10 live days · Your work, in practice
Direct a Factory for project delivery.
Choose MasterCourse for all ten days and the exclusive Capstone. Test a bounded project from initial request to accepted handover using simulated updates.
Build an AI working method around a project you recognize. Start with a useful brief, give recurring preparation and follow-up to proactive agents, then coordinate several proactive AI agent teams to carry a client or internal project through to a reviewed handover.
A professional often owns the space between an unclear request and a result someone else can use. The course follows a sample service-improvement project, with room to substitute a comparable assignment from your role while keeping scope, commitments and review responsibility clear.
What you learn
Learn to connect role-specific prompts and proactive project agents into a Factory of proactive AI agent teams that research, plan, prepare and review work together.
Build a Factory of proactive AI agent teams for project preparation. Use a Dot to coordinate continuing work across their handoffs and return current actions, draft deliverables and decisions holding up progress. Test changing inputs, blocked work and a later restart. The project owner approves scope, commitments and stakeholder communication.
Proactive Agents · OpenAI Dots
Create it. Name it. Put it to work.
Create and test a proactive AI agent, give its role a stable name, and define what it may do. Then hand supported work to OpenAI Dots for one run or a continuing responsibility. Your Dot can keep working between conversations, using approved context and connected tools, and return results or ask for a decision without a fresh prompt for every step.
Give the role a name and a brief
Name the role Project Follow-through. Provide the approved request, scope, evidence, owners, deadline and acceptance criteria. Limit connections to the permitted project queue and folder; record the accepted brief so later requests can be checked against it.
Choose a run or an ongoing responsibility
A Dot has its own cloud computer and browser. When the assignment, files and tools are available there, it can work while your phone or computer is off. Always-on means available to continue the responsibility; it may wait for a schedule, input or approval and remains subject to access and usage limits. Work using local files or applications still needs that connected computer online with the ChatGPT app open.
Set the return and the review rhythm
Return current actions, draft deliverables and decisions holding up progress under the same named responsibility, with source versions and completed, waiting and blocked work clearly separated. Agree whether you need a scheduled report, an update on a material change, or a decision request. The project owner approves scope, commitments and stakeholder communication.
Agree when results are due, which changes deserve an alert and where to review them. Confirm recurring schedules, time zones and end dates; connecting an app alone does not enable monitoring. Test a changed input and a blocked step. Before retiring the responsibility, stop its delegated work and cancel its schedules separately. Keep the reviewed instructions so you can recheck access and resume when needed.
Connect only what the role needs
Use approved project material and limit personal or customer data to what the task needs. Keep client-confidential records and employee information out of unapproved connections. If your role involves hiring or other decisions about people, use fictional examples and keep those decisions with the authorized human reviewer.
A project connection does not authorize access to every client workspace or permission to contact stakeholders. Define the permitted project, recipients and actions before continuing work.
This practice is part of the existing proactive agent assignments and review time. It does not add class days or extend the hours shown in your booking.
The learning map
Work units by day
10 days of practical work for Consultants, project leads, managers and professionals who turn information into plans, decisions and client work. Every unit below has an output and a review point.
Your learning plan: these are the tasks you will practice. The time suggested for each task is a guide; your booking shows the confirmed class dates and start and end times.
