Aishwarya Srinivasan

AI@Fireworks AI | Global Speaker(100+ talks)| EB1-A Recipient| 570k+ Followers| AI Engineer| GenAI/LLM Inference| LinkedIn Top Voice| Author-What's Your Worth?| Startup AI Advisor| Angel Investor| Ex-Google,Microsoft,IBM

𝗙𝗼𝗿 𝗽𝗮𝗿𝘁𝗻𝗲𝗿𝘀𝗵𝗶𝗽 𝗶𝗻𝗾𝘂𝗶𝗿𝗶𝗲𝘀, 𝗰𝗼𝗻𝘁𝗮𝗰𝘁 𝗺𝘆 𝘁𝗲𝗮𝗺 𝗮𝘁 💌 partnerships@illuminate-ai.org

I write about:
- AI engineering
- Applied machine learning
- Generative AI Applications
- LLM/ LLMOPs (Training, post-training, inferencing)
- Fundamentals of Data science/ ML/ AI
- ML roles interview tips
- Learning roadmaps (beginner to advanced)
- Importance of personal branding for career growth

**All the posts reflect my own views and do not represent my employer.**

AI Advisor || Responsible AI Advocate || LinkedIn Top Voice - Data & AI  || Top 10 AI Influencer || EB1-A Receipt


Bio: 
Aishwarya currently leads the Developer Relations - Growth at Fireworks AI. She was previously at Microsoft for Startups as a Senior AI Advisor to help Y Combinator startups build machine learning solutions, leveraging core Microsoft/ OpenAI products. Prior to this, Aishwarya was working as a Data Scientist in Google Cloud and before that an AI & ML Innovation Leader at IBM Data & AI, where she was working cross-functionally with the product team, data science team and sales to research AI use-cases for clients by conducting discovery workshops and building assets to showcase the business value of the technology. She holds a post-graduate in Data Science from Columbia University. 

Aishwarya has been awarded Trailblazer of the Year by Women in AI in 2022 and Women of Influence by Business Journal in 2022. She was awarded EB1A - extraordinary ability visa for her contributions in the AI field.

She is an advocate for open-source technologies, and was an open source Developer Advocate for Deepchecks and Lightning AI, and a contributor to Scikit Learn. 


She holds a Patent Award (2018) for developing a Reinforcement Learning model for Machine Trading.

She has over 500,000+ follower base on LinkedIn and actively organizes events and conferences to inspire budding data scientists. She has been spotlighted as a LinkedIn Top Voice 2020 for Data Science and AI, which features Top 10 Machine Learning influencers across the world. 

She is an ardent reader and has contributed to the scholastic community. To spread her knowledge in the space of data science, and to inspire budding Data Scientists, she actively writes blogs related to machine learning on LinkedIn and Instagram: www.instagram.com/the.datascience.gal

Besides being a data junkie, she is a fitness fanatic who is into martial arts (Krav Maga) and yoga.

Senior AI Advisor

As an AI engineer, LLM Twin is an important architecture to understand.

An LLM Twin refers to a system where a language model is designed to represent the knowledge, writing patterns, and decision logic of a specific person, team, or organization. The goal is consistency and reliability, not novelty.

At its core, an LLM Twin is built around how information flows. Think of it as 4 steps:

1️⃣ First, content is collected from real sources: blogs, internal documents, posts, code repositories, or knowledge bases. This data reflects how the person or organization actually thinks and communicates.

2️⃣ Next, the data is structured for two purposes.
One path prepares instruction-style examples that help the model learn how to respond.
Another path prepares retrieval data so the system can pull relevant context at inference time. This ensures responses stay grounded in real material.

3️⃣ Then comes training and evaluation. Models are fine-tuned where appropriate, tested against clear criteria, and versioned before deployment. This step looks very similar to traditional ML workflows, just adapted for language models.

4️⃣ Finally, at inference time, user requests are combined with retrieved context and passed through the deployed model. Monitoring is critical here: quality, latency, and cost all need to be observed continuously.

Where is this used in practice?

✦ Personal or creator assistants that help scale writing and communication
✦ Company-wide assistants that maintain a consistent product or brand voice
✦ Internal tools that answer questions based on code, docs, or prior decisions
✦ Support systems that reflect how experienced engineers respond to issues

Why should AI Engineers understand this?
This architecture reflects how GenAI systems are actually built and maintained. It forces you to think beyond prompts and focus on data quality, retrieval design, evaluation, and long-term system behavior.

My 2 cents 🤌
This is a GREAT topic to build a portfolio project around!! 

Credit: LLM Engineer’s Handbook by Paul Iusztin  and Maxime Labonne. I really like how this book breaks down AI engineering clearly and goes deep into different GenAI system architectures without hand-waving.

Over the past few months, Arvind and I've delivered seven deep technical workshops across agentic AI, RAG, context engineering, AI evals, MCP, vibe coding, and more.

One theme kept coming up: you want something more structured. Not just standalone sessions, but a clear end-to-end roadmap from A to Z.

So that’s what we’re building.

