Progress will remain available on this page, but it will not persist after you leave. Easy Mode remains available.
About this workshop
Workshop mission: Turn motivated, open-minded, non-technical sales professionals into AI superheroes who can match the practical output and problem-solving pace of technical peers who are not using AI, while staying evidence-grounded, governed, and honest about what the tools proved.
Boundary: synthetic qualitative evidence only—not a customer KPI, measured production result, live connection, or publication approval.
Found something inaccurate? Use Report an issue at that point. It opens a prefilled GitHub issue for review and does not submit anything automatically.
These points and badges are local, self-reported workshop progress—not externally verified proof or a capability claim.
This opens one prefilled progress issue containing every badge currently earned here. Nothing syncs until you submit it. Resubmitting later merges newly earned badge IDs without duplicate score, and one public issue submission opts your GitHub account into a public verified profile.
1
Workshop setup
Open GitHub Copilot Chat
Start in GitHub Copilot Chat. No Frontier desktop app is required; the Easy Mode skill handles any additional setup.
Get ready
Open VS Code with the GitHub Copilot Chat extension installed.
Sign in to GitHub with an account that has Copilot access.
Open the Copilot Chat panel and select Agent mode.
Expected result
GitHub Copilot Chat is open in VS Code, signed in, and set to Agent mode.
What you will learn
Use the single Easy Mode skill.
Build and prove the portable agent.
Deploy the reviewed solution as an unpublished Draft.
Confirm the behavior yourself in Copilot Studio Preview.
Recognize the evidence that means the module is complete.
Before you begin
Use VS Code with GitHub Copilot Chat in Agent mode.
Sign in to GitHub with Copilot access.
Have access to a Copilot Studio environment.
The skill handles setup for you.
Do not publish. This module ends with a validated Draft.
Easy mode
2
Prepare your Copilot
Brief your Copilot with one line
One skill owns discovery, testing, Draft deployment, and Preview validation.
Do this
Open GitHub Copilot Chat in VS Code and select Agent mode.
Paste this one line and send it. Copilot reads the skill itself; nothing to download.
Send this message
Go and read https://raw.githubusercontent.com/microsoft/aibast-agents-library/main/skills/aibast-easy-mode/SKILL.md and run the Product Line Optimization workshop for me.
Expected result
Copilot says it has read the skill and is running the workshop. The skill owns the remaining setup and validation.
3
Prove the solution locally
Ask Easy Mode to build and test Product Line Optimization
This step proves the portable business logic before any Copilot Studio work begins. The harness retrieves the immutable package, verifies the source, loads the agent, and runs every locked case.
Send this message
Give me Product Line Optimization using Easy Mode and test it for me.
Expected result
Copilot reports a verified source and 4/4 locked local cases passed.
Copilot should end by suggesting the next message: Deploy it into Copilot Studio for me.
4
Create the reviewed Draft
Deploy the already-tested solution to Copilot Studio
The harness now uses the verified Microsoft Copilot Studio plugin to reuse or create the source-controlled Draft, synchronize the reviewed instructions and assets, validate the PAC project, and leave publication off.
Send this message
Deploy it into Copilot Studio for me.
Expected result
Draft: Product Line Manual
Model: Claude Opus 5
Knowledge files: 2
Skills: 4
Status: Draft; published: false
The harness then validates the real Preview front door before returning its final verdict.
5
Verify the real experience
Confirm the Draft in Copilot Studio Preview
The harness already runs these checks automatically. Repeat them here so you understand what was proven and can recognize a correct result yourself.
Open the validated Draft.
Select Preview.
Choose New chat before each case.
Paste the exact prompt.
Compare the answer with the required and forbidden markers.
Every case passes in a fresh Preview conversation, and the agent still appears as Draft.
PLO-01 · Plant Manager
Confirm the expected evidence
Which production line needs attention today, and what is driving the loss?
Must include
Polymer Molding Line CElectronics Assembly Line A
Must not claim
I don't have accessprovide the line
Visible positive anchors: Polymer Molding Line C; Electronics Assembly Line A. The screenshot supports the learner checkpoint; the full case pass remains the deterministic machine gate. Source: 1424×863 JPEG. Download original.
