I built and sold a business to HubSpot in just 17 months.

I co-founded Mindstream, an AI newsletter that scaled to 150,000+ subscribers. Today, Mindstream is part of the HubSpot Media Network, where I lead brand strategy for the AI media products. 

Along the way, I’ve grown a 200,000+ following on LinkedIn, sharing real, unfiltered lessons on AI, entrepreneurship, and business growth. The wins and the mistakes.

I believe action beats hesitation. The biggest risk? Never starting.

Adam Biddlecombe

Helping Entrepreneurs Build with AI | Founder, Mindstream (Acquired by HubSpot)

Co-Founder & CEO 

AI is eating the world.
And you can’t even define “LLM”?
Yikes.

Don't stay clueless.
Don't stay behind.
Don't stay outdated.

These 40 AI terms explained easily will make you 10x smarter today.

1. Bias
When an AI unfairly prefers some answers over others, often because of the data it was trained on.

2. Label
A tag or answer given to data so AI knows what it is.

3. Model
The final program that can do tasks after learning from data.

4. Training
The process where AI learns from examples to get better at its job.

5. Chatbot
A computer program that talks to people in text or voice.

6. Dataset
A big collection of information that AI learns from.

7. Algorithm
Step-by-step instructions for solving a problem.

8. Token
Words or pieces of words AI uses to read and write text.

9. Overfitting
When AI learns the training data too well and can’t handle new, different examples.

10. AI Ethics
Making sure AI is used in ways that are right and fair to everyone.

If you want to know more AI terms, 
Check the infographic below 👇 

Have you started learning AI?
Comment below 👇 

Learn AI for free: https://lnkd.in/euYZeAdb 

♻️ Share this to help your network learn AI terms

AI is eating the world.
And you can’t even define “LLM”?
Yikes.

Don't stay clueless.
Don't stay behind.
Don't stay outdated.

These 40 AI terms explained easily will make you 10x smarter today.

Bias
When an AI unfairly prefers some answers over others, often because of the data it was trained on.

2. Label
A tag or answer given to data so AI knows what it is.

3. Model
The final program that can do tasks after learning from data.

4. Training
The process where AI learns from examples to get better at its job.

5. Chatbot
A computer program that talks to people in text or voice.

6. Dataset
A big collection of information that AI learns from.

7. Algorithm
Step-by-step instructions for solving a problem.

8. Token
Words or pieces of words AI uses to read and write text.

9. Overfitting
When AI learns the training data too well and can’t handle new, different examples.

10. AI Ethics
Making sure AI is used in ways that are right and fair to everyone.

If you're not using AI

You're not managing your growth wisely. 

(And no. I'm not talking about basic motivation) 

Personal development becomes efficient when humans and AI work together. 

✅ Write a prompt 
✅ Get a solution from ChatGPT 
✅ Follow up and keep brainstorming till you get the best solution 

 Self-improvement use cases on which you can collaborate with ChatGPT: 
✅ SMART Goal Setting
✅ Visualization Exercise
✅ Habit Formation Blueprint
✅ Growth Mindset Cultivation
✅ Personal Mission Statement
✅ Evening Wind-Down Routine
✅ Morning Routine Optimization
✅ Journaling for Self-Awareness
✅Weekly Time Management Plan
✅ Accountability Partner Simulation

And more covered in the infographic below. 

For what use cases do you use ChatGPT? 
Comment below 👇 

Learn AI for free 👉 https://lnkd.in/euYZeAdb 

♻️ Share this post to help your network use ChatGPT for personal growth

If you're not using AI

You're not managing your growth wisely. 

(And no. I'm not talking about basic motivation) 

Personal development becomes efficient when humans and AI work together. 

✅ Write a prompt 
✅ Get a solution from ChatGPT 
✅ Follow up and keep brainstorming till you get the best solution 

 Self-improvement use cases on which you can collaborate with ChatGPT: 
✅ SMART Goal Setting
✅ Visualization Exercise
✅ Habit Formation Blueprint
✅ Growth Mindset Cultivation
✅ Personal Mission Statement
✅ Evening Wind-Down Routine
✅ Morning Routine Optimization
✅ Journaling for Self-Awareness
✅Weekly Time Management Plan
✅ Accountability Partner Simulation

You waste time doing manual work. 

Even when you have AI now. 

Here's how to go from zero to pro in AI:

Core AI skills:
✅ Computer Vision
✅ Model Deployment
✅ Deep Learning (DL)
✅ Explainable AI (XAI)
✅ Generative AI (GenAI)
✅ Machine Learning (ML)
✅ Reinforcement Learning
✅ Model Monitoring & Versioning
✅ Natural Language Processing (NLP)

Top websites to learn AI:
✅ Fast AI
✅ Mindstream
✅ Kaggle
✅ Coursera
✅ Deeplearning
✅ Mygreatlearning

And a lot more covered in the infographic below

Have you started learning AI?
Comment below 👇

Learn AI for free 👉 https://lnkd.in/euYZeAdb 

♻️ Repost to help your network learn AI

You waste time doing manual work. 

Even when you have AI now. 

Here's how to go from zero to pro in AI:

Core AI skills:
✅ Computer Vision
✅ Model Deployment
✅ Deep Learning (DL)
✅ Explainable AI (XAI)
✅ Generative AI (GenAI)
✅ Machine Learning (ML)
✅ Reinforcement Learning
✅ Model Monitoring & Versioning
✅ Natural Language Processing (NLP)

Top websites to learn AI:
✅ Fast AI
✅ Mindstream
✅ Kaggle
✅ Coursera
✅ Deeplearning
✅ Mygreatlearning

You’re wasting hours doing tasks an AI Agent could finish in seconds.

The twist? You don’t even have to build them.

I’ve curated the 40 best plug-and-play Zapier Agent templates that do it all for you.

How do Zapier Agent templates help?
- Each template provides you a ready-to-use framework for a task.
- You get in-depth explanation about how the template works.
- You get to know why you should use a particular template.
- You get the perfect tool stack built in that template so you don’t need to juggle with random tools.