A structured, comprehensive course for:
- Hands-on builders: software, AI, and ML engineers
- AI product managers
- Tech leaders and CXOs looking to upskill meaningfully

Before we finalize it, I’d love your input. I’ve created a short survey to understand where you are, what you want to learn, and your career goals.

It takes under 10 minutes.

As a thank you, you’ll receive an additional 10% discount when we launch the course soon 🫶

Survey: https://lnkd.in/gQYeBCRP

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Here’s my honest pattern with almost every AI tool I try.

I end up using a lot of tools, usually early access. After repeating this cycle enough times, I realized my reactions are almost predictable.

👉First hour
There’s real excitement.
I’m clicking around, testing odd prompts, trying things that used to fail. No strategy yet, just my curiosity and momentum.

👉Next few hours
I start comparing.
Where would this actually fit in my work?
What would I stop using if I kept this?
Is this clearly better, or just new?

👉Later that day
I experiment without guidance.
I skip the docs and examples on purpose. I try incomplete ideas, messy workflows, prompts I would never put in a demo. This tells me more than any tutorial ever could.

👉Day two
Then I look at the examples the team shared.
They usually work smoothly. They’re polished. They show the tool at its best, which is exactly what they’re meant to do.

👉After a few days
This is where the real understanding kicks in.
I start tweaking those examples. Changing assumptions. Using it in ways that feel realistic, not ideal. That’s when the boundaries show up. Not frustration. Just clarity.

Here’s the takeaway I’ve learned the hard way:
If you haven’t noticed limitations yet, you probably haven’t pushed the tool very far.

And honestly, if I use something consistently for three days and still can’t find a meaningful flaw, that’s rare. That earns real respect.
I haven’t experienced that yet.

Curious how others see this.
Are there tools you’ve used deeply where the limits still haven’t shown up?

Just a couple of weeks ago, Arvind and I hosted an in-person AI meetup with The Hub Bengaluru.

Over 300 people showed up in person.

Every single one of them was either already working in AI or actively trying to break into the space. The energy in the room was unreal. It genuinely felt like a room full of builders, practitioners, and people who are curious enough to go deep.

During the event, we rolled out a small challenge. We asked attendees to share a recap of what they learned, and we said we would pick one winner.

Really excited to share that Suraj V is that lucky winner 🎉
Suraj gets free access to all the The Gen Academy workshops we have hosted so far.

Huge congratulations, Suraj V!! 

Building The Gen Academy has always come from a very real observation that Arvind and I see every single day in our work. The adoption of generative AI and LLMs is moving incredibly fast, but the depth of AI engineering skills needed to build reliable systems is not keeping up.

There is a very real skill gap in AI engineering right now! There are so many curious souls who want to become AI engineers- but they aren't able to get those opportunities; and there are so many companies out there who  want to hire, but aren't finding the right talent. 

Our mission is to bridge that skill-gap!

As people who are deeply involved in this space, we felt a responsibility to help bridge that gap. Not just for people who are already experienced, but also for entry-level folks who want to build strong foundations the right way.

That is why our workshops are intentionally designed to be both intuitive and practical. We focus on theory that actually helps you reason about systems, and we pair that with hands-on demos where you build real things using modern toolkits and frameworks.

So far, we have hosted 6 workshops, and the response has been incredibly encouraging. We have trained 1500+ people already ❤️ 

Our next workshop is coming up on February 15th, and it will be focused on AI evaluations (link in comments)

Do follow The Gen Academy to stay updated on all our upcoming workshops.

Six months ago, Arvind and I started The Gen Academy with one simple goal- to create workshops that are deeply-technical, practical, cuts through the ton of noise out there, and that provides people clarity on building productive-grade AI systems.

So far we have trained 2100+ people. We’ve hosted 7 workshops, and consistently we’ve had 300–400 builders join us live.

The audience has been incredible.
- Software engineers moving into AI.
- AI engineers building LLM systems in production.
- Product leads thinking about reliability and evaluation.
- Directors and VPs from top tech and Fortune 500 companies who want to truly understand what’s under the hood.
- Even people from non-tech background who wanted to strengthen their technical fundamentals 

Recently, we hosted a workshop on AI Evaluations.

And this one felt especially important.

Because evaluating non-deterministic generative systems is fundamentally different from traditional ML evaluation.

We covered:

✦ How to evaluate non-deterministic generative AI systems
✦ How to think about benchmarks and what they actually tell you
✦ How to design your own evaluation dataset
✦ How to choose the right metrics for qualitative and system-level evaluation
✦ How to combine human evals, code-based evals, and LLM-as-a-judge
✦ A hands-on walkthrough so this isn’t just theory

If you’re building LLM applications, RAG pipelines, or agentic systems, evaluation is not optional. It is the difference between a demo and a reliable product.

If you missed the live session, we’ve shared the recording here: https://lnkd.in/gzMdbfWH

We’ll continue building these workshops for engineers who want to go beyond experimentation and into production.

More coming soon, so do follow us & The Gen Academy to get updates on our next workshops.

