GPT-5.6 Prompt Playbook

By Arjav Jain

Brand: @lifeofarjav

Use case: A launch-ready prompting guide for getting the most out of GPT-5.6, or whichever latest GPT model is available when you use this.

A clean, practical prompt library for research, writing, content, business strategy, sales, coding, data analysis, agents, automation, and personal productivity.

Built for people who do not want generic AI output. Use this when you want sharper thinking, cleaner execution, and repeatable workflows.

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Important Note Before You Use This

At the time of creating this guide, public details about GPT-5.6, Sol, Terra, and Luna may still change or may not be fully confirmed in official OpenAI documentation.

So treat this playbook as model-ready, not rumor-dependent.

Use it with:

• GPT-5.6 if and when available
• The latest GPT model in ChatGPT
• GPT models in the OpenAI API
• Any future GPT model where better reasoning, writing, coding, multimodal understanding, or agentic workflows are available

Arjav note: The lazy version is asking, “What can this model do?” The useful version is building a test bench, running your real workflows through it, and finding where the new model actually changes your output.

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The @lifeofarjav Prompting Formula

Use this structure when writing your own prompts:

ROLE:
Act as [expert role].

GOAL:
Help me achieve [specific outcome].

CONTEXT:
Here is the relevant background: [context].

INPUT:
Here is the actual material to work on: [input].

CONSTRAINTS:
Follow these rules: [rules, tone, format, limits].

OUTPUT:
Return the answer as [table, checklist, brief, markdown, JSON, script, etc.].

QUALITY BAR:
Before finalizing, check for gaps, assumptions, hallucinations, weak logic, and generic advice.

A strong GPT prompt has five things:

1. A clear job
2. Real context
3. Specific constraints
4. A defined output format
5. A quality check before the final answer

If one of these is missing, the model has room to produce vague nonsense.

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How to Use This Playbook

1. Pick the category closest to your task.
2. Copy the prompt.
3. Replace placeholders like [TOPIC], [PRODUCT], [CONTEXT], [TEXT], [DATA], [AUDIENCE], [GOAL], and [URL].
4. Add your own examples if quality matters.
5. Ask the model to critique its own output before you use it.
6. Save prompts that work into your own Notion, ChatGPT Project, custom GPT, or API workflow.

Do not just collect prompts.

Test them, improve them, and turn the winning ones into your personal operating system.

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Launch-Day GPT-5.6 Testing Protocol

Use this when a new model drops.

Step 1: Build a benchmark set

Create 10 real tasks you actually care about:

Step 2: Run the same prompts across models

If Sol, Terra, and Luna become available, test the same prompt across all three.

Step 3: Score output brutally

Use this scorecard:

Step 4: Build your model routing system

Do not use the strongest model for everything. That is expensive and lazy.

Use the best model for the job:

• Use the strongest model for strategy, research, complex coding, and important decisions.
• Use the balanced model for everyday drafting, analysis, and planning.
• Use the cheaper model for formatting, cleanup, extraction, and first drafts.

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Table of Contents

1. Launch Setup & Model Testing
2. Research & Truth
3. Writing & Voice
4. Content & Social Growth
5. Business Strategy
6. Sales & Outreach
7. Coding & Product
8. Agents & Automation
9. Data & Analysis
10. Learning & Personal OS

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1. Launch Setup & Model Testing

Prompt 01: Model Comparison Bench

Act as an AI model evaluator. I want to compare [MODEL A], [MODEL B], and [MODEL C] on my real workflows.

Create a benchmark test suite with 10 tasks across writing, research, strategy, coding, data analysis, vision, and automation.

For each task, give me:
1. The exact test prompt
2. The ideal output criteria
3. The failure modes to watch for
4. A scoring rubric from 1-10
5. Which model type should win and why

My main use cases are: [USE CASES].
Return this as a clean table.

Prompt 02: Launch-Day Feature Discovery

Act as a power user testing a newly released GPT model.

Based on the model behavior I show you below, identify what seems improved, what still looks weak, and what use cases I should test next.

Input:
[PASTE MODEL OUTPUTS OR OBSERVATIONS]

Return:
1. Likely strengths
2. Likely weaknesses
3. 10 high-leverage tests to run
4. 5 workflows where this model may save me time
5. 5 places where I should not trust it yet

Be skeptical. Do not hype the model without evidence.

