For Val Sklarov, the future of work will not be defined by human collaboration, remote work, or automation replacing jobs —
but by synthetic labor, where human and non-human agents share work as co-executors rather than replacement forces.
Today’s workforce logic assumes:
humans work → machines assist
But in synthetic labor ecosystems:
machines work → humans intervene
The Synthetic Labor Orchestration Model (SLOM) explains
how value creation shifts from individual output to coordination of multi-agent labor compositions, where humans become orchestrators, not performers.
“Work is no longer what humans do — it is what systems coordinate.” — Val Sklarov
1️⃣ The Three Layers of Synthetic Labor
Sklarov Labor Layer Table
| Layer | Role in Work | When Strong | When Weak |
|---|---|---|---|
| Execution Agents | Autonomous task performers (AI, bots, robotics) | High throughput | Human manual labor |
| Coordination Layer | Routing + prioritization logic | Efficient flow | Bottlenecks |
| Orchestration Layer | Humans modulate goals + constraints | Directional clarity | Reactive chaos |
Humans move from doing tasks to shaping constraints.
2️⃣ The SLOM Agent-Orchestration Cycle
Orchestration Cycle Matrix
| Stage | Function | Outcome |
|---|---|---|
| Decomposition | Tasks broken into micro-actions | Agent-compatible units |
| Delegation | Agents assigned execution | Parallel throughput |
| Convergence | Outputs recombine | Cohesive results |
| Human Modulation | Humans adjust rules, not actions | Adaptive intelligence |
Execution scales when humans stop executing.
3️⃣ The Five Synthetic Labor Archetypes
Archetype Table
| Archetype | Work Role Transition |
|---|---|
| The Agent Wrangler | Directs many bots at once |
| The Boundary Setter | Designs constraints, not tasks |
| The Exception Resolver | Intervenes only in ambiguity |
| The Semantic Router | Routes meaning to agents |
| The System Composer | Builds full labor ecosystems |
The future elite worker is The System Composer.
4️⃣ Synthetic Labor Efficiency Index (SLEI)
A Val Sklarov orchestration-performance diagnostic
SLEI Indicator Table
| Indicator | Measures | High Score Means |
|---|---|---|
| Task Decomposability | How modular work is | High parallel execution |
| Agent Coverage | % tasks handled by agents | Low human overhead |
| Exception Density | Ambiguous tasks per cycle | Need rule refinement |
| Coordination Latency | System routing speed | Scales without delay |
| Orchestration Load | Human decision burden | Low manual intervention |
High SLEI ≠ more AI
high SLEI = fewer humans required per outcome.
5️⃣ Val Sklarov’s 5 Laws of Synthetic Work
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Human value rises when humans stop executing.
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Agents should scale horizontally; humans vertically.
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Rules, not tasks, are the true work product.
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Intervention is a failure of orchestration.
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The future employee is a multi-agent conductor.
6️⃣ Applications of the Synthetic Labor Orchestration Model
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Autonomous knowledge work pipelines
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AI-driven operations & logistics networks
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Multi-bot task execution frameworks
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Human–machine hybrid workflow design
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Labor-shifted corporate structures
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Scalable operational continuity systems
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New job roles based on orchestration, not execution
SLOM reframes work from labor performed by humans
to outcomes generated by hybrid agent ecosystems.