Agentic AI Systems
π Agentic systems explained with chickens. Workflows, agents & orchestration made simple. Mermaid diagrams included
Agentic AI Systems π
Agentic systems explained with chickens β because AI orchestration doesn't have to be scary
Main Agent spawns Subagents like a hen with her chicks ππͺΊπ¦
π§± Foundations β’ βοΈ Workflows β’ π Agents β’ π οΈ Implementation β’ πΊοΈ Guides
Overview
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mindmap
root((π Agentic Systems))
π§± Foundations
Augmented LLM
βοΈ Workflows
ποΈ Baseline
βοΈ Chaining
π¦ Routing
π€οΈ Parallel
π¦ Orchestrator
π©» Evaluator
π Agents
Autonomous
Multi-Window
π οΈ Implementation
π¦ Subagent
𦴠Command
π Skill
πͺ Hook
πΊοΈ Navigation
π§± FoundationsThe building block for everything
βοΈ WorkflowsPredefined orchestration β code controls the flow
|
π AgentsDynamic autonomy β LLM controls the flow
π οΈ ImplementationClaude Code components & architecture
πΊοΈ Guides & π Reference
|
Quick Decision
%%{init: {'theme': 'base', 'themeVariables': {'lineColor': '#64748b'}}}%%
flowchart LR
START((π― Task)) --> DEST{Destructive?}
DEST -->|Yes| WIZ[π§ Wizard]
DEST -->|No| COMP{Complex?}
COMP -->|No| BASE[ποΈ Baseline]
COMP -->|Yes| PRED{Predictable<br/>steps?}
PRED -->|Yes| WORK{Need<br/>specialists?}
PRED -->|No| AGENT[π Agent]
WORK -->|No| CHAIN[βοΈ Chain]
WORK -->|Yes| ORCH[π¦ Orchestrator]
classDef default fill:#f8fafc,stroke:#64748b,stroke-width:1px,color:#1e293b
classDef decision fill:#fef3c7,stroke:#f59e0b,stroke-width:2px,color:#92400e
classDef baseline fill:#64748b,stroke:#475569,stroke-width:2px,color:#ffffff
classDef wizard fill:#14b8a6,stroke:#0d9488,stroke-width:2px,color:#ffffff
classDef workflow fill:#8b5cf6,stroke:#7c3aed,stroke-width:2px,color:#ffffff
classDef agent fill:#ec4899,stroke:#db2777,stroke-width:2px,color:#ffffff
START:::decision
DEST:::decision
COMP:::decision
PRED:::decision
WORK:::decision
BASE:::baseline
WIZ:::wizard
CHAIN:::workflow
ORCH:::workflow
AGENT:::agent
| Situation | β Use |
|---|---|
| Simple task (1 step) | ποΈ Baseline |
| Sequential (2-4 steps) | βοΈ Prompt Chaining |
| Categorize inputs | π¦ Routing |
| Independent subtasks | π€οΈ Parallelization |
| Multiple specialists | π¦ Orchestrator-Workers |
| Quality iteration | π©» Evaluator-Optimizer |
| Open-ended / unknown steps | π Autonomous Agent |
| Destructive operations | π§ Wizard |
| Long-running (>10 min) | π₯οΈ Multi-Window Context |
Anthropic Taxonomy
%%{init: {'theme': 'base', 'themeVariables': {'lineColor': '#64748b'}}}%%
flowchart LR
subgraph WORKFLOWS["βοΈ WORKFLOWS"]
direction TB
W1[ποΈ Baseline]
W2[βοΈ Prompt Chaining]
W3[π¦ Routing]
W4[π€οΈ Parallelization]
W5[π¦ Orchestrator]
W6[π©» Evaluator]
end
subgraph AGENTS["π AGENTS"]
direction TB
A1[π Autonomous]
A2[π₯οΈ Multi-Window]
end
CODE[π Code controls] --> WORKFLOWS
WORKFLOWS --> LLM[π§ LLM controls]
LLM --> AGENTS
classDef workflowBox fill:#ede9fe,stroke:#8b5cf6,stroke-width:2px,color:#5b21b6
classDef agentBox fill:#fce7f3,stroke:#ec4899,stroke-width:2px,color:#9d174d
classDef control fill:#f1f5f9,stroke:#64748b,stroke-width:1px,color:#475569
WORKFLOWS:::workflowBox
AGENTS:::agentBox
CODE:::control
LLM:::control
Key distinction: Workflows have predefined paths (code controls). Agents decide their own path (LLM controls).
Critical Rule
%%{init: {'theme': 'base', 'themeVariables': {'lineColor': '#64748b'}}}%%
flowchart LR
U1[πββοΈ User] -->|request| MA[π Main Agent]
MA -->|πͺΊ spawn| SA1[π¦ Subagent]
MA -->|πͺΊ spawn| SA2[π¦ Subagent]
SA1 -->|result| MA
SA2 -->|result| MA
MA -->|response| U2[πββοΈ User]
SA1 x--x|"β CANNOT spawn"| SA3[π¦]
classDef user fill:#6366f1,stroke:#4f46e5,stroke-width:2px,color:#ffffff
classDef main fill:#f59e0b,stroke:#d97706,stroke-width:2px,color:#ffffff
classDef sub fill:#ec4899,stroke:#db2777,stroke-width:2px,color:#ffffff
classDef blocked fill:#ef4444,stroke:#dc2626,stroke-width:2px,color:#ffffff,stroke-dasharray: 5 5
U1:::user
U2:::user
MA:::main
SA1:::sub
SA2:::sub
SA3:::blocked
π¦ Subagents cannot spawn other π¦ subagents. All delegation flows through π Main Agent.
Repository Structure
.
βββ README.md # π You are here
β
βββ foundations/ # π§± Core concepts
β βββ augmented-llm.md
β
βββ workflows/ # βοΈ Predefined orchestration
β βββ 00-baseline.md
β βββ 01-prompt-chaining.md
β βββ 02-routing.md
β βββ 03-parallelization.md
β βββ 04-orchestrator-workers.md
β βββ 05-evaluator-optimizer.md
β
βββ agents/ # π Autonomous systems
β βββ autonomous.md
β βββ multi-window.md
β
βββ implementation/ # π οΈ Claude Code specifics
β βββ components/ # π¦π¦΄ππͺ
β βββ architecture/ # 5-layer system
β
βββ guides/ # πΊοΈ Selection & use cases
β βββ use-cases/ # 6 validated examples
β
βββ reference/ # π Glossary, standards
References
| Resource | Link |
|---|---|
| Building Effective Agents | anthropic.com/engineering |
| Claude Code Docs | docs.anthropic.com |
| Agent SDK | docs.anthropic.com/agent-sdk |
| Anthropic Cookbook | github.com/anthropics |
Contributing
Contributions welcome! See CONTRIBUTING.md.
Requirements: Official sources β’ Code examples β’ Mermaid diagrams β’ Established format