Shushant Lakhyani

Freelance marketer building TechnoBizzVault, where I help professionals discover modern tools so they can be productive without burning out.

Highly skilled content creator with a strong track record in newsletter growth, social media growth, and social media content creation. 

Proven success in building an audience on LinkedIn and Twitter/X and creating engaging content for newsletters. 

Experienced in creating content for LinkedIn, Twitter/X, and newsletters. 

Proficient in content creation and AI, no-code, and automation tools. 

Achievements:
✅ 150,000+ followers on LinkedIn and Twitter/X combined. 
✅ Helped Horizon AI reach 46,000+ newsletter subscribers from 1,800 subscribers in 6 months 
✅ Sold information products to more than 20,000 customers on Gumroad. 
✅ Worked with 5+ clients for ghostwriting 
✅ Gained 100M+ impressions on LinkedIn, Twitter/X, and Medium combined. 

Passionate about technology, content creation, and online business. 

Currently, working on building and growing TechnoBizzVault, an email newsletter where you discover hidden digital gems for free. 

Also, working as a freelance social media growth manager for a leading media brand in AI.

ClickUp Micro-Product Builder

I’m sad to see most people still don’t use YouTube for learning. 

Here are 15 YouTube channels that will help you learn new skills. 

🔖 Save this post for later 

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1. Andrew Huberman

Learn everything about health, fitness, and improving your physical and mental performance in detail.

🔗 https://lnkd.in/d53rNe8u 

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2. FreeCodeCamp

Get to learn everything and anything about programming. 

🔗 https://lnkd.in/d59jRDdH 

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3. Matt Wolfe

Get to learn everything happening in the AI world with tutorials and tools to use. 

🔗 https://lnkd.in/dsuNEgxU 

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4. MIT OpenCourseWare

Get free tutorials from one of the top universities in the world. 

🔗 https://lnkd.in/dtQ85xbn 

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5. Crash Course

Get small and easy-to-understand tutorials on topics that matter. 

🔗 https://lnkd.in/d9gKHxtf 

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6. Trevor Jones

Learn end-to-end about video editing. 

🔗 https://lnkd.in/dEjN8Uab  

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7. No Code MBA

Learn everything you need to know about using different tools to build websites and applications without writing code. 

🔗 https://lnkd.in/dQZzvbPE  

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8. Design with Canva

Get to learn everything you need to know about graphic design with Canva 

🔗 https://lnkd.in/d_-ws85s 

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9. Flux Academy

Learn everything you need to know to be a web designer. 

🔗 https://lnkd.in/drcJsVUX 

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10. Nicolas Cole 

Learn how to make money online by writing for others, growing your own channels, selling digital products, and writing ebooks.  

🔗 https://lnkd.in/dwZcDeuh  

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11. Liam Ottley

He helps you learn how to automate your manual work with AI and help businesses automate their manual work too.

🔗 https://lnkd.in/dk7se_6x 

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12. Kallaway 

He helps you learn how to social media create content and grow your business with it.  

🔗 https://lnkd.in/d2RgCAgy 

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13. Alex Hormozi

If you’re an entrepreneur or you want you be an entrepreneur, his channel is the entire guide for you build, manage, and grow a business. 

🔗 https://lnkd.in/dyXAk3QA 

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14. Starter Story

This channel helps you learn how people are making money by building digital businesses. 

🔗 https://lnkd.in/dFtgka_f 

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15. Alux .com

This channel helps you level up your career, income and personal finance skills. 

🔗 https://lnkd.in/dwdTpv5b 

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Would you like to recommend any other channel? 

Let me know in the comments 👇 

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Discover hidden digital gems for free: https://lnkd.in/daKFh4Gr 

🔁 Repost to help your network learn from the best YouTube channels 

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Just Ship It

Subscribe to my newsletter to decode disruptive business models every week: https://digital-disruptor.beehiiv.com/

If you still do work manually in 2026, you are choosing to stay behind.

Here are 19 AI tools that will make you unstoppable.

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1. Tweet Hunter

An AI-powered tool that will help you grow on Twitter/X with content ideas, viral posts inspiration, scheduling, engagement assistance, and analytics. 

🔗 https://lnkd.in/dD_aWkgv 

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2. Sandcastles AI

Find outlier content in your niche, understand why they went viral, and remix them to create your next hit.

🔗 https://lnkd.in/draKtReh 

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3. Cursor

AI-powered code editor that boosts productivity with smart multi-line autocompletion, natural language code edits, AI-driven refactoring, and deep codebase understanding.

🔗 https://cursor.com/ 

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4. aiCarousels

Create carousels using AI in minutes.

🔗 https://lnkd.in/dxVQueqX 

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5. Submagic

Create AI-powered perfectly edited short videos in minutes.

🔗 https://lnkd.in/dRmEq-x3 

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6. Expertise AI

 Turn your website visitors into meetings and qualified pipeline with this AI agent platform.

🔗 https://www.expertise.ai/ 

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7. 10Web

Build your websites without writing any code from just AI prompts.

🔗 https://10web.io/ 

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8. VEED

All-in-one AI video content creation and editing tool.

🔗 https://lnkd.in/dwzDqVvC 

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9. Superhuman

AI-powered email management for high-performance teams.

🔗 https://superhuman.com/ 

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10. Zapier

Create AI-powered workflow automation in minutes using AI and AI agents.

🔗  http://zapier.com/ 

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11. Taplio

It is the best all-in-one AI-powered tool for LinkedIn growth.

🔗 https://lnkd.in/dZGhtivW 

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12. Beehiiv

Write your newsletter using AI, schedule it, grow, monetize, and get in-depth detailed analytics.

🔗 https://lnkd.in/dMvdenTq 

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13. Kickresume

Create your resume and cover letter in minutes with AI.

🔗 https://lnkd.in/d5ZKKg3K 

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14. Quadratic

Chat with your data and get insights in seconds.

🔗 https://lnkd.in/dKHMmQtW 

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15. Gamma

Create persuasive presentations, landing pages, and docs powered by AI in minutes

🔗 https://gamma.app/ 

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16. Lovable

This is one of the best tools to cook complete web apps easily in minutes from just a single prompt.

🔗 https://lnkd.in/dsgtVz5w 

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17. VidIQ

All-in-one AI-powered YouTube growth tool that helps with ideas, titles, keywords, thumbnails and more all in one place.

🔗 https://lnkd.in/djr8HZvX 

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18. Opus

Create multiple viral short video clips from one long video in minutes.

🔗 https://www.opus.pro/ 

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19. Freepik

Suite of AI-powered tools for generating and editing images, videos, and design assets from simple prompts.

🔗 https://www.freepik.com/  

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Discover hidden digital gems for free: https://lnkd.in/daKFh4Gr

🔁 Repost to help your network use the best AI tools 

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If you still do work manually in 2026, you are choosing to stay behind.

Here are 19 AI tools that will make you unstoppable.

🔖 Save this post for later 

1. Tweet Hunter

An AI-powered tool that will help you grow on Twitter/X with content ideas, viral posts inspiration, scheduling, engagement assistance, and analytics. 

🔗  https://tweethunter.io/?via=shushant 

2. Sandcastles AI

Find outlier content in your niche, understand why they went viral, and remix them to create your next hit.

🔗 https://www.sandcastles.ai/  

3. Cursor

AI-powered code editor that boosts productivity with smart multi-line autocompletion, natural language code edits, AI-driven refactoring, and deep codebase understanding.

🔗 https://cursor.com/    

4. aiCarousels

Create carousels using AI in minutes.

🔗 https://www.aicarousels.com/editor?via=shushant  

5. Submagic

Create AI-powered perfectly edited short videos in minutes.

🔗 https://www.submagic.co/?fpr=shushant59  

6. Expertise AI

I can’t believe people still don’t use newsletters for learning.

Here are 15 newsletters to revolutionize your life, career, and mindset.

🔖 Save this post for later 

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1. TechnoBizzVault 

Get to know the best tools online to get more done in less time. 

Link: https://lnkd.in/daKFh4Gr 

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2. Mindstream 

Stay informed with the latest developments in AI 

Link: https://lnkd.in/gFxjCXky 

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3. Future/Proof

A newsletter by Dan Koe to help you learn what skills you need to master to have a futureproof career in this AI era. 

Link: https://lnkd.in/eZrduJqG 

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4. Unsubscribe

A newsletter by Justin Welsh to help you build your one-person calm business and monetise your expertise online.

Link: https://lnkd.in/ePMvZkS6 

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5. High Agency

A newsletter by George Mack to help you be a better version of yourself with practices that you miss out on. 

Link: https://lnkd.in/eQaaqJgw 

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6. Balajis .com

A newsletter by Balaji Srinivasan to help wannabe builders, entrepreneurs, investors, finance enthusiasts, and people who care about the future of our world.

Link: https://balajis.com/ 

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7. David Senra

A newsletter in which you get to learn about history’s greatest founders and what you can use from their insights and advice to apply in your life.

Link: https://lnkd.in/edv-mQmr 

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8. Miss Excel 

Learn how to use Excel in a more efficient way. 

Link: https://lnkd.in/gExwnJHK 

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9. The Publish Press 

Get the latest creator news. 

Link: https://lnkd.in/gxb6BgpZ 

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10. The High Performance Journal 

Learn how to build your body and increase performance. 

Link: https://lnkd.in/gzHS8Xu7 

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11. The MilkRoad 

Get smarter about Crypto. 

