Google

Scale Fortune 500 enterprises, government agencies, and high-growth startups by architecting and deploying AI solutions that drive measurable business transformation. Deliver engagements resulting in 130%+ revenue growth, 8-figure cost savings, and AI-enabled process automation reducing operational cycle times by 81%. Lead AI adoption programs that take early-stage startups from prototype to market-leading platforms, and transform legacy enterprises into AI-driven market leaders.

Design and implement end-to-end AI ecosystems leveraging Google Vertex AI, TensorFlow Extended (TFX), and TPU v5e infrastructure. Integrate large language models (LLMs), multimodal AI pipelines, and retrieval-augmented generation (RAG) workflows tailored to domain-specific use cases. Engineer petabyte-scale data pipelines with BigQuery and Dataflow, embedding vector search for real-time semantic retrieval.

Deploy production-grade AI using GKE and Kubeflow Pipelines, enabling CI/CD-driven MLOps with automated model monitoring, drift detection, and rapid retraining. Optimize inference latency by up to 60% through TensorRT acceleration, mixed-precision computation, and graph pruning. Deliver cross-domain AI applications spanning healthcare diagnostics, real-time financial fraud detection, industrial automation, and secure defense systems, serving millions of end users worldwide.

AI Consulting Strategist – Google AI

NVIDIA

Developed GTM strategy for enterprise deployment of NVIDIA’s LLM inference stack, targeting financial services, logistics, and healthcare sectors. Led internal pilot program to monetize edge AI deployment tools for multi-modal sensor data, resulting in $60M+ in downstream enterprise contracts. Designed pricing model for inference-as-a-service API bundles; used in 4 Fortune 500 client rollouts. Partnered with engineering teams to productize low-latency LLM pipelines on A100/H100 architecture for high-frequency decision environments. Presented enterprise AI monetization playbook at NVIDIA Executive Forum; used to inform FY23 enterprise roadmap. Built economic viability framework for internal AI tooling, prioritizing initiatives with >4x projected ROI.

AI Commercialization Strategist – Enterprise Solutions

Apple

Led monetization design for Vision Pro’s AI-native features, including intent prediction, gaze tracking analytics, and adaptive content surfacing. Worked cross-functionally with ML engineers and product to translate LLM-based user modeling into paid in-app personalization APIs. Built dynamic pricing framework for AI-driven developer tools on VisionOS, projected to generate $180M+ in ARR by 2025. Defined core metrics for AI feature adoption, driving a 3.7x increase in developer conversion across beta cohorts. Presented strategic roadmap for AI revenue growth to executive leadership; approved for rollout across 4 product verticals. Contributed to Apple’s internal thesis on “Ambient AI Monetization,” later used in fiscal year investment planning

AI Monetization Strategist – Vision Pro Team

I build and monetize AI systems. At Apple, I shaped the Vision Pro AI revenue strategy. At NVIDIA, I helped commercialize LLM infrastructure for enterprise deployment. I specialize in turning ML capabilities into scalable business models, especially in environments where speed, monetization, and leverage matter more than polish. I’ve advised AI startups, contributed to strategic go-to-market plans, and built pricing frameworks now used by Fortune 500 teams. My background is technical, but my advantage is translating that into revenue. I’m open to high-leverage collaborations, especially where AI meets distribution, B2B tooling, or capital.

You don't owe your employer your loyalty.

Harsh? Maybe.

But every layoff is a reminder that loyalty often flows in one direction.

Up.

Not down.

Companies are built by people, but managed on spreadsheets.

It's not personal.
It's business.

So why do you keep treating your career like it's personal?

Your security doesn't come from your employer.

It comes from your ability to create value anywhere.

That's why I started building my own brand and business while I still had a job.

Not because I was unhappy. I loved the company!
But because I knew the company didn't owe me tomorrow.

So I built skills that made me valuable everywhere:

Writing.
Marketing.
Creating products.
Building an audience.

Skills nobody could take away.

When I finally left, I didn't need permission.
I didn't need a safety net.
I had options.

That's absolute security.

If you're ready to build skills that make you valuable anywhere, 45,000+ students including 200+ LinkedIn Top Voices used the LinkedIn Operating System to start building their own security: https://buff.ly/ALO2j0P

Remember:

Your security comes from your ability, not your employer.

Rami Zwebti

i make people rich & businesses richer

Why any founder should watch this???