PLO-02 · Production Engineer
Confirm the expected evidence
Where is the bottleneck on each line, and which station should the plant team address first?
Must include
Functional TestRobotic WeldingInjection Molding
Must not claim
I don't have access
Visible positive anchors: Functional Test; Injection Molding; Robotic Welding. The screenshot supports the learner checkpoint; the full case pass remains the deterministic machine gate. Source: 1424×863 JPEG. Download original.
PLO-03 · Operations Director
Confirm the expected evidence
Give me the practical options to improve throughput without hiding the quality tradeoffs.
Must include
Option 1Option 2Quality improvement
Must not claim
I don't have access
Visible positive anchors: Option 1; Option 2; Quality improvement. The screenshot supports the learner checkpoint; the full case pass remains the deterministic machine gate. Source: 1424×863 JPEG. Download original.
PLO-04 · Plant Manager
Confirm the expected evidence
Translate the current line performance into a day, swing, and night shift plan.
Must include
DaySwingNight
Must not claim
I don't have access
Visible positive anchors: Day; Swing; Night. The screenshot supports the learner checkpoint; the full case pass remains the deterministic machine gate. Source: 1424×863 JPEG. Download original.
6
Recognize completion
Know what “done” looks like
The workshop is complete only when both the portable agent and the Copilot Studio front door prove the same behavior.
Local proof4/4 locked cases passedPreview proof4/4 locked cases passedDraft identityProduct Line ManualModelClaude Opus 5Inventory2 knowledge · 4 skillsPublication gateDraft · published false
The harness reports status: complete, exact case totals, the Draft identity, and published: false. The module ends here; it does not offer publication.
Troubleshooting
What you see
What it means
What to do
Copilot ignores the workshop
The wrong skill was read, or the chat began before the one line was sent.
Start a new Agent-mode chat and send the one line first.
Local validation is not 4/4
The portable source, package, or locked behavior does not match.
Stop. Do not deploy. Let the harness report the exact failed case and marker.
No active Copilot Studio environment
PAC has no selected environment.
Sign in or select the intended environment, then resend the deploy message.
The Draft already exists
The recorded schema is already in the environment.
The harness should clone and reconnect automatically. Treat an attendee choice prompt as a harness defect.
A Preview case misses a marker
The real front door does not match the reviewed contract.
Keep the case failed. Inspect instructions and assets; do not retry until it happens to pass.
The agent is Published
The workshop crossed its safety boundary.
Stop immediately. The module must end at Draft with published: false.
Facilitator evidence and portable download
These links support audit, troubleshooting, and offline delivery. They are not learner steps.
See how Product Line Optimization Agent is built, one capability at a time.
Optional. Easy mode already did all of this for you from one skill file. This path replays every action the AI took, one real browser frame per step, so you can understand the agent before you adapt it. No PAC CLI, YAML import, or plugin architect; stop at Draft.
Synthetic disclosure: this is qualitative workflow evidence using packaged synthetic inputs. It is not a customer KPI or a live-system result.
Found something inaccurate? Use Report an issue on that step. It opens a prefilled GitHub issue for review and does not submit automatically.
Manual-mode progress is saved on this device and contributes to the same achievement profile.
Build and verify
1
Create a blank Copilot Studio agent
Step 1 of 18
Action
Create a blank Copilot Studio agent
Expected resultA blank Copilot Studio agent is visible in the captured Draft workspace.
Positive visual checkpoint: Untitled Agent. Source capture: 1424×863 JPEG. The full pass remains the deterministic machine gate. Download original.
2
Name Product Line Manual
Step 2 of 18
Action
Product Line Manual
Name Product Line Manual
Expected resultThe page header shows the recorded manual build name: Product Line Manual.
Positive visual checkpoint: Product Line Manual. Source capture: 1424×863 JPEG. The full pass remains the deterministic machine gate. Download original.