Prompt 03: Personal GPT Setup

Help me configure ChatGPT for my work.

My role: [ROLE]
My goals: [GOALS]
My writing style: [STYLE]
My recurring tasks: [TASKS]
My standards: [STANDARDS]
Things I hate in AI output: [DISLIKES]

Create:
1. Custom instructions
2. A reusable project description
3. A personal voice card
4. Default output rules
5. A checklist the model should use before answering

Make it strict, practical, and optimized for high-quality work.

Prompt 04: Sol vs Terra vs Luna Router

Assume I have access to three model tiers:
- Sol: strongest, highest quality
- Terra: balanced
- Luna: lower-cost, faster

Build a routing system for my workflows.

My workflows:
[LIST WORKFLOWS]

For each workflow, tell me:
1. Best model tier
2. Why
3. Required context
4. Output format
5. Risk level if the cheaper model gets it wrong
6. When to escalate to a stronger model

Return as a decision table.

Prompt 05: Prompt Upgrade Audit

Audit this prompt and make it 10x stronger for a latest-generation GPT model.

Prompt:
[PROMPT]

Improve it by adding:
1. Clear role
2. Specific goal
3. Context requirements
4. Output format
5. Quality checks
6. Hallucination controls
7. Optional examples

Return:
- The upgraded prompt
- What changed
- Why it will perform better
- What information I should add before using it

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2. Research & Truth

Prompt 06: Evidence-First Research Brief

Act as a research analyst. Research [TOPIC] using only the sources I provide.

Sources:
[PASTE SOURCES]

Return:
1. One-sentence bottom line
2. 5 key findings
3. Evidence supporting each finding
4. Where sources disagree
5. What is unknown
6. What decision this should inform
7. Confidence level for each claim

Do not invent sources. If evidence is missing, say so clearly.

Prompt 07: Source Conflict Map

Analyze these sources about [TOPIC].

Sources:
[PASTE SOURCES]

Create a conflict map:
1. Claims all sources agree on
2. Claims that conflict
3. Why they may conflict
4. Which source is most credible and why
5. What evidence would settle the disagreement
6. My recommended conclusion

Be brutally honest. Do not average weak evidence into a fake consensus.

Prompt 08: Fact Check Table

Fact-check this text line by line.

Text:
[TEXT]

Return a table with:
- Claim
- Verdict: supported, disputed, unverifiable, misleading, or false
- Evidence
- Confidence level
- What would change your mind
- Safer rewrite

Do not soften the verdict. If the claim is weak, say it is weak.

Prompt 09: Executive Research Memo

Turn this research into an executive memo for a founder.

Research:
[PASTE RESEARCH]

Format:
1. Bottom line in one sentence
2. What matters
3. What is noise
4. Strategic implications
5. Risks
6. Recommended next move
7. Questions still unanswered

Keep it sharp, decision-oriented, and free of academic filler.

Prompt 10: Blind Spot Finder

I am about to make this decision:
[DECISION]

Here is my reasoning:
[REASONING]

Act as a skeptical advisor. Find:
1. What I am assuming
2. What I am underestimating
3. What incentives I may be ignoring
4. What could go wrong
5. What evidence would change the decision
6. The strongest argument against my current view

End with a clear recommendation.

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3. Writing & Voice

Prompt 11: Voice Card Builder

Analyze these writing samples and build my voice card.

Samples:
[SAMPLES]

Extract:
1. Sentence length patterns
2. Common phrases
3. Tone
4. Rhythm
5. Topics I sound strongest on
6. Words I overuse
7. Words I should avoid
8. “Sounds like me” examples
9. “Does not sound like me” examples

Then create a reusable instruction block I can paste before writing prompts.

Prompt 12: Human Rewrite

Rewrite this AI-generated text so it sounds human, sharp, and natural.

Text:
[TEXT]

Rules:
- Remove generic phrases
- Vary sentence length
- Add specificity
- Keep the meaning intact
- Avoid corporate filler
- Do not make it overdramatic

Return:
1. Rewritten version
2. What you changed
3. Sentences that still feel weak
4. One punchier version if I want it more direct

Prompt 13: Founder Essay Draft

Write a founder-style essay about [TOPIC].

