> 🌐 中文版本 / Chinese version: [L1_L5_COMPLETE_COURSE_PLAN.md](L1_L5_COMPLETE_COURSE_PLAN.md)

# Complete L1-L5 Course Plan and Classroom Content

Last updated: 2026-05-13

## 1. Course Design Goals

This course is not simply about teaching tools; it guides the enterprise along the L1-L5 maturity progression to build verifiable AI organizational capability step by step.

Every level must define:

- Course objectives.
- Target audience.
- Pre-class requirements.
- Classroom content.
- In-class hands-on practice.
- Post-class assignments.
- Completion criteria.
- Verifiable deliverables.
- The Stage Gate for advancing to the next level.

## 1.5 Pre-Class Story: Show the Future Before the Curriculum

The L1-L5 course should begin by helping clients imagine the capabilities they will have after training. Clients are not attracted to tools first; they are attracted to a believable future work scenario.

Recommended opening story:

> Three months later, employees no longer use disconnected AI tools on their own. Everyone logs in with their own OpenWebUI account, personal workspace, and permissions. Department heads convert expert methods into Skills. n8n connects Gmail, Sheets, Notion, CRM, APIs, and ERP into workflows. Hermes Agent produces daily briefings and follow-up lists. ClawTeam coordinates specialist agents for cross-functional tasks. The purpose of this course is to move the company toward that operating state, one level at a time.

| Level | Future Capability Clients Should Imagine | Evidence Produced in Class |
| --- | --- | --- |
| L1 | Every employee has a controlled AI workspace and knows the data boundaries | OpenWebUI account / group / permission sheet, personal workspace screenshots, Prompt Library |
| L2 | Departmental expert methods become reusable Skills | Skill Library, Skill template, non-author test records |
| L3 | AI performs work across systems instead of only answering questions | n8n Workflow PoC, Execution Log, integration sheet, HITL review |
| L4 | Agents read data, query Wiki memory, call tools, produce briefings, and keep evidence | Hermes Agent task card, Wiki records, briefing, acceptance gates 4A-4E |
| L5 | Multiple agents collaborate on cross-functional work | Agent Team role cards, task dispatch records, integrated report template |

The goal of this story is to make clients understand that they are not buying "a training course"; they are buying a capability path from personal AI use to an enterprise AI Operating Model.

## 1.6 The Two Axes of L1-L5, and a Terminology Note

L1-L5 is not "five tools" — it is **two axes**:

- **Scale axis (L1 → L2 → L3)**: individual → department → cross-department / company-wide. These three levels are "human-in-the-loop, humans use AI, humans supervise AI" — AI is a tool.
- **AI-autonomy axis (L4 → L5)**: AI super-assistant → AI team. These two levels are the digital workforce the enterprise grows in addition to its people; AI is operationally autonomous, but **the governance framework is still built by humans, and humans retain oversight** — the human is upgraded to "governor," not replaced.
- The key boundary is **L3 → L4**: crossing from "humans drive the work" to "AI drives the work." Full story: [`../00_Overview/AI_TRANSFORMATION_STORY_AND_STRUCTURE.md`](../00_Overview/AI_TRANSFORMATION_STORY_AND_STRUCTURE.md) §3.0.

**Terminology (used throughout this course series):**

- **Stage Gate = acceptance gate** — the deliverables of a level must pass acceptance before advancing to the next level; Gates 1-5 below are each level's acceptance gate.
- **HITL = Human-in-the-Loop** — a checkpoint in the workflow where a human confirms; AI does not make high-risk decisions directly. Any "human gate" below means exactly this.

## 2. Course Overview

| Level | Course Name | Tool / Platform | Suggested Hours | Core Outputs | Stage Gate |
| --- | --- | --- | ---: | --- | --- |
| L1 | Controlled AI Access — fundamentals and enterprise usage policy | OpenWebUI | 3-6 hours | AI usage policy, Prompt Library, personal productivity cases | Gate 1 |
| L2 | Knowledge Codification — departmental knowledge capture | Antigravity / Claude Code / Codex | 6-12 hours | Skill Library, 3-5 Skills, Owner and versions | Gate 2 |
| L3 | Workflow Automation — cross-department workflow automation | n8n | 6-18 hours | n8n Workflow PoCs, system integration sheet, Log and review nodes | Gate 3 |
| L4 | Autonomous Agent — task delegation | Hermes Agent | 6-12 hours | Agent task cards, tools list, permission sheet, test records | Gate 4 |
| L5 | Multi-Agent Organization — multi-Agent collaboration | ClawTeam | 6-12 hours | Agent Team role cards, task dispatch, integrated report template | Gate 5 |

## 3. Course Packaging Recommendations

### 3.1 Half-day Experience Course: 3 hours

Suitable for: first-time customer contact, executive alignment sessions, business development.  
Content: L1-L5 overview, 10-question rapid diagnostic, one scenario demonstration.  
Outputs: preliminary maturity assessment, course ratio recommendation, next-step proposal.