5 days to go! 
Arvind and I are super excited to be hosting an AI evals hands-on workshop on February 15.

It’s a 90-minute session where we’ll cover the fundamentals of AI evaluations and then actually do it together. You’ll walk away having built and reasoned through real evals yourself. 

If you’re aspiring to be an AI engineer or planning to upskill for AI roles in 2026, understanding how to evaluate LLM applications is critical.

Building an LLM app is often the easy part. Knowing whether it truly works in production is where most teams struggle.

LLM evaluation is not just about correctness anymore. You are judging usefulness, safety, faithfulness to sources, consistency across runs, cost, latency, and real user outcomes across prompts, RAG pipelines, tools, and agentic workflows.

Because this is hard, many teams fall back to vibe-evals. If a few outputs look good, they ship. That approach breaks quickly when models change, prompts regress, retrieval fails, or user behavior shifts. Without evals, problems surface only after users complain.

Why learning evals matters:
✦ Evals turn LLM development from guesswork into engineering
✦ They help catch regressions as models, prompts, or tools evolve
✦ They are essential for scaling RAG systems and agentic workflows
✦ In 2026, strong teams use hybrid evals combining automated metrics, LLM-as-a-judge, and targeted human review

Evals are no longer optional. They are a core AI skill.

In this workshop, Arvind and I will walk through how AI evals are done in real systems, with hands-on exercises so you build intuition.

This is designed for AI engineers and tech leads building systems, and even business leaders who want intuition for what “good” really means in production. Even if you are a beginner, don't worry, we will give you the foundations for you to understand everything comprehensively, and enough resources that you can review at your own pace.

If you want to level up your AI skills for 2026, register here:
https://lnkd.in/dQSR7yhU

Evaluation Resources

Fine-tuning is going to be one of the biggest focus areas for AI engineering teams this year.

We’re past the stage where calling an API is enough. The teams creating real leverage are the ones adapting models to their own data, workflows, and edge cases. Out-of-the-box models are powerful, but they are generic. Fine-tuning is where enterprises unlock meaningful efficiency gains and build real differentiation.

If you want to upskill in AI engineering, this is a topic you cannot skip.
Arvind and I are hosting a deep, hands-on workshop on Fine-Tuning LLMs.

In 90 minutes, you’ll learn:
✦ When fine-tuning makes sense and when it does not
✦ How SFT, RLHF, and DPO fit into real-world pipelines
✦ An end-to-end, code-based demo from raw data to a specialized model
✦ How to evaluate true performance improvements and avoid production pitfalls

This session is designed for software engineers, AI engineers, and data scientists, and it is equally valuable for product managers, solutions architects, tech leads, and executives working closely with model ecosystems.

If you want to move from using LLMs to actually optimizing them, this workshop will give you a practical framework to do it: https://lnkd.in/g-5gHrsY

In 2026, AI isn’t judged by a wow factor anymore.
It’s judged by whether it actually improves your workflows.

One of the most common questions I get from founders and teams I advise is how to automate go-to-market and sales properly. Real GTM automation needs deep ICP research, clear definitions, personalized messaging, and credible sources. This isn’t a one-prompt problem.

Normally, building a solid GTM or sales report would take me several hours, even with existing AI tools helping with research.

I recently got early access to Airtable’s new Superagent, and what impressed me was the approach. It didn’t treat my request as a single task. It broke it into ~16 steps, ran multiple agents in parallel, did deep research per subtask, cited sources, and stitched everything together into one structured output called a Super Report.

I used it to build a technical, informational report on AI for GTM/Sales in minutes. No fluff. No hallucinations. Just deeply researched content I could actually use with business leaders.

If your work involves building reports, decks, or MVP websites that need accuracy and depth, this feels less like “AI that makes things pretty” and more like AI that does real work.

Do check it out here: https://lnkd.in/gDkfSSG2

PS: You can get 2 months free for @Superagent, using code: AISH2FREE

#SuperagentPartner, #ad, #SuperagentbyAirtable

Ranked #1 LinkedIn HR Creator (Global), #2 Female Creator (US) | Positioning Companies & Founders to Attract Talent, Capital & Credibility | 100M+ Organic Reach | Ex-Amazon, Cognizant, Labcorp

200K+ LinkedIn & Newsletter Community 🐝 LinkedIn Growth Support, Talent Acquisition/Hiring & Brand Partnerships🐝 Neurodiversity Advocate 🐝

Hiring. Visibility. Credibility.

The three levers every founder, CEO, coach, or consultant needs to scale.
The problem? Most get them wrong.

That’s where I come in.

I built 𝐏𝐫𝐨𝐯𝐞𝐧 𝐏𝐚𝐭𝐭𝐞𝐫𝐧𝐬 to help seed to Series B startups, lean teams, and high-stake leaders attract the right talent, amplify their brand visibility, and build credibility that wins capital and clients.

What sets us apart?
We operate at the intersection of AI, recruitment, and brand strategy turning overlooked processes into growth systems.