Context:
[CONTEXT]

Voice:
[VOICE NOTES]

Structure:
1. Sharp opening claim
2. Personal observation
3. The mistake most people make
4. The lesson
5. Practical takeaway
6. Final line that sticks

Keep it under [WORD COUNT]. Make it intelligent, direct, and not motivational-poster nonsense.

Prompt 14: LinkedIn Post From Raw Thought

Turn this messy thought into a strong LinkedIn post.

Raw thought:
[TEXT]

Audience:
[AUDIENCE]

Goal:
[GOAL]

Rules:
- Strong first line
- Short paragraphs
- No fake vulnerability
- No generic “here are 5 lessons”
- Add one specific example
- End with a question that invites comments

Return 3 versions:
1. Direct
2. Story-driven
3. Contrarian

Prompt 15: Newsletter Writer

Write a newsletter issue about [TOPIC] for [AUDIENCE].

Angle:
[ANGLE]

Include:
1. Subject line options
2. Opening hook
3. Main insight
4. Example or story
5. Tactical breakdown
6. Action step
7. Soft CTA

Tone: smart, useful, founder-led, no fluff.
Keep it skimmable.

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4. Content & Social Growth

Prompt 16: 30-Day Content Engine

Act as a content strategist for my personal brand @lifeofarjav.

Niche:
[NICHE]

Audience:
[AUDIENCE]

Goals:
[GOALS]

Create a 30-day content calendar with:
1. Post topic
2. Hook
3. Format: reel, carousel, story, thread, newsletter, or short post
4. Why it will work
5. CTA
6. Repurposing idea

Rotate between education, authority, personality, proof, and contrarian takes.

Prompt 17: Reel Script System

Create a short Instagram reel script for [TOPIC].

Audience:
[AUDIENCE]

Goal:
[GOAL]

Format:
1. Hook in first 2 seconds
2. 3-5 punchy beats
3. Pattern interrupt
4. Simple example
5. CTA

Rules:
- No long intro
- No jargon unless explained
- Make every sentence easy to say on camera
- Keep it under [DURATION] seconds

Return the script, captions, on-screen text, and thumbnail title.

Prompt 18: Carousel Builder

Turn this idea into a 7-slide Instagram carousel.

Idea:
[IDEA]

Audience:
[AUDIENCE]

Brand:
@lifeofarjav, clean, minimal, premium, practical AI education.

Return:
1. Slide-by-slide copy
2. Visual direction for each slide
3. CTA slide
4. Caption
5. Comment keyword
6. Hook alternatives

Make it save-worthy, not just pretty.

Prompt 19: Hook Lab

Generate 30 hooks for [TOPIC].

Sort them into:
1. Curiosity hooks
2. Contrarian hooks
3. Pain hooks
4. Status hooks
5. Outcome hooks

For each hook, score:
- Clarity
- Novelty
- Scroll-stopping power
- Risk of sounding clickbait

Then pick the top 5 and explain why they work.

Prompt 20: Content Post-Mortem

Analyze these posts and tell me what is working.

Posts and metrics:
[PASTE POSTS + METRICS]

Find:
1. Best hooks
2. Worst hooks
3. Topic patterns
4. Format patterns
5. What my audience seems to care about
6. What I should double down on
7. What I should stop posting

Return a clear next-week content plan.

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5. Business Strategy

Prompt 21: Offer Critique

Act as a brutally honest offer strategist.

My offer:
[OFFER]

Audience:
[AUDIENCE]

Price:
[PRICE]

Current problem:
[PROBLEM]

Tell me:
1. What is unclear
2. What is weak
3. What is commoditized
4. What is actually compelling
5. What proof is missing
6. How to reposition it
7. The strongest version of the offer in one sentence

Do not be polite. Be useful.

Prompt 22: ICP and Positioning

Help me sharpen the ICP for [PRODUCT/SERVICE].

Current target:
[TARGET]

Current offer:
[OFFER]

Use cases:
[USE CASES]

Return:
1. Best-fit customer profile
2. Worst-fit customer profile
3. Pain points
4. Buying triggers
5. Objections
6. Messaging angle
7. Who I should stop selling to immediately

Be specific. Do not give generic market segmentation.

Prompt 23: Market Map

Map the market for [CATEGORY].

Include:
1. Main competitors
2. Indirect alternatives
3. Budget alternatives
4. Premium alternatives
5. Differentiation opportunities
6. Gaps in messaging
7. Underserved segments
8. Positioning wedge I could own

Return as a strategic memo with a clear recommendation.

