Why Your AI Output is Average

Ye tools use karte ho:

🤖 Claude 💬 ChatGPT ⚡ Cursor 🔵 GitHub Copilot

Aur output generic aata hai. Tum sochte ho — prompt better likhna chahiye. Lekin problem actually prompt nahi hai. Problem yeh hai ki AI ko context kaise de rahe ho.

Hum plain text padhte hain linearly — upar se neeche. AI alag karta hai. AI pehle structure ko scan karta hai — headings, lists, bold text, code blocks. Jo cheez structured nahi hai, usse AI ek generic blob ki tarah treat karta hai.

How AI Processes Context
  ── Human Reading ──────────────────────────────────────────────
  Top → bottom, word by word, linear

  ── AI Processing ──────────────────────────────────────────────

  Step 1: Structure scan
    # Heading found    → HIGH PRIORITY section marker
    ## Sub-heading     → SECTION BOUNDARY
    **bold text**      → CRITICAL INFORMATION
    - bullet point     → RULE / CONSTRAINT (follow this)
    ```code```         → TECHNICAL SPEC (literal, not paraphrase)
    | table |          → STRUCTURED DATA (process as unit)

  Step 2: Unstructured text
    "big paragraph with everything in one block"
    → AI treats as BACKGROUND / LOW PRIORITY blob
    → Important details inside? Likely missed.
            
The insight: Markdown nahi likhte toh AI ko wo signals nahi milte jo usse batate hain ki kaunsi cheez important hai. Sab kuch equally low-priority lagta hai. Isliye output generic hota hai.

Rule 1 — Headings High Priority Signal

1

AI headings ko section boundaries ki tarah padhta hai. Heading ke andar jo bhi hai — AI usse us section ka context maanta hai. Jo heading ke bina hai — wo AI ke liye low priority floating text hai.

Practical example: agar tujhe AI se koi complex kaam karwana hai jisme alag-alag parts hain — unhe headings mein tod do. AI har section ko independently process karta hai aur usse zyaada accurately follow karta hai.

Without Headings — AI Treats as Blob
I want you to review my code. Check for performance issues. Also look at security. Make sure naming conventions are followed. Return all findings.
With Headings — AI Follows Each Section
## Task Review the code below. ## Check For - Performance issues - Security vulnerabilities - Naming convention violations ## Output Format Return findings per category.
Rule: Jo cheez heading nahi hai — AI ke liye wo low priority hai. Heading nahi banaya, toh AI skip kar sakta hai.

Rule 2 — Bullets aur Numbered Lists Rules AI Follows

2

Paragraph mein likha rule — AI skip kar sakta hai. List mein likha rule — AI follow karta hai. Yeh difference critical hai jab tujhe AI se specific constraints ya steps follow karwane hain.

Numbered lists especially effective hain jab sequence matter karta hai. AI numbered lists ko ordered steps ki tarah treat karta hai — ek-ek follow karta hai.

Paragraph — Rules Get Lost
Please write the function in TypeScript and make sure it handles null inputs and also the response should be typed properly and don't use any and add JSDoc comments to explain what it does.
List — Every Rule is Followed
Write a TypeScript function. Requirements: 1. Handle null inputs explicitly 2. All types must be defined — no `any` 3. Return type must be typed 4. Add JSDoc with @param and @returns
Pro tip: Agar koi constraint ya requirement hai jo AI zaroor follow kare — list mein dalo. Paragraph mein diya toh AI "suggested" treat karta hai, "required" nahi.

Rule 3 — Code Blocks Literal Spec Signal

3

Code blocks ke andar AI sirf literal code expect karta hai. Sirf code daalo andar — explanation nahi. Dono mix karo — AI dono ko ek saath confuse kar deta hai aur output unpredictable hota hai.

Yeh ek common mistake hai: log code block ke andar explanation aur code dono daalte hain. AI tab code ko paraphrase karne lagta hai — literal interpret nahi karta. Code literally follow karwana hai? Code block mein sirf code hona chahiye.

