must have evidence, time, criteria, authority, and accountability. A symbolic final approval is not enough.
🏋 Try: Require a specialist to review sensitive cases before response is sent.Let the reviewer see the source document, not only the AI summary.
👩🏫 Ask learners to give one example from their own context and explain why the concept matters for their artifact.
Control System — A control system is the set of review points, criteria, roles, records, and escalation paths that keeps work within acceptable limits.
Controls should catch errors while they are still reversible. They make responsibility operational.
🏋 Try: Write a rule: if confidence is low, route to a human before action.Document every override and why it happened.
👩🏫 Ask learners to give one example from their own context and explain why the concept matters for their artifact.
Controls should catch errors while they are still reversible. They make responsibility operational.
🏋 Try: Write a rule: if confidence is low, route to a human before action.Document every override and why it happened.
👩🏫 Ask learners to give one example from their own context and explain why the concept matters for their artifact.
Escalation — Escalation is the process of moving a case to a higher level of expertise, authority, or care.
Escalation protects people when the case is sensitive, uncertain, high impact, or outside the tool's safe scope.
🏋 Try: Escalate employee health, conflict, or legal questions to a trained person.Escalate customer complaints involving loss, harm, or distress.
👩🏫 Ask learners to give one example from their own context and explain why the concept matters for their artifact.
Escalation protects people when the case is sensitive, uncertain, high impact, or outside the tool's safe scope.
🏋 Try: Escalate employee health, conflict, or legal questions to a trained person.Escalate customer complaints involving loss, harm, or distress.
👩🏫 Ask learners to give one example from their own context and explain why the concept matters for their artifact.
Before the session
- Review the matching learner-facing session before facilitating.
- Prepare a simple example of a completed Control Rule that is safe to discuss.
- Remind learners not to paste confidential, personal, regulated, or sensitive information into public tools.
- Decide whether learners will work individually, in pairs, or in role-based groups.
- Prepare a visible timer so action time does not disappear into discussion.
Opening move
- Ask learners where this session topic already appears in their real work or life.
- Invite them to name one mistake that would be costly if they handled the topic casually.
- State that the goal is a concrete artifact, not agreement with the facilitator.
Guided action support
Use the learner actions from the improved guide. Your job is to keep each action concrete, safe, and evidenced.
Choose one workflow where AI contributes to output, recommendation, triage, or decision support.
👉 Make the choice visible. Ask learners what they rejected and why, not only what they selected.
🔎 Evidence: A selected option with one sentence explaining why it is the best safe next step.
👉 Make the choice visible. Ask learners what they rejected and why, not only what they selected.
🔎 Evidence: A selected option with one sentence explaining why it is the best safe next step.
Identify the earliest point where a harmful error could appear.
👉 Keep the learner working on a real case. Ask for a concrete sentence, example, or decision before moving on.
🔎 Evidence: A visible entry in the learner worksheet that another person can understand.
👉 Keep the learner working on a real case. Ask for a concrete sentence, example, or decision before moving on.
🔎 Evidence: A visible entry in the learner worksheet that another person can understand.
Place review where the error can still be detected and corrected.
👉 Treat review as action. Ask who checks, what evidence they use, and what power they have to pause or change the result.
🔎 Evidence: A verification note showing source, reviewer, criteria, or correction.
👉 Treat review as action. Ask who checks, what evidence they use, and what power they have to pause or change the result.
🔎 Evidence: A verification note showing source, reviewer, criteria, or correction.
Define the reviewer, evidence, criteria, time allowed, and authority to pause or override.
👉 Treat review as action. Ask who checks, what evidence they use, and what power they have to pause or change the result.
🔎 Evidence: A verification note showing source, reviewer, criteria, or correction.
👉 Treat review as action. Ask who checks, what evidence they use, and what power they have to pause or change the result.
🔎 Evidence: A verification note showing source, reviewer, criteria, or correction.
Write escalation rules for uncertainty, sensitive topics, complaints, safety issues, or rights-impacting decisions.
👉 Ask for a short written output, then have learners underline the parts that are specific, checkable, and owned.
🔎 Evidence: A usable written sentence, rule, script, prompt, or brief.
👉 Ask for a short written output, then have learners underline the parts that are specific, checkable, and owned.
🔎 Evidence: A usable written sentence, rule, script, prompt, or brief.
Learner worksheet guidance
Tell learners to fill these fields during the session. Do not let the worksheet become decoration; pause and inspect it.
- Workflow
- AI role
- Possible error
- Review point
- Reviewer
- Evidence available
- Review criteria
- Authority
- Escalation trigger
Choice path facilitation
Ask learners which option they would naturally choose before revealing the consequence. This surfaces habits and risk tolerance.
⚠️ Add final human approval after the tool completes everything
Often symbolic. Late review may not catch hidden errors or may be too rushed.
Often symbolic. Late review may not catch hidden errors or may be too rushed.
✅ Place human control at the meaningful risk point
Best choice. Review becomes real protection, not ceremony.
Best choice. Review becomes real protection, not ceremony.
⚠️ Let humans review only complaints after the fact
Too late for many high-impact uses.
Too late for many high-impact uses.
Prompt safety and use
These learner prompts can be useful, but remind learners to use only information they are allowed to share.
Design human-in-the-loop control for this workflow: [workflow]. Identify error points, review points, reviewer criteria, evidence needed, authority, and escalation triggers.
Rewrite this vague control rule into an operational one: 'A human reviews AI outputs before use.'