Prompt 24: Pricing Strategy

Design a pricing strategy for [PRODUCT/SERVICE].

Context:
[CONTEXT]

Current price:
[CURRENT PRICE]

Goal:
[GOAL]

Include:
1. Recommended pricing tiers
2. What to include in each tier
3. What to keep out
4. Guarantee or risk reversal
5. Upgrade path
6. Pricing objections and counters
7. What price would make us look too cheap

Be practical, not theoretical.

Prompt 25: One-Page GTM Plan

Create a one-page go-to-market plan for [PRODUCT].

Audience:
[AUDIENCE]

Budget:
[BUDGET]

Timeline:
[TIMELINE]

Return:
1. Positioning
2. Primary channel
3. Secondary channels
4. Launch sequence
5. Outreach angle
6. Content strategy
7. Metrics to track
8. First 14-day execution plan

Make it lean, focused, and realistic.

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6. Sales & Outreach

Prompt 26: Cold Email Sequence

Write a 4-email cold email sequence for [PRODUCT/SERVICE].

Target:
[AUDIENCE]

Pain:
[PAIN]

Proof:
[PROOF]

Offer:
[OFFER]

Rules:
- Under 90 words per email
- No “quick question”
- No fake personalization
- Clear reason for outreach
- Soft CTA
- Follow-ups should add value, not nag

Return subject lines, email body, and personalization variables.

Prompt 27: Prospect Research Brief

Create a prospect research brief for this company.

Company:
[COMPANY]

Website or notes:
[URL OR NOTES]

My offer:
[OFFER]

Return:
1. What they do
2. Likely priorities
3. Possible pain points
4. Why my offer may matter
5. Personalization angles
6. Risks or bad-fit signs
7. Best cold email angle

Keep it concise and sales-useful.

Prompt 28: Objection Handling Map

List the top objections for buying [PRODUCT/SERVICE].

Audience:
[AUDIENCE]

Price:
[PRICE]

For each objection, give:
1. What they say
2. What they actually mean
3. Best response
4. Proof needed
5. Where to address it: sales call, landing page, email, case study, or FAQ

Return as a table.

Prompt 29: Sales Call Prep

Prepare me for a sales call with [PROSPECT].

Context:
[CONTEXT]

Their likely pain:
[PAIN]

My offer:
[OFFER]

Return:
1. Call objective
2. Discovery questions
3. Diagnosis framework
4. Likely objections
5. Proof points to use
6. Red flags
7. Closing path
8. Follow-up email template

Prompt 30: Rescue a Stalled Deal

This deal has stalled.

Context:
[CONTEXT]

Last message:
[LAST MESSAGE]

Analyze:
1. Why it likely stalled
2. What I may have done wrong
3. Whether to push, nurture, or walk away
4. Best next message
5. Follow-up sequence
6. What to change in the sales process next time

Be direct. Do not write needy sales copy.

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7. Coding & Product

Prompt 31: Product Spec From Idea

Turn this idea into a build-ready product spec.

Idea:
[IDEA]

Users:
[USERS]

Goal:
[GOAL]

Return:
1. Problem statement
2. User stories
3. MVP scope
4. Out of scope
5. Data model
6. User flows
7. Edge cases
8. Success metrics
9. Build sequence
10. Risks

Make it clear enough for an engineer to start building.

Prompt 32: Architecture Review

Act as a senior software architect. Review this architecture.

Architecture:
[PASTE ARCHITECTURE OR CODEBASE SUMMARY]

Check:
1. Scalability
2. Security
3. Maintainability
4. Data flow
5. Failure points
6. Cost risks
7. Complexity that should be removed

Return:
- What is good
- What is fragile
- What I should change first
- A cleaner architecture proposal

Prompt 33: Bug Diagnosis

Analyze this bug.

Error:
[ERROR]

Code:
[CODE]

Context:
[CONTEXT]

Return:
1. Most likely root cause
2. Why it is happening
3. Minimal fix
4. Robust fix
5. Test to prevent regression
6. What logs I should add
7. What I should check if this fix fails

Do not guess. Mark uncertainty clearly.

Prompt 34: PR Review From Hell

Review this pull request like a strict senior engineer.