### 3.2 One-day Workshop: 6 hours

Suitable for: department managers, HR, seed personnel.  
Content: L1 + L2 + L3 scenario inventory.  
Outputs: draft AI usage policy, Prompt Library, Skill candidate list, Workflow candidate list.

### 3.3 Two-day Onboarding Bootcamp: 12 hours

Suitable for: seed team, IT, process owners.  
Content: L2 Skill construction + L3 n8n PoC + L4 Agent task card.  
Outputs: 3-5 Skills, 1 n8n PoC, 1 Hermes Agent task card.

### 3.4 Consulting Diagnostic Project: 2-4 weeks

Suitable for: leadership, cross-functional teams.  
Content: questionnaire, interviews, As-Is, gap analysis, To-Be, roadmap.  
Outputs: AI transformation diagnostic report, ROI tracking matrix, follow-up SOW.

## 4. L1 Controlled AI Access: OpenWebUI

### 4.1 Course Objectives

Enable employees to safely use AI for daily knowledge work via a controlled AI gateway, and to establish enterprise AI usage boundaries. The focus of the enterprise edition of L1: every employee logs in to OpenWebUI with their own account and owns their own chat area; Admin / IT can manage accounts, roles, groups, models, features, and data permissions.

The complete design of the OpenWebUI enterprise enablement course is documented in `L1_OPENWEBUI_COURSE_PLAN.md`.

### 4.2 Target Audience

- All employees.
- Departmental seed personnel.
- HR / training functions.
- IT and information security contacts.

### 4.3 Pre-class Requirements

| Item | Description |
| --- | --- |
| AI gateway | OpenWebUI or a company-approved AI tool |
| Accounts | Each learner has their own test account; no shared accounts |
| Admin account | IT / HR / AI administrator has Admin privileges |
| Groups / permissions | Pre-plan department groups, model visibility, file upload, Web Search, and sharing policy |
| Sample data | Low-sensitivity documents, meeting minutes, email samples |
| Draft policy | If none exists, create the first version during class |

### 4.4 Classroom Content

| Module | Duration | Content | Method |
| --- | ---: | --- | --- |
| L1-L5 maturity introduction | 30 min | The evolution from personal AI use to Agent Team | Lecture |
| OpenWebUI personal operations | 45 min | Login, personal chat area, model selection, conversation, files, history | Demo |
| OpenWebUI Admin management | 60 min | Account approval, roles, groups, permissions, model and feature governance | Demo + hands-on |
| Prompt fundamentals | 60 min | Role, task, background, constraints, output format | Lecture + practice |
| Daily-work hands-on | 90 min | Email, summaries, meeting minutes, executive reports | Hands-on |
| AI usage policy | 45 min | Can input / must not input / requires human confirmation | Workshop |
| Outcome review | 30 min | Showcase Prompts and outputs | Group feedback |

### 4.5 In-class Hands-on Practice

- Write a customer email draft.
- Each learner creates 2 chat topics using their own account.
- Admin creates or approves test accounts and configures at least 1 department group.
- Convert meeting minutes into action items.
- Distill a long document into an executive summary.
- Build 3 personal frequently-used Prompts.
- Judge 10 data cases for whether they may be input into AI.

### 4.6 Post-class Assignments

- Each learner submits 3 work Prompts.
- Each department submits a list of 5 high-frequency tasks.
- IT / Admin submits the account, group, permission, and model-visibility configuration sheet.
- IT / HR completes the draft AI usage policy.

