Framework
WRM — Work Resource Management
Design the work first. Decide whether a human, an artificial resource or a hybrid should do it second. The position exists before its occupant.
WRM — Work Resource Management — is the discipline that designs, assigns, governs and optimizes work regardless of whether the resource executing it is human or artificial.
The founding idea is to separate the position from its occupant. First there is an organizational need; from it a position or responsibility is born, with purpose, ownership, results, KPIs, authority, limits, relationships, tools and escalation. Only then do you decide which resource should fill it. The declaration governs the order of birth, not the rest of the life: occupants — human occupants above all — reshape their positions, and a framework that denied job crafting would be Taylorism with better vocabulary. What the framework requires is that every reshaping be declared and versioned, because in a hybrid organization the declared position is the interface: a human colleague can read an undeclared role from the corridor; an artificial one can only read the graph.
Architecture
Where WRM sits
Human resources and artificial resources should not be designed as isolated disciplines. Both live inside a higher one.
WRM — Work Resource Management
The work, its positions, results, authority and controls
Optimal workforce architecture
Human Resource Management
People who execute work
Performance + rights + human development
Artificial Resource Management
AI systems that execute work
Performance + safety + technical control
Hybrid Workforce Management
Interaction and allocation between both
Coordination, transition and optimization
Classification
Three classes of principle
This separation avoids two errors: anthropomorphising software unnecessarily, and managing powerful agents as if they were simple tools.
Universal
Principles of work administration that hold regardless of who executes.
Role, responsibilities, KPIs, manager, authority, escalation, audit.
Adapted
Human principles that keep an equivalent function but change mechanism.
Probation → shadow mode; coaching → configuration feedback; promotion → wider scope.
Exclusively human
Rights, needs and experiences that follow from the human condition.
Health, rest, freedom of association, belonging, satisfaction, wellbeing.
Analogies like “the AI needs holidays” or “the AI feels engagement” import mechanisms with no operational referent, and forcing them degrades the framework. Equivalence must be operational, never anthropomorphic.
Scope
The ten domains
Organizational and job design
Purpose, responsibilities, authority, ownership, unity of command and interdependencies.
Selection and allocation
Define the position first, then assess fit, competencies, cost, risk and prior testing.
Onboarding and enablement
Company knowledge, SOPs, policies, org chart, tools and access.
Direction, collaboration and communication
Delegation, escalation, handoffs, channels, context and interaction rules.
Objectives and performance
KPIs, quality standards, feedback, review, underperformance and improvement.
Learning and development
Gaps, training, updates, memory, knowledge and capability evolution.
Human experience and rewards
Motivation, compensation, health, rest, rights and labor relations — when the resource is human.
Governance, security and risk
Least privilege, segregation, auditability, privacy, incidents and compliance.
Mobility, continuity and exit
Promotion and scope, succession and fallback, transfer, offboarding and knowledge retention.
Workforce planning and analytics
Capacity, make-vs-buy, human/AI mix, costs, productivity, quality and continuous improvement.
Lifecycle
The lifecycle of a work resource
Automating does not remove management. It makes it continuous.
| # | Stage | Objective |
|---|---|---|
| 01 | Design | Define result, responsibilities, KPIs, authority, limits and risk. |
| 02 | Allocate | Decide Human / Assisted human / Deterministic automation / Artificial. |
| 03 | Select | Person, model, agent, vendor or architecture with demonstrable fit. |
| 04 | Onboard | Knowledge, SOPs, culture and policies, relationships and escalation. |
| 05 | Enable | Tools, access, credentials, budget and authority. |
| 06 | Prove | Probation or shadow mode, simulations, evaluations and intensive approval. |
| 07 | Operate | Recurring work with observability and management by exception. |
| 08 | Measure | KPIs, quality, cost, incidents, interventions and outcomes. |
| 09 | Develop | Coaching or updates to instructions, knowledge, models and tools. The signal may originate with the manager or with the resource reporting divergence from its own data. |
| 10 | Reassign | Change scope, move between occupant types, revise which functions run with assistance. |
| 11 | Suspend | Stop work or access on risk, incident or unacceptable performance. |
| 12 | Retire | Offboarding, revocation, knowledge transfer and retention or deletion. |
Non-negotiable
Ten non-negotiable rules
- 01
Every position must exist before its occupant, with purpose, responsibilities, results and KPIs — and no position may outlive its purpose.
- 02
Every work resource must have exactly one accountable owner, even when it collaborates with many people or areas and even when its supervision is delegated. One owner is primary, not exclusive: data, security, compliance and vendor obligations survive intact.
- 03
Responsibility and authority must travel together: no result is demanded without granting the necessary faculties.
- 04
All authority must be explicit, limited and revocable.
- 05
Every resource must know its limits, its handoffs and when to escalate.
- 06
Access is granted under least privilege and is separated from the identity of the model or the prompt. Context is provisioned on the same basis: what is granted and what is withheld are both recorded design decisions.
- 07
Every material action executed by an AI Employee must be traceable and auditable.
- 08
Performance is measured by outcomes, quality, risk and cost — not by activity, hours, tokens or message count.
- 09
A transition between occupant types must remain reversible until stable performance is demonstrated.
- 10
Final responsibility for an AI Employee stays with an identified person or human governance body, however many artificial supervisors sit between them.