Project briefing · Clear scope
Turn a request into a working brief
- 1.1Identify the decision and the user
- 1.2Summarize the supplied evidence
- 1.3Write an actionable project brief
Options · Stakeholder communication
Prepare a recommendation people can use
- 2.1Compare practical options
- 2.2Draft the next-step communication
- 2.3Refine prompts for your role
Proactive Intake agent · Request triage
Organize requests as they arrive
- 3.1Define the request proactive intake agent
- 3.2Test repeat and incomplete requests
Proactive Research agent · Changing evidence
Keep the project evidence current
- 4.1Create an evidence-update proactive agent
- 4.2Review weak and conflicting findings
Action proactive agent · Dependencies
Keep actions and dependencies visible
- 5.1Maintain the action register
- 5.2Handle delays and blocked work
Delivery proactive agent · Controlled revisions
Prepare the next useful deliverable
- 6.1Build a deliverable-preparation proactive agent
- 6.2Respond to reviewed changes
Project reporting · Ongoing operation
Test the proactive agents over a project cycle
- 7.1Produce a recurring project review
- 7.2Test interruption and resumption
Factory design · proactive Project AI agent teams
Organize proactive AI agent teams around the outcome
- 8.1Give each proactive AI agent team a defined output
- 8.2Specify the handoff agreements
Factory coordination · Scope changes
Carry a change through the project
- 9.1Run the proactive AI agent team handoffs
- 9.2Resolve conflicting requirements
Factory operation · Accepted handover
Deliver a system you can direct
- 10.1Refine the proactive AI agent team operating rules
- 10.2Define the handover decision
- 10.3Run the complete project simulation
The work behind the map
Daily detail
Follow the work from its starting material to a result you can inspect. Each checkpoint gives you a reason to approve, revise or stop.
Intro
Days 1–2 · Tasks
Frame a useful first pass.
Direct one important task at a time. Give the prompt enough context, inspect the result and improve it before reuse.
Day 01Turn a request into a working brief
Use a sample service-improvement request or a permitted example from your role. Decide what the requester needs before asking AI to produce a polished answer.
- 1.1
Identify the decision and the user
Describe who will use the work, what decision or action it supports and the constraints that matter. Separate the stated request from assumptions about the underlying need.
Suggested time for this task: 1 hour in Full Course; 30 minutes in Crash Course. Part of your class day, not extra time.- Practice result
- A task brief with audience, purpose and boundaries.
- 1.2
Summarize the supplied evidence
Prompt a concise summary of the sample notes and documents. Attach references and mark disagreements, missing facts and questions for the requester.
Suggested time for this task: 1 hour 20 minutes in Full Course; 40 minutes in Crash Course. Part of your class day, not extra time.- Practice result
- A checked evidence summary and open-question list.
- 1.3
Write an actionable project brief
Combine the scope and evidence into a brief with deliverables, exclusions and acceptance criteria. Review it as the person who will receive the work.
Suggested time for this task: 1 hour 40 minutes in Full Course; 50 minutes in Crash Course. Part of your class day, not extra time.- Practice result
- A project brief and reusable briefing prompt.
By the end of the day
A clear project brief that defines useful work and makes uncertainty visible.
Review checkpoint
Check every commitment against the request and make sure missing information is not disguised as an agreed requirement.
Day 02Prepare a recommendation people can use
Compare a small set of project options and write a useful next-step message. Keep evidence, judgment and approval separate.
- 2.1
Compare practical options
Use supplied constraints to compare two or three approaches by effort, dependencies and expected usefulness. Mark estimates and assumptions rather than inventing precise benefits.
Suggested time for this task: 1 hour in Full Course; 30 minutes in Crash Course. Part of your class day, not extra time.- Practice result
- An options table with a clear basis for comparison.
- 2.2
Draft the next-step communication
Write a concise recommendation for the sample requester, explaining the proposed approach, unresolved choices and action needed. Keep unapproved commitments out of the message.
Suggested time for this task: 1 hour 20 minutes in Full Course; 40 minutes in Crash Course. Part of your class day, not extra time.- Practice result
- A draft recommendation and stakeholder message.
- 2.3
Refine prompts for your role
Review the brief and options against their sources. Refine the prompts for scope, summary, comparison and communication, with checks appropriate to your own responsibilities.
Suggested time for this task: 1 hour 40 minutes in Full Course; 50 minutes in Crash Course. Part of your class day, not extra time.- Practice result
- Practice adapting prompts to your role and checking their results against the brief.
By the end of the day
Practice turning a request into a clear brief, comparing options and explaining the next step.
