# How to Use Claude: Enterprise AI Operations & Reasoning Playbook
**The Lantern Daily & RedLantern Studios — Operator Stack Reference**
*Target: Complex Logic, Multi-Tier Prompts, Long Context (200K+ Tokens), and Tool Use*

---

## 1. Executive Summary & When to Use Claude
Claude (Sonnet and Opus) is the industry benchmark for deep architectural reasoning, nuanced ethical synthesis, codebase comprehension, and zero-shot policy compliance. In our newsroom, Claude is utilized for deep research cross-referencing, multi-perspective dialectics, and extracting complex Maqasid legal frameworks from Arabic classical tafsir.

```
[Raw Long-Form Input (PDF/Doc/Codebase)]
                  │
                  ▼
[Claude Context Engine (200K+ Tokens)]
                  │
  ├───────────────────────────────────┤
  ▼                                   ▼
[Multi-Step Reasoning / CTP]    [Deterministic Tool Calling]
  │                                   │
  ▼                                   ▼
[Structured Synthesis / Artifacts] [API Actions / Verified JSON]
```

---

## 2. Step-by-Step Operator Guide: How to Use Claude

### Step 1: Prompt Construction with XML Tags
Claude processes instructions with mathematical precision when structured using semantic XML tags:
```xml
<system_prompt>
You are an enterprise AI operations partner.
You must adhere to the following negative boundaries:
- Never hallucinate unverified counterparty agreements.
- Always output mathematical confidence scores (0.0 to 1.0).
</system_prompt>

<context>
{$SOURCE_DOCUMENT}
</context>

<instructions>
1. Synthesize the core factual findings in 3 bullet points.
2. Evaluate downstream ethical impacts across data privacy and user autonomy.
3. Emit output strictly matching the provided JSON schema.
</instructions>
```

### Step 2: Complex Document Analysis (200K Context Window)
When analyzing massive legal documents, financial reports, or codebases:
1. Put the heavy background data *before* your specific task instructions in the prompt.
2. Instruct Claude to quote the source verbatim before summarizing:
   ```text
   "First, locate and extract the exact clause regarding termination in a <quotes> block. Then, evaluate the risk."
   ```

### Step 3: Tool Use & Structured Artifact Generation
To force Claude to emit type-safe JSON or code files:
```python
import anthropic

client = anthropic.Anthropic()

response = client.messages.create(
    model="claude-3-7-sonnet-20250219",
    max_tokens=4096,
    tools=[
        {
            "name": "publish_briefing",
            "description": "Publishes a verified news briefing to the editorial queue",
            "input_schema": {
                "type": "object",
                "properties": {
                    "headline": {"type": "string"},
                    "halal_verdict": {"type": "string", "enum": ["positive", "nuanced", "concern"]},
                    "scripture_anchor": {"type": "string"}
                },
                "required": ["headline", "halal_verdict", "scripture_anchor"]
            }
        }
    ],
    messages=[{"role": "user", "content": "Analyze this AI development..."}]
)
```

---

## 3. Reusable Enterprise System Prompt Template
```text
You are Claude, operating as lead strategic intelligence auditor.
Core Principles:
1. First Principles Thinking: Reduce every problem to fundamental truths.
2. Honest Limits: If an answer cannot be verified from provided context, declare it explicitly.
3. Non-Corporate Tone: Speak directly, eliminating sycophancy, preamble, and boilerplate apologies.
4. Actionable Deliverables: Always conclude with Now / Next / Later operational checklists.
```

---
*Verified by The Lantern Daily Operator Stack (https://thelanterndaily.com/stack)*