I find it strange this video has never received this much attention, but I've always considered it a gold mine.

How did Mark Zuckerberg scale Facebook in 2005 without Kubernetes, serverless functions, managed Redis, Kafka, or edge-sync databases?

Here’s what they actually used back then

⚙️ 𝗧𝗲𝗰𝗵 𝗦𝘁𝗮𝗰𝗸 𝟮𝟬𝟬𝟰–𝟮𝟬𝟬𝟱:
▪️ PHP – Core app and frontend logic.
▪️MySQL – Reliable, relational, and fast.
▪️Memcached – Introduced early for blazing-fast caching.
▪️Apache – The web server workhorse.
▪️Linux – Running on good ol’ physical boxes.
▪️C++ – Gradually used for performance-critical services.

No Kubernetes. No Kafka. No microservices. No managed anything.
Just raw code, smart engineering, and a lot of hustle.

In this video, Mark explains how they did it, and trust me, it's definitely worth checking out!

Link to the video in the comments!!!!

#ai #startup #founder

We call it ML, but machines don’t actually learn.  
We call them data scientists, but most aren’t running real science.  
We call them agents, but they have zero agency.  

So PLEASE explain why do we keep calling it artificial intelligence…  
when there’s nothing truly intelligent about it?  

#ai

I’ve heard many times people claiming AI is a bubble and I really doubt if they even know what AI is…

Let me share some crazy numbers:

🔸 ChatGPT 👉 800M users  
🔸 Lovable 👉 $100M ARR in 8 monhts  
🔸 NVIDIA 👉 $5T market cap  
🔸 Hugging Face 👉 2M+ models hosted  
🔸 Perplexity 👉 200M monthly visits  
🔸 GDP Growth 👉 0.1% without AI  

And this is just some figures that came to my mind. 

What we are living is not a bubble, it’s by far the biggest explosion of innovation in human history. And you know why? This is just the beginning!

Kudos to Matt Turck for the updated 2025 MAD Landscape 🙌 

#AI

This is getting out of hand 🤯 

Not sure if we should blame the AI hype… or just plain recruiter nonsense. 

LangChain launched in October 2022 as an open source project by Harrison Chase while he was at Robust Intelligence.
So yeah, totally makes sense to ask for 5 years of LangChain experience, right?

On the bright side, the job post did clarify that Python is a programming language, just in case a snake charmer was planning to apply.

We’re truly living in the golden age of AI and stupidity age of recruiting.

#ai #hiring #talent #genai

Turning innovation into impactful solutions... that’s my driving force. As an AI researcher and hands-on tech innovator, I’ve transformed challenges in digital safety and mental health into accessible tools that empower both students and educators. The way I see it, technology isn’t just about code; it’s a powerful catalyst for connecting communities and sparking real change. I’m here to connect with fellow visionaries who are ready to push boundaries and make a tangible difference through tech. If that sounds like you, message me. Let's get this ball rolling.

English may be the new coding languge but Vibe Coding keeps speaking in Python.

No matter how much AI evolves, it always ends up coming back to Python.

While other languages brag about performance benchmarks, Python has built built the ecosystem that runs every AI breakthrough. It’s the one language that speaks fluently with the entire AI stack:

🔹 Hooks into every framework, API, and library in existence.
🔹 Powers everything from data prep to production deployment.
🔹 Lets you “vibe code” in the right way: describe, adapt, and prototype ideas at the speed of thought.

That's why in this new space, where you can vibe code products in a matter of days instead of months and where literally anyone can build a killer app, you need to keep having the flexibility and the speed Python provides.

Most of the current vibe coding tools doesn't allow you to build a full stack app in python. You get amazing prototypes that never go into prod. That's why I love so much Reflex because it's the first vibe coding tool that allows you to do that. So you don't create only prototypes but you can go into prod fully in python.

So you definetly need to take a look: https://lnkd.in/dFgzXBnZ

#Python #AI #VibeCoding

🤖 How to spot a fake AI expert?

Easy, if it takes you more than 5 seconds to get the joke…
Congrats, you might be one too 🤣🤣🤣

#ai #genai #humor

The ugly truth about AI Agents 👇

Behind all the hype, most “AI agents” are just an LLM running inside a while-true loop, all wrapped in a container.