How to use Zapier Agent templates?
1. Go to the link below 
2. Click on any template 
3. Click ‘Use Template’
4. Check out the Agent
5. Connect your web apps
6. Click ‘Create’
7. Configure and use your Agent

Here are the Agent templates you should try:

Productivity:
- Automated Email Reply Drafts Agent
- Daily Outlook Event Reminder
- Google Calendar Zoom Meeting Link Adder
- Hackathon Event Notifier
- Follow-Up Reaction Notifier

Product Management:
- Product Expiry Management System
- PRD Document Creator
- Customer Call Summary and PRD Generator
- Weekly Project Status Update Email Generator
- Slack Thread Insights Extractor 

Project Management:
- Project Brief Generator 
- Slack to Asana Campaign Organizer 
- Google Doc to Asana Status Update 
- Project Update Notifier 
- Incomplete Jira Tickets Commenter 

To know more powerful Agent templates,
Check the infographic below 👇 

Try Zapier Agent templates here :https://lnkd.in/eBkNHjRz

What do you think about using Agent templates to automate manual work?

Comment below 👇 

♻️ Share this to help your network use the best Agent templates 

#ZapierPartner

Stuck staring at a blank page?
Ideas refusing to show up?
Brain fried from overthinking?

ChatGPT can spark it.
Prompts can fuel it.
Your creativity can explode.

Here are 10 ChatGPT prompts built to smash creative blocks in seconds.

Market Entry Strategy Brainstorm
- Act as a strategic business consultant and use chain-of-thought reasoning to brainstorm a step-by-step market entry strategy for [business type] targeting [specific market or region], including potential risks, competitive analysis, entry barriers, and actionable timelines; structure the output as a bulleted list with pros, cons, and recommended next steps, limited to 500 words.

Product Innovation Ideas
- Think step-by-step like an innovative product developer and generate 10 creative ideas for new products or features in [business type], focusing on [specific problem or customer need], incorporating market trends and feasibility analysis; format the response as a numbered list with brief descriptions, potential revenue impacts, and implementation challenges.

Competitive Analysis Framework
- Employ chain-of-thought to analyze [number] key competitors in [business type], evaluating their strengths, weaknesses, opportunities, and threats relative to my [specific business aspect]; output in a structured SWOT matrix table format, followed by 5 strategic recommendations for differentiation.

Growth Hacking Tactics
- As a growth expert, reason through innovative growth hacking tactics for [business type] aiming to achieve [specific growth metric, e.g., 20% user increase], drawing from data-driven examples; present as a prioritized list of 8 tactics with step-by-step execution plans and expected outcomes.

Business Model Canvas
- Use structured reasoning to create a customized Business Model Canvas for [business type] with [unique twist or focus area], detailing key partners, activities, value propositions, and revenue streams; format as a clear, bulleted section-by-section breakdown with visual descriptions for easy adaptation.

To get more ChatGPT prompts,
Check the infographic below 👇

For what other use cases do you use ChatGPT?
Comment below 👇

Learn AI for free: https://lnkd.in/euYZeAdb 

♻️ Repost this to help your network use AI to brainstorm better

Stuck staring at a blank page?
Ideas refusing to show up?
Brain fried from overthinking?

ChatGPT can spark it.
Prompts can fuel it.
Your creativity can explode.

Here are 10 ChatGPT prompts built to smash creative blocks in seconds.

Market Entry Strategy Brainstorm
- Act as a strategic business consultant and use chain-of-thought reasoning to brainstorm a step-by-step market entry strategy for [business type] targeting [specific market or region], including potential risks, competitive analysis, entry barriers, and actionable timelines; structure the output as a bulleted list with pros, cons, and recommended next steps, limited to 500 words.

Product Innovation Ideas
- Think step-by-step like an innovative product developer and generate 10 creative ideas for new products or features in [business type], focusing on [specific problem or customer need], incorporating market trends and feasibility analysis; format the response as a numbered list with brief descriptions, potential revenue

AI isn’t replacing jobs.
It’s upgrading people who use it.
But only if you know how to use it.

Most people are learning the wrong stuff.
The job market is shifting under your feet.
Smart learners will dominate.

These 15 AI skills will future-proof your career in 2025.

1. Prompt Engineering
2. Staying Updated
3. Retrieval-Augmented Generation (RAG)
4. AI Agents
5. Multimodal AI Application
6. Fine-Tuning and AI Assistants
7. Voice AI & Avatars
8. AI Tool Stacking
9. AI Video Content Generation
10. SaaS Development
11. LLM Management
12. AI Content Marketing
13. AI Chatbots
14. Website Creation
15. AI Workflow Automation

To know more about these skills,
Check the infographic below 👇 

Have you started learning how to use AI?
Comment below 👇 

Learn AI for free: https://lnkd.in/euYZeAdb 

♻️ Share this to help your network learn AI

AI isn’t replacing jobs.
It’s upgrading people who use it.
But only if you know how to use it.

Most people are learning the wrong stuff.
The job market is shifting under your feet.
Smart learners will dominate.

These 15 AI skills will future-proof your career in 2025.

Prompt Engineering
Staying Updated
Retrieval-Augmented Generation (RAG)
AI Agents
Multimodal AI Application
Fine-Tuning and AI Assistants
Voice AI & Avatars
AI Tool Stacking
AI Video Content Generation
SaaS Development
LLM Management
AI Content Marketing
AI Chatbots
Website Creation
AI Workflow Automation


Stop using ChatGPT the default way.

Most people don’t realise they’re blocking 80% of its power.

Here’s how the Personalization feature in ChatGPT helps you get 10x better outputs from AI.

What is the Personalization feature in ChatGPT?
1. Allows users to set how ChatGPT should respond and what it should know about them via custom instructions.
2. Enables the model to adapt tone, style, and focus based on those user-defined preferences.
3. Utilises memory of past interactions (if enabled) so responses become more context-aware over time.
4. Gives different users distinct experiences even with similar prompts, reflecting their unique guidance.

Follow these steps:
1. Go to chatgpt.com
2. Click on your profile picture on bottom left.
3. Click ‘Personalization’.
4. Select ‘Base style and tone’ from the available options. This helps you set the basic style and tone of how ChatGPT responds to you.
5. In ‘Custom Instructions’ add what you want ChatGPT to have and not have in its outputs.
6. Add your nickname ChatGPT can use in chats.
7. Add your occupation so ChatGPT understands you better.
8. Add more information about your interests, values, tone of voice, writing style, and preferences.
9. Enable or disable memory to let ChatGPT know more about you
10. Enable or disable record mode to enable or disable ChatGPT using previous chats as references to create new outputs

Dos:
- Do specify your role and goals clearly so the model knows your context.
- Do define how you prefer the tone, style, and format of responses.
- Do keep your instructions concise and manageable rather than overly long.
- Do update or refine your custom instructions as your needs or projects evolve.
- Do use custom instructions to reduce repetition and improve consistency across chats.