Here’s what that looks like in numbers:
✔ 3,000+ hires placed globally across industries
✔ 250,000+ resumes reviewed with precision at scale
✔ 100M+ organic impressions without ad spend
✔ 150K+ community grown organically on LinkedIn
✔ 50K+ subscribers of our Li Newsletter: Incredible Edge
✔ Worked with enterprises like Amazon, Cognizant, Labcorp
✔ Partnered with unicorns like Atlan & Domino Data Lab
✔ Executed brand collabs with Lovable AI, Emergent AI, Gusto, Replit Agent 3, Gamma & GoPerfect
✔ Been named Favikon’s #1 HR Voice (Worldwide) and #2 Female Creator (US) - April'2025

But metrics are just the proof. The real outcome is this:

💡 Founders who save time and scale smarter.
💡 Executives who become visible authorities.
💡 Startups that attract capital and top talent on autopilot.

If you’re still struggling to hire right, stand out, or get noticed, it’s not because you lack potential.
It’s because you’re playing the wrong game.

My work is helping you change that.

📩 DM me or reach out: bookings@proven-patterns.com

Let’s build what they can’t ignore.

💜

Kumud Deepali R.

I’ll never forget the person who gave me a chance when I had nothing impressive to show.

No big-name company on my resume.
No standout achievements.
No long list of credentials.

All I had was a positive attitude and a genuine willingness to learn.

At the time, I didn’t realize how rare that kind of opportunity was. Someone looked past the lack of experience and saw potential. They saw effort. They saw hunger. They saw someone who was willing to show up early, stay late, ask questions, make mistakes, and try again.

That single decision changed the direction of my career.

We often underestimate the power of being given a first shot. For many of us, that moment is the foundation everything else is built on. It’s where confidence starts. It’s where belief grows. It’s where skills are sharpened.

Experience matters, yes.
But mindset matters more.

You can teach systems.
You can train for skills.
You can guide someone through processes.

What you can’t easily teach is work ethic. Curiosity. Coachability. Gratitude for the opportunity.

And here’s something I’ve learned along the way:
When someone takes a chance on you early in your career, you carry that forward. You remember how it felt. And when you’re eventually in a position to hire, mentor, or lead, you look for potential in others the same way someone once looked at you.

That’s how real leadership compounds.

So if you’re early in your journey and feel overlooked, keep going. Keep learning. Keep improving. The right opportunity often comes disguised as a small one.
And if you’re in a position to give someone their first shot, don’t underestimate the impact you can have.

Sometimes belief is more powerful than experience.

If this resonates with you, share it and repost. 
And follow me for more reflections on leadership, growth, and building careers with intention.

Kindness is not a weakness, it’s a leadership advantage.

In a world that often rewards speed, competition, and “winning at all costs,” kindness can feel underrated.

✔️ Kindness builds trust.
✔️ Kindness strengthens teams.
✔️ Kindness fuels collaboration.
✔️ Kindness creates leaders people want to follow.

Some of the strongest professionals I know are the ones who choose empathy even when it’s not the easiest option.

Let’s stop treating kindness like a liability.
It’s a skill.
A strategy.
A strength.

Imagine what our workplaces would look like if kindness was the standard, not the exception.

💬 How has kindness positively impacted your career, life or workplace?

I’ve been thinking a lot about who we choose to celebrate.

Every year, we see the same lists:
“30 Under 30.”
“40 Under 40.”
“Top Young Innovators.”

And don’t get me wrong, those achievements are impressive. Ambition deserves recognition. But here’s what we don’t talk about enough:
- The professional who had to start over at 52 after being laid off.
- The founder who rebuilt after a failed business.
- The parent who paused their career for a decade and came back stronger.
- The 60-year-old who finally earned their degree.
- The 70-year-old who published their first book after a lifetime of living, loving, losing, and learning.

That’s success too.

Not the fast-track version.

Not the highlight-reel version.

But the resilient version.

We tend to glorify speed. But longevity requires something different:
• Endurance
• Humility
• Perspective
• Emotional strength
• The courage to begin again

There’s something powerful about people who didn’t “make it early”, but made it anyway.
The ones with calloused hands and tender hearts.
The ones who stayed when quitting would have been easier.
The ones who kept showing up long after the applause faded.

Maybe we need fewer age-based accolades and more stories about resilience.
Because success isn’t about when you arrive.

It’s about whether you keep going.

If this resonates:
🔁 Repost to celebrate late bloomers and second acts
💾 Save this for the days you doubt your timeline
➕ Follow for more conversations about leadership, growth, and staying power

Who’s someone you admire who succeeded later in life or was it you? I’d love to hear their story.

Most people are using Copilot wrong.

They treat it like Google.

But Copilot isn’t a search engine.

It’s a productivity multiplier.