Link: https://milkroad.com/ 

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12. Bengingi 

If you are obsessed with food, you’ll love this. 

Link: https://www.bengingi.com/ 

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13. Marketing Examples 

A gallery of real world marketing examples from successful companies.  

Link: https://lnkd.in/dMEP7AGE  

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14. The Hustle 

Get smarter on business and tech 

Link: https://thehustle.co/ 

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15. Trends VC 

Dive into new markets and ideas. Mostly for entrepreneurs and wannabe entrepreneurs. 

Link: https://join.trends.vc/ 

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Discover hidden digital gems for free: https://lnkd.in/daKFh4Gr 

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Would you like to recommend any other good email newsletters? 

Let me know in the comments 👇

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I can’t believe people still don’t use newsletters for learning.

Here are 15 newsletters to revolutionize your life, career, and mindset.

🔖 Save this post for later 

1. TechnoBizzVault 

Get to know the best tools online to get more done in less time. 

Link: https://technobizzvault.beehiiv.com/subscribe 

1. Mindstream 

Stay informed with the latest developments in AI 

Link: https://www.mindstream.news/ 

1. Future/Proof

A newsletter by Dan Koe to help you learn what skills you need to master to have a futureproof career in this AI era. 

Link: https://letters.thedankoe.com/ 

1. Unsubscribe

A newsletter by Justin Welsh to help you build your one-person calm business and monetise your expertise online.

Link: https://www.theunsubscribed.co/ 

1. High Agency

A newsletter by George Mack to help you be a better version of yourself with practices that you miss out on. 

Link: https://essays.highagency.com/ 

1. Balajis .com

A newsletter by Balaji Srinivasan to help 

I don’t understand why people are still creating and editing videos manually.

These 10 AI tools turn hours of video creation and editing into minutes.

🔖 Save this post for later 

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1. HeyGen

You don’t need to record videos manually; you can instead use HeyGen to use your AI avatar to create talking head videos. 

Link: https://lnkd.in/dmDreE-5  

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2. Submagic

You can use this tool to make your short-form videos more captivating with captions, B-rolls, zooms, and sound effects. 

Link: https://lnkd.in/dRmEq-x3  

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3. Opus

If you have a podcast on YouTube or upload long-form video content, you can repurpose it to create short-form video content for other social media platforms.  

Link: https://www.opus.pro/  

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4. VEED

An all-in-one AI-powered video editing and creation tool with a wide variety of AI features and in-built AI video generators. 

Link: https://lnkd.in/dwzDqVvC  

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5. Vsub

Create AI caption videos, Reddit story videos, would you rather videos, AI videos, fake text videos, and quiz videos in 3 minutes.

Link: https://lnkd.in/dCEY9XW8  

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6. Keyframes .studio

An all-in-one video editing platform for creating, editing, and sharing videos on social media channels.  

Link: https://keyframes.studio/  

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7. VideoLeap

An all-in-one video editing platform that you can use from your phone.  

Link: https://lnkd.in/dGKNR69T  

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8. Descript 

AI-powered, fully featured, end-to-end video editor that you already know how to use.  

Link: https://www.descript.com/  

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9. Invideo

AI video generation tool for social media marketing and advertising use cases.  

Link: https://invideo.io/  

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10. Freepik

Use all the best AI video models of Runway, Kling, Google, and more all in one place.  

Link: https://www.freepik.com/  

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Chill.

You don’t need to use all of them.

Check all these tools and use only the ones that help speed up your video creation process.

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What do you think about using AI for video creation?

Let me know in the comments 👇 

---

Discover hidden digital gems for free: https://lnkd.in/daKFh4Gr 

🔁 Repost to help your network use the best AI video creation tools 

---

I don’t understand why people are still creating and editing videos manually.

These 10 AI tools turn hours of video creation and editing into minutes.

🔖 Save this post for later 

1. HeyGen

You don’t need to record videos manually; you can instead use HeyGen to use your AI avatar to create talking head videos. 

Link: https://app.heygen.com/login?sid=rewardful&via=shushant  

1. Submagic

You can use this tool to make your short-form videos more captivating with captions, B-rolls, zooms, and sound effects. 

Link: https://www.submagic.co/?fpr=shushant59  

1. Opus

If you have a podcast on YouTube or upload long-form video content, you can repurpose it to create short-form video content for other social media platforms.  

Link: https://www.opus.pro/  

1. VEED

An all-in-one AI-powered video editing and creation tool with a wide variety of AI features and in-built AI video generators. 

Link: https://veed.cello.so/ukABtJhPxfA  

1. Vsub

Create AI caption videos, Reddit story 

You are still using ChatGPT like it is Google.

No wonder it is giving you mid outputs and wasting your time.

Here is the complete ChatGPT guide that finally unlocks its full power.

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Do you use ChatGPT every day?

Let me know in the comments 👇

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Discover hidden digital gems for free: https://lnkd.in/daKFh4Gr 

🔁 Repost this to help your network be productive with ChatGPT 

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Complete ChatGPT Guide

Goodbye manual work. 

I don’t understand why people don’t use Google’s AI tools at work. 

Here are 22 AI tools by Google to help you get more done in less time. 

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Here are all the Google AI tools you’ll get in the carousel below:

1. NotebookLM
2. Gemini
3. Nano Banana Pro
4. Canvas
5. Veo 3.1
6. Guided Learning
7. Visual Layout
8. Gems in Gemini
9. Google AI Studio
10. Deep Research
11. Imagen-4
12. Gemini in Workspace apps
13. AI mode
14. Pomelli
15. Jules
16. Antigravity
17. Opal
18. Vids
19. Flow
20. Stitch
21. Whisk
22. MusicFX

--- 

Have you tried any of these Google AI tools?

Let me know in the comments 👇 

--- 

Discover hidden digital gems for free: https://lnkd.in/daKFh4Gr 

🔁 Repost to help your network work efficiently with Google’s AI tools 

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Google AI Tools

Here are 11 new AI hacks that will help you get more work done in less time. 

🔖 Save this post for later 

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What other new AI hacks would you recommend adding here?

Let me know in the comments 👇 

---

Discover hidden digital gems for free: https://lnkd.in/daKFh4Gr 

🔁 Repost to help your network use AI 

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New AI Hacks

Everyone wants advice from the top 1%.

These 20 ChatGPT prompts make that unfairly easy.

🔖 Save this post for later 

--- 

You’ll get coaching prompts of these people in the carousel below:

1. Elon Musk
2. Naval Ravikant
3. David Goggins
4. Jeff Bezos
5. Sam Altman
6. Reed Hastings
7. Joe Rogan
8. Tony Robbins
9. Reid Hoffman
10. Pieter Levels
11. Warren Buffett
12. Mark Zuckerberg
13. Jensen Huang
14. Peter Thiel
15. Mukesh Ambani
16. Oprah Winfrey
17. Mark Cuban
18. Chris Do
19. Andrew Huberman
20. Alex Hormozi 

--- 

What do you think about using AI to learn from the top 1%?

Let me know in the comments 👇 

--- 

Discover hidden digital gems for free: https://lnkd.in/daKFh4Gr 

🔁 Repost to help your network 

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20 ChatGPT Prompts To Get Coached By The Top 1%

Before: Spend hours solving problems manually.

Now: Use AI to solve problems faster. 

Here are 20 ChatGPT problems that will help you with problem-solving.

🔖 Save this post for later 

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Tip-1: You can transcribe this PDF on Mistral.

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Tip-2: All these prompts are prompt templates. You can customize them to your use case.

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Tip-3: You can use these prompts on different ChatGPT models, but it is best to use them on ChatGPT 5.2 in Auto mode.

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For what other problem solving use cases do you recommend using ChatGPT?

Let me know in the comments 👇

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Discover hidden digital gems for free: https://lnkd.in/daKFh4Gr 

🔁 Repost this to help your network use AI for problem-solving 

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ChatGPT Prompt Templates For Problem-Solving

I’m shocked people still don’t use AI to write better than their competitors. 

Here are 20 ChatGPT prompts that will help you write better and faster than ever. 

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20 use cases covered in these prompts in the carousel below: 

1. Clarity first rewrite
2. Audience-specific writing
3. Conciseness and impact
4. Logical flow Optimization
5. Tone transformation
6. Active voice enhancement
7. Strong openings
8. Strong conclusions
9. Precision and specificity
10. Sentence-level improvement
11. Persuasive writing upgrade
12. Simplification without dumbing down
13. Consistency check
14. Example and analogy enhancement
15. Reader engagement
16. Professional polish
17. Storytelling integration
18. Headline and subhead generation
19. Editing for skimmability 
20. Final editorial review 

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Do you use AI to refine your writing?

Let me know in the comments 👇 

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Discover hidden digital gems for free: https://lnkd.in/daKFh4Gr 

🔁 Repost to help your network write better with AI 

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ChatGPT Prompts To Help You Write 10x More Efficiently

AI isn't taking your job.

But someone with these skills might.

These are the 24 AI skills you can work on in 2026 to stay ahead.

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Chill. 

You don’t need to master all of them.

Pick 1-2 skills that will help you in your job and master them. 

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What other AI skill would you like to add here?

Comment below 👇 

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Discover hidden digital gems for free: https://lnkd.in/daKFh4Gr 

🔁 Repost to help your network work on their AI skills 

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linkedin.com

JSESSIONID

LinkedIn

li_at

24 AI Skills You Can Work On In 2026

R. AnandhaKumar

You’re still using ChatGPT like a search bar.

