The M-CaReM-AI Method: Defining Work for AI
Professional · IT · Certificate available
202 lessons 2.9h runtime 9 units 271 links between lessons Test yourself · 9 quizzes, a mid exam, and a final
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Begin with Unit 1: Why the Method Exists. It sets the foundation for everything that follows.
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Unit 1: Why the Method Exists 22 lessons, 1 lecture part
Lecture: Watch · 29:19
- 001 Fifty Stories Before Lunch
- 002 Three Problems With Fast Text
- 003 The Familiar Criteria
- 004 Material Problems, Not Wording Problems
- 005 Vague Domains, Invented Worlds
- 006 Material Cause, in One Line
- 007 Features Are Things You Do to Things
- 008 The Constraint AI Needs
- 009 The Five Phases, Named
- 010 When It Matters
- 011 The One Reflex
- 012 Feature-First Thinking
- 013 Hidden Domain Fracture
- 014 Legacy: Gold Mine and Scar Tissue
- 015 AI Amplifies the Material Problem
- 016 Reading a Domain for Its Things worked example
- 017 Spotting the Four Anti-Patterns worked example
- 018 Frameworks Govern Motion, Not Meaning worked example
- 019 Running the Six-Question Diagnostic worked example
- 020 Turning Each "No" Into a Backlog Line worked example
- 021 A Library, Diagnosed review
- 022 One Requirement, Two Readings review
Unit 2: The Four Causes, in Plain Terms 20 lessons, 1 lecture part
Lecture: Watch · 28:30
- 026 Four Answers About One Loan
- 027 Cause, in the Older Sense
- 028 Aristotle's Four, in His Words
- 029 Final Cause
- 030 Efficient Cause
- 031 Formal Cause
- 032 Material Cause
- 033 Several Causes at Once
- 034 A Chair and a Contract
- 035 The Cause Nobody Talks About
- 036 Not Just Data Modeling
- 037 A Shared Contract
- 038 Statistical and Generic
- 039 The Loan System, Cause by Cause worked example
- 040 Teaching the Tool Your Definition worked example
- 041 The Incident Report's Four Causes worked example
- 042 The Four-Causes Exercise worked example
- 043 Four Questions for Any Meeting worked example
- 044 A Library Loan's Four Causes review
- 045 Where the Group Hesitated review
Unit 3: The Five Phases, and AI as a Copilot 20 lessons, 1 lecture part
Lecture: Watch · 28:24
- 051 Lenses, Not Gates
- 052 Phase One: What Is It Made Of?
- 053 Phase Two: What Are We Doing to It?
- 054 Phase Three: One Place per Thing
- 055 Phase Four: Does It Match Reality?
- 056 Phase Five: What Else Must Change?
- 057 AI as an Efficient Cause
- 058 Three Copilot Principles
- 059 Three Failure Modes
- 060 Controlled Documents
- 061 Recording AI's Part
- 062 Not a Replacement
- 063 The Phases Across a Project worked example
- 064 What to Have Before What worked example
- 065 AI by Phase worked example
- 066 Stories, Specifications and Cards Together worked example
- 067 Other Methods, as the Method Sees Them worked example
- 068 The Five-Line Picture worked example
- 069 The Library Through Five Questions review
- 070 One Change, Five Lenses review
Unit 4: Phase One: Mapping Your World 24 lessons, 1 lecture part
Lecture: Watch · 32:09
- 076 The Auditor's Question
- 077 What Phase One Is For
- 078 What Phase One Is Not
- 079 Sources to Mine
- 080 Who to Involve
- 081 Listening for Nouns
- 082 The Object Inventory
- 083 Core and Supporting Things
- 084 Zones
- 085 How Deep Is Deep Enough
- 086 Five Mapping Pitfalls
- 087 Letting AI Define Your World
- 088 A Determination Is a Thing
- 089 Four Interview Questions worked example
- 090 Mining Documents With AI worked example
- 091 Writing an Inventory Row worked example
- 092 Drawing the Map worked example
- 093 The Hospital Map worked example
- 094 Running the Mapping Workshop worked example
- 095 Phase One With AI, Five Steps worked example
- 096 The Benefits Agency, Mapped worked example
- 097 The Library Inventory review
- 098 The Library Map review
- 099 The Audit Thing We Missed review
Unit 5: Phase Two: Writing Material Requirement Cards (part one of two) 25 lessons, 2 lecture parts
- 101 All Relevant Information
- 102 From Sentences to Cards
- 103 Atoms and a Molecule
- 104 Three Required Sections
- 105 Header and Business Statement
- 106 Constraints and Rules
- 107 The Optional Sections
- 108 One Behavior per Card
- 109 One Primary Thing per Card
- 110 Create, Read, Update, Delete, and Three More
- 111 Where AI Goes Wrong With Cards
- 112 Cards in Any Delivery Method
- 113 Four Card Pitfalls
- 114 Cards Are the Hinge
- 115 A Worked Card: Focus and Properties worked example
- 116 A Worked Card: Rules and Example worked example
- 117 Thinking in Change-Type Slices worked example
- 118 A First Set for the Determination worked example
- 119 Drafting a Card With AI worked example
- 120 Six Checks of a Good Card worked example
- 121 Card Patterns: Create and Transition worked example
- 122 Card Patterns: Generate, Sync, Schedule worked example
