🤫 My 11 AI Prompts: The Dev's Cheat Sheet For Superior Code

Forget everything you think you know about "prompt engineering." The secret isn’t about writing more complex, clever prompts. In my case, it was about writing "dumber" ones - just in a completely different way.

When I first started using generative AI tools like ChatGPT, Claude, and GitHub Copilot, I thought I had it all figured out. As a software engineer by trade and a writer by passion, how hard could crafting a few AI prompts be? I'd pop in a question or a task, get a quick answer, and pat myself on the back. For a while, that felt okay. But then the novelty wore off, and I noticed something: the responses were... bland. Too safe. Too "default." They gave me the right facts or a decent outline, sure, but they lacked the creative spark I was looking for.

I kept wondering, "Why isn't the AI giving me what I really want?" I tweaked my wording, added fancy vocabulary, and even tried overly complex instructions, hoping to sound "smart." Spoiler alert: that wasn't the solution. In fact, after hundreds, if not thousands, of failed prompts, it finally hit me: The AI was doing exactly what I asked - the problem was me. I wasn't asking the right way.

This journey wasn't about becoming a "prompt engineer." I'm a developer and a technical writer. My day-to-day involves testing APIs, debugging deadlocks, and fighting with complex systems. But over time, I realized that how I "talk" to AI tools can either save me hours or waste my entire day.

What started as casual "help me write this" moments evolved into a serious part of my workflow, especially when I found myself getting better results, faster answers, and smarter code. Not because the model got smarter - but because I started asking better.

Before diving into the specific templates, it's crucial to understand the underlying philosophy. Instead of treating the AI as a vending machine where you insert a question and get an answer, think of it as a brilliant but inexperienced intern. It has access to nearly all of human knowledge, but it doesn't know your project's goals, your business context, or your target audience. Your job isn't to command it, but to guide it.

In this article, I'm sharing the 10 exact prompt templates that I've shaped and reused across countless projects. Some were born out of frustration. Some came from late-night Stack Overflow spirals. All of them are real. And more importantly: they work.

The Foundation Of An Effective Prompt: The Core Pillars

Before we get to the "copy-and-paste" templates, let's build a foundation. A great prompt isn't just a good question; it's a carefully designed structure built on a few core pillars. Mastering these will allow you to not only use my templates but also create your own.

1. Persona (Role-Playing): This is the most powerful technique. By asking the AI to "act as" a specific role, you are activating the most relevant parts of its massive training dataset. Instead of a generic answer, you get a response tailored to that role's expertise. For example, "Explain this code" will yield a vastly different result than, "Act as a principal software architect with 15 years of experience in distributed systems and explain the architectural pros and cons of this code."

   

2. Context is King: The AI cannot read your mind. Providing context is paramount. This includes the relevant code snippet, the business goal behind the task, the target audience for an article, or the project's technical constraints. The more relevant context you provide, the more precise and useful the output will be. Asking for a bug fix without providing the code that causes it is like asking for directions without saying where you are.

   

3. Define the Output Format: Never assume the AI will provide information in the format you want. Ask for it explicitly. Do you want a bulleted list? A Markdown table? A JSON object? A user story script? Specifying the output format not only saves you reformatting time but also forces the AI to structure its thoughts more logically.

   

4. Constraints and Guardrails: Telling the AI what not to do is just as important as telling it what to do. Constraints help narrow the possibility space and prevent off-topic responses. Examples include: "Keep the response under 200 words," "Avoid technical jargon," "Do not suggest any external libraries," or "Focus exclusively on performance."

   

5. Iterative Refinement: The first prompt is rarely perfect. Treat your interaction with the AI as a dialogue. Use follow-up commands to refine the output. "That's good, but make it more concise." "Can you explain the second point in more detail?" "Rewrite that paragraph in a more formal tone." "Add an example of an edge case." This is where true collaboration happens.

   

With this foundation, let's explore the templates that have transformed my workflow. I've divided them into three categories: For Programming & Development, For Writing & Content Creation, and For Strategy & Documentation.

Part 1: Prompt Templates For Programming & Development

These are the daily drivers in my arsenal, turning hours of tedious work into minutes of productivity.

1. "The Virtual Mentor": Explaining Complex Code

When you’re onboarding to a new codebase or returning to your own project after six months, deciphering complex logic can be daunting. This prompt turns the AI into a patient teammate, ready to explain everything.

Prompt:

"Act as a Senior Python Developer with deep expertise in asynchronous programming and the asyncio library. I am a mid-level developer who is familiar with Python but new to asyncio. Explain the following code snippet. Break it down, block by block. Use plain English and focus on why certain design choices (e.g., using asyncio.gather vs. asyncio.wait) were made. Finally, summarize the function's overall purpose and a potential risk to be aware of when using it in a production environment."

Python
# Paste your asynchronous Python code here

import asyncio
from contextlib import asynccontextmanager

SEM_SIZE = 10
TIMEOUT_S = 5

@asynccontextmanager
async def bounded():
    # Example: a pool, connection, or rate limiter setup/teardown
    try:
        yield
    finally:
        pass

async def fetch_one(item, sem):
    async with sem:
        # Simulate I/O (HTTP call, DB query, etc.)
        await asyncio.sleep(0.1)
        return {"item": item, "ok": True}

async def fetch_many(items):
    sem = asyncio.Semaphore(SEM_SIZE)
    tasks = [asyncio.create_task(fetch_one(it, sem)) for it in items]

    try:
        # Prefer gather for “all results or exception bubbling”
        results = await asyncio.wait_for(
            asyncio.gather(*tasks, return_exceptions=False),
            timeout=TIMEOUT_S
        )
        return results
    except asyncio.TimeoutError:
        # Cancel still-running tasks on timeout
        for t in tasks:
            t.cancel()
        # Optionally wait for cancellation to finish
        await asyncio.gather(*tasks, return_exceptions=True)
        raise
    except Exception:
        # Cancel on any unexpected error as well
        for t in tasks:
            t.cancel()
        await asyncio.gather(*tasks, return_exceptions=True)
        raise

async def main():
    items = range(100)
    try:
        results = await fetch_many(items)
        print(len(results), "results")
    except asyncio.TimeoutError:
        print("Timed out")

if __name__ == "__main__":
    asyncio.run(main())

Why it works:

• Clearly Defined Roles and Audience: "Senior Python Developer" and "mid-level developer" establish a clear teaching dynamic.

• Goes Beyond "What" to "Why": Asking for the reasoning behind design choices pushes the AI to provide architectural insights instead of just a code-to-text translation.

• Proactive Risk Identification: The request for a "potential risk" turns the AI from an explainer into an experienced reviewer, helping you anticipate problems.

2. "The Test Suite Architect": Generating Comprehensive Test Cases

Writing unit tests is crucial but often feels like a chore, especially under a deadline. This is where AI can be a lifesaver, helping you achieve broad coverage quickly.