No wonder your workload keeps piling up.

Here are 10 ChatGPT prompts that will help you use ChatGPT as your personal assistant. 

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Here are all the 10 types of prompts you’ll get in the carousel.

1. Daily Executive Assistant
2. Inbox and Message Manager
3. Decision Making and Tradeoff Analysis
4. Research and Insight Synthesizer
5. Project Planning and Execution Assistant
6. Learning Accelerator and Skill Builder
7. Writing and Editing Assistant
8. Personal Productivity Optimizer
9. Meeting Preparation and Debrief Assistant
10. Personal Strategy and Goal Execution Assistant 

---

For what other personal consulting related use cases do you use ChatGPT?

Let me know in the comments 👇 

--- 

Discover hidden digital gems for free: https://lnkd.in/daKFh4Gr 

🔁 Repost this to help your network use AI as their personal consultant 

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ChatGPT Prompts To Use ChatGPT As Your Personal Assistant

You’re solving problems the wrong way.

Not because your brain is slow.

But because it’s untrained.

Master these 10 techniques to solve problems like a pro.

🔖 Save this post for later

---

10 types of problem-solving techniques covered in the carousel:

1. Mind Mapping
2. Five Whys
3. Fishbone Diagram (Cause and Effect)
4. SWOT Analysis
5. SCAMPER
6. Root Cause Analysis
7. Plan-Do-Check-Act (PDCA) 
8. Creative Problem Solving (CPS)
9. Design Thinking
10. Nominal Group Technique

---

What other powerful problem-solving technique would you like to recommend?

Let me know in the comments 👇 

---

Discover hidden digital gems for free: https://lnkd.in/daKFh4Gr 

🔁 Repost to help your network get better at problem solving 

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Best Problem Solving Techniques

AI is not hard.

Your sources are.

These 15 YouTube channels will make AI finally click.

🔖 Save this post for later  

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1. Matt Wolfe

He has his own AI tool directory and has a YouTube channel to help you learn AI. 

Link: https://lnkd.in/dnvGyi4T 

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2. The AI Grid

This channel helps you stay up-to-date on the cutting-edge of AI. 

Link: https://lnkd.in/dSJHvSVE 

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3. AI advantage

He will help you learn how to apply AI in your daily life. 

Link: https://lnkd.in/dZFHp5wQ 

---

4. Jason West

He shares about AI, maximizing the use of ChatGPT, the dynamic world of digital marketing, and sales funnels, and testing new time-saving software. 

Link: https://lnkd.in/dqpiRGK3 

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5. Liam Ottley 

He shares his learnings from running his AI development company, AI SaaS, and from helping his community of over 35,000 AI agency owners to start and scale their own AI businesses. 

Link: https://lnkd.in/d42MJMrr 

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6. Prompt Engineering

He has a PhD in artificial intelligence and he wants to help you learn how to use Artificial Intelligence. 

Link: https://lnkd.in/ddRCEaR9 

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7. The Next Wave

Hosted by Al experts Matt Wolfe and Nathan Lands and it is the essential guide for business owners navigating the complexities of artificial intelligence..

Link: https://lnkd.in/dpUWJp4k 

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8. Two Minute Papers

Get to know AI trends with their use cases. 

Link: https://lnkd.in/dyMUykkt 

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9. Nick Saraev

He has an AI automation agency and helps you learn how you can build and monetize your AI automation skills. 

Link: https://lnkd.in/dMD8m8QT 

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10. howtoai

Learn about how to use AI tools and AI automation strategies. 

Link: https://lnkd.in/dff4XYia 

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11. Nate Herk

He helps you learn how to automate manual work with AI.

Link: https://lnkd.in/dUCDDWmQ 

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12. Greg Isenberg

He talks about startup ideas & tutorials on how to use AI to build & grow your startup.

Link: https://lnkd.in/dpvbb4Vp 

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13. Kevin Stratvert

He helps you master technology and modern tools, achieve more at work, and succeed at school.

Link: https://lnkd.in/d-puVaKV 

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14. Carson Reed

He shares tips of learning and building his AI Agency while helping other likeminded people do the same.

Link: https://lnkd.in/dTzmvUcP 

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15. Jack Vs. AI

He shares how-to videos on how to use trending AI tools.

Link: https://lnkd.in/dd4763-S 

---

What other YouTube channel would you like to recommend?

Let me know in the comments 👇 

---

Discover hidden digital gems for free: https://lnkd.in/daKFh4Gr 

🔁 Repost to help your network learn AI 

---

AI is not hard.

Your sources are.

These 15 YouTube channels will make AI finally click.

🔖 Save this post for later  

1. Matt Wolfe

He has his own AI tool directory and has a YouTube channel to help you learn AI. 

Link: https://www.youtube.com/@mreflow 

1. The AI Grid

This channel helps you stay up-to-date on the cutting-edge of AI. 

Link: https://www.youtube.com/@TheAiGrid/ 

1. AI advantage

He will help you learn how to apply AI in your daily life. 

Link: https://www.youtube.com/@aiadvantage/ 

1. Jason West

He shares about AI, maximizing the use of ChatGPT, the dynamic world of digital marketing, and sales funnels, and testing new time-saving software. 

Link: https://www.youtube.com/@JWestdigital/ 

1. Liam Ottley 

He shares his learnings from running his AI development company, AI SaaS, and from helping his community of over 35,000 AI agency owners to start and scale their own AI businesses. 

Link: https://www.youtube.com/@LiamOttley/  

1. Prompt Engineering

I don’t understand why people don’t use AI for efficient brainstorming.

Here are 20 Google Gemini 3 prompts that turn blank brains into breakthroughs.

🔖 Save this post for later 

---

Here are the 20 brainstorming use cases covered in the carousel below:

1. First Principles Idea Deconstruction 
2. Visual Pattern Driven Ideation 
3. Constraint Based Creativity Engine 
4. Multi Perspective Stakeholder Brainstorm 
5. Analogical Transfer 
6. Future Backcasting Ideation 
7. Assumption Stress Test Brainstorm 
8. Opportunity Gap Mapping 
9. Modular Idea Construction 
10. Failure Inversion Brainstorm 
11. Cross Modal Ideation 
12. Extremes Exploration 
13. Behavioral Trigger Ideation 
14. Systems Leverage Point Brainstorm 
15. Competitive Reframing 
16. Narrative Driven Ideation
17. Scale Down to Scale Up 
18. Insight Synthesis Brainstorm 
19. Workflow Reinvention 
20. Evaluation Ready Idea Generator 

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What do you think about using Gemini 3 for brainstorming?

Let me know in the comments 👇 

---

Discover hidden digital gems for free here: https://lnkd.in/daKFh4Gr 

🔁 Repost to help your network use Gemini 3 for brainstorming 

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Google Gemini Prompts For Efficient Brainstorming

Your brain isn’t slow.

You’re just using outdated learning hacks.

Here are 10 techniques to supercharge your learning.

🔖 Save this post for later 

---

What other new learning techniques would you recommend adding here?

Let me know in the comments 👇 

---

Discover hidden digital gems for free: https://lnkd.in/daKFh4Gr 

🔁 Repost to help your network learn efficiently 

---

Best Learning Techniques

I’m shocked people still don’t use AI to create presentations. 

Here are 10 AI tools that will help you create beautiful presentations in minutes.

🔖 Save this post for later 

---

1. Gamma

Build beautiful presentations, documents, and websites without having any design or coding skills.

Link: https://gamma.app/ 

---

2. SlidesAI

Create Presentation Slides with AI in seconds

Link: https://www.slidesai.io/ 

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3. Decktopus

Build presentations for your business and academic use cases with AI prompts and AI features. 

Link: https://www.decktopus.com/ 

---

4. Genspark AI Agent

Go from text to slides with visuals, charts, and layout from just simple text prompts.

Link: https://lnkd.in/dgZ_bj5c 

---

5. MagicSlides

Just Enter Topic, Youtube URL, PDF, or Text to get a beautiful PPT in seconds.

Link: https://lnkd.in/gQrQy6Ck 

---

6. Beautiful AI

It is a powerful creative partner that designs slides quickly, helps brainstorm ideas, and generates text and images in a snap.

Link: https://lnkd.in/gt2gXxHD 

---

7. MotionIt AI

AI generates elegant slides from keywords or documents, taking care of formatting and image selection.

Link: https://www.motionit.ai/ 

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8. Pop AI

Create presentations with an AI agent from a simple prompt, text background, and files.

Link: https://lnkd.in/dkVN_bgg  

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9. PPT AI 

Use AI to create PPTs, infographics, charts, timelines, reports, product roadmaps and more.

Link: https://ppt.ai/  

---

10. PitchBob

AI tool to create pitch decks for startups.

Link: https://pitchbob.io/ 

--- 

Chill.

You don't need to use all of them. 

Use only one tool that you think would work best for you. 

--- 

Have you tried using AI for presentations?

Let me know in the comments 👇 

--- 

Discover hidden digital gems for free: https://lnkd.in/daKFh4Gr 

🔁 Repost this post to be the first one to inform your network 

---

I’m shocked people still don’t use AI to create presentations. 

Here are 10 AI tools that will help you create beautiful presentations in minutes.

🔖 Save this post for later 

1. Gamma

Build beautiful presentations, documents, and websites without having any design or coding skills.