Create five escalation triggers for this AI-supported workflow, including sensitive data, uncertainty, complaints, safety, and rights-impacting outcomes.
Mini-case bridge
A HR assistant drafts answers to employee questions. Sensitive topics such as health, conflict, rights, or discipline automatically route to a trained human with context, criteria, and authority to override the draft.
👩🏫 Ask learners what the person or team in the mini-case did well, what risk remained, and what they would copy or change in their own context.
👩🏫 Ask learners what the person or team in the mini-case did well, what risk remained, and what they would copy or change in their own context.
Debrief questions
- What changed in your understanding of build the human-in-the-loop control system after building the Control Rule?
- Where did you notice a temptation to skip a check, avoid a hard choice, or stay vague?
- What part of your work can you apply this to within the next seven days?
- What evidence would convince you that this session changed behavior, not only awareness?
Artifact review criteria
| Criterion | What good looks like | Red flag |
|---|---|---|
| Specificity | The Control Rule names a real context, user, task, decision, or situation. | The artifact uses vague language such as 'improve work' or 'use AI better.' |
| Actionability | The next step is small, dated, and possible within seven days. | The learner ends with an aspiration but no action. |
| Human responsibility | The learner names who decides, reviews, verifies, or carries responsibility. | The tool, policy, or system appears to be responsible by itself. |
| Evidence | The learner saves proof: a baseline, example, draft, rule, message, map, or review note. | The learner leaves with only an opinion or intention. |
| Safety | Sensitive information is removed, fictionalized, or kept inside approved systems. | The learner exposes real data unnecessarily or cannot name the data boundary. |
Common mistakes to watch for
- Assuming review equals responsibility.
- Reviewing only the AI answer without source material.
- Giving reviewers no time or power to stop the process.
- Failing to document why overrides happen.
Close the session
- Ask each learner to state the artifact they created and the next action they will take.
- Collect one unresolved question or risk from each learner or group.
- End by connecting the session back to Lojik360's three moves: delegate carefully, supervise rigorously, and strengthen what remains human.
Session 15 — Govern Risk, Ethics, and Compliance
Management · ⏱ 80 minutes · 🎯 Artifact: AI Risk Register Row
Learner outcome. Managers can create a practical AI risk register and connect it to data classification, vendor review, bias testing, incident response, and legal review.
Core idea. AI is a sociotechnical system. Risk lives in the data, people, supplier, process, interface, incentives, and decision rights.
Facilitator intent. Guide learners to produce a usable AI Risk Register Row while applying the title concepts from the improved learner guide. The session should feel like coached practice, not a lecture about govern risk, ethics, and compliance.
🧭 Domain note. Help leaders move from slogans to operating rules: owners, metrics, pilots, controls, and honest change conversations.
Watch for: Managers may speak in policy language. Push for examples, decision rights, stop rules, and visible feedback loops.
Watch for: Managers may speak in policy language. Push for examples, decision rights, stop rules, and visible feedback loops.
Title concepts to teach
Use this section to make the improved learner-guide title concepts practical before learners begin the worksheet. Keep this short and example-driven.
Govern — To govern is to set responsibilities, rules, oversight, controls, and review processes for how a system is used.
Governance makes AI visible and accountable. It connects daily use to risk, ethics, compliance, and leadership decisions.
🏋 Try: Assign an owner for each AI system.Review the AI register every quarter.
👩🏫 Ask learners to give one example from their own context and explain why the concept matters for their artifact.
Governance makes AI visible and accountable. It connects daily use to risk, ethics, compliance, and leadership decisions.
🏋 Try: Assign an owner for each AI system.Review the AI register every quarter.
👩🏫 Ask learners to give one example from their own context and explain why the concept matters for their artifact.
Risk — Risk is the possibility that an action or system creates harm, loss, error, unfairness, exposure, or missed responsibility.
Risk has probability, severity, detectability, and reversibility. Not all risks are equal.
🏋 Try: Rate one AI use by likelihood and severity of error.Write what would make a risk detectable early.
👩🏫 Ask learners to give one example from their own context and explain why the concept matters for their artifact.
Risk has probability, severity, detectability, and reversibility. Not all risks are equal.
🏋 Try: Rate one AI use by likelihood and severity of error.Write what would make a risk detectable early.
👩🏫 Ask learners to give one example from their own context and explain why the concept matters for their artifact.
Ethics — Ethics is the practice of asking what is fair, responsible, explainable, humane, and worthy of trust.
Ethics goes beyond legality. A use can be possible and still be unfair, opaque, or damaging.
🏋 Try: Ask who benefits and who carries the risk.Ask whether you could explain the decision publicly.
👩🏫 Ask learners to give one example from their own context and explain why the concept matters for their artifact.
Ethics goes beyond legality. A use can be possible and still be unfair, opaque, or damaging.
🏋 Try: Ask who benefits and who carries the risk.Ask whether you could explain the decision publicly.
👩🏫 Ask learners to give one example from their own context and explain why the concept matters for their artifact.
Compliance — Compliance means meeting applicable laws, policies, standards, contracts, and sector rules.
Compliance depends on country, sector, data type, purpose, and level of impact. AI should not be used to bypass qualified review.
🏋 Try: Route high-impact uses to legal, privacy, security, or compliance teams.Link each AI use in the register to the rule or policy it must follow.
👩🏫 Ask learners to give one example from their own context and explain why the concept matters for their artifact.
Compliance depends on country, sector, data type, purpose, and level of impact. AI should not be used to bypass qualified review.