3
Enter the reviewed global instructions
Step 3 of 18
Action
# Role
You are Product Line Optimization Pilot, a plant-operations
decision-support agent for a fictional manufacturing plant. You help
plant managers, production engineers, and operations directors
understand line health, station-level constraints, throughput
improvement options, and shift production planning across four
synthetic production lines, and plan the Production Line 3 holiday
demand surge (line analysis, optimization plan, implementation plan,
risk mitigation, financial analysis, monitoring plan).
# Pilot data boundary
- This pilot is fully self-contained. Use only the synthetic line,
station, defect, and shift records and the calculation rules
packaged with this project.
- The four lines are fixed: Production Line 3 (the demo line),
Electronics Assembly Line A, Metal Fabrication Line B, and Polymer
Molding Line C. Never invent
another line, station, product, defect, shift, or operator, and
never fabricate numbers beyond the packaged records.
- Every operating score, gap, cost, gain, projection, and investment
range is a synthetic planning estimate, not a measured result or a
commitment. Label estimates and planning figures as synthetic.
- Never claim or imply that you accessed a live ERP (Dynamics 365),
IoT or equipment telemetry (Azure IoT Hub), an MES, Power BI, or
any other live plant or reporting system. Do not say you lack
access either; simply work from the packaged synthetic records.
- End every substantive answer with:
`> Synthetic pilot data; figures are planning estimates, not a live ERP, IoT, or Power BI reading.`
# Natural-language routing
Decide the workflow from the user's intent using plant-floor
language. Never require an operation name and never ask the user to
pick or provide a line — work across all four synthetic lines for
plant-wide questions and on Production Line 3 for the holiday-surge
sequence.
- For "analyze production line 3 performance and optimize for the
holiday demand surge," give the Line 3 analysis: 2,400 units/day,
OEE 71% (world-class 85%), the 40% surge target of 3,360 units/day,
4 weeks to ramp, 45 production days, and the primary bottleneck SMT
Placement Station 3B (limiting to 2,450 units/day).
- For "show optimization plan," give the five-option Line 3 table
(+1,030 units/day total, 3,430 vs 3,360, 102% safety margin); for
"show implementation details," the 4-week plan; for "show risk
mitigation," the four risks; for "show financial analysis," the ROI
summary ($504,000 investment, ROI 286%, payback 11.7 production
days); for "show monitoring plan," the dashboards, alert thresholds,
stand-ups and the 151,200-unit season target.
- For "which line needs attention today" or "where are we losing
output / what is driving the loss," give the plant-wide operating
health review: rank the lines by operating score against the 75%
threshold and name the driver of each loss.
- For "where is the bottleneck / which station is slowing the line /
which station do we fix first," identify the constraining station
on each line from cycle-versus-takt and defect evidence.
- For "practical options to improve throughput without hiding the
quality tradeoffs," compare the process, added-capacity, and
quality response options for each line and keep the quality option
visible.
- For "translate line performance into a day, swing, and night
plan," build the three-shift output and operator staffing view.
Continue the agentic loop when a request needs more than one
workflow — for example, a shift plan may follow from the line-health
view, or an options request may build on the bottleneck analysis.
Ask one concise clarification only when the request genuinely cannot
be mapped to any of these workflows from the packaged records.
# Decision and safety rules
1. Lead with the operational decision or most important finding,
then the supporting facts (line, station, and figures).
2. Name the relevant line and, where applicable, the specific
station.
3. Report analysis and recommendations only. Never start, stop,
throttle, reschedule, or reconfigure a line, station, or shift;
never dispatch maintenance; never commit an investment or a
headcount change. Use "Recommended," "Suggested next step," and
"Projected."
4. Keep the quality tradeoff visible in every throughput
recommendation. Never present a throughput gain while hiding its
quality or defect impact. Preserve quality tradeoffs.
5. Ground every answer in the packaged synthetic evidence. Do not
recalculate figures from any other source and do not invent
lines, stations, or numbers.
6. For an unknown line or station, say what is missing and list the
known records rather than substituting another.
# Response style
Use concise Markdown suited to a plant floor: a short decision
statement first, then a compact table or tight bullets. Use uph for
rate, seconds for cycle and takt, and currency with separators.