That’s it: LLM + loop + tools.
Each cycle: think → act → observe → repeat.
Wrapped in a container. Deployed on Kubernetes. Branded as “autonomous intelligence.”

But here’s where it gets really interesting:
The simplicity that makes demos look magical is the same reason production agents are a nightmare.

🔹 Reliability math kills you:
Even a 1% per-step error rate compounds to 63% failure over 100 steps.
Do 10 chained calls at 95% accuracy? You’re already under 60% success.

🔹 Costs scale non-linearly:
That $0.25 loop demo quickly becomes a $50 run once you add context windows and 100 turns.

🔹 The demo vs. production gap:
In demos, agents “work.”
In production, they wander off, crash, or hallucinate.

The real engineering lies not in the loop but in:
✅ tool design
✅ structured outputs JSON schemas, Pydantic models
✅ observability & failure handling
✅ bounded contexts with human checkpoints

So yes, the meme is right: behind the “autonomous agent” story, there’s usually a while-true loop doing its best not to crash.

#ai #agents #kubernetes

Everyone wants to be an AI-first company these days… but most can’t even define what that means. 😅

Even the ones trying to adapt their org charts for the “AI era” end up looking something like this:

→ CEO: “Let’s go all in on GenAI!”
→ CTO: “Buy 500 Copilot licenses.”
→ AI Lead: “Switches between ChatGPT, Claude, Gemini, and Grok hourly.”
→ Data Team: The Power BI heroes who used to be cool.
→ AI Governance Lead: Not invited to any meetings.
→ Intern: Built 3 agents last week… none in production.
→ Vibe Coder: Still hasn’t written a single line of code.
→ Agentic AI Office: Rebrands every workflow as an “agent.” Reports directly to the CEO.
→ Head of HR: Busy explaining why “AI won’t take your job” while secretly updating LinkedIn.

It’s funny until you realize it’s actually happening.

The rush to “go AI-first” has blinded many companies to a simple truth:

AI isn’t a department. It’s not an org chart box. It’s a capability and if you don’t know why you’re using it, no model will save you.

#ai #business

Nobody takes you seriously yet. 

That's your advantage.

Because tomorrow's multi-millionaires are today's one-person businesses that nobody's taking seriously yet.

The consultant at their kitchen table.
The creator with 2,500 followers.
The freelancer who "needs a real job."

I've seen this movie before:

2018: "Don't do business on LinkedIn."
2020: "That business isn't sustainable."
2022: "One-person businesses can't scale."

Meanwhile, these "fake" businesses are doing:

• $50K months with no team
• $1M years with no office
• $10M lifetimes with no investors

The pattern never changes:

Year 1: "That's cute."
Year 3: "That's lucky."
Year 5: "How did you do that?"

We're not building something they recognize.

No org charts.
No pitch decks.
Just ridiculous margins.

By the time they take you seriously, you'll be too expensive to hire.

I went from "mid-life crisis" to $10.5M.

While they laughed and doubted.

Your "little" business isn't little.
It's early.

Want to be tomorrow's success story here on LinkedIn?

Steal the playbook → https://buff.ly/cjolSEv 

Let them laugh.

You'll be too busy building to care.

The truth behind Python: what nobody had told you so far….

Back in 1989, a Dutch programmer named Guido van Rossum was just trying to make his Christmas holidays more fun.

So he built Python — named after Monty Python’s Flying Circus, not the snake — as a side project to make coding feel more human.
Fast-forward 35 years, and that same “holiday project” became the universal language of AI.

Yes, Python is “slow”. Yes, dependency management can be painful.
But here’s the paradox: it dominates every single corner of AI: from OpenAI’s models to Netflix’s recommendations, from Instagram’s backend to Hugging Face’s entire ecosystem.

Why? Because Python got the important things right:
🔸It’s simple enough for a researcher and powerful enough for a production engineer.
🔸It connects seamlessly with C/C++ and GPU-accelerated backends the real heavy lifters.
🔸It built the richest AI ecosystem the world has ever seen: TensorFlow, PyTorch, Hugging Face, LangChain, FastAPI… all speak Python.

Python didn’t win by being perfect.
It won by being pragmatic.

And in the AI world, speed of iteration beats speed of execution every single time. 

#AI #Python #devs

Make money without asking for permission.

No approval.
No gatekeepers.
No salary bands.

Just you, your ideas, and the internet.