### 4.7 Completion Criteria

| Criterion | Verification Method |
| --- | --- |
| Learner can use OpenWebUI to complete basic tasks | In-class hands-on outputs |
| Each learner can log in with their own account and create personal chats | Login screenshot, personal chat screenshot |
| Admin can manage accounts, roles, groups, models, and permissions | Admin Panel screenshot, permission sheet |
| Learners understand data input boundaries | Data-case judgment sheet |
| Department has an initial Prompt Library | Prompt list |
| Company has a draft AI usage policy | Policy document |

### 4.8 L1 Deliverables

- Draft AI usage policy.
- First version of the Prompt Library.
- OpenWebUI usage workflow.
- OpenWebUI Admin Runbook.
- Account / group / permission / model-visibility configuration sheet.
- High-frequency task list.
- L2 Skill candidate list.

### 4.9 Gate 1: Eligibility to Enter L2

Pass criteria:

- A controlled gateway or approved tool exists.
- Each learner has their own account and personal chat area.
- Admin can approve accounts and configure roles, groups, models, and feature permissions.
- Seed personnel have completed the L1 hands-on practice.
- A policy on permitted / prohibited data exists.
- At least 10 high-frequency departmental tasks have been catalogued.

## 5. L2 Knowledge Codification: Antigravity / Claude Code / Codex

### 5.1 Course Objectives

Convert personal experience, Prompts, SOPs, templates, and Checklists into reusable departmental Skills. For IT / engineering / digital teams, L2 also includes Antigravity Agentic Developer training so that Agents can assist with planning, development, testing, documentation, and GCP deployment PoCs.

The complete design of the Antigravity engineering training is documented in `L2_ANTIGRAVITY_COURSE_PLAN.md`.

### 5.2 Target Audience

- Department managers.
- Senior staff.
- Seed personnel.
- Document / SOP Owners.
- IT or digital transformation contacts.

### 5.3 Pre-class Requirements

| Item | Description |
| --- | --- |
| High-frequency task list | Produced from L1 |
| SOPs / templates | Documents from customer service, sales, operations, administration, etc. |
| Sample inputs and outputs | Past successful cases |
| Tools | Antigravity / Claude Code / Codex |
| Engineering-class requirements | Antigravity, Chrome, gcloud, a GCP project, and a sample app or document-pipeline topic |

### 5.4 Standard Skill Format

| Field | Description |
| --- | --- |
| Skill name | A clear description of purpose |
| Usage scenario | When to use |
| Input | What data is required |
| Process | Steps the AI should follow |
| Output | Output format |
| Constraints | What must not be done |
| Quality Check | Acceptance criteria |
| Owner | Maintenance owner |

### 5.5 Classroom Content

| Module | Duration | Content | Method |
| --- | ---: | --- | --- |
| Skill AI concepts | 45 min | How personal know-how becomes departmental capability | Lecture |
| Skill decomposition methodology | 60 min | Input / Process / Output / Constraints | Workshop |
| Antigravity applications | 60 min | Task planning, document organization, formalization | Demo + hands-on |
| Antigravity engineering hands-on | 120 min | Agent Manager, Browser, App prototype, unit test, README | Demo + hands-on |
| Antigravity GCP hands-on | 180 min | GCS, Pub/Sub, Cloud Run, Gemini, BigQuery pipeline PoC | Engineering-class elective |
| Claude Code applications | 60 min | Documentation, specifications, code, and knowledge-work assistance | Demo + hands-on |
| Codex applications | 60 min | Code, data processing, document automation | Demo + hands-on |
| Skill Library | 45 min | Versioning, Owner, naming, quality checks | Lecture |
| Skill hands-on | 120 min | Each group builds 1-2 Skills | Hands-on |
| L2-to-L3 Bridge | 120 min | Trigger, input / output schema, n8n node map, human Gate, Log, error handling | Workshop |
| Outcome review | 60 min | Non-authors test the Skills | Peer Review |

### 5.6 In-class Hands-on Practice

Recommended choices by industry:

- R&D and manufacturing: 8D / 5Why Skill, ERP anomalous order Skill, SOP summary Skill.
- Hospitals: patient service FAQ Skill, registration workflow Skill, meeting minutes Skill.
- Marketing and services: copy generation Skill, proposal generation Skill, competitive analysis Skill.
- B2B sales: customer research Skill, visit summary Skill, CRM update Skill.
- IT / engineering: Antigravity app prototype Skill, unit test Skill, GCP serverless pipeline Skill.