Mixed — AI Gets Confused
``` // This function should get user from DB // Make sure to handle errors properly // userId is a string UUID async function getUser(userId) { // add your implementation } // Don't forget to return null if not found ```
Separated — AI Processes Each Correctly
## Implement this function: - userId is a string UUID - Return null if user not found - Handle DB errors with try/catch ```typescript async function getUser( userId: string ): Promise<User | null> { // implement } ```
Rule: Code block = sirf code. Instructions code block ke bahar, heading ya list mein. Mix karoge toh AI dono ko aadha-aadha process karta hai.

Rule 4 — Bold Text Critical Priority Signal

4

AI bold text ko highest priority signal maanta hai. Bina bold ke — sab kuch equally important lagta hai AI ko. Jab sab equally important hota hai, AI guess karta hai ki kya matter karta hai.

Bold specifically use karo un cheezon ke liye jo AI kabhi miss nahi karna chahiye — constraints, hard requirements, exceptions, critical output format instructions.

No Bold — AI Guesses Priority
Refactor this service to be async. Keep the existing API contract unchanged. Do not modify any test files. Use dependency injection for the database. The function names should stay the same.
Bold Used — AI Knows What's Critical
Refactor this service to be async. Constraints (non-negotiable): - Do NOT modify any test files - Keep existing API contract unchanged - Function names must stay the same Use dependency injection for the database.
How to think about bold: Agar AI yeh miss kare aur tujhe dobara karna pade — bold karo. Agar yeh miss ho toh "it's fine" — bold mat karo. Bold inflation se backo — sab kuch bold kiya toh nothing is bold.

Rule 5 — Tables Structured Data Signal

5

Jab bhi compare karna ho ya structured data ho — table use karo. Plain text mein likha comparison — AI partially process karta hai. Table mein — AI poora context ek saath leta hai because table ek self-contained data structure hai.

Tables especially powerful hain jab AI ko multiple attributes ke against compare karwana ho, ya jab alag-alag cases ke liye alag behavior define karna ho.

Plain Text — Partial Processing
For admin users show all data and allow delete. For editor users show all data but don't allow delete. For viewer users only show published data and no delete. All users need to be logged in.
Table — AI Gets Full Context at Once
## Access Control Rules | Role | Data Access | Can Delete | |---------|---------------|------------| | Admin | All records | ✅ Yes | | Editor | All records | ❌ No | | Viewer | Published only| ❌ No | All roles require authentication.
Where tables shine: Role-based permissions, environment configs (dev/staging/prod), API field definitions, feature comparison, error codes and their handlers. Koi bhi cheez jisme rows aur columns naturally fit hon — table better hai.

Copy-Paste Template

Yeh structure use karo har complex AI task ke liye. Fill in the blanks:

AI Context Template — Copy & Use
# [Task Name]

## Context
[Brief background — 1-3 sentences. What is this, what does it do?]

## Task
[What exactly do you want AI to do? One clear sentence.]

## Requirements
1. [First requirement — use numbered list for ordered steps]
2. [Second requirement]
3. [Third requirement]

## Constraints
- **[Non-negotiable constraint — bold it]**
- **[Another hard constraint]**
- [Softer guideline — no bold needed]

## Input
```[language]
[paste your code / data / config here — ONLY the code, no explanation]
```

## Output Format
[What should the output look like? Table? Code? List? Explain clearly.]

| If comparing options | Use a table like this |
|---------------------|-----------------------|
| Option A            | Description           |
| Option B            | Description           |
Quick checklist before sending to AI: Is there a clear heading for each part? Are requirements in a list? Is code inside a code block (with no mixed explanation)? Are hard constraints bolded? Is any comparison in a table?
Key Takeaways
  • AI plain text ko blob ki tarah treat karta hai. Structure se hi AI ko pata chalta hai kya important hai.
  • Headings = section boundaries. Heading nahi hai toh AI usse low-priority maanta hai.
  • Lists = rules AI follow karta hai. Paragraph mein likha rule "suggested" hota hai, "required" nahi.
  • Code blocks mein sirf code — explanation bahar rakho. Mix karna = AI confuse ho jaata hai.
  • Bold = highest priority signal. Jo cheez AI kabhi miss nahi karna chahiye — woh bold karo. Sab kuch bold mat karo.
  • Tables = structured data AI ek saath process karta hai. Comparison ya multi-attribute rules? Always use tables.
  • Yeh rules Claude, ChatGPT, Cursor, Copilot — sabke liye kaam karte hain. Markdown is the universal language of AI context.