Link: https://gamma.app/ 

1. SlidesAI

Create Presentation Slides with AI in seconds

Link: https://www.slidesai.io/ 

1. Decktopus

Build presentations for your business and academic use cases with AI prompts and AI features. 

Link: https://www.decktopus.com/ 

1. Genspark AI Agent

Go from text to slides with visuals, charts, and layout from just simple text prompts.

Link: https://www.genspark.ai/agents?type=slides_agent 

1. MagicSlides

Just Enter Topic, Youtube URL, PDF, or Text to get a beautiful PPT in seconds.

Link: https://www.magicslides.app/ 

1. Beautiful AI

It is a powerful creative partner that designs slides quickly, helps brainstorm ideas, and generates text and images in a snap.

Your degree is aging faster than you think.

Here are 30 job roles that will rise fast in 2026.

🔖 Save this post for later 

---

Here are all the job roles covered in the carousel below:

1. AI Engineer 
2. AI Automation Engineer 
3. AI Product Manager 
4. Machine Learning Specialist 
5. Data Scientist 
6. Cybersecurity Analyst 
7. Cloud Architect 
8. DevOps Engineer 
9. Software Developer (Full Stack) 
10. Digital Marketing Strategist 
11. Public Health Data Analyst 
12. Telemedicine Specialist 
13. Clinical Informatics Specialist 
14. AI Ethics Officer 
15. Sustainability Consultant 
16. Renewable Energy Engineer 
17. Wind Turbine Technician 
18. Solar Installer 
19. Robotics Technician 
20. Nurse Practitioner 
21. Occupational Therapist
22. Physical Therapist 
23. Speech Language Pathologist 
24. Growth Marketing Manager 
25. Blockchain Developer 
26. FinTech Engineer 
27. Quantum Software Developer 
28. UX/UI Designer 
29. Strategic Advisor And Independent Consultant 
30. Power Systems Engineer 

---

What other roles do you think will rise in 2026?

Let me know in the comments 👇 

---

Discover hidden digital gems for free: https://lnkd.in/daKFh4Gr 

🔁 Repost to be the first one to inform your network 

---

Job Roles That Will Rise Fast In 2026

🚨 BREAKING: This feels unreal.

AI research just got 10x better.

In AI research you now get library search, notebook saving, Zotero integration, and automated report generation.

Here's a guide on how it works 👇

🔖 Save this post for later 

---

Try SciSpace

It is an AI-powered research platform that automates academic workflows with tools for literature review, citations, and more.

---

SciSpace Agent

Unifies 150+ tools and 59 databases covering 280M+ papers to streamline literature reviews, manuscript writing, peer review, grants, patents, and reports through a single prompt.

---

BioMed Agent

AI co-scientist designed to accelerate biomedical research through multi-omics analysis, clinical reasoning, protocol comprehension, and AI-generated scientific visualizations.

---

SciSpace Library Search on Agent

- SciSpace Library now integrates with Agent for direct PDF search
- Query and analyze your uploaded papers without leaving Agent
- Run analysis across your entire personal library instantly
- All papers remain private and accessible only to you

---

Zotero Integration In Agent

- Zotero and GDrive integrations now live; Notion, Slack, GitHub, OneDrive coming soon
- Auto-syncs your documents, no manual uploads needed
- Agent analyzes files directly from connected accounts
- Faster, seamless workflow for research analysis

---

Report Writing Sub-Agent

- Auto-generates detailed research reports for complex queries
- A report-writing sub-agent handles literature reviews and summaries
- Any prompt needing a report automatically triggers the agent

---

Save To Notebook On Agent

- Save Agent .md files and citations to your Notebook
- Find saved items under My notebooks
- Store key insights for easy reference
- Revisit research as your work progresses

---

Try here: https://lnkd.in/dmCNZBg2

Coupon Codes:
SLJAN40 – 40% off (Annual)
SLJAN20 – 20% off (Monthly) 

---

What do you think about using AI to accelerate research? 

Let me know in the comments 👇

--- 

#ad #SciSpacePartner

Brand partnership • Freelance marketer building TechnoBizzVault, where I help professionals discover modern tools so they can be productive without burning out.

Here are 20 shifts that will change your life and mindset.

🔖 Save this post for later 

---

❎ Feel shy to use AI.
✅ Use AI wherever it accelerates your work.

❎ Stick to only ChatGPT.
✅ Use multiple AI models/LLMs not only for text generation but also for image, video, speech, and music generation. 

❎ Stick to only 1-2 AI tools.
✅ Keep testing free trials of new tools and how they can accelerate your work. 

❎ Use YouTube for entertainment.
✅ Use YouTube to learn something new.

❎ Use Reddit for gossip.
✅ Use Reddit to learn from niche learning related subreddits.

❎ Sleep on LinkedIn.
✅ Use it to build your personal brand, share your ideas, and get better opportunities.

❎ Use Twitter/X for political content.
✅ Using Twitter/X to learn from tech and business leaders about their thoughts.

❎ Use Instagram for brainrot content consumption. 
✅ Using Instagram to learn from creators like rpn, Keanu Visuals, kallaway, and more.

❎ Stick to one AI prompt framework/template.
✅ Test multiple AI prompt frameworks and templates

❎ Sacrifice sleep for Netflix.
✅ Sleeping for 7+ hours consistently and ignore Netflix.

❎ Ignore internal stress signals. 
✅ Working on personal stress management.

❎ Isolate yourself socially. 
✅ Having a closed friends group to talk to daily.

❎ Start days reactively.
✅ Work on one task at a time calmly.

❎ Depend on motivation alone. 
✅ Working on having better habits.

❎ Suppress emotions.
✅ Having a person you can share your feelings with every day. 

❎ Ignore small steps. 
✅ Celebrate your small wins.

❎ Assume abilities are fixed. 
✅ Adopt a growth oriented mindset

❎ Work nonstop for long hours. 
✅ Schedule regular recovery breaks

❎ Stay busy without direction. 
✅ Prioritize meaningful high impact work 

---

Discover hidden digital gems for free: https://lnkd.in/daKFh4Gr 

---

What other shifts would you recommend adding here?
Let me know in the comments 👇 

---

Here are 20 shifts that will change your life and mindset.

🔖 Save this post for later 

❎ Feel shy to use AI.

✅ Use AI wherever it accelerates your work.

❎ Stick to only ChatGPT.

✅ Use multiple AI models/LLMs not only for text generation but also for image, video, speech, and music generation. 

❎ Stick to only 1-2 AI tools.

✅ Keep testing free trials of new tools and how they can accelerate your work. 

❎ Use YouTube for entertainment.

✅ Use YouTube to learn something new.

❎ Use Reddit for gossip.

✅ Use Reddit to learn from niche learning related subreddits.

❎ Sleep on LinkedIn.

✅ Use it to build your personal brand, share your ideas, and get better opportunities.

❎ Use Twitter/X for political content.

✅ Using Twitter/X to learn from tech and business leaders about their thoughts.

❎ Use Instagram for brainrot content consumption. 

✅ Using Instagram to learn from creators like rpn, Keanu Visuals, kallaway, and more.

❎ Stick to one AI prompt framework/template.

✅ Test m

AI/ML Engineer | 300K+ Impressions | Python & Full-Stack Developer | Building Next-Gen AI Agents 🤖 | Mentor Empowering Students & IT Pros | Passionate About Smart, Scalable Systems

As an AI/ML Engineer and passionate Python developer, I specialize in building intelligent, scalable systems that solve real-world problems. With a strong foundation in Electrical and Electronics Engineering (B.E., CGPA 8.7), I transitioned into the world of artificial intelligence, machine learning, and full-stack development — driven by curiosity, creativity, and a deep commitment to continuous learning.

At Avasoft, I’ve had the opportunity to work on cutting-edge projects, including AI-powered chatbots, voice-based assistants, RAG (Retrieval-Augmented Generation) models, and real-time backend services using FastAPI, Flask, and PyTorch. I’ve also led data automation efforts through web scraping, vector similarity searches, and NLP-driven applications, deploying robust solutions via Docker and CI/CD pipelines.

Beyond engineering, I find great fulfillment in mentoring and uplifting students and IT professionals. I actively guide aspiring engineers and developers through technical challenges, career planning, and project development. Whether it's through code reviews, workshops, or one-on-one sessions, I believe in creating opportunities for others to grow and succeed in tech.

My strengths lie in end-to-end solution design, a deep understanding of modern AI architectures, and the ability to translate business needs into technical deliverables. I’m always excited to collaborate, share ideas, and innovate in the intersection of AI, software, and real-time systems.

Let’s connect if you’re looking to discuss AI, collaborative projects, or mentoring opportunities!

Reshma S

🚨 STOP Googling “Best AI Books”
You don’t need 1,000 books.
You need these 9.

If you’re serious about AI, ML, and LLMs in 2026, this is the only reading stack that actually matters.
Amazon is noisy.
This list is signal.