Don'ts:
- Don’t overload the instruction fields with every little preference; it can reduce effectiveness.
- Don’t assume the model will read between vague instructions; be explicit when necessary.
- Don’t include extremely sensitive or proprietary personal data if you’re unsure about usage/privacy.
- Don’t forget to review how the model is behaving; custom instructions aren’t a “set-it-and-forget-it” guarantee.
- Don’t expect custom instructions alone to solve all prompt-engineering issues; they complement good prompting, not replace it.

To know more about it,
Check the infographic below 👇

What do you think about the Personalization Feature In ChatGPT?
Comment below 👇

Learn AI for free: https://lnkd.in/euYZeAdb 

♻️ Repost to help your network use ChatGPT better

Stop using ChatGPT the default way.

Most people don’t realise they’re blocking 80% of its power.

Here’s how the Personalization feature in ChatGPT helps you get 10x better outputs from AI.

What is the Personalization feature in ChatGPT?
Allows users to set how ChatGPT should respond and what it should know about them via custom instructions.
Enables the model to adapt tone, style, and focus based on those user-defined preferences.
Utilises memory of past interactions (if enabled) so responses become more context-aware over time.
Gives different users distinct experiences even with similar prompts, reflecting their unique guidance.

Follow these steps:
Go to chatgpt.com
Click on your profile picture on bottom left.
Click ‘Personalization’.
Select ‘Base style and tone’ from the available options. This helps you set the basic style and tone of how ChatGPT responds to you.
In ‘Custom Instructions’ add what you want ChatGPT to have and not have in its outputs.

You’re analysing data wrong. 

Because you’re doing it manually. 

Here’s how ChatGPT helps you get hours of data analysis work done in minutes.

1. Go to chatgpt.com 
2. Add your dataset
3. Write your prompt.
4. Get the analysis done by ChatGPT.
5. Add a follow-up prompt if required

Prompt I've used: 
- Act as a professional data analyst. I've attached a dataset here of Uber rides. I want you to perform data cleaning of this data and spot inconsistencies, missing values, or duplicates in datasets & fix them. I also want you to highlight patterns, correlations, distributions & potential outliers in this dataset & create a report of takeaways from this dataset. 

After I got the output, I needed just concise key takeaways from the data. So, here's my follow-up prompt: 
- Write about 3 key takeaways from this data. 

Output I got:
- ChatGPT cleaned the data & gave me a good report, & then here are the key takeaways I got in an easy-to-understand way.

Do's of using ChatGPT for data analysis:
✅ Do prep your dataset.
✅ Do ask clear, specific analysis questions.
✅ Do validate AI results with real stats.
✅ Do use visualisations for better insights.
✅ Do cross-check with domain knowledge.

Don'ts of using ChatGPT for data analysis:
❎ Don't feed raw, messy data directly.
❎ Don't assume outputs are always accurate.
❎ Don't skip checking for bias or outliers.
❎ Don't use vague prompts like "analyse this".
❎ Don't rely on AI alone; always verify.

To get a more detailed explanation, 
Check the carousel below 👇 

What do you think of using ChatGPT for analysis?
Comment below 👇 

Learn AI for FREE: https://lnkd.in/eAAacxSK 

♻️ Share this to help your network use AI

How To Use ChatGPT For Analysis

I thought Google Nano Banana Pro was just another flashy update in AI image generation.

But I got a shock when I tried it for multiple business use cases.

Here’s the ultimate guide to creating mind-bending images with Google's Nano Banana Pro AI image generation model.

Prompt Template to create images:
Create a highly detailed image of [insert subject] set in [insert environment or setting], captured in [insert camera style or artistic style]. The scene should emphasize [insert key features, mood, or atmosphere], with lighting that enhances [insert lighting preference such as dramatic shadows, soft glow, neon reflections]. Include specific visual elements like [insert defining objects, textures, colors], and ensure the final image appears realistic, cinematic, and cohesive with strong composition.

How To Use It?
1. Go to gemini.google.com
2. Select the ‘Thinking’ model
3. Select ‘Create images’ in tools
4. Add your reference images if required
5. Add your prompt
6. AI generates the output in a minute

Do’s:
✅ Always use high-quality, well-lit reference images for crisp results.
✅ Specify subject, action, and setting clearly in each prompt.
✅ Refine with camera angle, lighting, and style details for better accuracy.
✅ Use constraints like aspect ratio or resolution for targeted results.
✅ Iterate by tweaking prompts for improved output quality.

Don’ts:
❎ Don’t use vague or generic prompts; results will be bland or off-target.
❎ Don’t overload with too many style or action requests in one prompt.
❎ Don’t use low-resolution or group photos as reference; AI struggles with blurry or crowded faces.
❎ Don’t forget identity markers when blending multiple people or scenes.
❎ Don’t expect perfect tiny text or intricate textures; these can render inaccurately.

To get more tips,
Check the infographic below 👇

Learn AI for free: https://lnkd.in/euYZeAdb 

What do you think about this new and trending AI image generation model?
Comment below 👇

♻️ Repost to help your network create better images with AI

I thought Google Nano Banana Pro was just another flashy update in AI image generation.

But I got a shock when I tried it for multiple business use cases.

Here’s the ultimate guide to creating mind-bending images with Google's Nano Banana Pro AI image generation model.

Prompt Template to create images:
Create a highly detailed image of [insert subject] set in [insert environment or setting], captured in [insert camera style or artistic style]. The scene should emphasize [insert key features, mood, or atmosphere], with lighting that enhances [insert lighting preference such as dramatic shadows, soft glow, neon reflections]. Include specific visual elements like [insert defining objects, textures, colors], and ensure the final image appears realistic, cinematic, and cohesive with strong composition. 

How To Use It?
Go to gemini.google.com
Select the ‘Thinking’ model
Select ‘Create images’ in tools
Add your reference images if required
Add your prompt

I used to end every day feeling like I worked all day but achieved less than my potential.