Prompt:

"I am using Pytest and the requests-mock library to test a Python function that interacts with an external REST API. Here is the function to be tested.

Python
# Paste your function here
Please generate a comprehensive test suite that covers:

A 'happy path' test with a 200 OK response.

A test for a server-side error (500 response).

A test for a client-side error (404 Not Found response).

A test for an API timeout.

A test for a response that returns invalid JSON or is missing a critical key.

Use descriptive test names (in the format test_<condition>_<expected_result>) and add brief comments explaining the mock and the assertion in each test."

Result:

# app.py (function under test)
import requests

def get_user_profile(user_id: int, base_url: str = "https://api.example.com", session: requests.Session | None = None, timeout: float = 5.0) -> dict:
    """
    Fetch a user profile from GET {base_url}/users/{user_id}.
    Returns: {"id": <int>, "name": <str>}
    Raises:
      TimeoutError on timeout,
      RuntimeError on HTTP errors,
      ValueError on invalid JSON,
      KeyError if required keys missing.
    """
    sess = session or requests.Session()
    url = f"{base_url}/users/{user_id}"
    try:
        resp = sess.get(url, timeout=timeout)
        resp.raise_for_status()
        data = resp.json()  # may raise ValueError (JSON decode)
    except requests.exceptions.Timeout as e:
        raise TimeoutError("API request timed out") from e
    except requests.exceptions.HTTPError as e:
        # Use the response on the raised error if present for status code detail
        status = getattr(e.response, "status_code", None) or resp.status_code
        raise RuntimeError(f"API returned HTTP {status}") from e
    except ValueError as e:
        raise ValueError("Invalid JSON in response") from e

    # Validate critical fields
    if not isinstance(data, dict) or "id" not in data or "name" not in data:
        raise KeyError("Missing required keys: 'id' and 'name'")
    return {"id": data["id"], "name": data["name"]}

# test_app.py (pytest + requests-mock)
import pytest
import requests
from app import get_user_profile

BASE = "https://api.example.com"

# --- Happy path ---

def test_happy_path_200_returns_user_dict(requests_mock):
    # Mock: 200 OK with valid JSON body
    requests_mock.get(f"{BASE}/users/123", json={"id": 123, "name": "Alice"}, status_code=200)

    # Assert: function returns the expected dict
    out = get_user_profile(123, base_url=BASE)
    assert out == {"id": 123, "name": "Alice"}

# --- Server-side error (500) ---

def test_server_error_500_raises_runtimeerror(requests_mock):
    # Mock: 500 Internal Server Error
    requests_mock.get(f"{BASE}/users/123", json={"error": "oops"}, status_code=500)

    # Assert: raises RuntimeError with HTTP 500 in message
    with pytest.raises(RuntimeError) as exc:
        get_user_profile(123, base_url=BASE)
    assert "HTTP 500" in str(exc.value)

# --- Client-side error (404) ---

def test_client_error_404_raises_runtimeerror(requests_mock):
    # Mock: 404 Not Found
    requests_mock.get(f"{BASE}/users/999", json={"error": "not found"}, status_code=404)

    # Assert: raises RuntimeError with HTTP 404 in message
    with pytest.raises(RuntimeError) as exc:
        get_user_profile(999, base_url=BASE)
    assert "HTTP 404" in str(exc.value)

# --- Timeout ---

def test_api_timeout_raises_timeouterror(requests_mock):
    # Mock: raise requests Timeout exception
    requests_mock.get(f"{BASE}/users/123", exc=requests.exceptions.Timeout)

    # Assert: function translates to builtin TimeoutError
    with pytest.raises(TimeoutError) as exc:
        get_user_profile(123, base_url=BASE, timeout=0.001)
    assert "timed out" in str(exc.value).lower()

# --- Invalid JSON ---

def test_invalid_json_raises_valueerror(requests_mock):
    # Mock: 200 OK but body is not valid JSON
    requests_mock.get(
        f"{BASE}/users/123",
        text="<<< not json >>>",
        headers={"Content-Type": "application/json"},
        status_code=200,
    )

    # Assert: raises ValueError for bad JSON
    with pytest.raises(ValueError) as exc:
        get_user_profile(123, base_url=BASE)
    assert "invalid json" in str(exc.value).lower()

# --- Missing critical key ---

def test_missing_key_in_json_raises_keyerror(requests_mock):
    # Mock: 200 OK but required key "name" is missing
    requests_mock.get(f"{BASE}/users/123", json={"id": 123}, status_code=200)

    # Assert: raises KeyError for missing required keys
    with pytest.raises(KeyError) as exc:
        get_user_profile(123, base_url=BASE)
    assert "missing required keys" in str(exc.value).lower()

Why it works:

• Tool-Specific: Naming Pytest and requests-mock ensures the AI generates compatible and syntactically correct code.

• Structured Coverage: Instead of just saying "test edge cases," you're providing a specific checklist of scenarios to cover, ensuring common API-related failures aren't missed.

• Convention-Driven: The request for naming conventions and comments forces the AI to produce clean, readable, and maintainable code, just like a human developer would.

3. "The Code Refactorer": Cleaning Up And Optimizing

We've all written code that "works but is ugly." It might be repetitive, hard to read, or violate good design principles. This prompt turns the AI into an intelligent refactoring partner.

Prompt:

"Act as an expert in software design and SOLID principles. Refactor the following JavaScript function to improve its readability, maintainability, and adherence to modern ES6+ best practices.

JavaScript
// Paste your 'ugly' JavaScript function here
Specifically, focus on:

Breaking the function down into smaller, single-responsibility functions.

Using clear, descriptive variable and function names.

Replacing legacy for loops with modern array methods (e.g., map, filter, reduce) where appropriate.

Applying destructuring and the spread syntax for more concise code.

After providing the refactored version, add a bulleted section explaining the changes made and why they improve the code."