### 5.7 Post-class Assignments

- Each department submits 3-5 Skills.
- Each Skill has an Owner assigned.
- Each Skill completes at least 2 test runs.
- Build the first version of the Skill Library.
- Convert at least 1 Skill into an L3 Workflow Blueprint.
- Complete the trigger, sample payload, output schema, human gate, log, and error handling.

### 5.8 Completion Criteria

| Criterion | Verification Method |
| --- | --- |
| At least 3-5 Skills produced | Skill Library |
| Skills include complete IPOC | Skill template |
| Non-authors can use them | Test records |
| Skills have Owner and version | Owner sheet and version log |
| Skills can flow into L3 | Workflow Blueprint, sample payload, n8n node map |

### 5.9 L2 Deliverables

- Skill Library.
- Standard Skill template.
- 3-5 usable Skills.
- Skill Owner and version sheet.
- Antigravity app prototype / test / docs artifacts.
- GCP Pipeline PoC and deployment verification records.
- L3 Workflow Blueprint.
- Trigger / Input / Output schema.
- n8n node map, human gate, log, error handling spec.
- L3 Workflow candidate list.

### 5.10 Gate 2: Eligibility to Enter L3

Pass criteria:

- At least 3 Skills are reusable.
- 1-2 process-ready scenarios have been selected.
- Required systems and data sources are inventoried.
- Trigger, input/output schema, and sample payload are defined.
- The n8n node map, human gate, log, and error-handling draft are complete.
- Human review requirements are defined.

## 6. L3 Workflow Automation: n8n

### 6.1 Course Objectives

Use n8n to integrate Gmail, Sheets, Notion, CRM, APIs, ERP, and other systems so that AI enters the workflow and completes verifiable PoCs.

The deep-dive TigerAI n8n course is documented in `L3_N8N_TIGERAI_COURSE_PLAN.md`. L3 takes over from the L2 Workflow Blueprint and adds Triggers, Credentials, Data Tables, Sub-workflows, Execution Logs, GitHub backup, human Gates, and the L4 Workflow Contract.

### 6.2 Target Audience

- IT.
- Process Owners.
- Departmental seed personnel.
- Digital transformation / automation personnel.

### 6.3 Pre-class Requirements

| Item | Description |
| --- | --- |
| L2 Skills | At least 1 Skill callable by a Workflow |
| Systems list | Gmail, Sheets, Notion, CRM, APIs, ERP |
| Test accounts | Avoid operating directly on production data |
| Test data | De-identified or low-sensitivity data |
| Permissions | Credential, API Key, Webhook permissions |

### 6.4 Classroom Content

| Module | Duration | Content | Method |
| --- | ---: | --- | --- |
| n8n fundamentals | 60 min | Trigger, Node, Credential, Execution | Demo |
| Data flow design | 45 min | Input, Transform, AI, Output | Lecture |
| Taking over the L2 Blueprint | 45 min | trigger, I/O schema, sample payload, node map | Workshop |
| Gmail / Email | 60 min | Receive, classify, summarize, draft replies | Hands-on |
| Webhook / LINE / Meta | 75 min | LINE Bot, Facebook Webhook, YouTube comments, or external-platform events | Hands-on |
| Sheets | 45 min | Logging records, survey scoring, KPI | Hands-on |
| Data Tables | 60 min | State management, customer-service FAQ, interaction logs, allow/deny lists | Hands-on |
| Notion | 45 min | Task creation, knowledge base, meeting minutes | Hands-on |
| CRM / API | 75 min | Customer lookup, Webhook, internal APIs | Demo + hands-on |
| ERP planning | 45 min | Orders, inventory, shipping, procurement, finance data | Architecture design |
| AI Node / RAG | 60 min | Classification, summarization, data lookup | Demo |
| Gemini / multimodal | 60 min | Image, voice, video, document analysis | Demo |
| Sub-workflow | 60 min | Modularization, reuse, process templates | Hands-on |
| Human review | 45 min | Human-in-the-loop, Gate, notifications | Hands-on |
| Log / Error | 45 min | Error notifications, retries, fallback | Hands-on |
| GitHub backup | 45 min | Workflow / Credential backup and version governance | Hands-on |
| PoC hands-on | 180 min | Each group completes 1 Workflow | Hands-on |

### 6.5 In-class Hands-on Practice

Standard PoC:

> Email / form intake → AI classification → data lookup → summary generation → human review → write to Sheets / Notion → notify Owner

Industry variations:

- Manufacturing: customer-complaint emails + CRM + ERP + QMS.
- Hospitals: customer-service questions + FAQ knowledge base + human review.
- Marketing and services: customer requirement form + CRM + proposal draft.
- Finance: expense data + variance analysis + executive summary.
- Customer service: Facebook / LINE Webhook + Data Tables + AI reply draft.
- HR: Gmail resume intake + Gemini screening + LINE / Email notification.
- Marketing: product image / topic input + copy / image / video generation + human review + multi-platform publishing.