Then I added a new tool to my workflow, and the upgrade felt almost unfair.
I've added Google's Gemini 3.

Here’s the complete guide on how to use Google Gemini 3 to get more work done in less time.

Prompt framework you should use:
Role: Define who the AI should act as (e.g., expert, teacher, coach).
Task: Specify the exact job or output you want the AI to complete.
Context: Give details, boundaries, and exclusions to guide the AI properly.
Reasoning: Ensure logical steps, accuracy, and validation checks.
Output format: Tell ChatGPT the exact structure in which to return results.
Stop conditions: Clarify when ChatGPT should consider the task finished.

Prompt template:
Act as [Role] to [Task].
Begin with a checklist of 3–7 steps to plan how you’ll complete the task.
Ensure the content is accurate, unique, and excludes [things to avoid].
Prioritize clarity and practical value when presenting results.
Internally validate and cross-check information before finalizing.
Return the results in this format: [desired output format].
The task is complete when [stop condition].

Use cases of Google Gemini 3:
1. Do data analysis 
2. Create data visualisations
3. Create insane visuals for marketing, training, sales, and support
4. Create presentations
5. Create research reports
6. Create web apps
7. Create websites
8. Solve problems faster
9. Create games

To get more tips on how to use it better,
Check the infographic below 👇 

Learn AI for free: https://lnkd.in/euYZeAdb  

What do you think about Google Gemini 3?
Comment below 👇 

♻️ Repost to help your network be productive at work with Google Gemini 3

I used to end every day feeling like I worked all day but achieved less than my potential.

Then I added a new tool to my workflow, and the upgrade felt almost unfair.
I've added Google's Gemini 3.

Here’s the complete guide on how to use Google Gemini 3 to get more work done in less time.

Prompt framework you should use:
Role: Define who the AI should act as (e.g., expert, teacher, coach).
Task: Specify the exact job or output you want the AI to complete.
Context: Give details, boundaries, and exclusions to guide the AI properly.
Reasoning: Ensure logical steps, accuracy, and validation checks.
Output format: Tell ChatGPT the exact structure in which to return results.
Stop conditions: Clarify when ChatGPT should consider the task finished.

Stop writing random prompts.

Start writing structured ones that make AI work as your partner.

Here are 30 ChatGPT prompt templates to write better prompts. 

1. Detailed Instruction Template
"Give me detailed, step-by-step instructions on how to [perform a task]."
Example:
"Give me detailed, step-by-step instructions on how to set up a home Wi-Fi network."

2. Role Play Specialist Template
"Act as a [role/expert]. Help me with [problem/situation]."
Example:
"Act as a tax accountant. Help me with filing self-employment taxes."

3. Explain Like I’m Five (ELI5) Template
"Explain [concept] to me as if I were five years old."
Example:
"Explain blockchain technology to me as if I were five years old."

4. Comparison Table Template
"Create a table comparing [items or concepts] based on [criteria]."
Example:
"Create a table comparing electric vehicles, hybrids, and gasoline cars based on price, range, and emissions."

5. Pros and Cons List Template
"List the pros and cons of [topic/decision/technology]."
Example:
"List the pros and cons of working remotely full-time."

To know more prompt templates,
Check the infographic below 👇

What other prompt templates would you recommend adding here?
Comment below 👇

Learn AI for free: https://lnkd.in/euYZeAdb 

♻️ Share this to help your network use ChatGPT

Stop writing random prompts.

Start writing structured ones that make AI work as your partner.

Here are 30 ChatGPT prompt templates to write better prompts. 

1. Detailed Instruction Template
"Give me detailed, step-by-step instructions on how to [perform a task]."
Example:
"Give me detailed, step-by-step instructions on how to set up a home Wi-Fi network."

2. Role Play Specialist Template
"Act as a [role/expert]. Help me with [problem/situation]."
Example:
"Act as a tax accountant. Help me with filing self-employment taxes."

3. Explain Like I’m Five (ELI5) Template
"Explain [concept] to me as if I were five years old."
Example:
"Explain blockchain technology to me as if I were five years old."

4. Comparison Table Template
"Create a table comparing [items or concepts] based on [criteria]."
Example:
"Create a table comparing electric vehicles, hybrids, and gasoline cars based on price, range, and emissions."

5. Pros and Cons List Template
"List the pros and cons of [topic/decision/

30 AI algorithms that secretly run your life.

They choose what you watch.
They predict what you buy.
They know you better than you know yourself.

Here are 30 AI algorithms you can't miss.

1. Linear Regression
Predicts a number based on a straight-line relationship. Example: Predicting house prices from size.

2. Logistic Regression
Predicts a yes/no outcome (like spam or not spam). Despite the name, it’s used for classification.

3. Decision Tree
Uses a tree-like model of decisions with if-else rules. Easy to understand and visualize.

4. Random Forest
Builds many decision trees and combines their answers. More accurate and less likely to overfit.

5. Support Vector Machine (SVM)
Finds the best line (or boundary) that separates different classes. Works well for high-dimensional data.

6. K-Nearest Neighbors (k-NN)
Looks at the ‘k’ closest data points to decide what a new point should be. No learning phase, just compares.

7. Naive Bayes
Based on Bayes’ Theorem and assumes all features are independent. Fast and good for text classification.

8. Gradient Boosting
Builds models one after another, each fixing the previous one’s mistakes. Powerful but slow.

9. AdaBoost
Like gradient boosting, it combines weak models into a strong one using weighted votes.

10. XGBoost
A super-efficient version of gradient boosting, very popular in machine learning competitions.

To know more AI algorithms, 
Check the infographic below 👇

Have you started learning AI?
Comment below 👇

Learn AI for free: https://lnkd.in/euYZeAdb 

♻️ Share this post to help your network learn AI

30 AI algorithms that secretly run your life.

They choose what you watch.
They predict what you buy.
They know you better than you know yourself.

Here are 30 AI algorithms you can't miss.

Linear Regression
Predicts a number based on a straight-line relationship. Example: Predicting house prices from size.

2. Logistic Regression
Predicts a yes/no outcome (like spam or not spam). Despite the name, it’s used for classification.