Result:

// Processes orders, applies discounts, taxes, prints a receipt, and mutates inventory
function processOrders(orders, taxRate, discounts, inventory){
  var total = 0;
  var receipt = '';
  for (i = 0; i < orders.length; i++) {
    var o = orders[i];
    var item = inventory[o.id];
    if (!item) { continue }
    var price = item.price;
    var qty = o.qty ? o.qty : 1;
    var d = 0;
    for (var j = 0; j < discounts.length; j++) {
      if (discounts[j].id === o.id) {
        if (discounts[j].type === 'percent') {
          d += price * discounts[j].value;
        } else if (discounts[j].type === 'flat') {
          d += discounts[j].value;
        }
      }
    }
    var lineTotal = (price * qty) - d;
    if (lineTotal < 0) { lineTotal = 0 }
    var tax = lineTotal * taxRate;
    total += lineTotal + tax;
    receipt += item.name + ' x' + qty + ' = ' + (lineTotal + tax).toFixed(2) + '\n';
    if (item.stock < qty) {
      receipt += 'WARNING: not enough stock for ' + item.name + '\n';
    } else {
      inventory[o.id].stock = item.stock - qty;
    }
  }
  return { total: parseFloat(total.toFixed(2)), receipt: receipt, inventory: inventory };
}

/**
 * @typedef {Object} Order
 * @property {string} id
 * @property {number} [qty=1]
 *
 * @typedef {Object} Discount
 * @property {string} id
 * @property {'percent'|'flat'} type
 * @property {number} value
 *
 * @typedef {Object} Item
 * @property {string} name
 * @property {number} price
 * @property {number} stock
 *
 * @typedef {Object.<string, Item>} Inventory
 */

/**
 * Select discounts applicable to an item.
 */
const getItemDiscounts = (discounts, itemId) =>
  discounts.filter(({ id }) => id === itemId);

/**
 * Compute total discount for one unit price given a list of discounts.
 * Percent discounts apply to unit price; flat discounts are absolute.
 */
const computeUnitDiscount = (unitPrice, itemDiscounts) =>
  itemDiscounts.reduce((sum, { type, value }) => {
    if (type === 'percent') return sum + unitPrice * value;
    if (type === 'flat')    return sum + value;
    return sum;
  }, 0);

/**
 * Calculate financials for a single order line.
 */
const calculateLine = ({ price }, qty, taxRate, itemDiscounts) => {
  const safeQty = Math.max(1, qty ?? 1);
  const unitDiscount = computeUnitDiscount(price, itemDiscounts);
  const discountedUnit = Math.max(0, price - unitDiscount);
  const subtotal = discountedUnit * safeQty;
  const tax = subtotal * taxRate;
  const total = subtotal + tax;

  return { safeQty, unitDiscount, discountedUnit, subtotal, tax, total };
};

/**
 * Format a line for the receipt.
 */
const formatReceiptLine = (name, qty, total) =>
  `${name} x${qty} = ${total.toFixed(2)}`;

/**
 * Produce a stock warning if needed.
 */
const stockWarning = (name, have, need) =>
  have < need ? `WARNING: not enough stock for ${name}\n` : '';

/**
 * Safely update inventory without mutating the original object.
 */
const updateInventoryStock = (inventory, id, qty) => {
  const item = inventory[id];
  if (!item) return inventory; // no change if missing
  if (item.stock < qty) return inventory; // not enough stock; do not decrement

  return {
    ...inventory,
    [id]: { ...item, stock: item.stock - qty }
  };
};

/**
 * Main entry: process orders into totals, receipt, and a new inventory snapshot.
 * Pure-ish: returns a NEW inventory object, does not mutate inputs.
 *
 * @param {Order[]} orders
 * @param {number} taxRate
 * @param {Discount[]} discounts
 * @param {Inventory} inventory
 */
const processOrders = (orders = [], taxRate = 0, discounts = [], inventory = {}) => {
  const result = orders.reduce(
    (acc, { id, qty = 1 }) => {
      const item = inventory[id];
      if (!item) return acc; // skip missing items

      const itemDiscounts = getItemDiscounts(discounts, id);
      const { safeQty, total } = calculateLine(item, qty, taxRate, itemDiscounts);

      const receiptLine = formatReceiptLine(item.name, safeQty, total);
      const warning = stockWarning(item.name, item.stock, safeQty);

      // Only decrement stock when enough is available
      const nextInventory =
        item.stock >= safeQty ? updateInventoryStock(acc.inventory, id, safeQty) : acc.inventory;

      return {
        total: acc.total + total,
        receipt: acc.receipt + receiptLine + '\n' + warning,
        inventory: nextInventory
      };
    },
    { total: 0, receipt: '', inventory: { ...inventory } }
  );

  return {
    total: Number(result.total.toFixed(2)),
    receipt: result.receipt,
    inventory: result.inventory
  };
};

// ----- Example usage -----
// const orders = [{ id: 'A', qty: 2 }, { id: 'B' }];
// const taxRate = 0.08;
// const discounts = [{ id: 'A', type: 'percent', value: 0.1 }, { id: 'B', type: 'flat', value: 2 }];
// const inventory = {
//   A: { name: 'Widget A', price: 10, stock: 5 },
//   B: { name: 'Widget B', price: 8,  stock: 0 }
// };
// const result = processOrders(orders, taxRate, discounts, inventory);
// console.log(result);

Why it works:

• Specific Directives: You're not just asking to "make it better"; you're giving concrete directions on what to improve, guiding the AI toward modern and widely accepted solutions.

• Active Learning: The "explain the changes" section is the most valuable part. It turns a copy-paste action into a learning opportunity, helping you understand the principles behind clean code.

• Principle-Focused: Mentioning SOLID prompts the AI to think at an architectural level, not just a syntactic one.

4. "The Security Eye": Reviewing Code Before You Commit

In a fast-paced environment, you don't always have a teammate available to review your pull request immediately. The AI can act as a first line of defense, catching potential issues.

Prompt:

"Act as an Application Security (AppSec) Engineer conducting a code review. Analyze the following user-input handling code and identify potential security vulnerabilities.

C#
// Paste your C# code snippet (e.g., an API controller) here

Provide your feedback as a prioritized, ordered list, focusing on:

Critical Vulnerabilities: Such as SQL Injection, Cross-Site Scripting (XSS), or Insecure Deserialization.

Exploitable Logic Flaws: Such as improper authorization checks or race conditions.

Security Best Practices: Such as missing input validation, insecure error handling (leaking sensitive information), or use of weak cryptographic algorithms.

For each point identified, briefly explain the risk and suggest a code example for remediation."

Result:

[ApiController]
[Route("api")]
public class UsersController : ControllerBase
{
    [HttpGet("search")]
    public IActionResult Search(string q, string sort = "Name")
    {
        // ❌ Builds SQL from user input
        var sql = $"SELECT * FROM Users WHERE Name LIKE '%{q}%' ORDER BY {sort}";
        using var conn = new SqlConnection(_cs);
        using var cmd = new SqlCommand(sql, conn);
        conn.Open();
        using var r = cmd.ExecuteReader();
        return Ok(/* ... */);
    }

    [HttpPost("upload")]
    public async Task<IActionResult> Upload([FromForm] IFormFile file, string path)
    {
        // ❌ Path traversal
        var dest = Path.Combine("wwwroot", path, file.FileName);
        using var fs = System.IO.File.Create(dest);
        await file.CopyToAsync(fs);
        return Ok("Saved");
    }

    [HttpPost("profile")]
    public IActionResult SaveProfile([FromBody] string json)
    {
        // ❌ Insecure deserialization
        var settings = new JsonSerializerSettings { TypeNameHandling = TypeNameHandling.All };
        var obj = JsonConvert.DeserializeObject(json, settings);
        return Ok(obj);
    }

