介绍生产级Prompt架构:XML标签分离指令、用角色设定约束模型行为、Chain of Thought引导推理等实战技巧。
大多数开发者和高级用户与 LLM(Claude 3.5 Sonnet、GPT-4o、Gemini 1.5 Pro)交互时,使用的都是简单、非结构化的自然语言查询,比如:
"你能重构这个函数让它更快吗?"或者"为什么这段代码会报错?"
虽然前沿模型能够轻松对话,但把 LLM 当作随意聊天机器人来对待,会使其 80% 的推理和指令遵循能力被浪费。
在我最近出版的新书《AI Prompt Bible: Master ChatGPT, Claude, Gemini, and Microsoft Copilot with Over 1,000 Ready-to-Use Prompts》(作者 P.S. Darren)中,我详细拆解了专为软件工程师、系统架构师和技术专家设计的生产级提示框架。
以下 5 个经过实战检验、没有废话的提示架构,均附有真实代码示例,可以直接复制使用。
Claude 模型在解析 XML 标签方面经过微调,表现尤为出色。将系统指令、行为边界、原始输入文本和输出约束分离到明确的 XML 标签中,可以消除歧义并防止意外幻觉。
<system_guidelines>
You are a Staff TypeScript Architect with 15+ years of experience optimizing mission-critical backend microservices. Adhere strictly to clean architecture, zero-dependency utility design, and mathematical time-complexity minimization.
</system_guidelines>
<task>
Refactor the provided TypeScript function to eliminate nested O(N^2) iterations. Replace the naive linear search with an O(N) single-pass lookup using a Map or Set. Provide strict TypeScript 5+ types, JSDoc annotations, and Jest unit test cases.
</task>
<source_code>
interface UserTransaction {
id: string;
userId: string;
amount: number;
category: string;
}
// Naive O(N^2) duplication check
export function findDuplicateTransactions(transactions: UserTransaction[]): UserTransaction[] {
const duplicates: UserTransaction[] = [];
for (let i = 0; i < transactions.length; i++) {
for (let j = i + 1; j < transactions.length; j++) {
if (
transactions[i].userId === transactions[j].userId &&
transactions[i].amount === transactions[j].amount &&
transactions[i].category === transactions[j].category
) {
if (!duplicates.some(d => d.id === transactions[i].id)) {
duplicates.push(transactions[i]);
}
}
}
}
return duplicates;
}
</source_code>
<constraints>
1. Output ONLY valid TypeScript inside a single markdown code block.
2. Ensure O(N) time complexity and O(N) space complexity.
3. Include 3 comprehensive Jest test assertions (empty array, unique list, multiple duplicate collisions).
4. No conversational chit-chat before or after the code.
</constraints>
当你设计一份技术 RFC、数据库 schema 或分布式管道时,自然会受到确认偏见的困扰——你设计了它,所以假设它能正常工作。
这个提示将 LLM 转变为一个愤世嫉俗、久经沙场的首席基础设施工程师,其任务是找出系统将在生产环境中如何崩溃。
Act as a skeptical, highly analytical Principal Infrastructure & Security Architect at a tier-1 fintech company.
Audit the technical design proposal provided below. Your goal is NOT to validate my ego or compliment the design. Your sole objective is to stress-test this architecture and expose failure modes before it goes to production.
Audit Tasks:
1. Identify the 3 most dangerous architectural assumptions.
2. Pinpoint race conditions, deadlocks, or latency bottlenecks under 100x traffic spikes.
3. Highlight obscure edge cases (network partitions, clock skew, out-of-order webhook delivery) that could corrupt data.
4. Provide a concrete, resilient refactoring recommendation with pseudo-code for the critical path.
---
PROPOSED ARCHITECTURE SPECIFICATION:
Service: Asynchronous Payment Webhook Ingestion Engine
Stack: Node.js, Express, PostgreSQL, Redis Pub/Sub
Flow:
1. External payment provider sends HTTP POST webhook to `/api/webhooks/payment`.
2. The endpoint reads the payload, queries PostgreSQL `SELECT * FROM orders WHERE id = $1` to fetch order status.
3. If order status is 'PENDING', update PostgreSQL to 'PAID', generate an invoice PDF in-memory, and dispatch an email via SendGrid.
4. If payment provider retries the webhook concurrently, Redis `SETNX lock:order:{id}` with a 10-second TTL is used to prevent duplicate emails.