9 (Essential) AI / ML Books You Can’t Miss
1️⃣ AI Engineering – Chip Huyen
How real ML systems are built, shipped, and scaled (not Kaggle demos).
🔗 https://lnkd.in/gDNusNaZ

2️⃣ Prompt Engineering for LLMs – Albert Ziegler & John Berryman
The why + how of prompting beyond copy-paste hacks.
🔗 https://lnkd.in/gFy7UfWn

3️⃣ Hands-On Large Language Models – Jay Alammar & Maarten Grootendorst
The clearest mental model for LLMs I’ve seen.
🔗 https://lnkd.in/gJVrtbbq

4️⃣ LLM Engineer’s Handbook – Paul Iusztin & Maxime Labonne
From experiments → production-grade LLM systems.
🔗 https://lnkd.in/gbHrBKmn

5️⃣ Building LLMs from Scratch – Sebastian Raschka, PhD
If you want to truly understand LLMs, start here.
🔗 https://lnkd.in/gESJ9hJ6

6️⃣ Building LLMs for Production – Louis-François Bouchard & Louie Peters
Latency, cost, monitoring, failures — the real problems.
🔗 https://lnkd.in/gJM2vcHT

7️⃣ Designing Machine Learning Systems – Chip Huyen
A must-read before you call anything “production ready.”
🔗 https://lnkd.in/gZrz6iba

8️⃣ Deep Learning – Goodfellow, Bengio & Courville
The DL bible. Hard. Worth it.
🔗 https://lnkd.in/gFzvz3QW

9️⃣ Mathematics for Machine Learning – Deisenroth, Faisal & Ong
The math that quietly separates builders from button-clickers.
🔗 https://lnkd.in/gtjpSrGr

🎯 Why this list matters
Most people:
 Read random blogs
 Watch endless tutorials
Never build real systems

These books:
✅ Teach foundations
✅ Explain production reality
✅ Scale with you from beginner → expert
📌 Save this  your future self will thank you
♻️ Repost to help an AI dev who’s learning the hard way
💬 Comment “BOOKS” I’ll DM you how I’d read these in order

Director @lumay.ai | 1M+ Impressions | Helping Students professional to Build Next-Gen AI Agents | Mentor Empowering Students & IT Pros | Passionate About Smart, Scalable SystemsD

🚨 BREAKING: Zero → AI Engineer in 6 Months (Not by Watching Tutorials)
Most people ask me this:

Where do I actually PRACTICE GenAI instead of just watching videos?
Here’s the honest answer 👇
You don’t learn AI by jumping between random tools.
You learn it by building systems in the right order.
So here’s a 6-month roadmap that combines
Stanford-level theory
 Real ML thinking
 Hands-on GenAI + Agents
Production mindset

🗓️ Month 1 – Core Foundations (No shortcuts)
Before GenAI, you need engineering basics.
• Python (data structures, OOP)
• Math for ML (Linear Algebra, Probability)
• How models actually work
Start here (beginner friendly):
👉 https://lnkd.in/gdSCtXJv
Output: Simple ML scripts + GitHub repo

🗓️ Month 2 – Machine Learning Core
This is where most people quit and where real engineers are made.
• Supervised & unsupervised learning
• Feature engineering
• Model evaluation & bias
🎓 Stanford CS229 – Andrew Ng
👉 https://lnkd.in/gDc9siUC
Output: End-to-end ML project (data → model → evaluation)

🗓️ Month 3 – Deep Learning Systems
Now you stop “using models” and start understanding them.
• Neural networks, CNNs, RNNs
• Training deep models properly
• Debugging learning failures
🎓CS230 – Deep Learning
👉 https://lnkd.in/guaavVdk
CS231n – Vision + Generative Models
👉 https://lnkd.in/gVJZ-xMq
Output: Deep learning project with real training logic

🗓️ Month 4 – LLMs & Generative AI
This is where GenAI finally makes sense.
• Transformers & attention
• Embeddings & vector search
• NLP foundations
 CS224N – NLP with Deep Learning
👉 https://lnkd.in/gQdFAZXM
 CS224U – Language Understanding
👉 https://lnkd.in/gRsWMfA6
Practice here (real interview-level GenAI repo):
👉 https://lnkd.in/gRb53YAF
Output: LLM-powered system (not just prompts)

🗓️ Month 5 – AI Systems & MLOps
This is the difference between demos and production.
• Model deployment (APIs)
• Vector databases
• Monitoring & evaluation
• CI/CD for ML
 Build production-style AI systems, not notebooks
Output: Deployed AI system with monitoring

🗓️ Month 6 – Real-World AI Engineering
Now you think like an AI engineer, not a learner.
• Data pipelines
• Scale & performance
• Security & privacy
• Case studies (fintech, healthcare, SaaS)
 CS221 – Artificial Intelligence
👉 https://lnkd.in/gM9ndUCf
 CS234 – Reinforcement Learning (Agents mindset)
👉 https://lnkd.in/gVvz87Hc

Join the learning community 👉 https://lnkd.in/gyhqiuPG

Most people rush to tools.
Great AI engineers master foundations, then build systems that survive production.”
♻️ Repost to help someone learn AI the right way
📌 Save this  you’ll come back to it
➕ Follow me for real AI engineering & agent systems

Stop building toy AI apps.
Start engineering real AI systems.
Most “AI Engineering” tutorials stop at:
import openai
That’s not engineering.
That’s a demo.
Production is where the real pain begins:
Latency
Context limits
Hallucinations
Tool chaos
Evaluation gaps
Scaling issues
I spent days reading a 382-page AI Engineering handbook, and here’s what actually matters 👇

🚨 The biggest mistake builders make
They obsess over prompts.
Prompts matter 
but context matters more.
If your system can’t manage context, memory, tools, and evaluation,
no prompt will save you.
 What I learned (that most tutorials skip)

1️⃣ RAG fails alone
Static retrieval breaks.
Real systems need:
→ Dynamic agent flow
→ Multiple data sources
→ Smart retrieval strategies

2️⃣ Memory separates demos from products
Good agents don’t just respond, they remember.
→ Short-term = continuity
→ Long-term = personalization
→ Entity-level = real intelligence

3️⃣ MCP kills integration chaos
→ Standard tool protocol
→ No messy glue code
→ Works across systems

4️⃣ Evaluation needs depth
Accuracy ≠ quality.
You need:
→ Component-level traces
→ Multi-turn testing
→ Red-teaming for safety

5️⃣ Production needs optimization
This is where real engineering starts:
→ KV caching for speed
→ Continuous batching for scale
→ Smart deployment choices
Frameworks will change.
These patterns won’t.
If you’re serious about building AI systems (not demos),
this mindset shift matters.

🔖 Save this for later
♻️ Reposting for builders who want to ship production-grade AI, not tutorials.

Join the learning community -https://lnkd.in/gyhqiuPG

#AIEngineering #ArtificialIntelligence #SystemDesign #LLM #RAG #Agents #MCP #SoftwareEngineering #OpenSource

AI Engineering Book

🚨 Stop Saving Random AI Tools. Start Understanding the Stack.
Most AI projects don’t fail because of the 
model
.
They fail because everything around the model breaks.
And this visual nails that reality 👇
It shows what it actually takes to build production-grade AI systems in Python not just notebooks and demos.

🧠 Python Tools Powering Real AI Systems
🔹 Data Processing & Management
NumPy · Pandas · Polars · Dask
→ Where raw data becomes usable intelligence

🔹 Machine Learning Frameworks
Scikit-learn · XGBoost · LightGBM · CatBoost
→ Structured ML that still runs most businesses

🔹 Deep Learning
PyTorch · TensorFlow · Keras · JAX
→ Vision, NLP, multimodal, foundation models

🔹 MLOps & Automation
Airflow · Prefect · Dagster · Kubeflow
→ Pipelines, scheduling, reliability

🔹 Model Deployment & Serving
FastAPI · BentoML · Streamlit · Gradio
→ From model → usable product

🔹 Experiment Tracking & Monitoring
MLflow · Weights & Biases · Neptune · Comet
→ Reproducibility, metrics, drift tracking

🔹 Data Validation & Evaluation
Great Expectations · Evidently AI · Deepchecks
→ Trust, quality, and correctness

🔹 Visualization
Matplotlib · Seaborn · Plotly · Altair
→ Insights people can actually understand

🔹 Security & Privacy
OpenMined · PySyft · Presidio
→ Compliance, PII protection, safe AI

💡 Big takeaway:
AI today is not “learn a model and ship.”
It’s engineering + orchestration + monitoring + governance.
If you’re a Data Scientist, ML Engineer, or AI Founder, this is the kind of mental map you 
must have to design systems that survive production.

👏 Credits & Appreciation
Visual created by Legend Brij kishore Pandey phenomenal work simplifying a very complex ecosystem.

Join the learning community - https://lnkd.in/gyhqiuPG
🔖 Save♻️ Repost for your AI-building friends.

Director of AI Product Strategy & GTM

AI/ML  Engineer

Director @lumay.ai | 1M+ Impressions | Helping Students professional to Build Next-Gen AI Agents  | Mentor Empowering Students & IT Pros | Passionate About Smart, Scalable SystemsD

Prompt vs Context vs RAG.

Most people think AI answers come from prompts.
That’s the biggest misunderstanding in GenAI.

🔹 Prompt = Decision Logic (Instruction Layer)
A prompt is instruction logic, not knowledge injection.
Think of a prompt like giving operating instructions to a skilled professional.