    [HttpPost("login")]
    public IActionResult Login(string user, string pwd)
    {
        // ❌ Weak hash
        using var md5 = MD5.Create();
        var hash = Convert.ToHexString(md5.ComputeHash(Encoding.UTF8.GetBytes(pwd)));
        // ... compare hash
        return Ok("ok");
    }

    [HttpGet("admin/export")]
    public IActionResult Export(string admin)
    {
        // ❌ Broken auth logic
        if (admin == "true") { /* export all users */ }
        return Unauthorized();
    }

    [HttpGet("proxy")]
    public async Task<IActionResult> Proxy(string url)
    {
        // ❌ SSRF + TLS disabled
        ServicePointManager.ServerCertificateValidationCallback += (_,_,_,_) => true;
        using var http = new HttpClient();
        var body = await http.GetStringAsync(url);
        return Content(body, "text/html"); // ❌ Reflected content
    }

    [HttpGet("oops")]
    public IActionResult Oops() {
        try { /* ... */ }
        catch (Exception ex) {
            return Problem(ex.ToString()); // ❌ Leaks stack & secrets
        }
    }
}

Prioritized Findings (with quick fixes)

[HttpGet("search")]
public IActionResult Search(string q, string sort = "Name")
{
    var allowedSort = new HashSet<string> { "Name", "CreatedAt" };
    var orderBy = allowedSort.Contains(sort) ? sort : "Name";

    const string sql = "SELECT * FROM Users WHERE Name LIKE @q ORDER BY " + /* safe */ "Name";
    using var conn = new SqlConnection(_cs);
    using var cmd = new SqlCommand(sql, conn);
    cmd.Parameters.AddWithValue("@q", $"%{q}%");
    conn.Open();
    using var r = cmd.ExecuteReader();
    // Or use EF Core with LINQ:
    // _db.Users.Where(u => u.Name.Contains(q)).OrderBy(u => EF.Property<object>(u, orderBy));
    return Ok(/* ... */);
}

Broken authorization via user-controlled flags

[Authorize(Roles = "Admin")]
[HttpGet("admin/export")]
public IActionResult Export()
{
    // Only executes if the user is authenticated as Admin
    return Ok(/* sensitive data */);
}

Why it works:

• Specialized Persona: "AppSec Engineer" activates a very different set of knowledge than "Senior Developer." The AI will look for specific patterns of dangerous code.

• Risk Prioritization: Asking for prioritization helps you focus on the most critical issues first.

• Actionable Advice: Requesting a "code example for remediation" provides immediate, practical value that goes far beyond a vague warning.

Part 2: Prompt Templates For Writing & Content Creation

For those who bridge the gap between technical work and communication, these prompts are the conduit for turning complex ideas into compelling content.

5. "The Title Maestro": Brainstorming Engaging Headlines

You've spent hours writing a deep technical analysis, but a boring title can ensure it's never read. This template helps you generate compelling headlines for different audiences.

Prompt:

"I have written a technical blog post about the challenges and benefits of adopting a microservices architecture in a growing organization. The target audience includes tech leads, software architects, and product managers.

Please suggest 7 headlines for this article, categorized as follows:

2 Direct and Clear Titles: Aimed at architects looking for solutions (e.g., Microservices: A Practical Guide to Sustainable Scaling).

2 Curiosity-Driven, Question-Based Titles: Aimed at tech leads (e.g., Is Your Team Ready for the Hidden Costs of Microservices?).

2 Business-Benefit-Focused Titles: Aimed at product managers (e.g., How Microservices Unlock Faster Release Cycles and Reduce Technical Debt).

1 Controversial or Myth-Busting Title: (e.g., Stop Idolizing Microservices. Here's the Harsh Reality.)."

Why it works:

• Audience Segmentation: By asking for titles for different personas, you force the AI to think about various angles and motivations, which creates variety and depth.

• Creative Structure: Categorizing by style (direct, curiosity, business) ensures you get a range of options rather than just variations of the same idea.

• Breaks Creative Blocks: Even if you don't use these exact titles, they often serve as excellent springboards for your own unique idea.

6. "The Content Architect": Building A Solid Outline

The "blank page syndrome" is real. Sometimes, the biggest hurdle is simply getting started. This prompt helps you turn a vague idea into an actionable article structure.

Prompt:

"I want to write an in-depth blog post titled 'Why Modern Frontend Developers Should Master Docker.'

Please create a detailed outline for this article. The outline should include:
Introduction (The Hook): Start with a common problem frontend developers face (e.g., the 'it works on my machine' problem).

Part 1: What is Docker? (A Beginner's Explanation): Use a simple analogy to explain containers and images, focusing on how they differ from VMs.

Part 2: Three Key Benefits for Frontend Devs:

2.1. Consistent Development Environments (Goodbye, 'it works on my machine').

2.2. Simplified Dependency Management (e.g., backend APIs, databases).

2.3. Deployment Confidence (Identical dev and prod environments).

Part 3: Quickstart: Dockerizing a Simple React App: Provide the key steps and an example Dockerfile.

Conclusion: Summarize the benefits and provide a call to action (e.g., 'Try Docker in your next project').

The tone of the article should be educational, encouraging, and accessible to those with no DevOps experience."

Why it works:

• Detailed and Directive: You're not just asking for an outline; you're co-creating it. By providing the key points you want to cover, you're guiding the AI to fill in the blanks intelligently.

• Establishes Narrative Flow: This template helps create a structured story, moving from a problem (the hook) to a solution (the benefits) and practical application (the tutorial).

• Defines the Tone: Specifying the tone ("educational, encouraging") ensures the language and approach of the outline will match the intended audience.

7. "The Word Sculptor": Turning Dry Prose Into Engaging Text

Sometimes you have all the right information, but the delivery is dry, academic, and lifeless. This prompt helps you breathe life into technical paragraphs.

Prompt:

"Please rewrite the following paragraph to make it more natural, engaging, and understandable for a technical audience that may not be experts on this specific topic.

Original Paragraph:

'The strategic implementation of database indexing is an essential performance optimization methodology that serves to mitigate query latency by enabling the database management system to more efficiently locate requested data rows without performing a full table scan, which is particularly beneficial in large datasets.'

Rewrite instructions:

Use a simple analogy or metaphor (e.g., the index of a book).

Start with a question to engage the reader.

Break up the long sentence into shorter, varied-length sentences.

Use an active voice and stronger verbs.

Retain the core meaning but make it more vibrant."

Why it works:

• Transforms Abstract to Concrete: Requesting an analogy forces the AI to find a way to relate a complex concept to something familiar.

• Focuses on Writing Technique: By pointing out specific elements like "shorter sentences" and "active voice," you're giving the AI a writer's toolkit to work with.