- 123 The Library's Create Loan Card review
- 124 One Muddy Requirement, Two Cards review
- 125 A Card Checked Six Ways review
Unit 6: Phase Three: Building Object Packs (part one of two) 25 lessons, 2 lecture parts
- 126 Four Answers to One Question
- 127 One Place per Thing
- 128 The Right Size for a Prompt
- 129 A Short Manual, Not a Treatise
- 130 The Identity Sections
- 131 The Behavior Sections
- 132 The Use and Governance Sections
- 133 Bronze
- 134 Silver
- 135 Gold
- 136 A Seed and a Floor
- 137 The Object Steward
- 138 Versions and Change Logs
- 139 Five Pack Pitfalls
- 140 Building a Pack: Header to Properties worked example
- 141 Building a Pack: Lifecycle worked example
- 142 Building a Pack: Index, Links, Usage worked example
- 143 Building a Pack: Obligations, Questions, Examples worked example
- 144 The Determination Pack in Outline worked example
- 145 AI Drafts, You Edit worked example
- 146 Keeping a Pack in Sync worked example
- 147 Patterns for Things worked example
- 148 A Silver Pack for a Library Loan review
- 149 Does Anything in the Library Earn Gold? review
- 150 A Pack Change, Logged review
Unit 7: Phase Four: Checking Against Reality 22 lessons, 1 lecture part
Lecture: Watch · 31:58
- 151 We Never Use That State
- 152 What Validation Is
- 153 What Validation Is Not
- 154 Three Modes of Validation
- 155 Who Is in the Room
- 156 Session Goals
- 157 Preparing the One-Pager
- 158 Silence Is Dangerous
- 159 AI as Scribe, Not Judge
- 160 Validating Across Distance
- 161 Five Validation Pitfalls
- 162 Harm Level and Severity
- 163 The Session: Framing and Definition worked example
- 164 The Session: Fields worked example
- 165 The Session: Lifecycle and Cards worked example
- 166 Scenario Walkthroughs worked example
- 167 Desk Review worked example
- 168 Four Ways to Surface Disagreement worked example
- 169 The Validation Checklist worked example
- 170 Reviewing the Library Loan Pack review
- 171 Three Corrections and a Parked Disagreement review
- 172 From Notes to Pack Changes review
Unit 8: Phase Five: Tracing What Depends on What (part one of two) 24 lessons, 2 lecture parts
- 176 One Rule, Eleven Surprises
- 177 What Hangs Off a Thing
- 178 Document-Centric Traceability
- 179 Proving Versus Deciding
- 180 One Matrix per High-Risk Thing
- 181 The Rows of a Matrix
- 182 One Thing, Several Perspectives
- 183 AI as Impact Scout
- 184 Fabricated Links
- 185 Matrices in Any Delivery Method
- 186 Five Traceability Pitfalls
- 187 When Nothing Is Triggered
- 188 Building a Matrix: Pack and Rows worked example
- 189 Building a Matrix: Policies and Cards worked example
- 190 Building a Matrix: Data to AI worked example
- 191 The Determination Matrix worked example
- 192 Scenario: a Policy Change worked example
- 193 Scenario: a New Field worked example
- 194 Scenario: AI in a High-Risk Area worked example
- 195 When to Create a Matrix worked example
- 196 The Change-Impact Walk worked example
- 197 A Matrix for the Library Loan review
- 198 Loan Periods by Item Type, Traced review
- 199 The Change Plan review
Unit 9: The Method End to End 20 lessons, 1 lecture part
Lecture: Watch · 33:12
- 201 The Case Study's Hospital
- 202 The Team and the Goal
- 203 Names Shape the Work
- 204 Writing the Pack Reveals Cards
- 205 Usually True Somewhere
- 206 Lessons: Language, Packs, Cards
- 207 Lessons: Matrix, AI, Gold
- 208 The Method's Prompts, by Phase
- 209 The Case: Mapping worked example
- 210 The Case: Cards worked example
- 211 The Case: The Pack worked example
- 212 The Case: Validation worked example
- 213 The Case: Tracing a New Rule worked example
- 214 Translating the Case to Your World worked example
- 215 Five Questions at Every Step worked example
- 216 Capstone One: Your Inventory and Map review
- 217 Capstone Two: Three Cards review
- 218 Capstone Three: Your Pack review
- 219 Capstone Four: Review and Matrix review
- 220 The Whole Method review
Who this subject is for
- Business analysts and product owners
- Project and product managers
- Architects, testers and data staff
- Anyone who defines work for systems or AI tools
Why The M-CaReM-AI Method: Defining Work for AI matters
Most expensive requirements failures are disagreements about what a system is made of. This course teaches a method for naming those things, describing every change to them, and keeping AI inside the definitions people agree. It applies to:
- Writing requirements
- Domain modeling
- Validating with stakeholders
- Change impact analysis
- Grounding AI tools in your definitions
Time to complete
- of lessons (202, measured)
- 2.9 h
- of lectures (12)
- 5.0 h
- learning hours on the certificate, with quizzes and the final
- 11.5 h
Times are measured from the recordings and the exam time limits. Go at your own pace; nothing expires.
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