Avoid generic preambles and filler.
# Production seams
If this pilot is promoted, the packaged synthetic records could be
replaced by Dynamics 365 ERP production context, Azure IoT Hub
equipment telemetry, and Power BI reporting surfaces. Those are
future integration seams only; no live connector is configured in
this pilot.
Enter the reviewed global instructions
Expected resultThe reviewed manual/GLOBAL-INSTRUCTIONS.md policy is visible or saved without unrecorded edits.
Positive visual checkpoint: Role. Source capture: 1424×863 JPEG. The full pass remains the deterministic machine gate. Download original.
4
Save the instruction policy
Step 4 of 18
Action
Save the instruction policy
Expected resultThe reviewed manual/GLOBAL-INSTRUCTIONS.md policy is visible or saved without unrecorded edits.
Positive visual checkpoint: Draft. Source capture: 1424×863 JPEG. The full pass remains the deterministic machine gate. Download original.
5
Remove default web search
Step 5 of 18
Action
Remove default web search
Expected resultThe captured inventory no longer lists the default web-search capability.
Positive visual checkpoint: Provide trusted context to guide decisions. Source capture: 1424×863 JPEG. The full pass remains the deterministic machine gate. Download original.
Expected resultThe exact knowledge file linked for this step is attached under its complete filename. Wait for processing to finish before continuing. This step does not require the final inventory or prove the other uploads.
Positive visual checkpoint: aibast_production-optimization-rules.md. Source capture: 1424×863 JPEG. The full pass remains the deterministic machine gate. Download original.
Expected resultThe exact knowledge file linked for this step is attached under its complete filename. Wait for processing to finish before continuing. This step does not require the final inventory or prove the other uploads.
Positive visual checkpoint: aibast_production-line-synthetic-records.md. Source capture: 1424×863 JPEG. The full pass remains the deterministic machine gate. Download original.
8
Add skill: aibast_bottleneck_plo02
Step 8 of 18
Action
Add skill: aibast_bottleneck_plo02
Expected resultThe linked SKILL.md appears with its frontmatter name and description. Open it and compare the complete instructions with the source file. This step does not require the final inventory or prove the other uploads.
Positive visual checkpoint: constraining-station-identification. Source capture: 1424×863 JPEG. The full pass remains the deterministic machine gate. Download original.
9
Add skill: aibast_line-health_plo01
Step 9 of 18
Action
Add skill: aibast_line-health_plo01
Expected resultThe linked SKILL.md appears with its frontmatter name and description. Open it and compare the complete instructions with the source file. This step does not require the final inventory or prove the other uploads.
Positive visual checkpoint: plant-wide-operating-health-review. Source capture: 1424×863 JPEG. The full pass remains the deterministic machine gate. Download original.
10
Add skill: aibast_shift-plan_plo04
Step 10 of 18
Action
Add skill: aibast_shift-plan_plo04
Expected resultThe linked SKILL.md appears with its frontmatter name and description. Open it and compare the complete instructions with the source file. This step does not require the final inventory or prove the other uploads.
Positive visual checkpoint: day-swing-night-production-plan. Source capture: 1424×863 JPEG. The full pass remains the deterministic machine gate. Download original.
11
Add skill: aibast_throughput-options_plo03
Step 11 of 18
Action
Add skill: aibast_throughput-options_plo03
Expected resultThe linked SKILL.md appears with its frontmatter name and description. Open it and compare the complete instructions with the source file. This step does not require the final inventory or prove the other uploads.
Positive visual checkpoint: improvement-option-comparison. Source capture: 1424×863 JPEG. The full pass remains the deterministic machine gate. Download original.
12
Review model, skills, knowledge, and safety boundaries
Step 12 of 18
Action
Review model, skills, knowledge, and safety boundaries
Expected resultThe screenshot visibly confirms Claude Opus 5, 4 rendered skills, and no tools. Knowledge is verified separately in the two knowledge-upload checkpoints.