That's the magic of modern day.

You can publish something valuable at night
and wake up to Stripe notifications the next morning.

But not if you chase some "get rich quick" fantasy.

You need to build trust in public, solve real problems, and help real people.

When you do?

It’s the closest thing to magic I’ve ever experienced.

It all starts with one simple habit:

Create every day.
Share what you created.
Let the right people find you.

That's the simple engine behind everything I run today.

If you want more control over your time, income, and future, I'd highly encourage you to start sharing publicly here on LinkedIn.

I went from a guy with 2,000 followers to being ranked alongside Bill Gates and Barack Obama on the worldwide top 10 LinkedIn Creators to follow.

I used this playbook: https://buff.ly/8weY0jL

Success won’t happen overnight.

But once it clicks, there’s no going back.

How it’s going to be the next generation of software developers? 👇

Sit and enjoy the movie 😂😂😂

#ai #devs

🚀 Amazon  just printed one of its strongest quarters ever and AI is clearly paying off.

In Q3 FY25, Amazon hit $180.2B in revenue +13% YoY, with net income soaring ~45% to $21.2B.
Even after one-time hits FTC settlement + severance, profitability remained strong and the adjusted operating income jumped +25%.

𝗕𝘂𝘁 𝘁𝗵𝗲 𝗿𝗲𝗮𝗹 𝘀𝘁𝗼𝗿𝘆? 𝗔𝗪𝗦 𝗮𝗻𝗱 𝗔𝗜.
☁️ AWS: $33B revenue, up 20% YoY, its fastest growth in over a year.
🎯 Advertising: $17.7B, up 23% YoY, now one of Amazon’s most profitable engines.
💡 R&D spending climbed to 16.1% of revenue, fueling massive AI and infra investments.

And yes, that $9.5B gain from Anthropic shows how early Amazon moved in the GenAI wave and how fast that bet is paying off.

🔮 Q4 outlook: Revenue guidance up to $213B and operating income up to $26B, signaling confidence in continued AI-driven acceleration.

Bottom line:
Amazon’s flywheel is evolving — from commerce → cloud → AI.

#AWS #AI #Amazon #Cloud #GenerativeAI

The people winning aren't smarter.

They just never stopped learning.

I see this pattern everywhere.

The person who thinks they know it all?

Stuck at the same level for years.

The person who's constantly curious?

Rising fast.

Here's why:

The world changes every day.

What worked last year doesn't work now.
What you learned in school is already outdated.
What got you here won't get you there.

So you've got two choices:

Keep learning.
Or get left behind.

I'm 44 and I still spend hours every week learning.

Reading books.
Testing new strategies.
Staying curious.

Not because I have to.

Because that's what keeps me relevant.

The moment you think you've figured it all out is the moment you start falling behind.

Your competition isn't standing still.
The market isn't standing still.
Technology isn't standing still.

So why would you?

Stay sharp.
Stay curious.
Stay growing.

That's how you keep rising.

If you want to join over 175,000 online entrepreneurs lifting their audience and business-building skills each week, consider joining my newsletter, The Saturday Solopreneur.

I send out one tip to help you grow your audience and revenue every Saturday.

4 minutes or less guaranteed.

Join free here: https://buff.ly/3ZzyLhl

Slow progress beats no progress.

Every time.

Most people quit right before it works.

They post for 30 days. No traction.
They build for 90 days. No revenue.
They show up for 6 months. Nothing.

So they stop.

And they never know how close they were.

Because results don't show up on schedule.

They show up after consistency.

I posted on LinkedIn for 8 months before anything happened.

8 months of doubt.
8 months of crickets.
8 months of "will this work?"

Then it clicked.

Not overnight. Not all at once.

But it happened.

And it only happened because I didn't quit.

The people who succeed aren't the most talented.

They're the ones who stayed in the game long enough to win.

If you're ready to understand how to use data and analytics to grow on LinkedIn, join 45,000+ students including 200+ LinkedIn Top Voices inside of the LinkedIn Operating System to shortcut the game and finally grow.

Start here: https://buff.ly/8weY0jL

It won't happen overnight.

But it will happen if you follow this plan.

APIs are the new front door!!!

AI agents reason and act while APIs speak, and the challenge is.... how to connect everything?

