Agentic Architecture & Orchestration

1import anthropic
2
3client = anthropic.Anthropic()
4tools = [{"name": "lookup_customer", "description": "...", "input_schema": {}}]
5messages = [{"role": "user", "content": "Find customer John Smith"}]
6
7# The Agentic Loop
8while True:
9    response = client.messages.create(
10        model="claude-sonnet-4-20250514",
11        max_tokens=4096,
12        tools=tools,
13        messages=messages
14    )
15    
16    # KEY: Check stop_reason to control the loop
17    if response.stop_reason == "end_turn":
18        break  # Claude is done
19    
20    if response.stop_reason == "tool_use":
21        tool_block = next(
22            b for b in response.content if b.type == "tool_use"
23        )
24        result = execute_tool(tool_block.name, tool_block.input)
25        
26        messages.append({"role": "assistant", "content": response.content})
27        messages.append({
28            "role": "user",
29            "content": [{"type": "tool_result",
30                         "tool_use_id": tool_block.id,
31                         "content": result}]
32        })

1from claude_agent import Agent, Task
2
3coordinator = Agent(
4    model="claude-sonnet-4-20250514",
5    tools=[
6        Task,              # Required for spawning subagents
7        summarize_results, # Coordinator-level synthesis
8        format_report,     # Final output formatting
9    ]
10)
11
12# Subagent with scoped tool access (4 tools each)
13market_researcher = Agent(
14    model="claude-sonnet-4-20250514",
15    tools=[web_search, read_doc, extract_data, format_citation],
16)
17
18tech_analyst = Agent(
19    model="claude-sonnet-4-20250514",
20    tools=[read_code, grep_patterns, analyze_deps, format_report],
21)
22
23# Coordinator delegates with EXPLICIT context per subtask
24coordinator.run("""
25Research AI infrastructure market. Delegate:
261. Market research → market_researcher
272. Technology analysis → tech_analyst
28Pass each subagent ONLY the context relevant to their task.
29""")

1from claude_agent import Agent, Hook
2
3# PostToolUse hook: Block refunds above $500
4def refund_limit_hook(tool_name, tool_input, tool_output):
5    if tool_name == "process_refund":
6        amount = tool_input.get("amount", 0)
7        if amount > 500:
8            return {
9                "blocked": True,
10                "reason": f"Refund ${amount} exceeds $500 limit",
11                "action": "escalate_to_human",
12                "context": {
13                    "customer_id": tool_input.get("customer_id"),
14                    "requested_amount": amount,
15                    "agent_limit": 500,
16                }
17            }
18    return tool_output  # Allow all other tool calls
19
20agent = Agent(
21    model="claude-sonnet-4-20250514",
22    tools=[lookup_customer, check_order, process_refund],
23    hooks={"PostToolUse": [refund_limit_hook]},
24)

1# Resume a previous session (preserves full context)
2claude --resume
3
4# Resume a specific named session
5claude --resume --session-name "feature-auth-redesign"
6
7# Fork for exploration (inherits context, diverges)
8# Changes in fork do NOT affect the main session
9claude fork_session --reason "Exploring alternative API"
10
11# Start a new named session
12claude --session-name "sprint-47-backend"