A prompt controls:
Task definition → what exactly must be done
Role / persona → who the model should behave as
Reasoning style → analytical, step-by-step, concise, critical
Output structure → JSON, bullets, schema, tables
Constraints & guardrails → what must not happen


1. Zero-shot prompt
No examples. Relies entirely on model’s prior training.
Risky for strict formats or edge cases
2. One-shot prompt
One example provided.
Helps pattern matching
Reduces ambiguity
3. Few-shot prompt
Multiple examples showing input → output mapping.
Strongly improves consistency
Crucial for classification, transformation, extraction tasks
4. Persona / Role prompt
Defines expertise and decision boundaries.
“Act as a senior backend engineer reviewing code”
5. System / Instruction prompts
Global rules applied across interactions.
Tone, Safety, Formatting rules, Behavioral boundaries
6. Guardrail prompts
Explicit negative instructions.
What not to assume
When to say “I don’t know”
👉 Prompts don’t teach facts.
They shape decision-making behavior and reasoning patterns.


🔹 Context = Working Memory (State Layer)
Context is temporary intelligence, not long-term storage.
It is the information window the model can reference for this specific interaction.

Key Context Engineering Principles
1. Relevance over volume
More tokens ≠ better answers.
2. Signal selection
Only include information that changes the decision.
3. Structure matters
Unstructured dumps reduce reasoning accuracy.
4. Compression matters
Summarize without losing intent or constraints.
5. Context decay awareness
Long conversations degrade relevance unless managed.
6. Separation of concerns
System context (rules)
Bad context → hallucinations, confusion, inconsistency
Good context → accurate reasoning at that moment
👉 Context determines how correct the reasoning is right now.


🔹 RAG = External Brain (Knowledge Layer)
RAG exists because LLMs shouldn’t be trusted to remember or update your business knowledge.
It’s a runtime retrieval system, not a prompt hack.
What RAG does (in practice):
1.Pulls knowledge from PDFs, databases, APIs, and websites
2.Converts content into embeddings and stores them in a vector index
3.Retrieves only relevant chunks at query time
4.Filters by metadata (source, date, role)
5.Injects verified context before generation
Grounds answers in real, traceable sources
👉 RAG controls truth, freshness, and reliability not creativity.
Visual credit: Huge thanks to Rahul Agarwal for creating the visuals that inspired this breakdown.

♻️ Repost if this clarified things for you it’ll save someone weeks of confusion.

🚨 If your RAG is “working” but not reliable this is why.
Most teams are debugging models.
The real bug is chunking.
Chunking isn’t a preprocessing step.

It’s not “split every N characters and add overlap.”
Chunking is retrieval design.
It decides what your system can retrieve…
and what it will never see.

When chunking is wrong, the symptoms look familiar:
• Retrieval feels close, but never precise
• Citations exist, but can’t be trusted
• Answers sound confident, yet miss exact lines
• Token usage keeps climbing
• Accuracy plateaus no matter how many models you try
This is why many RAG systems sound right
but fail in production.

When chunking is done intentionally, everything changes:
• The right evidence shows up consistently
• Answers get shorter, sharper, and grounded
• Hallucinations drop because context is cleaner
• Traceability improves (critical for enterprise & regulated AI)
• Iteration becomes measurable, not guesswork
That’s why I built this carousel.

It breaks down 14 production-grade chunking strategies 
from semantic and structure-aware chunking
to parent–child, query-aware, and evaluation-driven approaches.
No theory.
No “one-size-fits-all.”
Only patterns that actually reduce retrieval failures.

🔖 Save this if you’re building RAG for production
♻️ Repost if your team is shipping customer-facing AI
💬 Comment “CHUNKING” if you want a deep dive on evaluation metrics next

Chunking_Guide

This time last year, I thought my future was slipping away.
No visa slots.
Spring missed. Fall missed.
Lost admission to my dream university.
I did everything right.
Paperwork. Process. Patience.
Still nothing moved.

At the same time, life hit harder.
Work pressure.
No balance.
Living paycheck to paycheck.
Depending on a monthly salary just to survive.

That’s when it hit me 👇
If nothing is opening for me… maybe I’m not meant to go there.
Maybe I’m meant to build something here.
That failure didn’t break me.

It redirected me.
In June, I started posting on LinkedIn.
No audience. No reach. No shortcuts.
Just:
• Consistency
• Learning in public
• Sharing real value
• Showing up even when no one cared
The results surprised even me.
5K followers.
Then 10K.
Then 15K.
Today 32K+ in under 8 months.

From someone chasing opportunities to:
➡️ Director of AI Product Strategy & GTM
➡️ AI Engineer & system builder (production > demos)
➡️ Educator training the next-gen AI workforce
➡️ Creator on LinkedIn & Instagram (32K+ community)
➡️ Speaker at Women in AI & global tech forums
➡️ Mentor to students & working professionals breaking into AI
➡️ Community leader shaping how AI is actually learned & shipped
All because one door stayed closed.

So if you’re in that phase right now, hear this clearly:
🚫 It’s not rejection
🚫 It’s not delay
🚫 It’s not bad luck
It’s redirection to something bigger than you planned.
Don’t be stressed.
Start new. Learn again.
Let’s get those dreams done. 🤍

If you’re feeling lost, overwhelmed, or behind you’re not broken.
You just need direction, not pressure.
🔑 Skills that actually change your trajectory
• Strong Python & APIs
• Core AI / LLM fundamentals
• RAG (Retrieval-Augmented Generation)
• Systems thinking (not tool chasing)
• Evaluation & debugging
• Clear communication

📚 Trusted resources to start (free & real)
• Stanford LLM Course (Free – YouTube)
https://lnkd.in/gG2WCZmx
• DeepLearning.AI – GenAI & RAG
https://lnkd.in/g_GFxpku
• Hugging Face Learn
https://lnkd.in/gGE2nqsd
• LangChain (RAG & AI apps)
https://lnkd.in/gRdYAt7J
• Real-world RAG tutorial (Real Python)
https://lnkd.in/g2e2KWtt
• Analytics Vidhya – Free AI Courses
https://lnkd.in/gZkH8Kvg
You don’t need to learn everything.

Just start with one skill, one resource, one week.
Trust yourself.
Stay consistent.
Upskill relentlessly.
Outwork yesterday’s version of you.

♻️ Repost this if you or someone you know feels stuck in their career, this motivation + resources might be the reset they need.
Sometimes, one closed door is the push that builds your entire future.

I Kept Posting Even When No One Was Watching
20 days.
5,000 new people.

That number looks exciting now.
But it didn’t feel exciting on Day 1.
Day 1 felt like posting into silence.
Day 5 felt like questioning if this was even worth it.
Day 10 felt uncomfortable showing up without knowing if it would work.
But I showed up anyway.

I posted when I was tired.
I shared when it wasn’t perfect.
I chose progress over polish.
I learned in public.
I built in public.
This growth didn’t happen by luck.
It happened because I refused to disappear when no one was clapping.

And here’s the truth I’ve learned the hard way 👇
In 2026, self-branding is no longer optional.
It’s mandatory.
If you don’t show your work,
people won’t know your value.
If you stay silent,
opportunities quietly move on.

Consistency isn’t loud.
It’s boring.
It’s repetitive.
And it’s powerful.

So I’m committing to this publicly:
 More videos (even when it’s uncomfortable)
 More real insights (not recycled noise)
 More behind-the-scenes building
No matter the reach.
No matter the algorithm.
No matter the noise.

Because consistency is the only real key.
And this journey would not feel the same without the people who stood beside me when the results weren’t visible yet.

A heartfelt thank you to my friends and fellow LinkedIn creators who supported, encouraged, and pushed me to keep showing up:
• Brij kishore Pandey  Palanisamy Charlie  Pooja Jain Shushant Lakhyani Manthan Patel Alex Hina Arora  Sangeetha B Naresh Edagotti Chandra Sekhar Saurabh Dubey Gitanjali 
Your likes, comments, reposts, honest feedback, and quiet DMs mattered more than you know 🤍

This growth isn’t just about numbers.
It’s about community, consistency, and collective energy.
We’re just getting started.

Pick one niche, one insight a day, and post consistently.
 Comment "Strategy" I'll send to your Dm's, Self-branding works when you stay visible, not when you wait.

💾 Save this if you’re building quietly
♻️ Repost to remind someone to keep showing up
👉 Follow for what’s coming next

1K followers in 48 hours, I didn’t go viral. I went intentional and gained.
No paid tools.
No viral hacks.
No copying content.
Just understanding LinkedIn + consistent action.
If I can do this, anyone can including you.

 What Most People Get Wrong on LinkedIn
❌ Posting the same way from Day 1
❌ Copy-pasting trending content
❌ Chasing likes instead of attention
❌ Depending on tools instead of strategy
LinkedIn doesn’t reward noise.
It rewards originality, clarity, and consumption.

📈 What Actually Moves the Algorithm
1️⃣ Test, don’t assume
Rotate formats: text, visuals, carousels.
Your audience decides what works, not trends.

2️⃣ Your voice > viral templates
Take inspiration, never duplication.
Copied content = suppressed reach.

3️⃣ Design matters more than you think
Clean visuals = longer reading time.
Low effort design = scroll away.

4️⃣ Dwell time is king 
If people stop, read, and finish your post,
LinkedIn pushes it further.

5️⃣ Consistency beats intensity
2–3 high-quality posts per week
outperform random daily posting.

 Hard Truth (But Necessary)
Self-branding is not optional anymore.
If you don’t tell your story:
• Someone else will
• Or you’ll stay invisible
Opportunities don’t just come from skills 
they come from visibility + trust.