Diff:
[DIFF]

Look for:
1. Broken logic
2. Security issues
3. Performance problems
4. Naming problems
5. Over-engineering
6. Missing tests
7. Edge cases

Return:
- Blocking issues
- Non-blocking suggestions
- What to approve
- What to reject
- Exact comments I can leave on the PR

Prompt 35: Front-End Build Prompt

Act as a world-class front-end engineer and product designer.

Build this screen:
[SCREEN DESCRIPTION]

Brand:
[BRAND GUIDELINES]

Users:
[USERS]

Requirements:
[REQUIREMENTS]

Return:
1. UX structure
2. Component hierarchy
3. Responsive layout
4. Empty, loading, and error states
5. Accessibility notes
6. Implementation plan
7. Final code if requested

Make it clean, modern, fast, and not like a generic AI dashboard.

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8. Agents & Automation

Prompt 36: Agent vs Workflow Router

For this task, decide whether I need a simple prompt, prompt chain, workflow automation, or agent.

Task:
[TASK]

Context:
[CONTEXT]

Evaluate:
1. Predictability
2. Need for tool use
3. Risk of wrong action
4. Need for memory
5. Need for human approval
6. Cost and latency
7. Failure modes

Return the recommended pattern and the simplest version that ships.

Prompt 37: Tool Specification

Design the tool set for an AI agent that does [WORKFLOW].

For each tool, define:
1. Tool name
2. Purpose
3. Inputs
4. Output schema
5. Error cases
6. Rate limits
7. When the agent should call it
8. When the agent must ask for approval

Return as a tool spec table.

Prompt 38: Automation Runbook

Design an automation for [WORKFLOW].

Trigger:
[TRIGGER]

Goal:
[GOAL]

Tools available:
[TOOLS]

Return:
1. Step-by-step workflow
2. Field mapping
3. Error handling
4. Retry rules
5. Human approval step
6. Logging
7. Success metric
8. Maintenance checklist

Make it production-safe, not a toy Zap.

Prompt 39: Eval Harness

Build an eval harness for this AI workflow.

Workflow:
[WORKFLOW]

Good output means:
[CRITERIA]

Return:
1. 10 test cases
2. Expected outputs
3. Common failure modes
4. Scoring rubric
5. Regression checks
6. Pass/fail threshold
7. How to monitor drift over time

Make the tests realistic, not academic.

Prompt 40: Agent Guardrail Policy

Create a guardrail policy for an agent that can [ACTIONS].

Risks:
[RISKS]

Define:
1. Allowed actions
2. Banned actions
3. Actions requiring approval
4. Data the agent must not expose
5. Stop conditions
6. Escalation path
7. Audit log requirements
8. User-facing explanation for failures

Return as a clear policy document.

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9. Data & Analysis

Prompt 41: First-Pass Data Audit

Run a first-pass audit on this dataset.

Dataset:
[DATA OR CSV SUMMARY]

Return:
1. Row count and column summary
2. Missing values
3. Duplicate risks
4. Suspicious outliers
5. Columns not to trust yet
6. Possible data leakage
7. 5 questions this dataset can answer
8. 5 questions it cannot answer safely

Be skeptical about data quality.

Prompt 42: KPI Dashboard Design

Design a KPI dashboard for [BUSINESS/PROJECT].

Goal:
[GOAL]

Audience:
[AUDIENCE]

Return:
1. North Star metric
2. Supporting metrics
3. Leading indicators
4. Lagging indicators
5. Guardrail metrics
6. Dashboard layout
7. Alert thresholds
8. What decisions each metric should trigger

Avoid vanity metrics.

Prompt 43: Experiment Analysis

Analyze this experiment.

Hypothesis:
[HYPOTHESIS]

Variant A:
[DATA]

Variant B:
[DATA]

Return:
1. Winner
2. Confidence level
3. Statistical concerns
4. Sample size concerns
5. Confounders
6. What to test next
7. Whether we should ship, retest, or kill it

Do not declare a winner if the data is weak.

Prompt 44: Cohort Analysis

Design a cohort analysis for [PRODUCT/BEHAVIOR].

Data available:
[DATA]

Return:
1. Cohort definition
2. Retention event
3. Time windows
4. SQL or pseudocode
5. Table layout
6. How to interpret the triangle
7. What patterns would worry you
8. What actions to take based on findings

Prompt 45: Anomaly Investigation

Investigate this metric spike or drop.