### 6.6 Post-class Assignments

- Complete the Workflow diagram.
- Export the n8n Workflow JSON.
- Complete test data and test records.
- Add permissions, Log, human review, and error handling.
- Add Data Tables / Sheets / DB Schema.
- Add the Sub-workflow Library.
- Add the GitHub backup record.
- Add the Workflow Contract callable by the L4 Hermes Agent.

### 6.7 Completion Criteria

| Criterion | Verification Method |
| --- | --- |
| Workflow is executable | n8n Execution Log |
| At least 2-3 systems integrated | System integration sheet |
| Has a human review node | Review records |
| Has error handling | Failure test record |
| Has backup and version governance | GitHub backup commit |
| Bridges to L4 | Workflow Contract |
| Produces a clear business result | Test outputs |

### 6.8 L3 Deliverables

- n8n Workflow PoC.
- Workflow JSON.
- System integration sheet.
- Credential / permission sheet.
- Data Tables / Sheets / DB Schema.
- Sub-workflow Library.
- Execution Log.
- Human review records.
- GitHub Backup / version management SOP.
- L4 Workflow Contract.
- L4 Agent task candidate list.

### 6.9 Gate 3: Eligibility to Enter L4

Pass criteria:

- At least 1 Workflow runs stably.
- Log, human review, and error handling are in place.
- Backup, version governance, and a permission sheet exist.
- Tools or Workflows callable by an Agent are defined.
- The L4 Workflow Contract is complete.
- Agent permission boundaries are defined.

## 7. L4 Autonomous Agent: Hermes Agent

### 7.1 Course Objectives

Design a controlled, verifiable, and operable Hermes Agent that uses a Wiki as long-term memory, invokes L2 Skills and L3 Workflows, completes data ingestion, analysis, query, update, reminders, and reporting, and preserves human Gates.

The complete L4 course design is documented in `L4_HERMES_AGENT_COURSE_PLAN.md`. This section serves as the L1-L5 syllabus summary.

### 7.2 Target Audience

- Department managers.
- Process Owners.
- IT.
- Seed personnel.
- Knowledge workers.
- Executive assistants / PMs.

### 7.3 Pre-class Requirements

| Item | Description |
| --- | --- |
| L2 Skills | Skills the Agent can call |
| L3 Workflows | Workflows the Agent can start |
| Task scenarios | Weekly reports, customer service, operations, sales, administration, research, document management |
| Knowledge foundation | `purpose.md`, `SCHEMA.md`, `INBOX.md`, `queue.md`, `watchlist.md`, `tasks.md`, `wiki/` |
| Technical foundation | Hermes Agent, the five core skills, tools, SQLite / FTS index, scheduling mechanism |
| Permission sheet | What the Agent can and cannot do |
| Human Gate | When human confirmation is required |

### 7.4 Agent Task Card Format

| Field | Description |
| --- | --- |
| Agent name | Role name |
| Task goal | What is to be accomplished |
| Input | Data required for the task |
| Tools | Callable Skills / Workflows / APIs |
| Process | Task decomposition steps |
| Output | Reporting format |
| Constraints | Prohibited actions |
| Escalation | Conditions for escalating to a human |
| Evidence | Execution records, source citations, Log, review records |

### 7.5 Hermes Agent IPOE

| Category | Definition |
| --- | --- |
| Input | Customer tasks, departmental documents, PDFs, SOPs, FAQs, research data, API responses, n8n Workflow results, L2 Skills, `purpose.md`, `SCHEMA.md`, `watchlist.md`, `queue.md`, permission sheet |
| Process | orient-first, bootstrap, ingest, source analysis, keyword extraction, index upsert, query, update, lint, autonomous discovery, briefing, graph synthesis, human review |
| Output | Wiki pages, source analysis, concept/entity/claim pages, query answers, daily briefings, pending watchlist, task tracking list, Agent execution records, improvement suggestions |
| Evidence | `hermes doctor` results, installed-skills list, configuration files, Wiki files, Logs, SQLite queries, queue/watchlist/tasks, briefing email, n8n execution records, human review records |