🏋 Try: Route high-impact uses to legal, privacy, security, or compliance teams.Link each AI use in the register to the rule or policy it must follow.
👩🏫 Ask learners to give one example from their own context and explain why the concept matters for their artifact.
Before the session
- Review the matching learner-facing session before facilitating.
- Prepare a simple example of a completed AI Risk Register Row that is safe to discuss.
- Remind learners not to paste confidential, personal, regulated, or sensitive information into public tools.
- Decide whether learners will work individually, in pairs, or in role-based groups.
- Prepare a visible timer so action time does not disappear into discussion.
Opening move
- Ask learners where this session topic already appears in their real work or life.
- Invite them to name one mistake that would be costly if they handled the topic casually.
- State that the goal is a concrete artifact, not agreement with the facilitator.
Guided action support
Use the learner actions from the improved guide. Your job is to keep each action concrete, safe, and evidenced.
Choose one AI use, official or informal.
👉 Make the choice visible. Ask learners what they rejected and why, not only what they selected.
🔎 Evidence: A selected option with one sentence explaining why it is the best safe next step.
👉 Make the choice visible. Ask learners what they rejected and why, not only what they selected.
🔎 Evidence: A selected option with one sentence explaining why it is the best safe next step.
Record purpose, owner, users, data, supplier, autonomy level, impact, and review date.
👉 Pause for data safety. Ask learners what information must not be shared and what can be safely fictionalized.
🔎 Evidence: A completed data note with allowed, forbidden, and unknown information clearly separated.
👉 Pause for data safety. Ask learners what information must not be shared and what can be safely fictionalized.
🔎 Evidence: A completed data note with allowed, forbidden, and unknown information clearly separated.
Name the main risks: privacy, security, bias, explainability, error, dependence, cost, compliance, or reputational harm.
👉 Keep the learner working on a real case. Ask for a concrete sentence, example, or decision before moving on.
🔎 Evidence: A visible entry in the learner worksheet that another person can understand.
👉 Keep the learner working on a real case. Ask for a concrete sentence, example, or decision before moving on.
🔎 Evidence: A visible entry in the learner worksheet that another person can understand.
Attach at least one control and one incident signal to each serious risk.
👉 Keep the learner working on a real case. Ask for a concrete sentence, example, or decision before moving on.
🔎 Evidence: A visible entry in the learner worksheet that another person can understand.
👉 Keep the learner working on a real case. Ask for a concrete sentence, example, or decision before moving on.
🔎 Evidence: A visible entry in the learner worksheet that another person can understand.
Write a stop rule for critical error, bias, cost drift, vendor change, inability to verify, or complaint threshold.
👉 Ask for a short written output, then have learners underline the parts that are specific, checkable, and owned.
🔎 Evidence: A usable written sentence, rule, script, prompt, or brief.
👉 Ask for a short written output, then have learners underline the parts that are specific, checkable, and owned.
🔎 Evidence: A usable written sentence, rule, script, prompt, or brief.
Learner worksheet guidance
Tell learners to fill these fields during the session. Do not let the worksheet become decoration; pause and inspect it.
- Use case
- Owner
- Users
- Data
- Supplier
- Autonomy level
- Impact
- Controls
- Incident signal
- Stop rule
Choice path facilitation
Ask learners which option they would naturally choose before revealing the consequence. This surfaces habits and risk tolerance.
⚠️ Track only official systems
Incomplete. Informal tools can create real risk.
Incomplete. Informal tools can create real risk.
✅ Register all meaningful AI uses, including pilots and informal workflows
Best choice. You cannot govern what you cannot see.
Best choice. You cannot govern what you cannot see.
⚠️ Wait for legal to create the perfect register
Too passive. Start lightweight and improve it with risk, legal, security, and users.
Too passive. Start lightweight and improve it with risk, legal, security, and users.
Prompt safety and use
These learner prompts can be useful, but remind learners to use only information they are allowed to share.
Create an AI risk register row for this use case: [describe]. Include owner, purpose, users, data, supplier, autonomy, impact, controls, incidents, review date, and stop rule.
Review this AI use for privacy, security, bias, explainability, error, vendor, cost, compliance, and reputation risks: [describe].
Generate stop rules for this AI system. Include thresholds for error, bias, complaints, vendor changes, inability to verify, and unexpected cost.
Mini-case bridge
A recruitment tool ranks applicants but seems to miss nontraditional profiles. HR records the use, tests outcomes by relevant groups, limits the tool to organizing files, and restores independent human review until controls are validated.
👩🏫 Ask learners what the person or team in the mini-case did well, what risk remained, and what they would copy or change in their own context.
👩🏫 Ask learners what the person or team in the mini-case did well, what risk remained, and what they would copy or change in their own context.
Debrief questions
- What changed in your understanding of govern risk, ethics, and compliance after building the AI Risk Register Row?
- Where did you notice a temptation to skip a check, avoid a hard choice, or stay vague?
- What part of your work can you apply this to within the next seven days?
- What evidence would convince you that this session changed behavior, not only awareness?
Artifact review criteria
| Criterion | What good looks like | Red flag |
|---|---|---|
| Specificity | The AI Risk Register Row names a real context, user, task, decision, or situation. | The artifact uses vague language such as 'improve work' or 'use AI better.' |
| Actionability | The next step is small, dated, and possible within seven days. | The learner ends with an aspiration but no action. |
| Human responsibility | The learner names who decides, reviews, verifies, or carries responsibility. | The tool, policy, or system appears to be responsible by itself. |
| Evidence | The learner saves proof: a baseline, example, draft, rule, message, map, or review note. | The learner leaves with only an opinion or intention. |
| Safety | Sensitive information is removed, fictionalized, or kept inside approved systems. | The learner exposes real data unnecessarily or cannot name the data boundary. |
Common mistakes to watch for
- Treating pilots as outside governance.