Review checkpoint
Confirm that the recommendation explains its tradeoffs and asks for the right decision without claiming approval already exists.
Intensive
Days 3–7 · Proactive Agents
Keep recurring work moving.
Build proactive agents that run defined tasks over time. Give each one a trigger, working record and limits, then review its exceptions and results.
Build the proactive agent and test one complete run. Name its role, approve its inputs and connections, then hand suitable work to a Dot. Choose a single assignment or a continuing responsibility with clear reports, review points and a way to stop.
Day 03Organize requests as they arrive
Build a proactive agent that processes new sample requests into a consistent queue. Give it a narrow job and preserve what it has already handled.
- 3.1
Define the request proactive intake agent
Set a new-request trigger, required fields, allowed source locations and triage prompt. Save request identifiers and route missing or out-of-scope material to a person.
Suggested time for this task: 2 hours in Full Course; 1 hour in Crash Course. Part of your class day, not extra time.- Practice result
- A request proactive intake agent and a structured work queue.
- 3.2
Test repeat and incomplete requests
Run successive batches containing a duplicate and a request without an owner. Verify saved state, one bounded retry for temporary failure and an explicit unresolved-items list.
Proactive agent practice. Create and test the project preparation proactive agent on one sample run. Name the role Project Follow-through and hand supported work to a Dot using an approved request queue, project brief and evidence folder. Define permitted actions and the return you expect; inspect the first result before giving it an ongoing responsibility.
Suggested time for this task: 2 hours in Full Course; 1 hour in Crash Course. Part of your class day, not extra time.- Practice result
- A tested intake run and exception record.
By the end of the day
A recurring proactive intake agent that prepares work for a person’s prioritization.
Review checkpoint
The proactive agent may classify and draft questions; it must not accept new commitments, change priorities or contact a client without permission.
Day 04Keep the project evidence current
Give a proactive research agent a defined source set and update cycle. Useful monitoring reports what changed and why it matters to the assignment.
- 4.1
Create an evidence-update proactive agent
Configure a scheduled check of approved sample sources. Record the last accepted version, extract relevant changes and connect each finding to the project question.
Suggested time for this task: 2 hours in Full Course; 1 hour in Crash Course. Part of your class day, not extra time.- Practice result
- A research-update proactive agent and source register.
- 4.2
Review weak and conflicting findings
Introduce an outdated source and a contradictory update. Have the proactive agent distinguish observed changes from interpretation and queue unsupported claims instead of merging them into the brief.
Proactive agent practice. Connect the approved evidence location or provide a reviewed export. Set when the proactive research role should check for updates. Return dated findings and conflicts with the accepted brief, keeping source selection within scope.
Suggested time for this task: 2 hours in Full Course; 1 hour in Crash Course. Part of your class day, not extra time.- Practice result
- A change digest with confidence limits and review questions.
By the end of the day
A recurring evidence digest that preserves references and flags what needs judgment.
Review checkpoint
Open a sample of the cited sources and confirm that the reported change is real, relevant and not simply a duplicate.
Day 05Keep actions and dependencies visible
Build a proactive agent around approved project actions. Its work is to maintain a reliable picture of commitments, not to invent owners or deadlines.
- 5.1
Maintain the action register
Trigger an update when approved notes or decisions arrive. Extract actions, owners and due dates, preserve earlier decisions and mark unassigned items for review.
Suggested time for this task: 2 hours in Full Course; 1 hour in Crash Course. Part of your class day, not extra time.- Practice result
- An action-tracking proactive agent and versioned action register.
- 5.2
Handle delays and blocked work
Simulate a late dependency and a changed deadline. Produce an impact summary and a draft follow-up; require approval before any external message or commitment change.
Proactive agent practice. Confirm the action-register review schedule and escalation rules. Introduce a missed dependency; let the proactive role identify affected work and ask for the owner’s decision without changing commitments.