### 7.6 Classroom Content

| Module | Duration | Content | Method |
| --- | ---: | --- | --- |
| L4 positioning | 45 min | Agent vs Chatbot vs Skill vs Workflow; the boundary between L4 and L5 | Lecture |
| Hermes architecture | 60 min | Wiki, SQLite, skills, tools, runtime schema, policy, scheduling | Demo |
| Task decomposition | 60 min | Goal, steps, tools, output, risk, human Gate | Workshop |
| Knowledge Base | 60 min | `purpose.md`, `SCHEMA.md`, INBOX, queue, watchlist, tasks | Hands-on |
| Ingest loop | 90 min | Document ingestion, source analysis, keyword, index, log | Hands-on |
| Query / Update | 75 min | Cited answers, write-back, diff, human review | Hands-on |
| Tool Calling | 60 min | Calling Skills, n8n, APIs, DB | Demo |
| Briefing / Discovery | 75 min | morning briefing, 2h ping, watchlist, P2 queue | Demo |
| Permissions and governance | 60 min | Least privilege, data classification, human Gate, Log, fallback | Lecture |
| Agent testing | 120 min | Design and test one Hermes Agent loop | Hands-on |

### 7.7 In-class Hands-on Practice

Optional Agents:

- Customer service case organization Agent.
- Operations weekly report Agent.
- Sales visit preparation Agent.
- Patient service customer-service assist Agent.
- Marketing campaign analysis Agent.
- R&D literature / technical document organization Agent.

Each group must complete:

- Hermes Agent task card.
- L4 IPOE table.
- Draft `purpose.md` and `SCHEMA.md`.
- One document ingest test.
- Three traceable queries.
- One briefing.
- Gate 4A-4E acceptance sheet.

### 7.8 Post-class Assignments

- Complete the Agent task card.
- Complete the Agent permission sheet.
- Complete Agent test records.
- Complete human-handoff rules.
- Complete Wiki / Log / Index / Briefing evidence.
- Select candidate tasks for an L5 Agent Team.

### 7.9 Completion Criteria

| Criterion | Verification Method |
| --- | --- |
| Agent task is well-defined | Agent task card |
| Agent has a knowledge foundation | `purpose.md`, `SCHEMA.md`, Wiki structure |
| Agent can perform ingest / query / update | source page, query record, update diff |
| Agent can call Skills / Workflows | Tool invocation logs, n8n execution log |
| Agent permission boundaries are clear | Permission sheet |
| High-risk tasks can be handed off to humans | Human-handoff records |
| Agent outputs are traceable | Execution Logs, SQLite queries, cited sources |
| Agent can operate sustainably | briefing, watchlist, queue, schedule |

### 7.10 L4 Deliverables

- Hermes Agent task card.
- L4 IPOE table.
- Hermes Agent architecture diagram.
- Initial Wiki: `purpose.md`, `SCHEMA.md`, INBOX, queue, watchlist, tasks.
- Agent available-tools list.
- Agent permission sheet.
- Ingest / Query / Update test records.
- Briefing template.
- Stage Gate 4A-4E records.
- Human-handoff rules.
- Operations Runbook.
- L5 Agent Team candidate scenarios.

### 7.11 Gate 4: Eligibility to Enter L5

Pass criteria:

- At least 1 Hermes Agent passes Gate 4A-4E.
- The Agent can call at least 1 Skill and 1 Workflow.
- The Agent's input, process, output, and evidence are all traceable.
- Wiki memory, Logs, indexes, briefings, and human Gates are in place.
- Cross-functional tasks and Agent role division are defined.

## 8. L5 Multi-Agent Organization: ClawTeam

### 8.1 Course Objectives

Design a multi-Agent collaboration pattern in which different role Agents jointly complete cross-functional, enterprise-grade tasks.

### 8.2 Target Audience

- Leadership.
- Cross-functional managers.
- PM / project management.
- IT / AI Center.
- Seed teams with an L4 foundation.

