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Work Charts

What capabilities will humans need to offer a valuable point of difference when AI dominates intellectual pursuits?

We need an open matrix of the transformation of work as Phygital Beings take control of the underlying feedback loops that society operates on.

Core JTBD Matrix

What capabilities do you need per JTBD Workflow? What outcomes define success? How do you validate that outcomes are aligned with good intentions?

DomainProcessWorkflow / ActivityHuman Role (today)AI Role (today)AI %Protocol - AlgorithmArtifacts
StrategyVision & PositioningDefine company vision & narrativeFounders set direction, story, constraintsGenerate options, synthesize market insights25%strategy-principles
StrategyStrategic PlanningAnnual/quarterly planningSet priorities, trade-offs, resourcingScenario modeling, forecasting, risk simulation40%planning-protocols
StrategyPricingDesign & update pricing modelsChoose value metric, guardrails, exceptionsElasticity modeling, competitor & cohort analysis60%business/growth/pricing
StrategyOKR / KPI DesignDefine metrics & targetsDecide what matters, acceptable riskSuggest metric trees, simulate targets50%performance-metrics-standards
MarketingICP & SegmentationDefine ICP, personas, segmentsValidate insights, pick focusAggregate data, cluster, draft personas50%marketing-protocols
MarketingContent StrategyPlan content calendar & pillarsChoose themes, angles, quality barPropose calendars, topic clustering60%marketing-content-strategy
MarketingContent ProductionLong-form articles & pagesSet brief, edit, final voice & claimsDrafts, rewrites, SEO suggestions80%marketing-article-copywriting
MarketingCampaign ManagementDesign & launch campaignsApprove offers, creative directionVariant generation, audience selection65%marketing-campaign-workflow
MarketingEmail & NurtureBuild nurture sequencesDefine journey logic, complianceDraft emails, subject lines, timing suggestions75%marketing-lifecycle-email
MarketingAnalytics & ReportingReview performance, insightsDecide narrative, next betsAuto-dashboards, anomaly detection70%marketing-performance
SalesLead QualificationScore & prioritize inbound leadsFinal judgment on fit, edge casesScoring, enrichment, routing80%sales-lead-qualification
SalesOutbound ProspectingResearch and list buildingApprove target profiles, sequencesProspect list gen, personalization suggestions85%sales-prospecting-workflow
SalesDiscovery CallsRun live discoveryBuild trust, read nuance, adapt in real timeLive assist, note-taking, suggested questions30%sales-discovery-playbook
SalesProposal & QuoteDraft proposals and offersStructure deal, terms, negotiation strategyDraft docs, pricing scenarios, comparisons70%sales-proposal-workflow
SalesPipeline ManagementUpdate CRM & forecastsOverride forecasts, deal risk judgmentAuto-updates, forecast models65%sales-pipeline-operations
Customer JourneyOnboardingNew customer onboardingRelationship, expectation setting, exceptionsChecklists, comms drafts, environment setup60%customer-onboarding-workflow
Customer JourneySupport (Tier 1)Handle common support ticketsHandle escalations, policy callsTriage, auto-replies, knowledge surfacing85%support-tier1-automation
Customer JourneySuccess / QBRsQBRs & health reviewsStrategy, upsell, relationshipData prep, decks, risk signals50%customer-success-playbook
Customer JourneyFeedback CollectionSurveys, NPS, interviewsQuestion design, interpretationSurvey flows, clustering, sentiment analysis70%customer-feedback-process
ProductProduct DiscoveryProblem discovery & validationRun interviews, sense-making, visionUser research synthesis, pattern detection50%product-discovery-workflow
ProductRoadmappingPrioritize roadmapTrade-offs, bet sizingImpact/effort modeling, dependency mapping45%product-roadmap-process
ProductSpec WritingWrite PRDs / specsDecide scope, constraints, acceptanceDraft specs from patterns & conversations70%product-specification-workflow