Suggested time for this task: 2 hours in Full Course; 1 hour in Crash Course. Part of your class day, not extra time.- Practice result
- A dependency report and approval-ready follow-up queue.
By the end of the day
An action record that shows what changed, who owns it and what cannot move yet.
Review checkpoint
Check that inferred dates and owners are not presented as agreed commitments and that blocked work remains visible.
Day 06Prepare the next useful deliverable
Give a proactive agent a repeatable drafting assignment using the accepted brief and evidence. A changed requirement should result in a traceable revision.
- 6.1
Build a deliverable-preparation proactive agent
Define the accepted-brief trigger, template, source snapshot and review standard for a sample implementation plan. Save the draft version and stop when mandatory inputs are missing.
Suggested time for this task: 2 hours in Full Course; 1 hour in Crash Course. Part of your class day, not extra time.- Practice result
- A delivery proactive agent and a first implementation-plan draft.
- 6.2
Respond to reviewed changes
Return a draft with specific feedback and introduce a changed requirement. Have the proactive agent revise only the affected sections, record the changes and escalate conflicting instructions.
Proactive agent practice. Keep deliverable preparation active against the approved brief and review notes. Apply accepted changes, preserve the previous version and return work against the same acceptance criteria at the agreed review point.
Suggested time for this task: 2 hours in Full Course; 1 hour in Crash Course. Part of your class day, not extra time.- Practice result
- A revised deliverable and change log.
By the end of the day
A delivery proactive agent that prepares and revises work against an agreed brief.
Review checkpoint
Review whether the revision satisfies the request without quietly expanding scope or losing a prior accepted requirement.
Day 07Test the proactive agents over a project cycle
Connect the proactive agents through a shared project record. Run a compressed sequence of updates to see what a manager would need to review over time.
- 7.1
Produce a recurring project review
Schedule a proactive reporting agent to collect accepted evidence, actions and deliverable status. Highlight changes, blocked work and decisions needed without sending the report automatically.
Suggested time for this task: 1 hour 40 minutes in Full Course; 50 minutes in Crash Course. Part of your class day, not extra time.- Practice result
- A project-review proactive agent and a concise status pack.
- 7.2
Test interruption and resumption
Interrupt a run, repeat an input and withhold a decision. Check bounded retries, completed-work records and the rule for resuming only when the missing decision is supplied.
Proactive agent practice. Let Project Follow-through continue a cloud-capable assignment while you leave the chat. Inspect the result, block one input and test recovery. Then retire the responsibility: stop active delegates, cancel future schedules and retain the reviewed instructions. Recheck access and inputs before calling it back into service.
Suggested time for this task: 2 hours 20 minutes in Full Course; 1 hour 10 minutes in Crash Course. Part of your class day, not extra time.- Practice result
- A failure-test log and a project-proactive agent operating guide.
By the end of the day
A tested group of proactive agents for recurring preparation, follow-up and reporting.
Review checkpoint
Confirm that each exception has an owner and that repeated inputs do not create repeated tasks or communications.
MasterCourse - Capstone
Days 8–10 · MasterCourse only · Factory
Direct a Factory of proactive AI agent teams.
Coordinate multiple supervised proactive AI agent teams around a larger outcome. Define what each proactive AI agent team delivers, how work changes hands and where you approve the result.
Build a Factory of proactive AI agent teams around a shared outcome. Give each team accepted inputs, a named responsibility and a clear handoff. A Dot can coordinate continuing work and delegate bounded runs; each role does not need a separate personal Dot.
Day 08Organize proactive AI agent teams around the outcome
Build a Factory for the sample service-improvement project. Separate the proactive AI agent teams that establish the evidence, prepare the delivery plan and check whether the handover is usable.
- 8.1
Give each proactive AI agent team a defined output
Create a Discovery proactive AI agent team with intake and proactive research agents, a Delivery Planning proactive AI agent team with action and proactive drafting agents, and an Acceptance proactive AI agent team with checking and handover proactive agents.