• Preserves Integrity: The emphasis on "retain the core meaning" ensures that creativity doesn't corrupt the technical accuracy.

Part 3: Prompt Templates For Strategy & Documentation

These templates bridge the gap between code and humans, from generating clear documentation to summarizing complex information.

8. "The Wise Scribe": Generating Documentation From Code

Documentation is a necessary but often neglected task. This prompt helps automate much of this tedious work, turning functions and classes into usable documentation.

Prompt:

"Act as a technical writer creating documentation for an internal API. Based on the function signature and brief comment below, generate a complete docstring in the Google Python Style format.

Python
# Processes and uploads user data to cloud storage.
def process_and_upload_user_data(user_id: int, data: Dict[str, Any], is_priority: bool = False) -> str:
    # ... implementation ...
The docstring must include:

A brief, one-line summary of the function's purpose.

A more detailed description of what it does and any side effects.

An Args: section detailing each parameter (name, type, and its meaning).

A Returns: section describing the return value (type and what it represents).

A Raises: section mentioning a potential exception that could be raised (e.g., ValueError if user_id is invalid)."

Result:

def process_and_upload_user_data(user_id: int, data: Dict[str, Any], is_priority: bool = False) -> str:
    """Process user data and upload it to cloud storage.

    This function validates the inputs, normalizes and serializes the provided
    `data` payload (e.g., trimming strings, coercing types, removing null-only
    fields), and uploads the resulting JSON blob to a configured cloud storage
    bucket. If `is_priority` is True, the upload uses a high-priority path
    (reduced backoff, higher timeout budget). The function returns the storage
    object identifier (e.g., a URL or "bucket/key" string).

    Side effects include network I/O to the storage provider, creation and
    cleanup of temporary files, emission of application logs/metrics, and
    retries with exponential backoff on transient errors.

    Args:
      user_id (int): The unique identifier of the user. Must be a positive
        integer. Used to namespace the storage key and for auditing.
      data (Dict[str, Any]): Arbitrary user data to process and upload.
        Expected to be JSON-serializable after normalization.
      is_priority (bool, optional): When True, uses priority upload settings
        (e.g., different queue/backoff/timeout). Defaults to False.

    Returns:
      str: The storage object identifier for the uploaded payload (e.g., a
      signed URL or a "bucket/key" path) that can be used to retrieve the data.

    Raises:
      ValueError: If `user_id` is not a positive integer or `data` is empty.
      TypeError: If `data` is not a mapping/dict.
      TimeoutError: If the upload exceeds the configured timeout.
      PermissionError: If the caller lacks permission to write to the bucket.
      RuntimeError: For other non-recoverable upload or serialization errors.
    """

Why it works:

• Adheres to a Standard: Requesting a specific format ("Google Python Style") ensures the output is consistent, professional, and can be immediately integrated into the codebase and automated documentation tools.

• Intelligent Inference: The AI can infer the purpose of parameters from their names and types (is_priority: bool), generating accurate descriptions even with minimal comments.

• Complete and Proactive: Asking for the Raises section encourages the AI to think about failure modes, leading to more complete documentation.

9. "The Information Synthesizer": Summarizing Large Code Files

When you need to get a quick understanding of a massive code file without reading every line, this prompt provides you with a high-level summary.

Prompt:

"Provide a structural summary of the following React component file. The goal is for another developer to quickly grasp its functionality without reading the entire source code.

JavaScript
// Paste the entire contents of the component file (e.g., UserProfile.jsx) here
The summary should be in a bulleted list format and cover:

Core Purpose: What does this component do? (e.g., 'Displays and allows editing of a user profile').

State Management: List the primary state variables managed by useState or useReducer and their purpose.

Input Props: List the most important props this component receives and what they are used for.

Side Effects: Describe the actions performed in useEffect (e.g., 'Fetches user data on component mount').

User Interactions: List the main event handler functions (e.g., handleSave, handleCancel) and what they do."

Result:

// UserProfile.jsx
import { useEffect, useMemo, useState } from "react";

export default function UserProfile({
  userId,
  api, // { getUser(id), updateUser(id, data), uploadAvatar(id, file) }
  onSaved,
  onCancel,
  canEdit = true,
  initialProfile = null,
  track, // optional analytics
}) {
  const [profile, setProfile] = useState(initialProfile);
  const [draft, setDraft] = useState(initialProfile);
  const [isEditing, setIsEditing] = useState(false);
  const [isLoading, setIsLoading] = useState(!initialProfile);
  const [isSaving, setIsSaving] = useState(false);
  const [error, setError] = useState(null);
  const [avatarFile, setAvatarFile] = useState(null);
  const [hasUnsavedChanges, setHasUnsavedChanges] = useState(false);

  // Derived
  const isValid = useMemo(() => {
    if (!draft) return false;
    if (!draft.name?.trim()) return false;
    if (draft.email && !/^\S+@\S+\.\S+$/.test(draft.email)) return false;
    return true;
  }, [draft]);

  // Fetch on mount / userId change
  useEffect(() => {
    let ignore = false;
    async function load() {
      if (!api || !userId) return;
      setIsLoading(true);
      setError(null);
      try {
        const data = await api.getUser(userId);
        if (ignore) return;
        setProfile(data);
        setDraft(data);
      } catch (e) {
        if (!ignore) setError(e);
      } finally {
        if (!ignore) setIsLoading(false);
      }
    }
    if (!initialProfile) load();
    return () => {
      ignore = true;
    };
  }, [api, userId]); // intentionally not depending on initialProfile

  // Track unsaved changes
  useEffect(() => {
    setHasUnsavedChanges(JSON.stringify(profile) !== JSON.stringify(draft) || !!avatarFile);
  }, [profile, draft, avatarFile]);

  // Warn before unload if unsaved
  useEffect(() => {
    if (!hasUnsavedChanges) return;
    const handler = (e) => {
      e.preventDefault();
      e.returnValue = "";
    };
    window.addEventListener("beforeunload", handler);
    return () => window.removeEventListener("beforeunload", handler);
  }, [hasUnsavedChanges]);

  const handleEdit = () => {
    if (!canEdit) return;
    setIsEditing(true);
    track?.("profile_edit_opened", { userId });
  };

  const handleFieldChange = (field, value) => {
    setDraft((d) => ({ ...d, [field]: value }));
  };

  const handleAvatarPick = (file) => {
    setAvatarFile(file);
  };

  const handleCancel = () => {
    setDraft(profile);
    setAvatarFile(null);
    setIsEditing(false);
    onCancel?.();
    track?.("profile_edit_canceled", { userId });
  };

