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4:["$","h2",null,{"className":"font-[family-name:var(--font-outfit)] text-2xl font-semibold tracking-tight text-foreground mt-10 mb-3","children":"Pattern 1: The Router-Specialist Architecture"}]
5:["$","p",null,{"className":"text-base leading-relaxed text-muted mb-5","children":"This is the pattern I use most. A lightweight router agent classifies the request and delegates to specialized agents."}]
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7:["$","p",null,{"className":"text-base leading-relaxed text-muted mb-5","children":["$","strong",null,{"className":"font-semibold text-foreground","children":"Why this works:"}]}]
8:["$","ul",null,{"className":"list-disc list-inside space-y-2 text-muted mb-5","children":["\n",["$","li",null,{"className":"text-base leading-relaxed","children":"The router uses a fast, cheap model (GPT-4 mini or Claude Haiku)"}],"\n",["$","li",null,{"className":"text-base leading-relaxed","children":"Each specialist has its own tailored prompt, tools, and guardrails"}],"\n",["$","li",null,{"className":"text-base leading-relaxed","children":"Adding a new category means adding one specialist — no changes to existing agents"}],"\n",["$","li",null,{"className":"text-base leading-relaxed","children":"Classification confidence below threshold triggers clarification instead of guessing"}],"\n"]}]
9:["$","h2",null,{"className":"font-[family-name:var(--font-outfit)] text-2xl font-semibold tracking-tight text-foreground mt-10 mb-3","children":"Pattern 2: The Pipeline Architecture"}]
a:["$","p",null,{"className":"text-base leading-relaxed text-muted mb-5","children":"For tasks with sequential stages, I use a pipeline where each agent's output feeds into the next."}]
b:["$","pre",null,{"className":"overflow-x-auto rounded-xl border border-[var(--card-border)] bg-[var(--surface)] p-4 text-sm mb-5","children":["$","code",null,{"className":"rounded bg-[var(--card-bg)] px-1.5 py-0.5 text-sm font-mono text-accent","children":"[Document Ingestion] → [Entity Extraction] → [Analysis] → [Report Generation]\n"}]}]
c:["$","p",null,{"className":"text-base leading-relaxed text-muted mb-5","children":["$","strong",null,{"className":"font-semibold text-foreground","children":"Real-world example: Medical Report Analysis"}]}]
d:["$","p",null,{"className":"text-base leading-relaxed text-muted mb-5","children":"In our healthcare platform, when a doctor uploads a patient report:"}]
e:["$","ol",null,{"className":"list-decimal list-inside space-y-2 text-muted mb-5","children":["\n",["$","li",null,{"className":"text-base leading-relaxed","children":[["$","strong",null,{"className":"font-semibold text-foreground","children":"Extraction Agent"}],": Pulls structured data (lab values, medications, diagnoses) from unstructured text"]}],"\n",["$","li",null,{"className":"text-base leading-relaxed","children":[["$","strong",null,{"className":"font-semibold text-foreground","children":"Validation Agent"}],": Cross-references extracted data against medical ontologies (ICD-10, SNOMED)"]}],"\n",["$","li",null,{"className":"text-base leading-relaxed","children":[["$","strong",null,{"className":"font-semibold text-foreground","children":"Analysis Agent"}],": Identifies patterns, flags abnormalities, suggests differential diagnoses"]}],"\n",["$","li",null,{"className":"text-base leading-relaxed","children":[["$","strong",null,{"className":"font-semibold text-foreground","children":"Report Agent"}],": Generates a structured clinical summary for the doctor"]}],"\n"]}]
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11:["$","h2",null,{"className":"font-[family-name:var(--font-outfit)] text-2xl font-semibold tracking-tight text-foreground mt-10 mb-3","children":"Pattern 3: The Debate Architecture"}]
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13:["$","p",null,{"className":"text-base leading-relaxed text-muted mb-5","children":"This pattern is critical in our medical AI system where diagnostic accuracy matters:"}]
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19:["$","p",null,{"className":"text-base leading-relaxed text-muted mb-5","children":["$","strong",null,{"className":"font-semibold text-foreground","children":"The escalation should include:"}]}]
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20:["$","h3",null,{"className":"font-[family-name:var(--font-outfit)] text-xl font-semibold text-foreground mt-8 mb-3","children":"3. The Context Leak"}]
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26:["$","p",null,{"className":"text-base leading-relaxed text-muted mb-5","children":"You cannot debug multi-agent systems without proper observability. At minimum, you need:"}]
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28:["$","p",null,{"className":"text-base leading-relaxed text-muted mb-5","children":"We use LangSmith for tracing and custom Prometheus metrics for monitoring. The dashboard shows real-time agent performance and automatically alerts when error rates exceed thresholds."}]
29:["$","h2",null,{"className":"font-[family-name:var(--font-outfit)] text-2xl font-semibold tracking-tight text-foreground mt-10 mb-3","children":"Key Takeaways"}]
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