Suggested time for this task: 1 hour 40 minutes in Full Course; 50 minutes in Crash Course. Part of your class day, not extra time.- Practice result
- A project Factory plan with proactive AI agent team deliverables and decision owners.
- 8.2
Specify the handoff agreements
Define the brief, source references, assumptions and approval status each proactive AI agent team must pass onward. Add acceptance checks so incomplete work returns to the right owner.
Proactive agent practice. Give the Dot the Discovery, Delivery Planning and Acceptance proactive AI agent teams’ handoff requirements. Test that an incomplete brief cannot silently become an approved delivery commitment. Give each role a stable name and decide which responsibilities continue between cycles.
Suggested time for this task: 2 hours 20 minutes in Full Course; 1 hour 10 minutes in Crash Course. Part of your class day, not extra time.- Practice result
- Proactive AI agent team handoff contracts and a shared project record.
By the end of the day
A Factory of multiple proactive AI agent teams organized around one accepted project handover.
Review checkpoint
Every proactive AI agent team needs a distinct contribution; no handoff should depend on an unstated assumption or an unassigned decision.
Day 09Carry a change through the project
Run the proactive AI agent teams from accepted request to reviewed delivery plan. Introduce a change late enough to test coordination rather than only initial drafting.
- 9.1
Run the proactive AI agent team handoffs
Pass the checked discovery brief to Delivery Planning, then send the proposed plan and evidence to Acceptance. Record returned work and the reason it did not meet the agreed standard.
Suggested time for this task: 1 hour 40 minutes in Full Course; 50 minutes in Crash Course. Part of your class day, not extra time.- Practice result
- A coordinated project run with accepted and rejected handoffs.
- 9.2
Resolve conflicting requirements
Introduce a new requester preference that conflicts with the approved scope. Pause affected work, present the tradeoff to the owner and propagate the approved decision to all proactive AI agent teams.
Proactive agent practice. Change a project requirement after planning begins. Have the Dot route the change to affected proactive AI agent teams and return a reconciled plan with any new tradeoff for the owner. Check that waiting work resumes only after the required input or decision is accepted.
Suggested time for this task: 2 hours 20 minutes in Full Course; 1 hour 10 minutes in Crash Course. Part of your class day, not extra time.- Practice result
- A scope-decision log and a consistent revised plan.
By the end of the day
A Factory that can revise work coherently when the project changes.
Review checkpoint
Check the final plan, action register and handover note against the same approved scope version.
Day 10Deliver a system you can direct
Demonstrate the Factory through a short, complete project simulation. Make its limits and approval requirements clear enough for another responsible person to inspect.
- 10.1
Refine the proactive AI agent team operating rules
Use the test findings to clarify permissions, scheduling, saved state and escalation. Separate work the proactive agents may continue from work that needs a new decision.
Suggested time for this task: 1 hour in Full Course; 30 minutes in Crash Course. Part of your class day, not extra time.- Practice result
- Reusable proactive AI agent team instructions and an exception guide.
- 10.2
Define the handover decision
Write acceptance criteria for completeness, source support, feasible dependencies and recipient usefulness. Assign the final approval to the project owner.
Suggested time for this task: 1 hour 20 minutes in Full Course; 40 minutes in Crash Course. Part of your class day, not extra time.- Practice result
- A project acceptance checklist and release procedure.
- 10.3
Run the complete project simulation
Process a seeded request, a changed requirement and one returned deliverable. Assemble the accepted output with its source and decision records.
Proactive agent practice. Run a second project cycle and inspect the final handover against the approved scope. Confirm who accepted each output and verify that pending work and reminders are stopped when the exercise ends. Retire the Factory’s active work and schedules, then rehearse a restart from its reviewed roles and a fresh approved input.
Suggested time for this task: 1 hour 40 minutes in Full Course; 50 minutes in Crash Course. Part of your class day, not extra time.- Practice result
- A demonstrated project Factory, reviewed handover pack and operating guide.