ProductUX & Interaction DesignDesign flows and interfacesTaste, usability judgmentVariant generation, heuristic checks60%design-system-workflow
ProductAnalytics & ExperimentationDefine & run experimentsHypotheses, ethical constraintsExperiment design suggestions, analysis65%product-experimentation
EngineeringArchitecture & DesignSystem architecture decisionsFirst principles, risk, trade-offsGenerate options, model performance40%platform-architecture-standards
EngineeringImplementationWrite & review application codeComplex logic, integration, final reviewCode generation, tests, refactors75%engineering-development-workflow
EngineeringDevOps & InfraCI/CD, infra changesGuardrails, incident response decisionsIaC suggestions, config generation, monitoring65%platform-operations
EngineeringQA & TestingDefine test strategy, edge casesRisk-based test designTest gen, execution, regression detection80%quality-assurance-process
EngineeringIncident ManagementTriage & resolve incidentsCommand, communication, trade-offsDetection, runbooks, suggested actions50%incident-response-playbook
OperationsProcess DesignDesign & document workflowsDecide owners, SLAs, exceptionsDraft workflows, map tools & data60%process-optimisation
OperationsVendor ManagementSelect & manage vendorsRelationship, negotiation, riskShortlisting, scorecards, monitoring50%vendor-management-workflow
OperationsInventory / FulfillmentPlan and track inventory & fulfillmentEdge-case decisions, supplier relationshipsForecasting, routing, re-order suggestions70%supply-operations
OperationsFacilities / IT SupportInternal IT / office opsEscalations, exceptionsSelf-service flows, triage, automation75%it-operations
HRWorkforce PlanningHeadcount & role planningCulture fit, strategic betsScenario modeling, comp benchmarks50%human-resources-planning
HRTalent AcquisitionSourcing & screeningFinal judgment, interviewsScreening, outreach, CV ranking70%human-resources-recruitment
HROnboarding (People)New hire onboardingRelationship, cultural imprintSchedules, docs, checklists65%human-resources-onboarding
HRPerformance ManagementReviews, feedback, progressionJudgment, difficult conversationsDraft reviews, 360 synthesis, pattern spotting55%performance-management-process
HRLearning & DevelopmentL&D programsStrategy, curation, coachingPersonalized learning paths, content curation70%learning-development-workflow
LegalContract DraftingDraft & review standard contractsEdge cases, negotiation, risk appetiteTemplate gen, clause suggestions, comparisons75%legal-contracting-process
LegalCompliance MonitoringMonitor regulatory complianceInterpret gray zones, escalationRule mapping, monitoring, alerting70%legal-compliance-operations
LegalPolicy ManagementDraft internal policiesValue & culture alignmentDrafting from standards & laws65%legal-policy-workflow
FinanceBookkeepingRecord transactionsExceptions, reconciliationsAuto-categorization, reconciliation suggestions85%accounting-process
FinanceManagement ReportingMonthly/quarterly reportingNarrative, decision recommendationsClose automation, dashboards, variance analysis70%finance-reporting-workflow
FinanceBudgeting & ForecastingBudgets and cashflow forecastsStrategic constraints, risk toleranceForecast models, scenario generation65%budgeting-forecasting-process
FinanceBilling & CollectionsInvoicing, collectionsEdge cases, relationship-sensitive collectionsInvoice gen, reminders, payment plans80%billing-collections-workflow
GovernanceRisk ManagementIdentify & manage key risksRisk appetite, trade-offsRisk registers, scenario analysis50%risk-management-standards
GovernanceBoard / Investor UpdatesBoard packs, investor commsNarrative, commitmentsDraft decks, metrics, scenario visualizations60%investor-relations-workflow

HiTL Capabilities

What does the "Human Role" column actually demand? Eight patterns of human work survive AI. Each maps to specific capabilities from the scorecard.