3. Decision Tree
Uses a tree-like model of decisions with if-else rules. Easy to understand and visualize.

4. Random Forest
Builds many decision trees and combines their answers. More accurate and less likely to overfit.

5. Support Vector Machine (SVM)
Finds the best line (or boundary) that separates different classes. Works well for high-dimensional data.

6. K-Nearest Neighbors (k-NN)
Looks at the ‘k’ closest data points to decide what a new point should be. No learning phase, just compares.

Most people think they’re critical thinkers. 
They’re not.

They confuse skepticism with depth.
They confuse doubt with wisdom.
They confuse noise with thought.

These 25 ChatGPT prompts show you what real critical thinking looks like. 

1. First-Principles Deconstruction 
Act as a first-principles analyst. Decompose the problem: “{insert problem}” into its smallest assumptions, physical/financial/logical constraints, and causal mechanisms. For each assumption, evaluate its necessity (must-have vs convenience) and testability (how to falsify). Rebuild a solution from only the indispensable parts. Output in sections: Assumptions, Constraints, Mechanisms, Tests, Rebuild, Risks, Final Recommendation.
 
 2. Steelman the Opposition 
Act as an impartial philosopher. State my position: “{insert position}.” Identify the strongest possible opposing thesis that a highly intelligent critic would advance. Present the opponent’s best arguments, evidence, and counterexamples. Then respond by improving my position (not attacking a strawman) with revisions, concessions, and better evidence. Output sections: My Thesis, Steelman Opposition, Rebuttal, Revisions to My Thesis, Updated Thesis.
 
 3. Decision Tree with Expected Value 
Act as a decision scientist. For the choice “{insert decision},” enumerate mutually exclusive options. For each option, map a decision tree with key uncertainties and outcomes. Estimate probabilities, costs, and benefits; compute expected values and confidence ranges. Conclude with the dominant option, critical variables (by EV sensitivity), and what evidence would most change the decision. Output: Options, Trees, EV Table, Sensitivity, Value of Information, Recommendation.
 
 4. Red Team Pre-Mortem 
Act as a red-team strategist. Assume the plan “{insert plan}” failed catastrophically in 12 months. List the top 10 plausible failure modes, early warning signals for each, severity/likelihood ratings, and concrete countermeasures. Conclude with a prioritized mitigation roadmap and a monitoring dashboard (leading indicators, thresholds, and actions).
 
 5. Causal Map and Intervention Points 
Act as a causal modeler. Build a cause-effect map for “{insert outcome to improve},” identifying upstream drivers, mediators, and feedback loops. Label each link with direction and plausible strength. Propose 5 leverage points where small interventions could yield outsized effects, including intervention design, measurement, risks, and fallback plans.

To get more ChatGPT prompts, 
Check the infographic below 👇 

Have you tried using AI as your thinking partner?
Comment below 👇 

Learn AI for free: https://lnkd.in/euYZeAdb 

♻️ Share this to help your network use AI for critical thinking

Most people think they’re critical thinkers. 
They’re not.

They confuse skepticism with depth.
They confuse doubt with wisdom.
They confuse noise with thought.

These 25 ChatGPT prompts show you what real critical thinking looks like. 

1. First-Principles Deconstruction 
Act as a first-principles analyst. Decompose the problem: “{insert problem}” into its smallest assumptions, physical/financial/logical constraints, and causal mechanisms. For each assumption, evaluate its necessity (must-have vs convenience) and testability (how to falsify). Rebuild a solution from only the indispensable parts. Output in sections: Assumptions, Constraints, Mechanisms, Tests, Rebuild, Risks, Final Recommendation.

You give it a prompt.
It replies in seconds.
But here’s the part nobody tells you...

It doesn’t understand the way you do.
It’s not trained like humans.
It’s just... predicting?

Here’s the truth about how ChatGPT works and why it’s terrifyingly effective.

Step 1: You type a prompt.
Step 2: ChatGPT splits your input into smaller pieces called “tokens”.
Step 3: It converts these tokens into numbers (vectors) so the computer can understand them.
Step 4: ChatGPT checks where each token appears in your message using “positional encoding”.
Step 5: It uses powerful “transformer” neural networks to analyze all tokens at once, not just one by one.
Step 6: The model pays special attention to the most important words in your input using the “attention mechanism”.
Step 7: All this information passes through many transformer layers to understand deeper meaning.
Step 8: The model recalls patterns & knowledge learned from millions of examples in its training data.
Step 9: It predicts what word (token) should come next, aiming for the most likely and meaningful response.
Step 10: ChatGPT generates one token at a time, building its reply step by step. 

To know more about how ChatGPT works,
Check the infographic below 👇

Have you started learning AI?
Comment below 👇

Learn AI for free: https://lnkd.in/euYZeAdb 

♻️ Share this to help your network learn how ChatGPT works

You give it a prompt.
It replies in seconds.
But here’s the part nobody tells you...

It doesn’t understand the way you do.
It’s not trained like humans.
It’s just... predicting?

Here’s the truth about how ChatGPT works and why it’s terrifyingly effective.

Step 1: You type a prompt.
Step 2: ChatGPT splits your input into smaller pieces called “tokens”.
Step 3: It converts these tokens into numbers (vectors) so the computer can understand them.
Step 4: ChatGPT checks where each token appears in your message using “positional encoding”.
Step 5: It uses powerful “transformer” neural networks to analyze all tokens at once, not just one by one.
Step 6: The model pays special attention to the most important words in your input using the “attention mechanism”.
Step 7: All this information passes through many transformer layers to understand deeper meaning.
Step 8: The model recalls patterns & knowledge learned from millions of examples in its training data.

You’re learning AI randomly, and that’s why you’re not improving fast.

You need a structured path that removes the guesswork.

Here are the 28 levels you should go through to go from zero to the best in the world in AI.

Level 0: 
AI Awareness: Learn what AI is and what it is not, and understand basic terminology.

Level 1: 
Digital Literacy: Master computer fundamentals, file systems, basic coding concepts, and internet research skills.

Level 2: 
Programming Foundations: Learn Python, control structures, functions, data types, and basic scripting.

Level 3: 
Math for AI Foundations: Understand linear algebra basics, probability fundamentals, and essential calculus concepts.

Level 4: 
Data Handling Basics: Learn data cleaning, preprocessing, visualisation, and working with datasets using Python libraries.