By the end of the day
Practice directing proactive project agents and coordinated proactive AI agent teams through a complete handover, with review at each stage.
Review checkpoint
The owner must approve the handover. The class demonstrates a bounded project process, not the completion of a real client engagement.
Days 8–10 · MasterCourse - Capstone
A Factory with clear handoffs.
Carry a sample service-improvement request from evidence gathering to an accepted implementation plan and handover.
Proactive AI agent team 1
Discovery
- Proactive agent roles
- Request intake, Evidence-update, Brief-checking
- Deliverable
- An accepted project brief and referenced evidence bundle.
- Handoff
- Send the accepted brief to Delivery Planning and unresolved scope questions to the project owner.
- Acceptance check
- The user, purpose, constraints, sources and unanswered questions are explicit.
Proactive AI agent team 2
Delivery Planning
- Proactive agent roles
- Action-tracking, Plan-drafting, Dependency
- Deliverable
- A proposed implementation plan with owners, dependencies and draft communications.
- Handoff
- Send the plan and decision record to Acceptance; return missing requirements to Discovery.
- Acceptance check
- The plan follows the accepted scope and identifies unapproved commitments rather than presenting them as agreed.
Proactive AI agent team 3
Acceptance
- Proactive agent roles
- Requirement-checking, Consistency, Handover
- Deliverable
- A checked handover pack and a list of decisions required for release.
- Handoff
- Return incomplete work to its owner and present acceptable work to the project owner.
- Acceptance check
- The pack is consistent with the approved brief, usable by its recipient and explicitly approved before release.
Simulate several project updates, a late requirement and a rejected draft. proactive AI agent teams preserve a shared scope version and return work with specific revision reasons.
The project owner approves scope changes, commitments and release. External messages and system changes remain behind explicit permission.
The Capstone builds and tests a supervised prototype with sample cycles, revisions and exceptions. Longer projects continue beyond class; three days do not imply completion of a full production program.
A Factory that can carry work forward
Coordinate Discovery, Delivery Planning and Acceptance as teams of proactive AI agents. The Dot follows accepted work through the shared project record, checks dependencies between cycles and routes changed requirements back for review. The owner approves changes to scope or commitments before downstream work proceeds.
Keep the approved brief, source versions and decisions in the shared handoff record. Notes help preserve context; they do not replace a checked record. Test a second cycle, a blocked handoff and recovery. Retire the Factory by stopping active delegates and future schedules; retain the reviewed roles for a later restart.
Your time commitment
How long is each class day?
You attend 10 live classes, one on each scheduled day. Choose Full Course or Crash Course for all 10 days. The times below include breaks.
Full Course
6 hours per day
More time to practice, ask questions and review your work.
Suggested plan for one day
- Lessons and hands-on practice
- 4 hours
- Review and questions
- 30 minutes
- Lunch break
- 1 hour
- Two short breaks
- 15 minutes each
10 class days × 6 hours = 60 hours totalIncludes all scheduled breaks.
Crash Course
2 hours 30 minutes per day
The same topics in shorter classes, with prepared examples and less practice time.
Suggested plan for one day
- Lessons and hands-on practice
- 2 hours
- Review and questions
- 20 minutes
- One short break
- 10 minutes
10 class days × 2 hours 30 minutes = 25 hours totalIncludes all scheduled breaks.
Lunch, breaks and review time are already included in each day. The task times in Daily detail fit inside the practice time above. Your trainer may adjust the plan; the start and end times shown with your selected dates are the ones to follow.
Choose your starting point
One progression. Three choices.
Intro teaches individually directed prompts. Intensive puts recurring work into proactive agents. MasterCourse connects the whole pathway and adds the Factory Capstone.
Intro
Learn to turn a work request into a clear prompt, check a project brief and compare options against the evidence.
