System Setup
Multi-agent orchestration. Multiple agents coordinating through defined workflows and primitives.
Overview
APL4 is where you stop using individual agents and start building systems made of agents. Multiple agents coordinate, delegate, and execute through defined workflows. This is the ceiling of the current framework.
What This Level Is
System Setup means you are orchestrating multiple agents that work together. Each agent has a defined role, a set of tools, and constraints. They communicate through shared state, message passing, or workflow primitives.
This is not "using agent tools." This is engineering agent systems.
Tools at This Level
- LangChain / LangGraph - Framework for chaining LLM calls with tools and memory
- CrewAI - Multi-agent framework with role-based agents
- AutoGen - Microsoft's multi-agent conversation framework
- AWS Bedrock - Amazon's managed model API with multi-agent orchestration support
- Azure OpenAI - Microsoft's hosted OpenAI models with enterprise orchestration
- Vertex AI - Google's managed ML platform for agent pipelines
- NVIDIA NIM - NVIDIA's inference microservices used to power custom agent pipelines
- Custom pipelines - Purpose-built orchestration using model APIs directly
What You Can Do
- Orchestrated multi-step workflows with agent handoffs
- Agent specialization - one agent researches, another writes, another reviews
- Automated pipelines that run end-to-end without human intervention
- System-level automation with defined contracts and schemas
- Self-correcting loops where agents validate each other's output
What You Cannot Do (Safely)
- Run ungoverned agents with production access
- Trust agent coordination without observability
- Deploy multi-agent systems without kill switches
- Assume agents share the same context or understanding
Risks at This Level
- Cascade failure: One agent's bad output propagates through the entire pipeline
- Ghost state: Agents accumulating context that is invisible to you
- Coordination bugs: Agents working at cross purposes due to ambiguous instructions
- Permission explosion: Each agent needs access, and the surface area multiplies
- Observability debt: The system works until it does not, and you cannot see why
Governance Essentials
- Define explicit contracts between agents (input/output schemas)
- Implement logging at every agent boundary
- Use circuit breakers - automatic stops when output quality degrades
- Run agents with minimum necessary permissions
- Test the system, not just the individual agents
Who Needs This
Most builders do not need APL4. APL3 covers the vast majority of use cases. APL4 is for teams building agent-native products, automation platforms, or infrastructure where the agent is the system - not just a tool within it.
The builders who get the most out of APL4 are the ones who already mastered APL3. Start there.