64 lines
2.4 KiB
Markdown
64 lines
2.4 KiB
Markdown
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---
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type: xpost
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source_url: https://x.com/AnatoliKopadze/status/xxxxxxxx
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retrieved: 2026-07-26
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author: "@AnatoliKopadze"
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is_thread: true
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tags: [graph-engineering, ai-agents, agent-architecture, workflows, orchestration, graph-shapes, parallel-execution, verification-nodes]
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people: [anatoli-kopadze]
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---
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# Graph Engineering Guide for AI Agents
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**Author:** Anatoli Kopadze (@AnatoliKopadze)
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**Posted:** 2026-07-25
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**Source:** X-Thread (viral, full thread captured via OME-Community)
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## Summary
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Anatoli Kopadze hat einen viralen Thread über Graph Engineering für AI Agents veröffentlicht — die 4 fundamentalen Shapes (Chain, Diamond, Router, Cycle) plus einen Step-by-Step-Build-Guide.
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## Thread Content
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### Shape 0 – Basics
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Ein Graph ist ein visueller Plan für AI Workflows. Tasks = Nodes, Dependencies = Edges. Graph Engineering optimiert den Plan so, dass unabhängige Tasks parallel laufen statt sequentiell. Ersetzt alte lineare Loops.
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### Shape 1 – The Chain
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A → B → C. Nur wenn Tasks wirklich voneinander abhängen. Langsam, aber einfach.
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### Shape 2 – The Diamond (The Workhorse)
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Start → fan-out (parallel workers) → verifier/merge → output. Perfekt für Research, Market Scans, Code Reviews. Das ist das mächtigste Pattern für den Alltag.
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### Shape 3 – The Router
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Decision node evaluiert Ergebnis und routet zu passendem Pfad. Branching-Logik lebt in der Graph-Struktur, nicht im Model Guess.
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### Shape 4 – The Cycle
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Controlled Loop für Discovery-Work (Bug Sweeps, iterative Refinements). Braucht hard stop condition.
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### Step-by-Step: How to build a graph from scratch
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1. Define goal
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2. List every sub-task
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3. Draw dependencies
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4. Choose dominant shape (start with Diamond)
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5. Add Router/Cycle only where needed
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6. Add verification nodes
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7. Set limits (max parallel, max cycles, timeout)
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8. Test small
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9. Visualize and iterate
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10. Scale
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### Key Insight
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> "Most people use 10% of AI — type one prompt, close tab. The people using the other 90% aren't typing prompts at all. They're running agents in parallel, wired into graphs that check their own work."
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## Cross-References
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- Ergänzt die bestehende Graph-vs-Loop-Debatte ([[wiki/concepts/agents/graph-based-agents.md]] / [[wiki/concepts/agents/agent-loops.md]])
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- Konkretisiert das Shape-Vokabular, das bei LangGraph nur implizit existiert (Chain, Diamond, Router, Cycle)
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- Verwandt mit [[wiki/concepts/agents/graph-based-agents.md]] (Shape-Design als Vorstufe zur LangGraph-Implementation)
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