Here’s how to actually use Copilot across Microsoft 365 👇
🔵 Copilot in Word – Write faster, think sharper
 Use it to:
 • Draft documents from short prompts
 • Rewrite for clarity and tone
 • Summarize long reports into key takeaways
💡 Pro tip:
 “Summarize this document into 5 bullet points with action items.”
🟢 Copilot in Excel – Turn data into decisions
 Use it to:
 • Build charts, formulas, and pivot tables
 • Clean messy datasets
 • Highlight trends automatically
💡 Pro tip:
 Select your data and ask:
 “What’s driving this number?”
🟠 Copilot in PowerPoint – Build story-driven slides
 Use it to:
 • Create full decks from Word docs
 • Turn reports into visuals
 • Generate speaker notes instantly
💡 Pro tip:
 “Turn this report into a 7-slide executive summary.”
🟣 Copilot Chat – Your AI teammate
 Use it to:
 • Summarize meetings
 • Draft replies
 • Analyze PDFs and reports
 • Catch up on everything you missed
💡 Pro tip:
 “Summarize everything I missed this week.”

Stop asking Copilot to give you information.
Start asking it to help you think.

AI won’t replace professionals.
But professionals using AI will replace those who don’t.

If you're using Copilot at work, what’s your favorite prompt?

Hit the notification button and follow me on LinkedIn as I share the latest AI, career and workplace trends.

The difference between a boss and a leader is subtle, but powerful.

A boss looks at what you’ve already achieved and piles on more work.
A leader looks at what you’re capable of and opens doors to new opportunities.

I’ll never forget a moment early in my career.
I was delivering results and thought my “reward” would be more tasks. Instead, my manager surprised me: they asked me to lead a client presentation.

At first, I was terrified; I didn’t feel ready. But that single opportunity pushed me out of my comfort zone, built my confidence, and shaped the way I approach challenges to this day.

That experience taught me the kind of leader I want to be: one who recognizes potential and creates space for others to rise.

If you’re in a leadership role, ask yourself:
➡️ Am I only rewarding performance with more work?
➡️ Or am I recognizing potential and creating paths for others to thrive?

True leadership isn’t about control, it’s about empowerment.

Have you had a leader who saw your potential before you saw it yourself? Share in the comments below. 

♻️ Let’s spread this message, comment, share, or repost if you believe we need more leaders who empower, not just manage.

Let’s be honest.
Doing the right thing isn’t always popular.
And doing what everyone else is doing doesn’t make it right.

Leadership has a funny way of revealing this.
Your title might shape how people see you.
But your daily choices show who you really are.

That’s where emotional intelligence and integrity come together.
Leaders with strong EQ don’t shift with every opinion.
They pause. They think. They stay grounded, especially under pressure.
Here’s a simple way to tell the difference.

High EQ is NOT:
– Protecting your ego instead of listening
– Staying quiet just to avoid tension
– Ignoring how your decisions land on others
– Reacting before taking a breath
– Blaming circumstances instead of owning mistakes
– Saying yes for approval
– Compromising values to fit in
– Letting emotions run the show
– Avoiding uncomfortable conversations
– Choosing pride over people
– Giving in when pressure shows up

High EQ IS:
– Admitting when you’re wrong
– Standing by decisions rooted in values
– Saying no, even when it’s uncomfortable
– Responding with intention, not impulse
– Leading with empathy, not ego
– Doing the right thing, even if you’re alone
– Regulating emotions to think clearly
– Speaking up when it actually matters
– Helping others grow, not just follow
– Staying true to yourself amid outside noise
– Truly hearing perspectives beyond your own

Here’s the thing:
Integrity isn’t tested when it’s easy.
It’s tested when it costs you something.

So when the pressure’s on, do your values stay the same?

Most people chase AI shortcuts.
Stanford quietly did the opposite.

They released their entire LLM course publicly, 
no paywall, no fluff, no “executive summary.”

Nine full lectures.

The actual Autumn curriculum on Transformers & Large Language Models.
Available free on YouTube.

This isn’t content about AI.

It’s the material used to train people who build it.

And if your goal in 2026 is to ship real AI systems, not demos, this distinction matters.

Here’s the full course, 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


The part most people overlook:
AI roles are already splitting into two groups:
→ Those who interact with models
→ Those who understand why they break

The second group will look very familiar:
Engineers who know how data, objectives, decoding strategies, context windows, and evaluation metrics interact.

The most dangerous AI failures won’t look wrong.

They’ll look correct; until cost, safety, or trust is damaged.
That’s why this course isn’t just “learning Transformers.”
It’s learning:
where hallucinations originate
how reasoning degrades
why evaluation lies
and how silent failure creeps into production

How I’m using it (simple, high ROI):
🔶One lecture per week
🔶Feed the transcript into NotebookLM
🔶Generate:
- a concept map
- a one-page visual explainer
- a teach-it-back summary

Build something small immediately (RAG, eval script, tuning experiment). Two focused hours beats twenty hours of passive watching.

If this helped you:
👉 Repost so others don’t miss it
👉 Save to refer to later
👉 Follow for more practical AI systems thinking

Image Credit: Steve Nouri

He woke up at 4 AM.

Worked as a trash collector to support his family.

Graduated with a 4.0 GPA.

And just got accepted into Harvard Law School.

Let that sink in.

No shortcuts.

No excuses.

No “perfect timing.”

Just discipline, sacrifice, and belief.