You don’t need:
• Perfect English
• A big audience
• Fancy tools
You just need:
✅ To start small
✅ To show up consistently
✅ To speak from experience
I started.
It worked.
Now it’s your turn.

🔁 Repost for early access to proven LinkedIn growth strategies.
💬 Connect & Comment “STRATEGY”
I’ll share the exact posting strategy that helped me grow.
👉 Follow Reshma S | #reshmawithai for real LinkedIn growth & personal branding insights


Join the learning community: https://lnkd.in/gjDjHn95 to get started

AI Engineer | 1M+ Impressions | Helping Students professional to Build Next-Gen AI Agents | Mentor Empowering Students & IT Pros | Passionate About Smart, Scalable Systems

🚫 Fine-tuning isn’t dead.
Bad fine-tuning is.
Most teams still fine-tune LLMs like it’s 2022.
Random datasets.
One-shot training.
No evals.
No production feedback.
And then they wonder why models fail in real workflows.

So I put together this carousel:
13 LLM fine-tuning techniques that actually work in production.
Not theory.
Not benchmarks-only advice.
Only methods we’ve seen improve reliability, tool-use, and real-world behavior.
Inside this carousel, you’ll find:
• Domain & task-adaptive pretraining (DAPT, TAPT)
• Multi-stage curriculum fine-tuning
• QLoRA done right (not defaults)
• DORA / AdaLoRA for adaptive capacity
• Long-context tuning that avoids “lost-in-the-middle”
• RAG-aware fine-tuning with citation discipline
• Preference tuning (DPO, IPO, KTO)
• Tool-use fine-tuning with execution feedback
• And the eval mindset most teams still ignore

👉 Key takeaway:
Fine-tuning that ships = training + ruthless evaluation.
If you’re building LLMs for real users not demos this matters.
🔖 Save this for later
♻️ Repost if you’re building production AI
💬 Comment “FT” if you want a deeper breakdown of any technique

LLM fine tuning

Stop collecting GenAI tutorials you’ll never finish. 🚫
Start building things that actually work.

If you’re wondering:
“Where do I really practice GenAI  not just watch videos?”
This repo is the answer.
Gen-AI-Experiments by BuildFastWithAI is not another theory dump.
It’s 130+ production-ready GenAI apps, agents, and experiments you can run, break, debug, and rebuild.

Why this repo stands out 👇
You don’t learn GenAI here you ship it
→ Real apps using OpenAI, Gemini, Anthropic, QWEN, and open-source models
Beginner → Intermediate → Advanced
→ A structured path instead of random demos
100+ libraries covered
→ LangChain, LlamaIndex, CrewAI, Weaviate, ChromaDB, Pinecone, and more
Built for real-world use
→ English, Hindi, and Indian language use cases included

What you’ll actually build 
Starter
• LangChain workflows
• Fine-tuning with LoRA
• Pydantic AI
• Vector databases from scratch
Intermediate
• Multi-agent systems
• RAG pipelines
• AI customer support agents
• Data analysis agents
Advanced
• Enterprise-grade AI agents
• LLM testing & benchmarking
• Multimodal systems
• Advanced RAG architectures

Real apps  not toy demos 👇
• Chat with PDFs & websites
• AI business consultant
• Stock market & finance agents
• Game-playing AI
• Multilingual quiz & learning systems
• Automated research assistants
If you’re serious about:
✔️ Becoming a GenAI engineer
✔️ Shipping real AI products
✔️ Understanding agents, RAG, and orchestration deeply
This repo should already be starred ⭐
🔗 Repo: https://lnkd.in/gbUx4N2w

🔁 Repost to help someone who’s stuck in tutorial mode

Join the learning community 👉 https://lnkd.in/gyhqiuPG

#GenAI #LLM #AIAgents #RAG #BuildInPublic #AIEngineering

🚨 If you’re still coding the same way you did last year, you’re already behind.
Modern AI developers don’t just write code.
They orchestrate tools.

This carousel breaks down the GOATED AI tools powering real developers in 2026  not hype, not theory, but tools actually used.

Here’s the truth 👇
The advantage today isn’t talent alone.
It’s tool leverage.

Inside this stack:
• GitHub Copilot → kill boilerplate
• Cursor → refactor & reason across entire codebases
• Claude (API / Claude Code) → delegate complex backend work
• AIDER → terminal-first, serious engineering
• Otter.ai → never lose context from meetings
• Notion AI → turn chaos into structured knowledge
• SmartCall by LuMay.ai → autonomous voice workflows that actually execute
These tools don’t make you lazy.
They make you dangerously efficient.

If you’re building AI products, agentic systems, or scaling engineering workflows this is no longer optional.
👉 Swipe through the carousel
👉 Save this you’ll come back to it
♻️ Repost to help your developer network
💬 Comment “TOOLS” if you want my exact AI stack or how I use these together in real projects and Reach us to ship your agents.

#ReshmaWithAI #AIForDevelopers #AITools #GenAI #AgenticAI #FutureOfWork

GOATED AI TOOLS

🚨 Stop building AI toys. Start building AI systems.
Most GenAI projects don’t fail because of the model.
They fail because there is no system behind it.
A chat UI is not a product.
A prompt is not architecture.
A demo is not production.

If you want to move from “cool prototype” to enterprise-grade AI, you need to think in systems, not prompts.

I’ve condensed modern AI System Architecture into one executive + builder view 👇
🧠 1. The Brain -> Agentic Orchestration
This is where AI stops talking and starts doing.
• Tool & API orchestration
• Long-term + working memory
• Planning → Action → Feedback loops
If your AI can’t act, it’s just autocomplete.

📚 2. The Knowledge Engine ->Advanced RAG
General models guess.
Grounded systems deliver value.
• Hybrid retrieval (keyword + semantic)
• Reranking for relevance
• Vector databases with governance
Accuracy is an architectural decision.

☁️ 3. The Scale-> Infrastructure
The unglamorous layer that decides whether you survive production.
• Containerization (Docker, Kubernetes)
• GPU utilization & optimization
• Model serving (vLLM, managed platforms)
Great AI fails fast without great infra.

🩺 4. The Pulse -> Observability & Evaluation
If you can’t measure it, you can’t trust it.
• Tracing & execution visibility
• Retrieval + generation evaluation
• Cost, latency & failure monitoring

This is where demos turn into dependable systems.
 The real competitive edge in 2026 isn’t prompting.
It’s architecture.
The future belongs to builders who can design end-to-end AI systems, not just wrap a model with a UI.

♻️ Repost this will save someone months of trial and error.
👇 Comment: which layer is your biggest bottleneck right now?

#ArtificialIntelligence #AISystems #GenerativeAI #LLM #AgenticAI #RAG #AIArchitecture #TechStrategy #Engineering #DevOps #AIStrategy

Stanford just gave away what normally costs 50000$+.
 And most people are scrolling past it for free.
They released their entire LLM course online.
Free. On YouTube.
Not a thread summary.
Not a watered-down webinar.

This is the actual Autumn curriculum:
Transformers & Large Language Models (9 full lectures).
If you want to build real AI products in 2026, this matters far more than prompt tricks.
Because prompts don’t fail gracefully.
Systems do.

Here’s the full playlist, lecture by lecture 👇
• Lecture 1 -> Transformer
https://lnkd.in/ggtaFmRC
• Lecture 2 -> Transformer-Based Models & Tricks
https://lnkd.in/gjeWHtUw
• Lecture 3 -> Transformers & Large Language Models
https://lnkd.in/gBCdrmtt
• Lecture 4 -> LLM Training
https://lnkd.in/gs7zvdRg
• Lecture 5 ->LLM Tuning
https://lnkd.in/gA6duJHj
• Lecture 6 -> LLM Reasoning
https://lnkd.in/g-aad_xW
• Lecture 7 -> Agentic LLMs
https://lnkd.in/gQdTMUDD
• Lecture 8 -> LLM Evaluation
https://lnkd.in/gxaVe869
• Lecture 9 -> Recap & Current Trends
https://lnkd.in/ghVxfa4r

My take (the part most people miss):
In 2026, AI engineering splits into two camps:
1️⃣ People who can prompt models
2️⃣ People who can debug models
The winners will look like old-school engineers.
They won’t just ask “why is the output bad?”
They’ll ask:
• Is this a data issue?
• A training objective mismatch?
• A decoding problem?
• A context window limitation?
• An evaluation blind spot?
• A tooling / orchestration failure?
Because the most dangerous failures won’t look wrong.

They’ll look correct 
until money, trust, or safety is on the line.
That’s how production breaks.
Silently.
Why this course actually matters:
This isn’t just about learning Transformers.
It’s about learning where reality breaks in LLM systems
and how to build guardrails before production teaches you the hard way.

My learning workflow (simple, but insanely effective):
1️⃣ Watch one lecture per week
2️⃣ Pull the transcript into NotebookLM
3️⃣ Ask it to generate:
• a visual mind map
• a one-page infographic (key concepts + diagrams)
• a “teach-it-back” summary in your own words
4️⃣ Build something small from it
→ toy RAG
→ eval script
→ fine-tuning experiment
You’ll learn more in 2 focused hours this way
than 20 hours of passive watching.
If you’re serious about AI systems, not AI demos,
this is worth saving.

♻️ Repost for your AI-builder, learners and networks
💾 Save this you’ll thank yourself later

🚨 Most teams don’t have a productivity problem.
They have a tooling problem.
Hiring more people won’t fix broken workflows.
Meetings won’t fix execution drag.
Motivation won’t fix operational bottlenecks.