Level 5: 
Machine Learning Fundamentals: Understand supervised, unsupervised, and simple model training workflows with scikit-learn.

Level 6: 
Practical ML Application: Learn model evaluation, cross validation, feature engineering, and real-world ML pipelines.

Level 7: 
Deep Learning Foundations: Understand neural networks, backpropagation, activation functions, and basic model architectures.

Level 8: 
Applied Deep Learning: Learn to build and train CNNs, RNNs, LSTMs, and transformers and run experiments with PyTorch or TensorFlow.

Level 9: 
Natural Language Processing: Understand tokenisation, embeddings, sequence models, and transformer-based NLP workflows.

Level 10: 
Large Language Models: Basics Learn how LLMs function, including attention mechanisms, pretraining, fine-tuning, and inference concepts.

To know about the next levels,
Check the infographic below 👇 

Learn AI for free: https://lnkd.in/euYZeAdb  

Do you invest time in learning AI every day?
Comment below 👇 

♻️ Repost to help your network learn AI

You’re learning AI randomly, and that’s why you’re not improving fast.

You need a structured path that removes the guesswork.

Here are the 28 levels you should go through to go from zero to the best in the world in AI.

Level 0: 
AI Awareness: Learn what AI is and what it is not, and understand basic terminology.

Level 1: 
Digital Literacy: Master computer fundamentals, file systems, basic coding concepts, and internet research skills.

Level 2: 
Programming Foundations: Learn Python, control structures, functions, data types, and basic scripting.

Level 3: 
Math for AI Foundations: Understand linear algebra basics, probability fundamentals, and essential calculus concepts.

Level 4: 
Data Handling Basics: Learn data cleaning, preprocessing, visualisation, and working with datasets using Python libraries.

Level 5: 
Machine Learning Fundamentals: Understand supervised, unsupervised, and simple model training workflows with scikit-learn.

You're learning too slowly without realising it.

Here’s how to learn faster than ever with AI with Google NotebookLM.

About Google NotebookLM
- AI-powered “virtual research and learning assistant” that uses your uploaded content and prompt as a basis for conversation.
- Accepts diverse sources like PDFs, Google Docs, websites and Google Slides and can answer questions grounded in them.
- Generates summaries, explanations and even audio overviews (podcast-style) to help you understand learning materials quickly.

Follow these steps:
1. Go to notebooklm.google.com
2. Check any featured notebook if you want
3. Click ‘Create New Notebook’ to create a new one
4. Add the doc or link from which you want to learn
5. NotebookLM starts working on creating easy-to-digest content from your learning material.
6. You’ll get the study material summary prepared by NotebookLM.
7. Based on it, NotebookLM can create:
  - Audio podcast
  - Explainer video
  - Mind map
  - Reports
  - Flashcards
  - Quiz

How to use the output created by NotebookLM:
- You can share a custom link of your notebook for anyone to use it.

Do’s of using NotebookLM:
✅ Upload clean, relevant sources.
✅ Ask clear, specific questions.
✅ Organise into topic notebooks.
✅ Use summaries, quizzes, and overviews.
✅ Cross-check outputs with sources.

Don’ts of using NotebookLM:
❎ Don’t expect knowledge beyond uploads.
❎ Don’t dump irrelevant content.
❎ Don’t ask vague, broad questions.
❎ Don’t over-trust compressed summaries.
❎ Don’t share sensitive data.

To know more about NotebookLM,
Check the infographic below 👇

Have you tried using AI for learning?
Comment below 👇

Learn AI for free: https://lnkd.in/euYZeAdb 

♻️ Repost to help your network learn efficiently with AI

You're learning too slowly without realising it.

Here’s how to learn faster than ever with AI with Google NotebookLM.

About Google NotebookLM
AI-powered “virtual research and learning assistant” that uses your uploaded content and prompt as a basis for conversation.
Accepts diverse sources like PDFs, Google Docs, websites and Google Slides and can answer questions grounded in them.
Generates summaries, explanations and even audio overviews (podcast-style) to help you understand learning materials quickly.
Try here: notebooklm.google.com

Follow these steps:
Go to notebooklm.google.com
Check any featured notebook if you want
Click ‘Create New Notebook’ to create a new one
Add the doc or link from which you want to learn
NotebookLM starts working on creating easy-to-digest content from your learning material.
You’ll get the study material summary prepared by NotebookLM.
Based on it, NotebookLM can create:
Audio podcast
Explainer video
Mind map
Reports
Flashcards
Quiz

Anyone today can build an app.

With AI. In 5 minutes. From a single text prompt. Without any technical knowledge. 

Here’s the ultimate prompting guide to help you build apps with AI.

I use Replit.
It is a tool with which anyone can build mobile and web apps with AI from simple text prompts without writing a single line of code with Replit’s powerful AI agent.

How it works:
1. Go to replit.com 
2. Signup 
3. Describe the app or design idea in the build and design section
4. Select what you want to build
5. Add reference files or Figma designs or an existing project to build an app
6. Add your prompt
7. Get your prompt refined with AI if required
8. Submit your prompt
9. AI Agent starts building
10. You get the entire app built in minutes
11. Follow-up if you need any changes
12. Preview and test it
13. Invite your team to check and make any changes
14. Publish with Replit 

Do’s:
✅ Define a clear problem and user outcome before prompting.
✅ Start with a well-defined feature set and expand only after basic flow works.
✅ Provide concrete examples, data formats, and edge cases in your prompts.
✅ Test each generated feature manually in real user scenarios.

Don’ts:
✅ Do not expect the first generation to be production ready without review.
✅ Do not mix multiple unrelated features in a single long prompt.
✅ Do not skip security checks such as auth, validation, and rate limiting.
✅ Do not rely only on auto tests run by the tool without your own testing.
✅ Do not deploy to real users without monitoring, logging, and error alerts.

To get the complete guide to build apps with AI,
Check the infographic below 👇 

Try here: https://lnkd.in/e6Eua37q

What do you think about building apps with AI?
Comment below 👇 

♻️ Repost to help your network cook apps with AI

Every successful CEO has one secret weapon.

It’s not talent, money, or luck.
It’s the ability to make better decisions.

Here are 30 powerful ChatGPT prompts for efficient decision-making.