It’s easy to underestimate people based on their current situation. It’s harder to recognize the ambition they’re quietly building behind the scenes. This is what resilience looks like.

On LinkedIn, we often celebrate promotions, funding rounds, and titles.

But stories like this?

They remind us what real grit looks like.

Your starting point doesn’t define your finish line.
If you’re grinding in silence right now, keep going.

The early mornings. The long shifts. The unseen effort. It all compounds.
Success isn’t always loud.

Sometimes it starts in the dark at 4 AM.

💬 What’s one goal you’re working toward that people don’t see yet?

🔁 Repost to inspire someone.
💾 Save this for the days you feel like quitting.
➕ Follow for more stories that remind you what’s possible.

It’s wild how one person can change everything.

You can love your role, the work, even the mission, but one toxic colleague or unsupportive manager can make it unbearable.

And on the flip side?
 
One great leader or teammate can make even the toughest days feel worth it.
Work culture isn’t just policies and perks, it’s people.
 
The right ones elevate you.
The wrong ones drain you.

So if you’re a leader:
💬 Check in with your team.
👂 Listen more than you talk.
🙏 Be the reason someone wants to stay, not the reason they start job hunting.

What’s one thing a manager or teammate has done that made you love coming to work?

🔁 Repost if you’ve ever felt this way, someone needs this reminder today.
👥 Follow me, (Kumud Deepali R.) for more real takes on leadership, work culture, and career growth.

“Will you be my daddy… until I die?”

She was seven years old.
Sitting in a hospital bed.
Tubes in her nose.

And she asked a stranger,  a tattooed, intimidating-looking biker if he would pretend to be her father for however long she had left.

Mike was 58.
Tattoos down both arms.
The kind of man most kids are scared of at first glance.

Every Thursday, his motorcycle club volunteers at a children’s hospital, a tradition they started 15 years ago after one of their own experienced pediatric cancer in the family.

He’s read to dozens of sick kids.
But this time was different.
Her mother had left her at the hospital and never returned.

Halfway through a children’s book, she asked him if he had kids.
“I had a daughter,” he told her. “She passed away at sixteen.”
Then she asked quietly,
“Do you miss being a daddy?”
Every day.

She looked at him, far too wise for seven, and said she knew she was dying.
Then came the question:
“Will you be my daddy… until I die?”
He didn’t promise perfection.
He promised presence.
And just like that, he showed up.

The club rallied.
The hospital room filled with stuffed animals and laughter.
Thursdays became every day.

Six months passed.
Then nine.
Then a year.
Eighteen months later, she walked out of that hospital holding his hand.
Today she’s fifteen.
 
Cancer-free.

And she still calls him Daddy.

Every Thursday, they ride back to that same hospital, together to read to kids who are scared and hurting.

Here’s what she taught him:
• You don’t have to be perfect to show up.
• Love heals in ways medicine can’t explain.
• Sometimes the thing that feels like it will break you… rebuilds you instead.

He thought he was saving her.
But she saved him.

If this moved you, don’t just scroll.
💛 Comment “LOVE” if you believe showing up matters. Showup for someone this Valentine's Day. 
🔁 Repost to remind someone that presence changes lives.

Working with smart people is great.

Working with kind and humble people is next-level amazing.

In today’s world, talent is everywhere.

But character? That’s rare.

The smartest person in the room can elevate performance.

The kindest person in the room elevates everyone.

I’ve learned that the teams that truly thrive aren’t just high-performing, they’re high-trust.
• They share credit.
• They listen deeply.
• They assume positive intent.
• They win without ego.

Skills build businesses.
Character builds cultures.
As leaders, we should hire for both, but never compromise on humility.

💬 What qualities do you value most in the people you work with?
👉 Repost if you agree
👉 Follow for more reflections on work, leadership, and growth

The Culture Illusion: You think pizza and free snacks keep employees happy?
They don’t.

𝗛𝗲𝗿𝗲’𝘀 𝘄𝗵𝗮𝘁 𝗮𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝗺𝗮𝘁𝘁𝗲𝗿𝘀:
🔶 Fair Pay
🔶 Competitive salaries
🔶 Performance-based bonuses
🔶 No one stays loyal to lowball offers
🔶 Real Recognition - Not just “Employee of the Month” gimmicks but consistent appreciation for hard work
🔶 Promotions based on merit, not favoritism

𝗕𝗼𝘁𝘁𝗼𝗺 𝗹𝗶𝗻𝗲:
Culture isn’t built on perks.
It’s built on respect, recognition, and real opportunities.

Give your people what actually matters, and watch them stay.

What do you think makes or breaks company culture? Drop your thoughts below!