HiTL PatternWhere It AppearsCapabilities RequiredT-BarAI Can't Because
Set directionStrategy, Product DiscoveryPlanning, Storytelling, First Principles, TasteV+HDirection requires conviction, not computation
Make trade-offsStrategy, Engineering Architecture, GovernanceSystems Thinking, Critical Thinking, Planning, InvestingVTrade-offs require values, not optimization
Build trustSales Discovery, Customer Success, OnboardingEmpathy, Listening, Selling, PresentingHTrust transfers between consciousness, not interfaces
Judge qualityMarketing, Product Design, QATaste, Critical Thinking, Pattern RecognitionV"Good enough" vs "good" requires lived context
Handle exceptionsLegal, Finance, Support EscalationCritical Thinking, First Principles, FocusVEdge cases require judgment outside training data
Create meaningContent, Campaign, UX DesignCreativity, Taste, Writing, VisualisationV+HMeaning requires someone who has experienced it
Negotiate termsSales Proposals, Vendor Mgt, ContractsNegotiation, Selling, PlanningHNegotiation requires reading what isn't said
Orchestrate agentsEngineering, Operations, Incident ResponseOrchestration, Systems Thinking, QuestioningH+VKnowing when to think vs delegate

As AI % rises, human work compresses from doing to directing, judging, trusting, and handling what breaks. Rows below 40% AI are human-led (direction, trust, trade-offs). Rows above 70% are AI-led with human exception handling. The middle band (40-70%) is where orchestration capability determines who leads.

The T-shaped professional survives this compression. Vertical depth keeps you irreplaceable in judgment rows. Horizontal range keeps you relevant across trust and distribution rows. Without both, you either get automated (all V, narrow domain) or commoditized (all H, no depth).

Commissioning Work

You have a commissioned workflow when any inexperienced agent can follow the decision tree and deliver expected outcomes without the need for an MKO to course correct.

Who does what in the L0-L4 commissioning process. The builder is never the commissioner.

LevelWho SpecifiesWho BuildsWho VerifiesAutomation
L0Dream teamDream teamPRD template gates
L1Dream teamEngineering agentEngineering testsSchema validation
L2Dream teamEngineering agentManual QAPlaywright stubs
L3Dream teamEngineering agentIntent specsE2E + intent specs automated
L4Dream teamEngineering agentIndependent commissionerBrowser walkthrough with evidence capture

The delegation chain: spec (intent) → build (action) → verify (proof). Verifiable intent applied to software delivery.

Validate Virtuous Feedback

Which VVFL station is human, which is AI, which is automated.

StationOwnerWork TypeInstrument
CaptureHumanObserve pain, write questionsTight Five protocol
PrioritiesHuman + AIScore PRDs, order build queue5P scoring algorithm
AttentionAI agentGenerate code, run testsEngineering agent + CI
ValueAI agentIntent specs, E2E testsPlaywright + Zod contracts
SystemsAI + HumanWire commissioning gaugeCommissioning API
StandardsHumanIndependent walkthroughBrowser MCP + evidence capture
DistributeAI + HumanDeploy, measure usagePostHog, Vercel
ReflectAIError tracking, gap analysisSentry, commissioning data
EvolveHumanUpdate templates, improve processReceipt patterns, legacy rule

The Shift

Prediction: Work Charts will eat Org Charts and Self-Interested Politics along the way.

Org ChartWork Chart
Who reports to whom?What work needs doing?
Where do you sit?What can you do?
Career = climbing boxesCareer = expanding capabilities
Fixed rolesFluid activities

Context

Questions

What would change if every team maintained a living work chart instead of an org chart?

  • Which rows in the matrix show AI % declining — and what does that reveal about the limits of automation?
  • If the template is the same for every function, why do most teams still describe work in paragraphs instead of matrices?
  • When two domains share identical AI % trends, does that signal a horizontal platform opportunity?
  • At what commissioning level does human judgment become irreplaceable — and does the delegation table match your intuition?