Strategic Business Decision Evaluation 
- I am deciding between [Option A], [Option B], and [Option C] for my business. Provide a structured decision matrix where you track each option against evaluation metrics such as long-term ROI, alignment, risks, and feasibility. Assign weights to each factor, rank for each score, and end with a scenario recommendation of the best choice along with possible trade-offs.
 
 Personal Life Choice Analysis 
- I need to decide between [Choice A], [Choice B], and [Choice C] for my personal situation. Consider life constraints like financial stability, budget, time, location, lifestyle impact, and weighted pros/cons to create a logical framework that concludes, supports, risks, and recommends the best direction based on what aligns with a clear justification.
 
 Career Path Decision Aid 
- I’m torn between pursuing [Career Path A] and [Career Path B]. Analyse both paths in terms of salary potential, required skills, long-term growth opportunities, and career stability. For each option note risks and rewards, highlight career paths made by others with similar roles, and decide which one is the best fit for my values [insert personal values].
 
Investment Opportunity Comparison 
- I am considering investing in [Investment A], [Investment B], or [Investment C]. Create a risk/return analysis, a timeline to liquidity, use of long-term potential gains, income stream potential, and which option is most aligned with my financial portfolio strategy. Provide a decision recommendation of which option is superior for my investor profile.
 
 Time Management Decision Support 
- I have [X hours] available per day and need to allocate them between [Activity A], [Activity B], and [Activity C]. Optimise the schedule with balances in effectiveness, rest, and long-term productivity. Recommend the best time allocation plan with practical proof and examples, and create a framework based on a sample day plan.

Note: AI can help you with fast decision-making, but take all important decisions only by adding your human thinking and intuition to it.

To get more ChatGPT prompts, 
Check the infographic below 👇 

Which one prompt did you like the most here?
Comment below 👇 

Learn AI for free: https://lnkd.in/euYZeAdb 

♻️ Share this post to help your network use AI for better decision-making

Every successful CEO has one secret weapon.

It’s not talent, money, or luck.
It’s the ability to make better decisions.

Here are 30 powerful ChatGPT prompts for efficient decision-making.

Strategic Business Decision Evaluation 
I am deciding between [Option A], [Option B], and [Option C] for my business. Provide a structured decision matrix where you track each option against evaluation metrics such as long-term ROI, alignment, risks, and feasibility. Assign weights to each factor, rank for each score, and end with a scenario recommendation of the best choice along with possible trade-offs.
 
 Personal Life Choice Analysis 
I need to decide between [Choice A], [Choice B], and [Choice C] for my personal situation. Consider life constraints like financial stability, budget, time, location, lifestyle impact, and weighted pros/cons to create a logical framework that concludes, supports, risks, and recommends the best direction based on what aligns with a clear justification.

You don't need to spend hundreds of hours on learning the old way. 

Perplexity can become your smartest tutor only if you know what to ask.

Here are 20 Perplexity prompts that will help you learn more in less time.

Here are the use cases for which you can use Perplexity for learning:
✅ Comprehensive Topic Overview
✅ Step-by-Step Learning Roadmap
✅ Concept Comparison Table
✅ Academic Paper Summary & Analysis
✅ Beginner-Friendly Theory Explanation
✅ Chronological Timeline of Key Events
✅ Case Study Breakdown
✅ List of Best Practices
✅ Technical Term Deep Dive
✅ Overview of Research Methodologies

And more use cases with prompts are covered in the infographic below 

Will you try using Perplexity for learning?
Comment below 👇 

Learn AI for free: https://lnkd.in/euYZeAdb 

🔁 Repost to help your network use AI for learning

You don't need to spend hundreds of hours on learning the old way. 

Perplexity can become your smartest tutor only if you know what to ask.

Here are 20 Perplexity prompts that will help you learn more in less time.

Here are the use cases for which you can use Perplexity for learning:
✅ Comprehensive Topic Overview
✅ Step-by-Step Learning Roadmap
✅ Concept Comparison Table
✅ Academic Paper Summary & Analysis
✅ Beginner-Friendly Theory Explanation
✅ Chronological Timeline of Key Events
✅ Case Study Breakdown
✅ List of Best Practices
✅ Technical Term Deep Dive
✅ Overview of Research Methodologies

It took them 9 years to hit $500,000,000 ARR.

Then just one year to 2x it.

This is what you get,
When infrastructure finally catches up with ambition.

Because scaling businesses globally shouldn’t feel like fighting gravity.

The fastest-growing companies, from Canva to Brex, aren’t waiting on legacy systems.
They’re growing with Airwallex

They’re moving money, 
Across 60+ currencies without friction.
Managing spend, 
And scaling financial operations for global businesses.

$1,000,000,000 ARR isn’t just a regular financial milestone.

It’s proof that borderless finance is becoming the default layer of global business.

And for founders building the next wave of AI, SaaS, or e-commerce,
This is the infrastructure quietly powering your growth behind the scenes.

The internet made business global.
Airwallex made finance global.

Why I like Airwallex 👇
→ Trusted by 150,000+ companies.
→ Built for scale, speed, and smarter cross-border ops.

Legacy banking had a good run.
But the next era of growth?
It’s built on infrastructure that moves as fast as you do.

Learn more here 👉 https://lnkd.in/e8KW2nv8

What do you think about using such a globally scalable financial infrastructure in businesses? 
Comment below 👇 

♻️ Share this to help your network use modern financial systems in their businesses 

#AirwallexPartner

Learn AI in 5 min a day. Join 500k+ others and subscribe to the AI Tool Report.

Building the #1 B2B AI Newsletter & Podcast. You don't need to be technical. Just informed. 

➡️ The Newsletter — 400k readers, top B2B AI newsletter, primarily US Audience, 55+% open rate. 
➡️ The podcast — C-suite focused, over 50 episodes done with weekly upload schedule. 
➡️ Upscaile — Custom training & implementation.  

Beyond the work?

I’ve spent the last 4+ years slow-traveling through 30+ countries, building remotely, and making hard things fun again.

Liam Lawson

I watched 50+ companies waste ChatGPT for 12 months.

How to actually unlock AI value in 5 steps:

One-off queries don't transform businesses.

You need two things:

1. Repeatable systems (not random prompts)
2. Structured workflows (most people miss this)

If I had to start using AI properly today, I'd build systems first.

Here's the exact blueprint:

Step 1: Identify Your Repeatable Tasks → 30 minutes

Stop asking ChatGPT random questions.