A Senior Engineer at a Fortune 50 company helped me put this together:

20 YouTube channels that teach AI better than most CS degrees. These are great resources for structured learning, and the latest in AI:

1. Andrej Karpathy
Deep, intuitive walkthroughs of neural networks and modern LLMs
Link: https://lnkd.in/gE6S6raT

2. 3Blue1Brown
Visual intuition for math, linear algebra, and neural networks
Link: https://lnkd.in/g4wC_iPQ

3. StatQuest with Josh Starmer
Clear, friendly explanations of statistics and ML fundamentals
Link: https://lnkd.in/gTaEyqYg

4. Stanford Online
University-grade ML and AI lecture series (Andrew Ng, CS229, etc.)
Link: https://lnkd.in/gavEEh5v

5. sentdex
Practical machine learning and Python projects
Link: https://lnkd.in/gPAY_ga8

6. Yannic Kilcher
Deep dives into ML and AI research papers
Link: https://lnkd.in/gFkDZWE7

7. MIT OpenCourseWare
Rigorous academic courses on ML, AI, and applied mathematics
Link: https://lnkd.in/gNaRSdSZ

8. Siraj Raval
High-level overviews and motivation around AI concepts
Link: https://lnkd.in/gSdzUetp

9. DeepLearningAI
Structured learning paths for deep learning and generative AI
Link: https://lnkd.in/gdGfUwpj

10. Two Minute Papers
Fast, accessible summaries of cutting-edge AI research
Link: https://lnkd.in/gr93SaYD

11. Umar Jamil
Clear, implementation-focused explanations of transformers and LLMs
Link: https://lnkd.in/gurTw-yi

12. Hugging Face
Open-source LLMs, transformers, and modern NLP tooling
Link: https://lnkd.in/g_sfHVnH

13. Steve Brunton
Dynamical systems, control theory, and scientific ML
Link: https://lnkd.in/gV4tYCFS

14. Michael Bronstein
Geometric deep learning and graph neural networks
Link: https://lnkd.in/gUURVY4B

15. Caltech
Advanced lecture series on ML, optimization, and theory
Link: https://lnkd.in/gsP9Kcz5

16. Lex Fridman
Long-form conversations with top AI researchers and practitioners
Link: https://lnkd.in/g4VduFAM

17. Arxiv Insights
Beginner-friendly explanations of recent AI papers
Link: https://lnkd.in/gt2Qvzze

18. Machine Learning Street Talk
Unfiltered, technical discussions on AI research and theory
Link: https://lnkd.in/gKHEsafg

19. Jeremy Howard
Practical deep learning with strong intuition
Link: https://lnkd.in/gjpiiJCK

20. Kaggle
Applied ML, competitions, notebooks, and real-world workflows
Link: https://lnkd.in/gd-m8w_j

These channels will keep you current with AI trends and help you sharpen your skills.
 Which one are you watching first, or is there a go-to AI channel you’d recommend? Drop it in the comments 👇

Repost, Save and like the post to share with your network. Adopt AI before it is too late. Thanks!

📚AI gives you information. Books give you wisdom.

The Ultimate Reading Roadmap for Personal & Professional Growth
If you’re serious about leveling up in 2026, start here.

This collection breaks down must-read books into 9 key areas of life and career growth

💼 Productivity
- Atomic Habits by James Clear
- Deep Work by Cal Newport
- Do It Today by Darius Foroux
💰 Personal Finance
- The Millionaire Fastlane
- Psychology of Money
- Richest Man in Babylon
💬 Communication
- Talk Like TED
- How to Win Friends and Influence People
- Never Split the Difference
🧠 Human Behavior
- The 48 Laws of Power
- Influence by Robert Cialdini
- Surrounded by Idiots
🔥 Discipline
- Can’t Hurt Me
- Living with a SEAL
- Make Your Bed
💞 Relationships
- How to Be an Adult in Relationships
- Men Are from Mars, Women Are from Venus
- Closer to Love
💭 Philosophy
- Meditations by Marcus Aurelius
- Being and Nothingness
- What Are You Doing with Your Life?
🧩 Critical Thinking
- Think Again by Adam Grant
- Thinking, Fast and Slow
- The Art of Thinking Clearly
🆘 Self-Help
- The Magic of Thinking Big
- The Subtle Art of Not Giving a Fck*
- Mindset by Carol Dweck

If you could only pick one category to master in 2026, which one would it be and why? Share in the comments below. 

♻️ Repost to remind someone not to forget reading.

Everyone asks: “Which AI model should I actually use in 2026?”

Top 6 AI Models Ranked, based on real-world use, not hype.

Quick takeaways + where to learn each one:
🔹 Claude 4.5 → Best for deep reasoning, long documents, and professional work
📚 Learn more: https://lnkd.in/gRwxGbz4
🔹 ChatGPT-5.2 → Still the most versatile all-rounder for content, workflows, and automation
📚 Learn more: https://openai.com/chatgpt
🔹 Gemini 3 → Strong inside Google’s ecosystem, great for research + docs
📚 Learn more: https://lnkd.in/gnEymgGy
🔹 Perplexity → The fastest path to reliable, cited answers
📚 Learn more: https://www.perplexity.ai
🔹 Grok 4.1 → Unmatched for real-time trends and cultural context
📚 Learn more: https://x.ai
🔹 DeepSeek 3.2 → Open-source powerhouse for technical and engineering teams
📚 Learn more: https://www.deepseek.com

📌 There’s no single “best” model. There’s only the best model for your use case.