The real leverage in 2026 is AI SaaS that removes friction.
That’s why I curated this list 👇
10 AI SaaS tools that are quietly multiplying team productivity across sales, support, marketing, product, and ops.
Not “cool AI demos.”
Not prompt toys.

Real tools used by scaling teams to do more with fewer people.
What these tools actually help with:
→ Reduce headcount dependency without sacrificing quality
→ Speed up GTM without burning teams out
→ Improve CAC, margins, and execution velocity
→ Scale globally without scaling complexity

This carousel breaks down:
• What each tool does
• Who it’s strategically built for
• Why it matters at scale (not just day-1 use)
If you’re a:
• Founder
• Operator
• Product leader
• GTM leader
👉 Save this.
You’ll come back to it when hiring stops being the answer.
♻️ Repost if this helped you think differently about productivity.
💬 Comment “AI STACK” if you want agentic workflows to build your own SAAS.

#AI #SaaS #Productivity #Founder #Startups #GTM #Operations #ReshmaWithAI

AI SAAS TOOLS

Most AI voice agents fail after the demo.
Not because the model is bad.
 But because production is unforgiving.
Demos sound impressive.

 Production exposes everything.
→ Missed greetings
 → Hallucinated actions
 → Broken flows after a tiny prompt change

Here’s the truth most teams learn too late:
Voice isn’t prompting.
 It’s orchestration.
State control.
 Tool gating.
 Barge-in handling.
 Deterministic flows.

If you’re building a real AI voice agent not a toy demo
 that’s where we come in.
Thinking of creating an AI voice agent?
 Reach us.

If you’re thinking of building a voice agent for your business 
 DM me “VOICE”.
 I’ll show you how SmartCall handles real calls, real users, real chaos.

♻️ Repost to save someone from shipping a demo
 💬 Comment “VOICE” I’ll DM how we build production-grade agents

Voice Agent

🚨 Most Data Science aspirants fail not because of Python…
…but because they never truly learn Machine Learning.

You can write SQL.
You can plot graphs.
You can clean data.

But without ML, you’re not influencing decisions  you’re just reporting history.
And interviews know this.

That’s why I always tell working professionals this 👇
Data Science starts where analysis ends.

Recently, I came across a doc titled
📄 “Machine Learning in Just 30 Days”
What impressed me wasn’t the timeline 
it was the thinking structure.
Not random topics.
Not scattered tutorials.
But exactly how real Data Science roles expect you to reason.

Here’s what it helps you build 👇
🔹 Strong ML foundations → Linear & Logistic Regression, Trees, SVMs
🔹 Interview-relevant math intuition → Probability, Statistics, Linear Algebra
🔹 Hands-on ML practice → Implementing algorithms, not just importing libraries
🔹 Real-world ML skills → NLP, CNNs, evaluation, hyperparameter tuning
🔹 End-to-end mindset → Data preprocessing → Modeling → Evaluation → Deployment
🔹 Practical projects → Churn, recommendations, NLP, forecasting

The real value?
You’re forced to work with real datasets, write code, and explain your choices.
And that’s where most candidates break in interviews.
If you’re a working professional planning a switch into Data Science,
this kind of structured ML prep can save you months of confusion.

Because the truth is simple:
♻️ Repost if this resonates,  Random learning feels productive. Structured learning gets you hired. 
🔖 Save this if Data Science is on your roadmap
#datascience #machinelearning #jobswitch #careergrowth #learninginpublic

Machine Learning

I’ve spent the last year building and selling AI agents.
Not demos.
Not toy chatbots.
Real agents doing real work.

And if I had to start again from zero,
these 10 GitHub repos would still be my foundation.
They taught me how agents actually work from LLM basics to production systems 👇

These 10 GitHub Repos Taught Me Everything About AI Agents
1️⃣ Hands-On Large Language Models
A complete notebook companion to the book.
Covers LLM fundamentals → fine-tuning → real implementations.
🔗 https://lnkd.in/eFR7xhhR

2️⃣ AI Agents for Beginners
An 11-part, no-fluff series to build your first working agent step by step.
Perfect if you’re overwhelmed by agent buzzwords.
🔗 https://lnkd.in/e-a2gqSv

3️⃣ GenAI Agents
From simple agent workflows to multi-step, real architectures.
Great for understanding how agents think, act, and iterate.
🔗 https://lnkd.in/euAyXsnQ

4️⃣ Made With ML
Teaches what most repos ignore:
➡️ deployment
➡️ iteration
➡️ production failures
This is where theory meets reality.
🔗 https://lnkd.in/euxk2M96

5️⃣ Prompt Engineering Guide
A must-bookmark resource.
Research, techniques, examples  all in one place.
Prompts matter more than most people admit.
🔗 https://lnkd.in/eeftKQGd

6️⃣ Hands-On AI Engineering
End-to-end LLM and agent projects you can clone, tweak, and ship.
This is how builders learn fastest.
🔗 https://lnkd.in/eyFfWu8u

7️⃣ Awesome Generative AI Guide
A curated map of the GenAI ecosystem  tools, papers, and frameworks.
Use it to explore, not to overwhelm yourself.
🔗 https://lnkd.in/eYW-JcqP

8️⃣ Designing Machine Learning Systems
If you want agents that scale and survive production, this is non-negotiable.
Systems thinking > model obsession.
🔗 https://lnkd.in/eRvyk62b

9️⃣ Machine Learning for Beginners (Microsoft)
Beginner-friendly, structured, and hands-on.
Still one of the cleanest ways to learn ML fundamentals.
🔗 https://lnkd.in/e7S8yDbS

🔟 LLM Course
Clear roadmaps + notebooks for building and deploying LLM-powered apps.
A solid bridge from learning → building.
🔗 https://lnkd.in/eg9JzpF8
My honest takeaway 👇
AI agents aren’t about tools.
They’re about systems, reasoning, workflows, and iteration.
Join the learning community 👉 https://lnkd.in/gyhqiuPG

📌 Save this
♻️ Repost to help someone in your community who’s serious about building AI agents in 2026.
💬 Comment “AGENTS”  I’ll share how I structure my learning path
Follow for real-world agent building not hype.

If you’re still prompting AI in 2026,
 you’re already behind.

AI didn’t jump.
It stacked. 🧱
If you look closely at the evolution of AI, it doesn’t look like disruption 
it looks like building blocks.

For decades, we focused on the foundation:
math, logic, optimization, pattern recognition.
But this stack makes one thing very clear 👇
the real shift is happening at the very top.

We are moving from the Pink Layer (Generative AI)
to the Purple Layer (Agentic AI).
Here’s the climb 👇
1️⃣ The Foundation  Classical AI & Machine Learning
This is where we taught machines rules and patterns.
Classification. Regression. Prediction.
Powerful, but reactive.
2️⃣ The Explosion — Generative AI
The last two years changed everything.
LLMs, Diffusion Models, multimodal systems.
Machines that can create text, code, images, video.
But still… they mostly wait for prompts.
3️⃣ The Frontier — Agentic AI 
Look at the keywords in the purple layer:
Planning. Tool Use. Autonomous Execution.
This is not about better prompts.
This is about systems with agency.

We’re no longer asking:
“Can you write an email?”
We’re building systems that can:
• Remember past interactions
• Plan multi-step workflows
• Decide what to do next
• Use tools (CRMs, calendars, APIs, software)
• Execute tasks end-to-end
This is the moment AI stops being an assistant
and starts becoming a co-worker.

👉 Generative AI was about creation.
👉 Agentic AI is about execution.
If you’re still thinking in terms of prompts,
you’re already one layer behind.

♻️ Repost if this perspective resonates
💬 Comment “AGENTS” if you’re actively building in this layer

📌 One Sketch That Explains More Than 50 Blogs

Sometimes a simple sketch explains what 50 blogs cannot.
The AI landscape today feels noisy  new terms, new models, new hype every week.

But when you step back, the journey is actually very logical.
This visual captures that journey beautifully.
Huge credit to my legend friend Brij kishore  not everyone can draw and explain AI evolution with this level of clarity. This is hard to do, and it’s done exceptionally well here.

Let me tell the story this sketch shows 👇
Classical AI ->Rules
We started by telling machines exactly what to do.
“If this happens, then do that.”
Powerful for logic, but limited to what humans could explicitly define.

Machine Learning -> Learning from Data
Instead of rules, we gave machines examples.
They learned patterns from data classification, regression, prediction.

Neural Networks -> Inspired by the Brain
We modeled neurons, weights, and learning through feedback.
Machines began learning representations, not just outcomes.

Deep Learning -> Patterns at Scale
With depth and compute, models learned vision, speech, and language.
This is where scale unlocked real-world intelligence.

Generative AI -> Creation
AI moved from understanding to creating.
Text, images, code, audio not copied, but generated from learned patterns.

Agentic AI -> Action
This is the next layer.
AI that can plan, remember, use tools, and take action.
Not just responding, but executing with intent.

The most important insight?
Each layer doesn’t replace the previous one.
It builds on it.
Rules → Learning → Patterns → Creation → Action.
Simple sketch.
Deep understanding.
Sometimes, clarity is the real innovation.

🔁 Repost :Sometimes a simple sketch explains what 50 blogs cannot.
💬 Which layer do you think most teams underestimate today?

taplio

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Reshma S

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taplio

The Battle

Shushant Lakhyani

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