### 8.3 Pre-class Requirements

| Item | Description |
| --- | --- |
| L4 Agent | At least 1 controlled Agent |
| Cross-functional task | New product, quality improvement, customer engagement, operational analysis |
| Agent roles | Market, product, marketing, customer service, finance, integrator |
| Data sources | CRM, ERP, Sheets, Notion, APIs |
| Human Gate | Review by leadership or project Owner |

### 8.4 Standard Agent Team Format

| Field | Description |
| --- | --- |
| Team task | The cross-functional task to be accomplished |
| Agent roles | What each Agent is responsible for |
| Input | Data each Agent requires |
| Process | Task dispatch, collaboration, integration |
| Output | Each Agent's output and the final output |
| Reviewer | Review role |
| Human Gate | Human decision point |
| KPI | Benefit measurement |

### 8.5 Classroom Content

| Module | Duration | Content | Method |
| --- | ---: | --- | --- |
| Multi-Agent concepts | 45 min | Difference between an Agent Team and a single Agent | Lecture |
| Role design | 60 min | Market, product, marketing, customer service, finance, integrator | Workshop |
| Task dispatch | 60 min | Task partitioning, dependencies, inputs and outputs | Workshop |
| Output integration | 60 min | Integrated report, conflict handling, decision summary | Hands-on |
| Reviewer / Critic | 45 min | Quality checks and risk checks | Lecture |
| Implementation & Change | 45 min | Permissions, Log, Stage Gate, KPI | Lecture |
| Team drill | 150 min | Complete 1 Agent Team case | Hands-on |

### 8.6 In-class Hands-on Practice

Optional Agent Teams:

- New product launch Agent Team.
- Quality improvement Agent Team.
- Customer engagement Agent Team.
- Patient service improvement Agent Team.
- Annual operations planning Agent Team.

### 8.7 Post-class Assignments

- Complete the Agent Team role cards.
- Complete the task dispatch sheet.
- Complete the final output template.
- Complete the Reviewer / Human Gate design.
- Complete ROI metrics.

### 8.8 Completion Criteria

| Criterion | Verification Method |
| --- | --- |
| Agent roles are clear | Role cards |
| Tasks can be dispatched | Task dispatch sheet |
| Each Agent's Input / Output is clear | IPOE table |
| Integration and review mechanisms exist | Integrated report and Reviewer design |
| ROI metrics exist | KPI sheet |

### 8.9 L5 Deliverables

- ClawTeam role cards.
- Multi-Agent task dispatch sheet.
- Agent Team IPOE table.
- Integrated report template.
- Reviewer / Human Gate design.
- ROI tracking sheet.

### 8.10 Gate 5: L5 Completion Criteria

Pass criteria:

- At least 1 Agent Team scenario design is completed.
- Each Agent has a role, Input, Output, and constraints.
- An integrating Agent or integrating workflow exists.
- Reviewer / Human Gate exists.
- ROI and governance design exist.

## 9. L1-L5 Course Completion Master Control Sheet

| Level | Course Completion Evidence | Verifiable Deliverables | Eligible to Advance? |
| --- | --- | --- | --- |
| L1 | In-class practice, Prompts, usage policy | AI usage policy, Prompt Library, L2 candidate list | Gate 1 passed |
| L2 | Skill tests, Owner, version | Skill Library, 3-5 Skills, L3 candidate workflows | Gate 2 passed |
| L3 | Workflow execution, Log, review | n8n Workflow JSON, system integration sheet, Execution Log | Gate 3 passed |
| L4 | Agent tests, tool calls, permissions | Hermes Agent task card, permission sheet, test records | Gate 4 passed |
| L5 | Agent Team drill, integrated report | ClawTeam role cards, task dispatch sheet, ROI sheet | Gate 5 passed |

## 10. Instructor Delivery Checklist

| Item | Description | Completed? |
| --- | --- | --- |
| Pre-class questionnaire completed | 10 or 25 questions | `[ ]` |
| Company profile survey completed | Industry, deployment, systems, data sensitivity | `[ ]` |
| Course ratio confirmed | L1-L5 ratio | `[ ]` |
| Course cases confirmed | Mapped to industry scenarios | `[ ]` |
| Hands-on data prepared | Low-sensitivity or de-identified data | `[ ]` |
| Learner grouping completed | Department / role / technical capability | `[ ]` |
| Deliverables collected | Prompts, Skills, Workflows, Agents, Roadmap | `[ ]` |
| Stage Gate assessment completed | Gate 1-5 | `[ ]` |
| Post-class consulting report input completed | Feedable into the diagnostic report | `[ ]` |