Map your recurring workflows:

- Customer support responses
- Content repurposing
- Data analysis reports
- Research summaries

Pick one workflow that happens weekly.
That's your starting point.

Step 2: Build Your System Prompt → 15 minutes

Create a master prompt template:

"You are a [role] that [specific function]. Your task is to [clear objective]. Always follow these rules: [your guidelines]."

Save this as your system foundation.
Reuse it every time.

Step 3: Add Context Controls → 10 minutes

Give ChatGPT the right inputs:

- {{customer_data}} for personalization
- {{brand_guidelines}} for consistency
- {{past_examples}} for quality standards

Variables make prompts reusable.
Not one-time queries.

Step 4: Create Output Structures → 10 minutes

Define exactly what you want back:

- Use JSON for structured data
- Request specific formats
- Set character limits
- Demand citations

ChatGPT follows structure better than vague asks.

Step 5: Build It Into Your Workflow → 30 minutes

Connect ChatGPT to your actual tools:

- Zapier automation
- API integrations
- Custom GPTs with actions
- Agent frameworks

Now it's a system, not a search engine.

The difference between search and systems?

Search = "Write me a blog post"
System = Automated workflow that turns your brief into SEO-optimized content using your brand voice, past examples, and target keywords

Search happens once.
Systems run forever.

The real power of treating ChatGPT as infrastructure:

- Scales your team without hiring
- Maintains consistency across outputs
- Compounds value over time
- Actually transforms operations

Most people use ChatGPT like an intern.

You should be using it like an operating system.

What workflow are you turning into a system first?

P.S. Want to learn more about AI?

1. Scroll to the top
2. Click "Visit my website"
3. Sign-up for our free newsletter

The #1 AI Newsletter & Podcast for Business Leaders (400k agree).

Stop Using Chatgpt Like Google

Most people treat ChatGPT's context window like unlimited storage.
It's not storage. It's working memory.

Here's how to use context windows properly in 4 steps:

Most AI outputs feel generic and disconnected.

Random prompts.
No structure or strategy.

You can't force better outputs.
But you can engineer better context.

Step 1: Understand What You're Working With

Context window = working memory, not storage.

Like RAM vs hard drive on your computer.

Claude Sonnet 4.5: 200K tokens (150,000 words)
GPT-4o: 128K tokens (96,000 words)
Most people use: 2K tokens (1,500 words)

You're using 1% of available capacity.

Step 2: Structure Your Context Hierarchically

Load information in priority order:
↳ Critical instructions first
↳ Core data and examples second
↳ Supporting documents third
↳ Reference material last

The model prioritizes early context.

Don't bury key info on page 50.

Step 3: Compress Before Loading

Use AI to prep your context:

1. Pre-summarize long documents
2. Extract only key points
3. Create hierarchical structure
4. Load compressed version

Turn 500 pages into 50K tokens of pure signal.

No noise, just relevance.

Step 4: Load Everything at Once

For complex work, give the full picture:
↳ Entire knowledge base
↳ All brand guidelines

↳ 50+ examples
↳ Complete customer data

Then prompt once.

Replace 20 back-and-forths with one session.

The old way: Prompt, add context, re-prompt, add more, repeat.
The new way: Structure 200K tokens strategically, prompt once.

Context windows aren't about fitting more.
They're about reasoning across everything simultaneously.

Save this. Test it tomorrow.

P.S. Want to learn more about AI?

1. Scroll to the top
2. Click "Visit my website"
3. Sign-up for our free newsletter

The AI Context Window Trick

What if science fiction wasn’t fiction anymore?

Hassaan Raza and Quinn Favret, co-founders of Tavus, aren’t just building tools... they’re turning 30 years of human-computer research into something people can actually use.

We’ve spent decades dreaming about digital assistants like Jarvis, Cortana, and Data.

But what if we stopped dreaming and started building?

In this episode, Hassan and Quinn share how Tavus is working to realize the sci-fi future and what it takes to help people not just imagine it, but believe in it.

Want more insights like this?

Subscribe to The AI Report here:
https://lnkd.in/eFfz6SVi

#TechFutures #HumanCenteredTech #DigitalAssistants #HCI #StartupVision #Tavus #TheAIReport #ProductLeadership #EmergingTech

Are people building with vision, or just chasing the next funding round?

As the hype around new tools continues to grow, a deeper issue is showing up across the ecosystem:

Too many teams are optimizing for money, not meaning.

In this episode, Quinn Favret and Hassaan Raza talked about why taste, craft, and intention still matter.

Not just in the product itself, but in how it’s built, how it feels, and the values that shape it.

Because when you love the technology and the people you're building for, that care shows up everywhere.

#TechLeadership #ProductCraft #FoundersMindset #BuildingWithCare #HumanCenteredTech #TheAIReport #VCTech #StartupCulture

What’s more powerful than a pitch? A customer proving your product works.

For decades, this industry has overpromised and underdelivered. So it’s no surprise that people are skeptical.

That’s why the best marketing isn’t hypothetical... it’s real results, told by the customers themselves.

In this episode, Ariel Kelman shares how Salesforce launched AgentForce by letting brands like FedEx, Pandora, and Lululemon show what it actually does, not in a demo, but in action.

→ Watch the full episode on our Youtube Channel.

Subscribe so you don’t miss it:
https://lnkd.in/e3jQsBJC

#CustomerSuccess #TrustInTech #ProductMarketing #Salesforce #DigitalTransformation #TheAIReport #PodcastClip

taplio

The Battle

Adam Biddlecombe

Liam Lawson

Followers

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Likes

Performance ScoreAdam Biddlecombe's LinkedIn Performance

Performance ScoreLiam Lawson's LinkedIn Performance

Ready to grow your LinkedIn presence?

taplio

The Battle

Adam Biddlecombe

Liam Lawson

Followers

Posts

Engagements

Likes

Performance Score.css-goub6s{font-size:var(--chakra-fontSizes-md);font-weight:500;color:var(--chakra-colors-gray-600);display:block;margin-top:var(--chakra-space-1);}Adam Biddlecombe's LinkedIn Performance

Performance ScoreLiam Lawson's LinkedIn Performance

Ready to grow your LinkedIn presence?

Performance ScoreAdam Biddlecombe's LinkedIn Performance