Claude Architect · Lesson

Conversational Patterns & Agentic Tools

Multi-turn memory, instruction persistence and safe tools.

The Stateless Truth

Scenario 7 of the exam is Conversational AI Architecture Patterns. The first thing it tests is whether you understand that the Claude API is stateless: the model keeps no memory between requests.

Every turn you send the full message history in the messages array. "Memory" in a conversational app is something you engineer client-side, not a server session the model holds for you.

system carries persistent instructions
messages carries the entire turn-by-turn history, every request

import anthropic

client = anthropic.Anthropic()

# Memory = the list YOU maintain and resend each turn
history = [
    {"role": "user", "content": "My order id is 8842."},
    {"role": "assistant", "content": "Got it, order 8842."},
    {"role": "user", "content": "When does it ship?"},
]

resp = client.messages.create(
    model="claude-sonnet-4-5",
    max_tokens=1024,
    system="You are a concise support agent.",
    messages=history,  # FULL history, every single turn
)

Instruction Persistence Lives in system

In multi-turn chat, instructions that must hold for the entire session belong in the system field, not buried in a user turn 20 messages ago.

Why this matters: models exhibit lost-in-the-middle behavior, attending more to the start and end of the context than the middle. An instruction wedged in turn 7 of a 40-turn chat is the easiest thing for the model to drift away from.

The system prompt is re-supplied verbatim on every request, so it is the most reliable home for persistent rules: tone, role, refusal policy, output constraints.

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