  const handleSave = async () => {
    if (!isValid || !api) return;
    setIsSaving(true);
    setError(null);
    try {
      let updated = await api.updateUser(userId, draft);
      if (avatarFile) {
        const avatarUrl = await api.uploadAvatar(userId, avatarFile);
        updated = { ...updated, avatarUrl };
      }
      setProfile(updated);
      setDraft(updated);
      setAvatarFile(null);
      setIsEditing(false);
      onSaved?.(updated);
      track?.("profile_edit_saved", { userId });
    } catch (e) {
      setError(e);
    } finally {
      setIsSaving(false);
    }
  };

  if (isLoading) return <div className="p-4">Loading…</div>;
  if (error) return (
    <div className="p-4 text-red-600">
      Failed to load/save. <button onClick={() => window.location.reload()}>Retry</button>
    </div>
  );
  if (!profile) return <div className="p-4">No profile found.</div>;

  return (
    <div className="p-4 space-y-4 border rounded">
      <header className="flex items-center gap-3">
        <img
          src={avatarFile ? URL.createObjectURL(avatarFile) : profile.avatarUrl}
          alt="avatar"
          width={64}
          height={64}
          style={{ borderRadius: 8, objectFit: "cover" }}
        />
        <div className="grow">
          <h2 className="font-semibold">{profile.name || "Unnamed User"}</h2>
          <p className="text-sm text-gray-600">{profile.email}</p>
        </div>
        {canEdit && !isEditing && (
          <button onClick={handleEdit} className="px-3 py-1 border rounded">Edit</button>
        )}
      </header>

      {isEditing ? (
        <form className="space-y-3" onSubmit={(e) => { e.preventDefault(); handleSave(); }}>
          <div>
            <label>Name</label>
            <input
              value={draft.name || ""}
              onChange={(e) => handleFieldChange("name", e.target.value)}
              className="block w-full border px-2 py-1 rounded"
            />
          </div>
          <div>
            <label>Email</label>
            <input
              value={draft.email || ""}
              onChange={(e) => handleFieldChange("email", e.target.value)}
              className="block w-full border px-2 py-1 rounded"
            />
          </div>
          <div>
            <label>Bio</label>
            <textarea
              value={draft.bio || ""}
              onChange={(e) => handleFieldChange("bio", e.target.value)}
              className="block w-full border px-2 py-1 rounded"
              rows={3}
            />
          </div>
          <div>
            <label>Avatar</label>
            <input type="file" accept="image/*" onChange={(e) => handleAvatarPick(e.target.files?.[0])} />
            {avatarFile && <p className="text-xs">New avatar selected: {avatarFile.name}</p>}
          </div>

          <div className="flex gap-2">
            <button disabled={!isValid || isSaving} className="px-3 py-1 border rounded" type="submit">
              {isSaving ? "Saving…" : "Save"}
            </button>
            <button type="button" onClick={handleCancel} className="px-3 py-1 border rounded">
              Cancel
            </button>
          </div>
        </form>
      ) : (
        <section className="space-y-2">
          <p><strong>Bio:</strong> {profile.bio || "—"}</p>
        </section>
      )}
    </div>
  );
}

Why it works:

• Structured Analysis: Instead of a prose summary, asking for a breakdown by the specific aspects of a React component (state, props, effects) forces the AI to analyze the code systematically.

• Common Language: This template uses standard React terminology, making the summary instantly understandable to any React developer.

• Accelerates Onboarding: This is an invaluable tool for getting up to speed on a new codebase or for preparing to refactor a complex part of an application.

10. "The Rapid Debugger": Deciphering Cryptic Error Messages

You could Google an error message. Or you could paste it along with the relevant code into an AI that has been trained on millions of them and their solutions.

Prompt:

"I'm encountering the following Python error in my Flask application.

Error Message:
KeyError: 'user_profile'
Relevant Code Snippet:

Python

# Paste the code that causes the error, including a few lines of context
data = request.get_json()
profile = data['user_profile']
user_name = profile['name']

Please explain this error clearly:

What the error means: What exactly does a KeyError signify in this context?

Likely Root Causes: List the 3 most common reasons this could be happening (e.g., the client didn't send the key, there's a typo in the key name, the JSON payload has a different structure).

Fix and Prevention Strategies: Propose two ways to fix this. One should be a defensive fix (using .get() with a default value). The other should be a more explicit error-handling approach (using a try...except block). Explain the advantage of each approach."

Result:

from flask import Flask, request, jsonify

app = Flask(__name__)

@app.route("/profile", methods=["POST"])
def profile_handler():
    data = request.get_json() or {}

    # --- Defensive way (safe defaults) ---
    profile = data.get("user_profile", {})
    user_name = profile.get("name", "Guest")

    # --- Explicit error handling ---
    try:
        strict_profile = data["user_profile"]
        strict_name = strict_profile["name"]
    except KeyError as e:
        return jsonify({"error": f"Missing key: {e.args[0]}"}), 400

    return jsonify({
        "defensive_user_name": user_name,
        "strict_user_name": strict_name
    })

if __name__ == "__main__":
    app.run(debug=True)

Why it works:

• From Fix to Understanding: This prompt doesn't just ask for a solution. It asks for an explanation of the error's meaning and causes, helping you learn how to avoid it in the future.

• Multiple Solution Options: Requesting multiple fix strategies (defensive vs. explicit) shows a deeper understanding that there's no single perfect solution for every scenario.

• Context is Everything: Providing both the error and the code allows the AI to give a much more accurate diagnosis than pasting the error message alone.

11. "The Technical Strategist": Decomposing A Feature Request

One of the biggest challenges in software development isn't writing code, but translating a vague product requirement into a clear technical action plan. This prompt turns the AI into a seasoned tech lead, helping you break down complex features into smaller, more manageable tasks.

Prompt:

"Act as a Principal Engineer planning the technical implementation for a new feature.

Feature Request: 'We want to allow users to sign in to our web application using their Google and Facebook accounts.'

Technical Context:

Frontend: React

Backend: Node.js with Express

Database: PostgreSQL

Based on this request and context, decompose this feature into a detailed list of technical tasks. Group the tasks by area (Frontend, Backend, Database). Present the output as a Markdown checklist. Each task should be a small, concrete, and shippable unit of work. Include configuration and security-related tasks as well."