- Listing a risk without a control.
- Forgetting incident response.
- Keeping a register that nobody reviews.
Close the session
- Ask each learner to state the artifact they created and the next action they will take.
- Collect one unresolved question or risk from each learner or group.
- End by connecting the session back to Lojik360's three moves: delegate carefully, supervise rigorously, and strengthen what remains human.
Session 16 — Lead Change Without Disengaging the Team
Management · ⏱ 70 minutes · 🎯 Artifact: Change Conversation Script
Learner outcome. Managers can communicate AI-era change honestly while creating participation, safety, and visible learning loops.
Core idea. People disengage when change feels done to them. They engage more when leaders tell the truth, invite local knowledge, and act on what they hear.
Facilitator intent. Guide learners to produce a usable Change Conversation Script while applying the title concepts from the improved learner guide. The session should feel like coached practice, not a lecture about lead change without disengaging the team.
🧭 Domain note. Help leaders move from slogans to operating rules: owners, metrics, pilots, controls, and honest change conversations.
Watch for: Managers may speak in policy language. Push for examples, decision rights, stop rules, and visible feedback loops.
Watch for: Managers may speak in policy language. Push for examples, decision rights, stop rules, and visible feedback loops.
Title concepts to teach
Use this section to make the improved learner-guide title concepts practical before learners begin the worksheet. Keep this short and example-driven.
Lead Change — To lead change is to help people move from current practice to new practice with direction, participation, learning, and trust.
Change leadership is not announcing decisions. It includes listening, explaining uncertainty, adjusting plans, and protecting people through transition.
🏋 Try: State what is decided and what is still open.Hold a feedback review after a pilot and show what changed.
👩🏫 Ask learners to give one example from their own context and explain why the concept matters for their artifact.
Change leadership is not announcing decisions. It includes listening, explaining uncertainty, adjusting plans, and protecting people through transition.
🏋 Try: State what is decided and what is still open.Hold a feedback review after a pilot and show what changed.
👩🏫 Ask learners to give one example from their own context and explain why the concept matters for their artifact.
Disengaging — Disengaging means people withdraw energy, trust, creativity, honesty, or effort from the work.
Disengagement often appears when people feel change is done to them, when risks are hidden, or when learning is demanded without support.
🏋 Try: Ask what would make people hide AI errors.Watch for silence, resistance, cynicism, and reduced problem reporting.
👩🏫 Ask learners to give one example from their own context and explain why the concept matters for their artifact.
Disengagement often appears when people feel change is done to them, when risks are hidden, or when learning is demanded without support.
🏋 Try: Ask what would make people hide AI errors.Watch for silence, resistance, cynicism, and reduced problem reporting.
👩🏫 Ask learners to give one example from their own context and explain why the concept matters for their artifact.
Psychological Safety — Psychological safety is the shared belief that people can speak up, ask questions, admit errors, and challenge ideas without humiliation or punishment.
It is essential for AI adoption because hidden errors and silent fear make systems dangerous.
🏋 Try: Thank someone publicly for reporting a tool mistake.Separate incident learning from blame.
👩🏫 Ask learners to give one example from their own context and explain why the concept matters for their artifact.
It is essential for AI adoption because hidden errors and silent fear make systems dangerous.
🏋 Try: Thank someone publicly for reporting a tool mistake.Separate incident learning from blame.
👩🏫 Ask learners to give one example from their own context and explain why the concept matters for their artifact.
Before the session
- Review the matching learner-facing session before facilitating.
- Prepare a simple example of a completed Change Conversation Script that is safe to discuss.
- Remind learners not to paste confidential, personal, regulated, or sensitive information into public tools.
- Decide whether learners will work individually, in pairs, or in role-based groups.
- Prepare a visible timer so action time does not disappear into discussion.
Opening move
- Ask learners where this session topic already appears in their real work or life.
- Invite them to name one mistake that would be costly if they handled the topic casually.
- State that the goal is a concrete artifact, not agreement with the facilitator.
Guided action support
Use the learner actions from the improved guide. Your job is to keep each action concrete, safe, and evidenced.
Write why change is being considered now, using plain business or service reasons.
👉 Ask for a short written output, then have learners underline the parts that are specific, checkable, and owned.
🔎 Evidence: A usable written sentence, rule, script, prompt, or brief.
👉 Ask for a short written output, then have learners underline the parts that are specific, checkable, and owned.
🔎 Evidence: A usable written sentence, rule, script, prompt, or brief.
Separate what is decided from what is still open.
👉 Keep the learner working on a real case. Ask for a concrete sentence, example, or decision before moving on.
🔎 Evidence: A visible entry in the learner worksheet that another person can understand.
👉 Keep the learner working on a real case. Ask for a concrete sentence, example, or decision before moving on.
🔎 Evidence: A visible entry in the learner worksheet that another person can understand.
Name risks honestly: job changes, quality, data, workload, trust, customer impact, or learning demands.
👉 Pause for data safety. Ask learners what information must not be shared and what can be safely fictionalized.
🔎 Evidence: A completed data note with allowed, forbidden, and unknown information clearly separated.
👉 Pause for data safety. Ask learners what information must not be shared and what can be safely fictionalized.