Pro tip: Most power users now rely on 2–3 models, not one.

Which AI are you using the most right now, and why? Drop it in the comments.

#ArtificialIntelligence #GenerativeAI #LLM #FutureOfWork #TechTrends #AItools #Productivity #2026

No matter how good you are, the wrong environment will make you question your worth.

I learned this the hard way.

A few years ago, I was in a role I had worked incredibly hard to earn. On paper, it looked perfect. Good title. Recognized company. Decent pay. From the outside, it seemed like I had “made it.”

But internally, I felt small.

Every meeting felt like a test. Every idea I shared was either ignored or picked apart. Feedback was rarely constructive. It was subtle, but constant. Over time, I stopped raising my hand. I started second guessing my instincts. I began over preparing for basic conversations because I assumed I would be challenged.

The worst part was not the criticism.

It was how I slowly started believing it.

I remember one evening sitting in my car after work, staring at the steering wheel longer than usual. I caught myself thinking, “Maybe I’m just not that good.” That thought scared me because I had never questioned my ability like that before.

Nothing about my skills had changed.

Nothing about my work ethic had changed.

The only thing that changed was the room I was in.

When you are in the wrong environment, even excellence feels average. Even confidence starts to shrink. Even effort feels invisible.

And when you are in the right environment, something completely different happens.
Your ideas are challenged, but with respect.
Your growth is supported, not threatened.
Your strengths are noticed.
Your weaknesses are coached, not weaponized.

I eventually made the decision to leave. It was not dramatic. No burned bridges. Just a quiet choice to bet on myself again.

The difference was immediate.

Same work ethic.
Same skill set.
Different culture.

Suddenly I was trusted with bigger projects. My voice carried weight. I felt energized instead of drained. It was not because I magically became better overnight. It was because I was finally in a place that valued what I brought to the table.

Here is what I wish someone had told me earlier:
If you constantly feel undervalued, it is not always a skill issue.
If you constantly feel unheard, it is not always a confidence issue.
If you constantly feel small, it is not always a competence issue.

Sometimes, it is simply misalignment.

We talk a lot about self improvement. We talk less about environment improvement.

If you are currently questioning your worth, pause before you question your ability. Ask yourself whether you are planted in the right soil.

Because even the strongest seed struggles in the wrong ground.

Have you ever experienced this shift when changing environments? I would love to hear your story.

Repost and like this post to share with your network, as someone might need this reminder and follow for more.

How will you choose to lift others today?

Kumud Deepali Rudraraju, SHRM CP

Life’s three best teachers:
 💔 Heartbreaks
 💸 Empty pockets
 ❌ Failures

These moments hurt the most, yet they shape us the deepest.

They teach resilience, humility, and the true value of growth.

❤️ Heartbreaks remind us to value people who stay.
💰 Empty pockets teach us gratitude and resourcefulness.
📉 Failures push us to learn, evolve, and try again, smarter this time.

No book or degree can teach what pain, loss, or struggle can.
They don’t break us; they build us.

👉 What’s one lesson you learned from your toughest phase in life? Share it in the comments, your story might inspire someone today.

🔁 Repost this to uplift someone who might need a reminder that tough times create strong people.

Image Credit: The Positive Trader

Make it a habit to respect people, without knowing their qualifications, title, or position.
In today’s world, respect has become conditional.

We respect the CEO.
We respect the one with the big title.
We respect the one with the credentials, the awards, the followers.

But what about the person with none of those things, yet?
Real character is revealed in how you treat people
who cannot “do” anything for you.

The assistant.
The intern.
The new hire.
The quiet voice in the room.
The person without a LinkedIn headline that impresses you.

Reality Check:
Titles change.
Positions rotate.
Power shifts.
But character?
Character is permanent.

Some of the most successful leaders I’ve seen share one common trait:
They treat everyone with the same level of dignity.
Not because they have to.
But because it’s who they are.

Respect is not a response to status.
 It’s a reflection of values.

When you lead with respect:
• People feel safe to contribute
• Teams collaborate better
• Loyalty increases
• Culture strengthens
• Reputation grows organically

And here’s something even more powerful:
You never know who someone will become.
Today’s intern could be tomorrow’s investor.
Today’s junior employee could be tomorrow’s industry leader.
Today’s quiet observer could be your biggest advocate.

But even beyond opportunity, respect should never be transactional.
It should be habitual.
In rooms where ego is loud, humility stands out.
In environments where hierarchy dominates, kindness differentiates.

So the real question is:
Do you respect people only when their title impresses you?
Or do you respect people because your standards do?
The strongest leaders don’t command respect.
They demonstrate it first.

If this resonates with you, I’d love to know:
What does respect in the workplace mean to you?

Repost if you share the sentiment and follow for more.

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The Battle

Aishwarya Srinivasan

Kumud Deepali R.

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The Battle

Aishwarya Srinivasan

Kumud Deepali R.

Followers

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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);}Aishwarya Srinivasan's LinkedIn Performance

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