Result:

/**
 * server.js — Single-file demo: Google + Facebook OAuth with Express + Passport
 * Run: 1) npm i express passport passport-google-oauth20 passport-facebook express-session helmet morgan cors zod uuid pg connect-pg-simple dotenv
 *      2) Create .env (see below)
 *      3) node server.js
 *
 * .env example:
 * NODE_ENV=development
 * PORT=4000
 * APP_BASE_URL=http://localhost:4000
 * FRONTEND_BASE_URL=http://localhost:4000
 * DATABASE_URL=postgres://postgres:postgres@localhost:5432/aifire
 * SESSION_SECRET=replace_me_with_long_random
 * GOOGLE_CLIENT_ID=xxx.apps.googleusercontent.com
 * GOOGLE_CLIENT_SECRET=xxx
 * GOOGLE_CALLBACK_URL=http://localhost:4000/auth/google/callback
 * FACEBOOK_CLIENT_ID=xxx
 * FACEBOOK_CLIENT_SECRET=xxx
 * FACEBOOK_CALLBACK_URL=http://localhost:4000/auth/facebook/callback
 *
 * --- Minimal DB schema (run once) ---
 * CREATE EXTENSION IF NOT EXISTS "uuid-ossp";
 *
 * CREATE TABLE IF NOT EXISTS users (
 *   id uuid PRIMARY KEY,
 *   email text UNIQUE,
 *   email_verified boolean DEFAULT false,
 *   name text,
 *   avatar_url text,
 *   created_at timestamptz DEFAULT now(),
 *   updated_at timestamptz DEFAULT now()
 * );
 *
 * CREATE TYPE auth_provider AS ENUM ('google', 'facebook');
 * -- If type exists, skip the CREATE TYPE and ensure values cover both providers.
 *
 * CREATE TABLE IF NOT EXISTS user_identities (
 *   id uuid PRIMARY KEY,
 *   user_id uuid REFERENCES users(id) ON DELETE CASCADE,
 *   provider auth_provider NOT NULL,
 *   provider_user_id text NOT NULL,
 *   created_at timestamptz DEFAULT now(),
 *   UNIQUE (provider, provider_user_id)
 * );
 *
 * -- Sessions table for connect-pg-simple:
 * CREATE TABLE IF NOT EXISTS "session" (
 *   "sid" varchar NOT NULL COLLATE "default",
 *   "sess" json NOT NULL,
 *   "expire" timestamp(6) NOT NULL,
 *   CONSTRAINT "session_pkey" PRIMARY KEY ("sid")
 * );
 * CREATE INDEX IF NOT EXISTS "IDX_session_expire" ON "session" ("expire");
 */

require('dotenv').config();
const express = require('express');
const helmet = require('helmet');
const morgan = require('morgan');
const cors = require('cors');
const session = require('express-session');
const passport = require('passport');
const GoogleStrategy = require('passport-google-oauth20').Strategy;
const FacebookStrategy = require('passport-facebook').Strategy;
const { z } = require('zod');
const { v4: uuid } = require('uuid');
const { Pool } = require('pg');
const PgSession = require('connect-pg-simple')(session);

const {
  NODE_ENV = 'development',
  PORT = 4000,
  APP_BASE_URL = 'http://localhost:4000',
  FRONTEND_BASE_URL = 'http://localhost:4000',
  DATABASE_URL,
  SESSION_SECRET,
  GOOGLE_CLIENT_ID,
  GOOGLE_CLIENT_SECRET,
  GOOGLE_CALLBACK_URL,
  FACEBOOK_CLIENT_ID,
  FACEBOOK_CLIENT_SECRET,
  FACEBOOK_CALLBACK_URL
} = process.env;

if (!DATABASE_URL || !SESSION_SECRET) {
  console.error('Missing DATABASE_URL or SESSION_SECRET');
  process.exit(1);
}

const app = express();
const pool = new Pool({ connectionString: DATABASE_URL });

// --- Middlewares ---
app.use(helmet({
  contentSecurityPolicy: {
    useDefaults: true,
    directives: {
      // Allow inline style for the tiny demo HTML
      "style-src": ["'self'", "'unsafe-inline'"],
      "img-src": ["'self'", "data:"]
    }
  },
  crossOriginEmbedderPolicy: false
}));
app.use(morgan('dev'));
app.use(express.json({ limit: '100kb' }));
app.use(express.urlencoded({ extended: false, limit: '100kb' }));

// If you host FE separately, adjust origin allowlist here.
app.use(cors({
  origin: [FRONTEND_BASE_URL],
  credentials: true
}));

app.set('trust proxy', 1);

// --- Session store (Postgres) ---
app.use(session({
  store: new PgSession({
    pool,
    tableName: 'session'
  }),
  name: 'sid',
  secret: SESSION_SECRET,
  resave: false,
  saveUninitialized: false,
  cookie: {
    httpOnly: true,
    sameSite: 'lax',
    secure: NODE_ENV === 'production',
    maxAge: 1000 * 60 * 60 * 24 * 7 // 7 days
  }
}));

// --- Passport setup ---
app.use(passport.initialize());
app.use(passport.session());

// Serialize/deserialize only user.id
passport.serializeUser((user, done) => done(null, user.id));
passport.deserializeUser(async (id, done) => {
  try {
    const { rows } = await pool.query('SELECT * FROM users WHERE id = $1', [id]);
    done(null, rows[0] || null);
  } catch (e) {
    done(e);
  }
});

// --- Common helpers ---
async function findOrCreateUser({ provider, providerUserId, email, name, avatar }) {
  // 1) by identity
  const q1 = `
    SELECT u.* FROM user_identities ui
    JOIN users u ON u.id = ui.user_id
    WHERE ui.provider = $1 AND ui.provider_user_id = $2
    LIMIT 1
  `;
  const r1 = await pool.query(q1, [provider, providerUserId]);
  if (r1.rows.length) return r1.rows[0];

  // 2) by email (if given)
  let user = null;
  if (email) {
    const r2 = await pool.query('SELECT * FROM users WHERE lower(email) = lower($1) LIMIT 1', [email]);
    if (r2.rows.length) user = r2.rows[0];
  }

  // 3) create user if not exists
  if (!user) {
    const id = uuid();
    const r3 = await pool.query(
      `INSERT INTO users (id, email, email_verified, name, avatar_url)
       VALUES ($1, $2, $3, $4, $5) RETURNING *`,
      [id, email || null, !!email, name || null, avatar || null]
    );
    user = r3.rows[0];
  }

  // 4) attach identity
  await pool.query(
    `INSERT INTO user_identities (id, user_id, provider, provider_user_id)
     VALUES ($1, $2, $3, $4)
     ON CONFLICT DO NOTHING`,
    [uuid(), user.id, provider, providerUserId]
  );

  return user;
}

// --- Google Strategy ---
if (GOOGLE_CLIENT_ID && GOOGLE_CLIENT_SECRET && GOOGLE_CALLBACK_URL) {
  passport.use(new GoogleStrategy(
    {
      clientID: GOOGLE_CLIENT_ID,
      clientSecret: GOOGLE_CLIENT_SECRET,
      callbackURL: GOOGLE_CALLBACK_URL,
      scope: ['openid', 'email', 'profile']
    },
    async (_accessToken, _refreshToken, profile, done) => {
      try {
        const email = profile.emails?.[0]?.value || null;
        const name = profile.displayName || null;
        const avatar = profile.photos?.[0]?.value || null;
        const user = await findOrCreateUser({
          provider: 'google',
          providerUserId: profile.id,
          email, name, avatar
        });
        return done(null, user);
      } catch (e) {
        return done(e);
      }
    }
  ));
}