🔎 Evidence: A completed data note with allowed, forbidden, and unknown information clearly separated.
Name protections and participation points: pilots, consultation, training, escalation, redeployment, or review dates.
👉 Treat review as action. Ask who checks, what evidence they use, and what power they have to pause or change the result.
🔎 Evidence: A verification note showing source, reviewer, criteria, or correction.
👉 Treat review as action. Ask who checks, what evidence they use, and what power they have to pause or change the result.
🔎 Evidence: A verification note showing source, reviewer, criteria, or correction.
Create a feedback loop with a date, channel, response owner, and visible action after feedback.
👉 Keep the learner working on a real case. Ask for a concrete sentence, example, or decision before moving on.
🔎 Evidence: A visible entry in the learner worksheet that another person can understand.
👉 Keep the learner working on a real case. Ask for a concrete sentence, example, or decision before moving on.
🔎 Evidence: A visible entry in the learner worksheet that another person can understand.
Learner worksheet guidance
Tell learners to fill these fields during the session. Do not let the worksheet become decoration; pause and inspect it.
- Why now
- What is decided
- What is open
- Risks
- Protections
- Participation points
- Feedback channel
- Next update date
Choice path facilitation
Ask learners which option they would naturally choose before revealing the consequence. This surfaces habits and risk tolerance.
⚠️ Tell people nothing until every decision is final
This creates fear and removes local knowledge from the design.
This creates fear and removes local knowledge from the design.
✅ Communicate honestly and invite participation before rollout
Best choice. Trust grows when people see both candor and action.
Best choice. Trust grows when people see both candor and action.
⚠️ Promise no roles will change
Unsafe promise. It may comfort briefly but damages credibility later.
Unsafe promise. It may comfort briefly but damages credibility later.
Prompt safety and use
These learner prompts can be useful, but remind learners to use only information they are allowed to share.
Draft an honest change message for this AI transition: [describe]. Include why now, what is decided, what is open, risks, protections, participation, and next update date.
Rewrite this change message so it is clear, human, and not defensive: [paste].
Act as a skeptical employee. What questions, fears, or objections would this message raise?
Mini-case bridge
A hospital department introduces an imaging support tool. Technicians, clinicians, and quality staff join the tests, review errors together, and shape usage rules. Adoption becomes gradual because the limits are visible.
👩🏫 Ask learners what the person or team in the mini-case did well, what risk remained, and what they would copy or change in their own context.
👩🏫 Ask learners what the person or team in the mini-case did well, what risk remained, and what they would copy or change in their own context.
Debrief questions
- What changed in your understanding of lead change without disengaging the team after building the Change Conversation Script?
- Where did you notice a temptation to skip a check, avoid a hard choice, or stay vague?
- What part of your work can you apply this to within the next seven days?
- What evidence would convince you that this session changed behavior, not only awareness?
Artifact review criteria
| Criterion | What good looks like | Red flag |
|---|---|---|
| Specificity | The Change Conversation Script names a real context, user, task, decision, or situation. | The artifact uses vague language such as 'improve work' or 'use AI better.' |
| Actionability | The next step is small, dated, and possible within seven days. | The learner ends with an aspiration but no action. |
| Human responsibility | The learner names who decides, reviews, verifies, or carries responsibility. | The tool, policy, or system appears to be responsible by itself. |
| Evidence | The learner saves proof: a baseline, example, draft, rule, message, map, or review note. | The learner leaves with only an opinion or intention. |
| Safety | Sensitive information is removed, fictionalized, or kept inside approved systems. | The learner exposes real data unnecessarily or cannot name the data boundary. |
Common mistakes to watch for
- Using hype instead of clarity.
- Pretending there is no risk.
- Asking for feedback without responding to it.
- Letting managers improvise different messages.
Close the session
- Ask each learner to state the artifact they created and the next action they will take.
- Collect one unresolved question or risk from each learner or group.
- End by connecting the session back to Lojik360's three moves: delegate carefully, supervise rigorously, and strengthen what remains human.
Session 17 — Turn Productivity Gains Into Learning Capacity
Management · ⏱ 60 minutes · 🎯 Artifact: Productivity Reinvestment Plan
Learner outcome. Managers can reinvest time saved by technology into training, quality, safety, documentation, and better work design.
Core idea. If every minute saved becomes more throughput, people hide learning needs and treat AI as a threat. Shared gains create trust and capability.
Facilitator intent. Guide learners to produce a usable Productivity Reinvestment Plan while applying the title concepts from the improved learner guide. The session should feel like coached practice, not a lecture about turn productivity gains into learning capacity.
🧭 Domain note. Help leaders move from slogans to operating rules: owners, metrics, pilots, controls, and honest change conversations.
Watch for: Managers may speak in policy language. Push for examples, decision rights, stop rules, and visible feedback loops.
Watch for: Managers may speak in policy language. Push for examples, decision rights, stop rules, and visible feedback loops.
Title concepts to teach
Use this section to make the improved learner-guide title concepts practical before learners begin the worksheet. Keep this short and example-driven.
Productivity Gains — Productivity gains are improvements in output, speed, quality, cost, or capacity produced by a better process or tool.
A gain is real only after setup, review, correction, coordination, and human impact are counted.
🏋 Try: Measure net time saved after checking outputs.Compare faster production with rework and customer satisfaction.
👩🏫 Ask learners to give one example from their own context and explain why the concept matters for their artifact.
A gain is real only after setup, review, correction, coordination, and human impact are counted.