Choose Intro for individual summarizing, planning and drafting tasks. Bring a role-relevant example or use the supplied service-improvement scenario.
Intensive
Learn to build and supervise proactive agents for request intake, research updates, action tracking, deliverable preparation and reporting, with clear permissions and exception review.
Choose Intensive to move beyond one-off prompts into proactive agents that run defined work over time. The five days cover curriculum days 3–7.
Create and test proactive AI agents for project preparation. Name a role such as Project Follow-through, then hand suitable work to OpenAI Dots to follow accepted requests and dependencies between your reviews. Choose one run or a continuing responsibility, with approved connections, agreed reports and a clear way to pause or retire the work.
MasterCourse
Learn to connect role-specific prompts and proactive project agents into a Factory of proactive AI agent teams that research, plan, prepare and review work together.
Choose MasterCourse for all ten days and the exclusive Capstone. Test a bounded project from initial request to accepted handover using simulated updates.
Build a Factory of proactive AI agent teams for project preparation. Use a Dot to coordinate continuing work across their handoffs and return current actions, draft deliverables and decisions holding up progress. Test changing inputs, blocked work and a later restart. The project owner approves scope, commitments and stakeholder communication.
Intensive is a five-day purchase, not a seven-day bundle. The three-day Capstone is available only inside the ten-day MasterCourse.
Live guidance · Continued reference
Come prepared. Keep what you learn.
Bring a computer, a reliable connection and a work example you are authorized to use. Sample or sanitized material lets you practice without introducing confidential source files.
Practice with guidance
Work through the assignments live, compare results and use trainer feedback to refine your prompts, proactive agent instructions and review standards.
Revisit your classes
Students have access to recordings of their classes in the members portal.
Specialist tools · Separate subscriptions
Tools serve the assignment.
Two specialist tools chosen for practical fit and an established learning ecosystem. Claude, OpenAI, Gemini and Open Source options support the prompt and proactive agent work. Specialist examples connect it to your field.
Microsoft 365 Copilot
Research, analysis and document work in Microsoft 365; supported agent creation and workflows are listed.
Plan and access
Copilot Business $25.20/user/month on monthly subscription.A separate qualifying Microsoft 365 license is required. Advanced agent usage may be metered; do not imply every workflow is bundled.
Notion AI
Workspace documents, search and Notion Agent support; Custom Agents can handle recurring work.
Plan and access
Business $20/member/month on the annual USD view; Free and Plus have limited AI trials.Custom Agents use Notion credits separately; current listed rate is $10 per 1,000 credits. Confirm workspace permissions.
Do I need my own software access?
Yes. Arrange full access to the required features before class, including suitable paid plans, usage credits and organization permissions. Software costs are separate from tuition. Free access may not cover every exercise.
How these tools support your course
Intro · Tasks
Use Microsoft 365 Copilot and Notion AI examples to summarize a request, compare options and draft a project brief. Keep references close to the claims they support.
Intensive · Proactive Agents
Use supported Microsoft 365 Copilot and Notion AI features, permitted exports or controlled simulations to process requests, track actions and prepare deliverables. Match proactive agent permissions to the project record.
MasterCourse - Capstone · Factory
Coordinate Discovery, Delivery Planning and Acceptance proactive AI agent teams using permitted Microsoft 365 and Notion records. Test returned work and shared project context before the project owner approves handover.
Vendor information checked September 29, 2026. Plans and limits can change. Proactive Agents use supported connections or approved exported inputs; specialist subscriptions do not imply universal proactive agent integration. Human approval remains part of publishing, releasing work and professional decisions.
OpenAI Dots · Proactive agents at work
Hands-on proactive agent and Dots work starts in Intensive. Check Dots availability, supported connections and your organization’s permissions before class. You authorize each app or browser session; Dots does not inherit all your logins. Subscriptions and usage charges are separate from tuition. Some specialist work needs a reviewed export or an online local application.