Metric:
[METRIC]

Change:
[CHANGE]

Context:
[CONTEXT]

Return:
1. Possible explanations
2. Data checks to run
3. Segment breakdowns
4. External factors
5. Instrumentation issues
6. Most likely cause
7. Recommended next action

Separate real signal from tracking noise.

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10. Learning & Personal OS

Prompt 46: Learn Any Skill Fast

I want to learn [SKILL] fast.

My current level:
[LEVEL]

Goal:
[GOAL]

Time available:
[TIME]

Create:
1. Skill tree
2. 14-day learning plan
3. Daily practice drills
4. Projects that prove competence
5. Common traps
6. Feedback loop
7. Final test to confirm I actually understand it

Make it practical and intense.

Prompt 47: Socratic Tutor

Be my Socratic tutor for [TOPIC].

Rules:
- Ask one question at a time
- Start easy, then get harder
- Wait for my answer
- If I am wrong, give a hint, not the answer
- After 8 questions, score me from 1-10
- Tell me exactly what to review next

Begin now with the first question.

Prompt 48: Weekly Operating System

Design my weekly operating system.

Roles:
[ROLES]

Goals:
[GOALS]

Constraints:
[CONSTRAINTS]

Return:
1. Weekly calendar structure
2. Deep work blocks
3. Admin blocks
4. Review ritual
5. Delegation list
6. Automation opportunities
7. Metrics to track
8. What to cut from my week

Be ruthless about focus.

Prompt 49: Decision Matrix

Help me choose between these options:
[OPTIONS]

Goal:
[GOAL]

Constraints:
[CONSTRAINTS]

Create a decision matrix using:
1. Upside
2. Risk
3. Time cost
4. Reversibility
5. Strategic alignment
6. Opportunity cost
7. Energy cost

Return:
- Scores
- Clear winner
- Runner-up
- What would change the answer
- The mistake I am most likely making

Prompt 50: Brutally Honest Advisor

Act as my brutally honest high-level advisor.

Situation:
[SITUATION]

Goal:
[GOAL]

What I am currently doing:
[CURRENT ACTIONS]

Tell me:
1. What I am doing wrong
2. What I am avoiding
3. What I am underestimating
4. Where I am wasting time
5. What I should stop doing
6. What I should do next
7. The highest-leverage move
8. The uncomfortable truth I probably do not want to hear

End with a 7-day execution plan.
No comfort. No fluff.

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Bonus: Prompt Quality Checklist

Before you paste a prompt, check this:

• Is the goal specific?
• Did I provide enough context?
• Did I define the output format?
• Did I say what bad output looks like?
• Did I include examples?
• Did I ask the model to surface assumptions?
• Did I ask for a confidence level?
• Did I include constraints?
• Did I make the model verify its answer?
• Did I remove room for generic advice?

If the answer is no, fix the prompt first.

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Bonus: GPT-5.6 Prompt Stack Template

Use this when you want premium output.

ROLE:
You are a [ROLE] with deep expertise in [DOMAIN].

MISSION:
Help me [GOAL] using the context below.

CONTEXT:
[CONTEXT]

INPUT:
[INPUT]

AUDIENCE:
[AUDIENCE]

CONSTRAINTS:
- [CONSTRAINT 1]
- [CONSTRAINT 2]
- [CONSTRAINT 3]

OUTPUT FORMAT:
Return:
1. [SECTION 1]
2. [SECTION 2]
3. [SECTION 3]

QUALITY CHECK:
Before finalizing, check:
- What assumptions are you making?
- What could be wrong?
- What is missing?
- What would make this answer stronger?
- What is the most useful next action?

TONE:
[TONE]

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Bonus: Model Comparison Scorecard

Use this whenever a new GPT model launches.

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Final Arjav Note

Prompts are not magic. They are leverage.

The amateur move is saving 500 prompts and using none of them properly.

The professional move is building 10 prompts that reliably improve your actual work, then turning those into repeatable systems.

Use this guide as a starting point, not a museum.

Follow @lifeofarjav for practical AI workflows, prompt systems, and automation breakdowns.

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Follow for more

• Instagram: @lifeofarjav
• LinkedIn: Arjav Jain
• Brand: Life of Arjav