---
当将 LLM 输出直接传送到下游 Python 脚本、CI/CD 管道或数据库摄取作业时,对话式填充语(例如"Sure, here is your JSON:")会完全导致 JSON.parse() 崩溃。
使用严格的 JSON Schema 约束:
{
"$schema": "http://json-schema.org/draft-07/schema#",
"type": "object",
"properties": {
"incident_id": { "type": "string" },
"total_errors_detected": { "type": "integer" },
"highest_severity": { "type": "string", "enum": ["CRITICAL", "HIGH", "MEDIUM", "LOW"] },
"primary_root_cause": { "type": "string" },
"affected_services": { "type": "array", "items": { "type": "string" } },
"remediation_steps": { "type": "array", "items": { "type": "string" } }
},
"required": ["incident_id", "total_errors_detected", "highest_severity", "primary_root_cause", "affected_services", "remediation_steps"],
"additionalProperties": false
}
RAW PRODUCTION LOG STREAM:
[2026-08-24T00:14:22.104Z] [auth-service] INFO: Healthcheck OK.
[2026-08-24T00:14:23.512Z] [billing-service] ERROR: Connection pool exhausted (max 50 connections).
[2026-08-24T00:14:23.515Z] [billing-service] FATAL: Failed to acquire client from Postgres pool after 5000ms timeout.
[2026-08-24T00:14:24.001Z] [gateway] WARN: Upstream billing-service returned HTTP 504 Gateway Timeout for user_id=98412.
[2026-08-24T00:14:25.110Z] [billing-service] ERROR: Unhandled rejection: QueryTimeout: Canceling statement due to lock timeout on table 'customer_subscriptions'.
CRITICAL INSTRUCTION:
Return ONLY the raw JSON object inside a ```
json
``` block. Do not prepend "Here is the JSON" or append closing remarks.
当面临高风险技术权衡时(例如在 Kafka 和 RabbitMQ 之间选择,或微服务与模块化单体之间选择),单一视角的提示只能给出泛泛的优缺点列表。
这个提示强制三个截然不同、存在冲突的技术思维在达成共识之前先相互辩论。
We are architecting a real-time collaborative workspace app (like Figma / Notion) supporting 50,000 concurrent active users editing shared canvas documents.
Simulate a rigorous technical debate between 3 senior technical leaders:
1. PERSONA 1: The Site Reliability & Data Integrity Lead
- Prioritizes: Zero data loss, operational simplicity, predictable disaster recovery, avoiding complex distributed state machines.
2. PERSONA 2: The Ultra-Low Latency Performance Engineer
- Prioritizes: Sub-20ms synchronization, WebSockets/WebRTC, operational transformation (OT) or CRDTs (Conflict-free Replicated Data Types), local-first client caching.
3. PERSONA 3: The Rapid-Delivery Product Architect
- Prioritizes: Developer velocity, ease of debugging in production, time-to-market, utilizing battle-tested managed cloud services.
Execution Rules:
Round 1: Each persona pitches their ideal state synchronization stack.
Round 2: Each persona directly attacks the hidden operational costs and failure modes of the other two approaches.
Round 3: The Council reaches an executive, pragmatic consensus detailing the exact recommended architecture for our team size (6 engineers).
当排查复杂状态机 bug、分布式竞态条件或内存泄漏时,AI 模型往往只会建议表面性的权宜之计(比如加 try/catch 或 setTimeout)。
这个提示强制模型退后一步,在动手改代码之前先分析根本性不变量。
Before proposing any code fixes or patches, execute a First-Principles Step-Back Analysis on the bug described below.
PROBLEM DESCRIPTION:
In our Node.js WebSocket gateway, clients occasionally stop receiving message updates after reconnecting following a brief network disconnect. The client reconnects successfully (HTTP 101 Switching Protocols), but server-side channel events are dropped silently without any error thrown in logs.
STEP-BY-STEP DECONSTRUCTION REQUIRED:
Phase 1: Invariant Analysis
- State the 3 fundamental system invariants that must be true for bi-directional socket subscriptions to deliver messages reliably.
Phase 2: Failure Mode Mapping
- Identify exactly where a reconnection lifecycle race condition can desynchronize the server's subscription map from the socket instance.
Phase 3: Robust Solution Architecture
- Provide a robust, idempotent reconnection protocol with client-side heartbeats, server-side channel re-attachment, and missed-message sequence replay.
- Include working, production-ready TypeScript code implementing this fix.
🚀 将你的 AI 工作流提升到下一个层次
这 5 个架构摘自我新书中的 1000 多个经过实战检验的提示系统:
📖 AI Prompt Bible: Master ChatGPT, Claude, Gemini, and Microsoft Copilot with Over 1,000 Ready-to-Use Prompts (ASIN: B0H6WNBSPG) — 现已在全球亚马逊 Kindle 商店上架。
探索 P.S. Darren 的更多出版作品:
Claude for Beginner: From Zero to Hero (ASIN: B0GZPC7L7Q)
Claude AI for Journalists (ASIN: B0H68FCT19)
Claude AI for Doctors (ASIN: B0GXWRQBNW)
访问官方网站获取免费提示 PDF 速查表、完整书摘和技术 playbook:👉 https://ps-darren.netlify.app