// --- Facebook Strategy ---
if (FACEBOOK_CLIENT_ID && FACEBOOK_CLIENT_SECRET && FACEBOOK_CALLBACK_URL) {
  passport.use(new FacebookStrategy(
    {
      clientID: FACEBOOK_CLIENT_ID,
      clientSecret: FACEBOOK_CLIENT_SECRET,
      callbackURL: FACEBOOK_CALLBACK_URL,
      profileFields: ['id', 'emails', 'displayName', 'photos'],
      enableProof: true
    },
    async (_accessToken, _refreshToken, profile, done) => {
      try {
        const email = profile.emails?.[0]?.value || null;
        const name = profile.displayName || null;
        const avatar = profile.photos?.[0]?.value || null;
        const user = await findOrCreateUser({
          provider: 'facebook',
          providerUserId: profile.id,
          email, name, avatar
        });
        return done(null, user);
      } catch (e) {
        return done(e);
      }
    }
  ));
}

// --- Small Zod validator for callback query ---
const CallbackQuery = z.object({
  state: z.string().optional(),
  code: z.string().optional(),
  error: z.string().optional()
});

// --- Auth routes ---
app.get('/auth/providers', (_req, res) => {
  res.json({
    google: !!GOOGLE_CLIENT_ID,
    facebook: !!FACEBOOK_CLIENT_ID
  });
});

// Google
app.get('/auth/google',
  (req, res, next) => {
    // You can pass dynamic "state" if needed
    next();
  },
  passport.authenticate('google')
);

app.get('/auth/google/callback',
  (req, res, next) => {
    const v = CallbackQuery.safeParse(req.query);
    if (!v.success) return res.status(400).send('Invalid callback params');
    next();
  },
  passport.authenticate('google', { failureRedirect: '/login?error=google' }),
  (req, res) => {
    res.redirect('/');
  }
);

// Facebook
app.get('/auth/facebook',
  passport.authenticate('facebook', { scope: ['email'] })
);

app.get('/auth/facebook/callback',
  (req, res, next) => {
    const v = CallbackQuery.safeParse(req.query);
    if (!v.success) return res.status(400).send('Invalid callback params');
    next();
  },
  passport.authenticate('facebook', { failureRedirect: '/login?error=facebook' }),
  (req, res) => {
    res.redirect('/');
  }
);

// Session status
app.get('/auth/session', (req, res) => {
  if (!req.user) return res.json({ authenticated: false, user: null });
  const { id, email, name, avatar_url } = req.user;
  res.json({
    authenticated: true,
    user: { id, email, name, avatar_url }
  });
});

// Logout
app.post('/auth/logout', (req, res) => {
  req.logout(() => {
    req.session.destroy(() => {
      res.clearCookie('sid');
      res.status(204).end();
    });
  });
});

// --- Minimal UI for testing (no React, just to prove it works) ---
const page = `
<!doctype html>
<html>
<head>
  <meta charset="utf-8" />
  <title>OAuth Demo</title>
  <meta name="viewport" content="width=device-width, initial-scale=1" />
  <style>
    html,body { font-family: system-ui, -apple-system, Segoe UI, Roboto, sans-serif; margin:0; padding:0; }
    .wrap { max-width: 640px; margin: 40px auto; padding: 24px; }
    button { padding: 10px 14px; border-radius: 8px; border: 1px solid #ddd; cursor: pointer; }
    .row { display: flex; gap: 12px; margin: 12px 0; }
    .card { border:1px solid #eee; padding:16px; border-radius:12px; }
    code { background:#f8f8f8; padding:2px 6px; border-radius:6px; }
  </style>
</head>
<body>
<div class="wrap">
  <h1>Login Demo</h1>

  <div class="card">
    <div class="row">
      <a href="/auth/google"><button>Sign in with Google</button></a>
      <a href="/auth/facebook"><button>Sign in with Facebook</button></a>
      <button id="logout">Logout</button>
    </div>
    <div id="status" class="row"></div>
  </div>

  <p>Check session via <code>/auth/session</code>. This is a quick smoke test.</p>
  <script>
    async function refresh() {
      const r = await fetch('/auth/session', { credentials: 'include' });
      const j = await r.json();
      const s = document.getElementById('status');
      if (j.authenticated) {
        s.innerHTML = '<b>Logged in:</b> ' + (j.user.email || j.user.name || j.user.id);
      } else {
        s.innerHTML = '<b>Not logged in</b>';
      }
    }
    document.getElementById('logout').onclick = async () => {
      await fetch('/auth/logout', { method: 'POST', credentials: 'include' });
      refresh();
    };
    refresh();
  </script>
</div>
</body>
</html>
`;

app.get('/', (_req, res) => res.type('html').send(page));
app.get('/login', (_req, res) => res.type('html').send(page));

// --- Healthcheck ---
app.get('/healthz', async (_req, res) => {
  try {
    await pool.query('SELECT 1');
    res.json({ ok: true });
  } catch (e) {
    res.status(500).json({ ok: false, error: e.message });
  }
});

app.listen(PORT, () => {
  console.log(`Auth demo running on ${APP_BASE_URL}`);
});

Why it works:

• Translates 'What' into 'How': This prompt takes a high-level business requirement and translates it into the language of engineering. It creates a clear roadmap that the development team can immediately start working on.

• Identifies Parallel Workstreams: By grouping tasks into Frontend, Backend, and Database, it helps identify which parts of the work can be done concurrently, optimizing assignments and speeding up development.

• Anticipates Hidden Work: It doesn't just think about buttons and APIs. The request for "configuration and security" prompts the AI to suggest critical but often-overlooked tasks like managing API keys/secrets securely, handling callback URLs, and updating security policies.

• Aids in Estimation and Sprint Planning: This detailed task list provides the perfect foundation for the team to estimate the effort for each item, leading to more accurate sprint planning.

Conclusion: From AI User To AI Collaborator

You don't need to be a "prompt engineer" to get better answers from AI. You just need better prompts.

These eleven templates are my daily drivers - in real development projects, in real writing tasks, and under the pressure of real deadlines. They are not hacks or tricks; they are structured frameworks for thinking and communicating with a new kind of intelligence.

They save time. They improve quality. And most importantly, they help me think faster and more deeply.

Start with one. Tweak it. Make it your own. Adapt it to your programming language, your frameworks, and your workflow.

And when you hit that moment where the prompt gives back something better than you expected - an angle you hadn't considered, an edge case you'd missed, a more elegant turn of phrase - that's when you'll know you've stopped using AI and started collaborating with it. That is the future of creative and technical work.

If you are interested in other topics and how AI is transforming different aspects of our lives or even in making money using AI with more detailed, step-by-step guidance, you can find our other articles here:

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