🏋 Try: Measure net time saved after checking outputs.Compare faster production with rework and customer satisfaction.
👩🏫 Ask learners to give one example from their own context and explain why the concept matters for their artifact.
Learning Capacity — Learning capacity is the time, energy, support, and practice space people have to build new skills.
When productivity gains are reinvested into learning, the team becomes more capable instead of just more loaded.
🏋 Try: Use part of saved time for peer review or documentation.Reserve weekly practice time after introducing a new tool.
👩🏫 Ask learners to give one example from their own context and explain why the concept matters for their artifact.
When productivity gains are reinvested into learning, the team becomes more capable instead of just more loaded.
🏋 Try: Use part of saved time for peer review or documentation.Reserve weekly practice time after introducing a new tool.
👩🏫 Ask learners to give one example from their own context and explain why the concept matters for their artifact.
Reinvestment — Reinvestment means deliberately using some gains to improve future capability, quality, safety, or well-being.
Reinvestment prevents AI from becoming only a pressure multiplier.
🏋 Try: Allocate 25 percent of saved time to training.Reward people who document lessons from failed tests.
👩🏫 Ask learners to give one example from their own context and explain why the concept matters for their artifact.
Reinvestment prevents AI from becoming only a pressure multiplier.
🏋 Try: Allocate 25 percent of saved time to training.Reward people who document lessons from failed tests.
👩🏫 Ask learners to give one example from their own context and explain why the concept matters for their artifact.
Before the session
- Review the matching learner-facing session before facilitating.
- Prepare a simple example of a completed Productivity Reinvestment Plan that is safe to discuss.
- Remind learners not to paste confidential, personal, regulated, or sensitive information into public tools.
- Decide whether learners will work individually, in pairs, or in role-based groups.
- Prepare a visible timer so action time does not disappear into discussion.
Opening move
- Ask learners where this session topic already appears in their real work or life.
- Invite them to name one mistake that would be costly if they handled the topic casually.
- State that the goal is a concrete artifact, not agreement with the facilitator.
Guided action support
Use the learner actions from the improved guide. Your job is to keep each action concrete, safe, and evidenced.
Measure net productivity gain after setup, review, correction, and coordination.
👉 Insist on a real baseline. If learners cannot measure exactly, ask for a reasonable proxy and a date to improve it.
🔎 Evidence: A number, proxy, or observation that can be compared after the test.
👉 Insist on a real baseline. If learners cannot measure exactly, ask for a reasonable proxy and a date to improve it.
🔎 Evidence: A number, proxy, or observation that can be compared after the test.
Decide what portion of gains goes to output, learning, quality, documentation, recovery, or customer improvement.
👉 Keep the learner working on a real case. Ask for a concrete sentence, example, or decision before moving on.
🔎 Evidence: A visible entry in the learner worksheet that another person can understand.
👉 Keep the learner working on a real case. Ask for a concrete sentence, example, or decision before moving on.
🔎 Evidence: A visible entry in the learner worksheet that another person can understand.
Make the reinvestment visible so people know adaptation is not just extra unpaid work.
👉 Keep the learner working on a real case. Ask for a concrete sentence, example, or decision before moving on.
🔎 Evidence: A visible entry in the learner worksheet that another person can understand.
👉 Keep the learner working on a real case. Ask for a concrete sentence, example, or decision before moving on.
🔎 Evidence: A visible entry in the learner worksheet that another person can understand.
Reward behaviors that protect the system: documenting, teaching, reporting risks, and stopping bad pilots.
👉 Keep the learner working on a real case. Ask for a concrete sentence, example, or decision before moving on.
🔎 Evidence: A visible entry in the learner worksheet that another person can understand.
👉 Keep the learner working on a real case. Ask for a concrete sentence, example, or decision before moving on.
🔎 Evidence: A visible entry in the learner worksheet that another person can understand.
Review whether workload silently expanded after the tool was introduced.
👉 Treat review as action. Ask who checks, what evidence they use, and what power they have to pause or change the result.
🔎 Evidence: A verification note showing source, reviewer, criteria, or correction.
👉 Treat review as action. Ask who checks, what evidence they use, and what power they have to pause or change the result.
🔎 Evidence: A verification note showing source, reviewer, criteria, or correction.
Learner worksheet guidance
Tell learners to fill these fields during the session. Do not let the worksheet become decoration; pause and inspect it.
- Tool or process
- Net gain measured
- Output reinvestment
- Learning reinvestment
- Quality reinvestment
- Recovery or focus time
- Recognition behavior
- Workload risk
Choice path facilitation
Ask learners which option they would naturally choose before revealing the consequence. This surfaces habits and risk tolerance.
⚠️ Use all saved time for more tasks
Short-term output may rise, but learning, quality, and trust can decline.
Short-term output may rise, but learning, quality, and trust can decline.
✅ Share gains between output, learning, quality, and recovery
Best choice. Productivity becomes capability, not just pressure.
Best choice. Productivity becomes capability, not just pressure.
⚠️ Hide productivity gains so workload does not increase
Understandable but unhealthy. Better to negotiate explicit reinvestment.
Understandable but unhealthy. Better to negotiate explicit reinvestment.
Prompt safety and use
These learner prompts can be useful, but remind learners to use only information they are allowed to share.
Help me create a productivity reinvestment plan for this tool: [tool/process]. Include net gain, output, learning, quality, documentation, recovery, and recognition.
What hidden costs should I subtract before claiming this tool saves time? Include setup, review, correction, approval, and user support.
Create a team agreement for how productivity gains from AI will be shared fairly and measured honestly.