Positive visual checkpoint: Claude Opus 5; improvement-option-comparison; day-swing-night-production-plan; plant-wide-operating-health-review; constraining-station-identification; aibast_production-line-synthetic-records.md; aibast_production-optimization-rules.md. Source capture: 1424×863 JPEG. The full pass remains the deterministic machine gate. Download original.
13
Open a fresh Preview conversation
Step 13 of 18
Action
Open a fresh Preview conversation
Expected resultA fresh Preview surface or its recorded qualitative result is visible; only the evidence file defines a pass.
Positive visual checkpoint: Product Line Manual. Source capture: 1424×863 JPEG. The full pass remains the deterministic machine gate. Download original.
14
Pass PLO-01: Plant Manager
Step 14 of 18
Action
Which production line needs attention today, and what is driving the loss?
Pass PLO-01: Plant Manager
Expected resultThe captured Preview evidence records PLO-01 with the recorded identifiers Polymer Molding Line C, Electronics Assembly Line A; do not infer results beyond it.
Before this case
Open Preview in a fresh conversation before running PLO-01. A previous response must not influence the evidence.
Positive visual checkpoint: Polymer Molding Line C; Electronics Assembly Line A. Source capture: 1424×863 JPEG. The full pass remains the deterministic machine gate. Download original.
15
Pass PLO-02: Production Engineer
Step 15 of 18
Action
Where is the bottleneck on each line, and which station should the plant team address first?
Pass PLO-02: Production Engineer
Expected resultThe captured Preview evidence records PLO-02 with the recorded identifiers Functional Test, Robotic Welding, Injection Molding; do not infer results beyond it.
Before this case
Open Preview in a fresh conversation before running PLO-02. A previous response must not influence the evidence.
Positive visual checkpoint: Functional Test; Injection Molding; Robotic Welding. Source capture: 1424×863 JPEG. The full pass remains the deterministic machine gate. Download original.
16
Pass PLO-03: Operations Director
Step 16 of 18
Action
Give me the practical options to improve throughput without hiding the quality tradeoffs.
Pass PLO-03: Operations Director
Expected resultThe captured Preview evidence records PLO-03 with the recorded identifiers Option 1, Option 2, Quality improvement; do not infer results beyond it.
Before this case
Open Preview in a fresh conversation before running PLO-03. A previous response must not influence the evidence.
Positive visual checkpoint: Option 1; Option 2; Quality improvement. Source capture: 1424×863 JPEG. The full pass remains the deterministic machine gate. Download original.
17
Pass PLO-04: Plant Manager
Step 17 of 18
Action
Translate the current line performance into a day, swing, and night shift plan.
Pass PLO-04: Plant Manager
Expected resultThe captured Preview evidence records PLO-04 with the recorded identifiers Day, Swing, Night; do not infer results beyond it.
Before this case
Open Preview in a fresh conversation before running PLO-04. A previous response must not influence the evidence.
Positive visual checkpoint: Day · Swing · Night. Source capture: 1424×863 JPEG. The full pass remains the deterministic machine gate. Download original.
18
Confirm Draft and stop before publish
Step 18 of 18
Action
Confirm Draft and stop before publish
Expected resultThe agent remains Draft and no Publish action is taken.
Positive visual checkpoint: Product Line Manual. Source capture: 1424×863 JPEG. The full pass remains the deterministic machine gate. Download original.
Manual-mode troubleshooting
A screenshot or browserfilm frame is missing
Stop. Do not invent, recreate, or substitute an image. Capture the real frame, update the browserfilm manifest, and regenerate without --allow-pending.
A knowledge file is still processing
Wait for ingestion to finish before Preview. A partial answer is not evidence.
A skill upload fails
Use the linked raw SKILL.md. Fix the reviewed source deliberately; do not silently skip the action.
The model differs from Easy mode
Record the substitution and stop the parity claim until Easy and Manual use the same reviewed model.
The Preview answer misses an identifier
Mark the recorded case failed, inspect instructions and inventory, then replay the exact prompt in a fresh conversation.
Should I publish?
No. Keep this manual duplicate in Draft unless publication is separately approved. Do not choose Publish as part of this tutorial.