A project connection does not authorize access to every client workspace or permission to contact stakeholders. Define the permitted project, recipients and actions before continuing work.
Before you choose
FAQ
Clear scope makes it easier to choose a course and arrive ready to work.
Which level should I choose?
Choose Intro for individual summarizing, planning and drafting tasks. Bring a role-relevant example or use the supplied service-improvement scenario. Choose Intensive to move beyond one-off prompts into proactive agents that run defined work over time. The five days cover curriculum days 3–7. Choose MasterCourse for all ten days and the exclusive Capstone. Test a bounded project from initial request to accepted handover using simulated updates.
What does Factory mean?
A Factory coordinates supervised teams of proactive AI agents around a shared outcome. Each AI agent team has a defined responsibility, a deliverable and an acceptance check for the next handoff. You control permissions, review exceptions and approve release. The MasterCourse-only Capstone tests continuing cycles as well as individual runs.
Are recordings available?
Yes. Students can access recordings of their classes in the members portal.
How long is each class, and how many days do I attend?
This MasterCourse has 10 class days. Full Course lasts 6 hours each day, including lunch and two short breaks. Crash Course lasts 2 hours 30 minutes each day, including one short break. Choose one format for the whole course. Both cover the same topics; Full Course gives you more practice time. Check your selected dates for the exact start and end times in your time zone.
Which time zone will I see?
The class chooser detects your time zone automatically. Use Change time zone to select another location; the dates and hours update together.
Can Intro or Intensive tuition count toward MasterCourse?
The amount actually paid for Intro and/or Intensive can be credited once toward one MasterCourse enrollment within twelve months of each purchase. Intro and Intensive do not credit each other. No credit toward other programs, software or cash. Credit requests are reviewed against purchase records and eligibility; they are not an automatic checkout discount.
Full refund, transfer and credit policyWhat happens if I miss a day?
A missed day has a guaranteed place on the same curriculum day in a later cohort, free of charge, within twelve months of the original cohort's last scheduled day. After this window, new enrollment uses the then-published fee; day credits have no cash value and cannot buy a different curriculum day. An attended day may be repeated without charge within the same twelve-month window, subject to space. One free transfer of the whole seat or its unused days to a later cohort, in either published format, without a reason or a price increase, within twelve months of the original cohort’s last scheduled day. A day already consumed on one format is consumed on both; unused curriculum days are portable across dates and formats.
Full refund, transfer and credit policyWhat should I know before enrolling?
Full refund for a cancelled live program before its first scheduled session begins, including individual and group purchases and an approved MasterMind season. No refund after the purchased program starts, including dissatisfaction or absence, except for a session the provider fails to deliver. Statutory rights are unaffected. Partial attendance consumes the day under the published attendance rules. Read the full terms before choosing your class.
Full refund, transfer and credit policyWhen do I start using Dots?
Intro teaches individual tasks, clear prompts and review. Intensive teaches you to create proactive agents, test their work and hand supported responsibilities to OpenAI Dots. MasterCourse adds a Factory of proactive AI agent teams with shared records and coordinated handoffs.
Can the work continue after I close my phone or computer?
A Dot has its own cloud computer and browser. When the assignment, files and tools are available there, it can work while your phone or computer is off. Always-on means available to continue the responsibility; it may wait for a schedule, input or approval and remains subject to access and usage limits. Work using local files or applications still needs that connected computer online with the ChatGPT app open.
How do I stay in control over time?
Give the Dot and its assignments recognizable names, keep approved context current, and agree what deserves a report. It can surface missing input, access or decisions. To pause or retire work, check active delegates and saved schedules separately; pausing the main conversation does not stop them all. Review access and inputs before resuming.
What material can I use for the cloud exercises?
Use approved project material and limit personal or customer data to what the task needs. Keep client-confidential records and employee information out of unapproved connections. If your role involves hiring or other decisions about people, use fictional examples and keep those decisions with the authorized human reviewer.