Mini-case bridge
A finance team uses AI to speed monthly commentary. The manager keeps part of the time for data visualization practice and peer review. The team becomes faster and better, not just busier.
👩🏫 Ask learners what the person or team in the mini-case did well, what risk remained, and what they would copy or change in their own context.
👩🏫 Ask learners what the person or team in the mini-case did well, what risk remained, and what they would copy or change in their own context.
Debrief questions
- What changed in your understanding of turn productivity gains into learning capacity after building the Productivity Reinvestment Plan?
- Where did you notice a temptation to skip a check, avoid a hard choice, or stay vague?
- What part of your work can you apply this to within the next seven days?
- What evidence would convince you that this session changed behavior, not only awareness?
Artifact review criteria
| Criterion | What good looks like | Red flag |
|---|---|---|
| Specificity | The Productivity Reinvestment Plan names a real context, user, task, decision, or situation. | The artifact uses vague language such as 'improve work' or 'use AI better.' |
| Actionability | The next step is small, dated, and possible within seven days. | The learner ends with an aspiration but no action. |
| Human responsibility | The learner names who decides, reviews, verifies, or carries responsibility. | The tool, policy, or system appears to be responsible by itself. |
| Evidence | The learner saves proof: a baseline, example, draft, rule, message, map, or review note. | The learner leaves with only an opinion or intention. |
| Safety | Sensitive information is removed, fictionalized, or kept inside approved systems. | The learner exposes real data unnecessarily or cannot name the data boundary. |
Common mistakes to watch for
- Measuring only raw speed.
- Treating training as personal time.
- Rewarding enthusiasm but not careful risk reporting.
- Letting the workload expand invisibly.
Close the session
- Ask each learner to state the artifact they created and the next action they will take.
- Collect one unresolved question or risk from each learner or group.
- End by connecting the session back to Lojik360's three moves: delegate carefully, supervise rigorously, and strengthen what remains human.
Session 18 — Execute a 90-Day Resilience Plan
Management · ⏱ 90 minutes · 🎯 Artifact: 90-Day Action Plan
Learner outcome. Managers and professionals can convert analysis into a 90-day cycle of baseline, pilot, learning, evidence, decision, and updated SWOT.
Core idea. Resilience is built by repeated action. A 90-day plan keeps the scope small enough to execute and concrete enough to prove progress.
Facilitator intent. Guide learners to produce a usable 90-Day Action Plan while applying the title concepts from the improved learner guide. The session should feel like coached practice, not a lecture about execute a 90-day resilience plan.
🧭 Domain note. Help leaders move from slogans to operating rules: owners, metrics, pilots, controls, and honest change conversations.
Watch for: Managers may speak in policy language. Push for examples, decision rights, stop rules, and visible feedback loops.
Watch for: Managers may speak in policy language. Push for examples, decision rights, stop rules, and visible feedback loops.
Title concepts to teach
Use this section to make the improved learner-guide title concepts practical before learners begin the worksheet. Keep this short and example-driven.
Execute — To execute is to turn an intention into scheduled action, evidence, decisions, and follow-through.
Execution matters because AI-era anxiety often stays abstract. A 90-day cycle makes action small enough to complete.
🏋 Try: Put two learning blocks on your calendar today.Choose a day-60 decision date before starting a pilot.
👩🏫 Ask learners to give one example from their own context and explain why the concept matters for their artifact.
Execution matters because AI-era anxiety often stays abstract. A 90-day cycle makes action small enough to complete.
🏋 Try: Put two learning blocks on your calendar today.Choose a day-60 decision date before starting a pilot.
👩🏫 Ask learners to give one example from their own context and explain why the concept matters for their artifact.
90-Day — A 90-day period is a short planning cycle long enough to learn but short enough to stay concrete.
Ninety days gives time for baseline, practice, pilot, reflection, and a revised SWOT without pretending to predict the future.
🏋 Try: Run a two-week pilot inside an eight-week learning plan.Refresh your SWOT at the end of the cycle.
👩🏫 Ask learners to give one example from their own context and explain why the concept matters for their artifact.
Ninety days gives time for baseline, practice, pilot, reflection, and a revised SWOT without pretending to predict the future.
🏋 Try: Run a two-week pilot inside an eight-week learning plan.Refresh your SWOT at the end of the cycle.
👩🏫 Ask learners to give one example from their own context and explain why the concept matters for their artifact.
Resilience Plan — A resilience plan is a practical sequence of actions that increases options, reduces risk, and strengthens capacity under uncertainty.
Resilience is built through repeated evidence-based action, not motivation alone.
🏋 Try: Pair one threat with one opportunity and one measurable action.Add your pilot result to your portfolio or team documentation.
👩🏫 Ask learners to give one example from their own context and explain why the concept matters for their artifact.
Resilience is built through repeated evidence-based action, not motivation alone.
🏋 Try: Pair one threat with one opportunity and one measurable action.Add your pilot result to your portfolio or team documentation.
👩🏫 Ask learners to give one example from their own context and explain why the concept matters for their artifact.
Before the session
- Review the matching learner-facing session before facilitating.
- Prepare a simple example of a completed 90-Day Action Plan that is safe to discuss.
- Remind learners not to paste confidential, personal, regulated, or sensitive information into public tools.
- Decide whether learners will work individually, in pairs, or in role-based groups.
- Prepare a visible timer so action time does not disappear into discussion.
Opening move
- Ask learners where this session topic already appears in their real work or life.
- Invite them to name one mistake that would be costly if they handled the topic casually.
- State that the goal is a concrete artifact, not agreement with the facilitator.
Guided action support
Use the learner actions from the improved guide. Your job is to keep each action concrete, safe, and evidenced.
Choose one realistic threat and one reachable opportunity for the next 12 months.
👉 Make the choice visible. Ask learners what they rejected and why, not only what they selected.
🔎 Evidence: A selected option with one sentence explaining why it is the best safe next step.
👉 Make the choice visible. Ask learners what they rejected and why, not only what they selected.
🔎 Evidence: A selected option with one sentence explaining why it is the best safe next step.
Measure your starting point: skill, time, errors, revenue, energy, network, or portfolio evidence.
👉 Insist on a real baseline. If learners cannot measure exactly, ask for a reasonable proxy and a date to improve it.
🔎 Evidence: A number, proxy, or observation that can be compared after the test.
👉 Insist on a real baseline. If learners cannot measure exactly, ask for a reasonable proxy and a date to improve it.
🔎 Evidence: A number, proxy, or observation that can be compared after the test.
Select one representative task for a two-week pilot.
👉 Make the choice visible. Ask learners what they rejected and why, not only what they selected.
🔎 Evidence: A selected option with one sentence explaining why it is the best safe next step.
👉 Make the choice visible. Ask learners what they rejected and why, not only what they selected.
🔎 Evidence: A selected option with one sentence explaining why it is the best safe next step.
Block weekly learning time and name a responsibility partner.
👉 Keep the learner working on a real case. Ask for a concrete sentence, example, or decision before moving on.
🔎 Evidence: A visible entry in the learner worksheet that another person can understand.
👉 Keep the learner working on a real case. Ask for a concrete sentence, example, or decision before moving on.
🔎 Evidence: A visible entry in the learner worksheet that another person can understand.
Make a day-60 decision: deploy, modify, or stop. Refresh your SWOT on day 90.
👉 Keep the learner working on a real case. Ask for a concrete sentence, example, or decision before moving on.
🔎 Evidence: A visible entry in the learner worksheet that another person can understand.
👉 Keep the learner working on a real case. Ask for a concrete sentence, example, or decision before moving on.
🔎 Evidence: A visible entry in the learner worksheet that another person can understand.
Learner worksheet guidance
Tell learners to fill these fields during the session. Do not let the worksheet become decoration; pause and inspect it.
- Priority threat
- Priority opportunity
- Baseline
- Pilot task
- Two-week test
- Weekly learning block
- Responsibility partner
- Day-60 decision
- Day-90 SWOT update
Choice path facilitation
Ask learners which option they would naturally choose before revealing the consequence. This surfaces habits and risk tolerance.
⚠️ Study everything until you feel ready
Too broad. Learning without action may become avoidance.
Too broad. Learning without action may become avoidance.
✅ Run a focused 90-day cycle with evidence
Best choice. Small repeated action builds resilience.
Best choice. Small repeated action builds resilience.
⚠️ Wait until your organization tells you what to learn
Risky. Your options improve when you start before urgency forces action.
Risky. Your options improve when you start before urgency forces action.
Prompt safety and use
These learner prompts can be useful, but remind learners to use only information they are allowed to share.
Help me build a 90-day resilience plan. My threat is [threat], my opportunity is [opportunity], and my current role is [role]. Include baseline, pilot, learning blocks, evidence, day-60 decision, and day-90 SWOT.
Challenge my 90-day plan. Is the scope too large? Are the metrics measurable? What is missing?
Create a two-week pilot plan for this representative task: [task]. Include hypothesis, cases, metrics, guardrails, and decision criteria.
Mini-case bridge
An assistant sees document preparation becoming automated. Over 90 days she measures her current work, tests quality control tools, documents exceptions, and proposes a new coordination role based on evidence.
👩🏫 Ask learners what the person or team in the mini-case did well, what risk remained, and what they would copy or change in their own context.
👩🏫 Ask learners what the person or team in the mini-case did well, what risk remained, and what they would copy or change in their own context.
Debrief questions
- What changed in your understanding of execute a 90-day resilience plan after building the 90-Day Action Plan?
- Where did you notice a temptation to skip a check, avoid a hard choice, or stay vague?
- What part of your work can you apply this to within the next seven days?
- What evidence would convince you that this session changed behavior, not only awareness?
Artifact review criteria
| Criterion | What good looks like | Red flag |
|---|---|---|
| Specificity | The 90-Day Action Plan names a real context, user, task, decision, or situation. | The artifact uses vague language such as 'improve work' or 'use AI better.' |
| Actionability | The next step is small, dated, and possible within seven days. | The learner ends with an aspiration but no action. |
| Human responsibility | The learner names who decides, reviews, verifies, or carries responsibility. | The tool, policy, or system appears to be responsible by itself. |
| Evidence | The learner saves proof: a baseline, example, draft, rule, message, map, or review note. | The learner leaves with only an opinion or intention. |
| Safety | Sensitive information is removed, fictionalized, or kept inside approved systems. | The learner exposes real data unnecessarily or cannot name the data boundary. |
Common mistakes to watch for
- Trying to solve every career risk at once.
- Skipping the baseline.
- Running a pilot with no decision date.
- Updating your story without evidence.
Close the session
- Ask each learner to state the artifact they created and the next action they will take.
- Collect one unresolved question or risk from each learner or group.
- End by connecting the session back to Lojik360's three moves: delegate carefully, supervise rigorously, and strengthen what remains human.