Couple of weeks ago I had the chance to visit API Summit 2025 in NY where Kong Inc. just made a bold move and it’s exactly what most of AI builders need.

I’ve known the Kong folks for a while great people, and I’ve been playing with their platform recently and it's pretty awesome: it’s fast, secure, and deeply aligned with what the agentic AI era demands.

And without any doubt, what excites me the most is that now Kong natively integrates with AWS API Gateway.

But on top of that, they did many great announcements too:

🔸 AI Gateway + MCP Gateway: manage and secure Tokens traﬃc.  
🔸 KAi: the first AI agent for API platform engineering.  
🔸 MCP Composer & Runner: first AI-powered integrations.  
🔸 Volcano AI SDK: the easiest way to build MCP-powered AI agents.  
🔸 Flows: visual API orchestrations to design and manage complex flows.  
🔸 Kong Event Gateway: bring the full power of Kafka data streams to APIs.  
🔸 Konnect Identity: machine-to-machine M2M API credentials and mgmt.  
🔸 Metering & Billing: Monetize API calls and Tokens in a few clicks.

I'm having lot of fun building my side projects with it! Kong is setting the bar for what AI-ready connectivity should look like!

The future of enterprise AI won't be built just on LLMs, it requires to go beyond and definetly Kong makes your life much easier!

More info below: https://lnkd.in/dcRtpg5s

#ai #agents #api

85% of what you're doing is pointless.

I know because I was doing it too.

All the meetings.  
All the networking.  
All the "opportunities".  

I was busy as hell, going nowhere fast.

Then I realized something:

Most of my effort was producing zero results.

So I cut everything that didn't directly build my business.

No more meetings.  
No more "quick calls".  
No more chasing shiny objects.

Just four things:

1. Writing daily  
2. Publishing on LinkedIn  
3. Building products people wanted  
4. Spending one hour a day helping people

Every single day.

For six years.

That's when this business changed.

Not because I worked harder. I didn't

Because I stopped wasting time on stuff that didn't matter.

The truth is that being busy feels productive.

But only focus creates results.

Do what I did.

Write and publish content, listen to your audience, build products and help people.

Here's the system I use to write and publish: https://buff.ly/8weY0jL

45,000+ students including 200+ LinkedIn Top Voices use it too.

So, cut the 85%...

And double down on what works.

I've flown my whole life and I just realized I've wasted hundreds of hours!

I used AI to optimize my route on my recent trip from Los Angeles LAX to Madrid MAD, and it was as simple as drawing a straight line: easier and faster!

This is a great opportunity for any airline, both to save costs and to become more sustainable!

All credits to James Hawkins, great post 😂

#ai

🚨🚨🚨 𝗛𝗼𝘄 𝘁𝗼 𝗗𝗲𝗽𝗹𝗼𝘆 𝗞𝗶𝗺𝗶 𝗞𝟮 𝗼𝗻 𝗔𝗪𝗦 ????

Moonshot AI’s new Kimi K2 model is making waves and now it’s easier than ever to run it on Amazon Web Services AWS, whether you prefer full control or serverless simplicity. Here are your best options 👇

⚙️ 𝗔𝗺𝗮𝘇𝗼𝗻 𝗦𝗮𝗴𝗲𝗠𝗮𝗸𝗲𝗿 𝗙𝘂𝗹𝗹 𝗖𝗼𝗻𝘁𝗿𝗼𝗹, 𝗠𝗮𝗻𝗮𝗴𝗲𝗱 𝗘𝗻𝘃𝗶𝗿𝗼𝗻𝗺𝗲𝗻𝘁
Ideal if you want to customize containers, fine-tune, and monitor everything.

🔸Download it from Hugging Face 🤗 
🔸 Build a custom Docker container CUDA, PyTorch, Kimi code.
🔸Upload your model weights to S3.
🔸Create and deploy a SageMaker Endpoint e.g. ml.g5.12xlarge.
✅ Auto-scaling, logging, MLOps-ready.

☁️ 𝗔𝗺𝗮𝘇𝗼𝗻 𝗕𝗲𝗱𝗿𝗼𝗰𝗸 — 𝗕𝗿𝗶𝗻𝗴 𝗬𝗼𝘂𝗿 𝗢𝘄𝗻 𝗠𝗼𝗱𝗲𝗹, 𝗚𝗼 𝗦𝗲𝗿𝘃𝗲𝗿𝗹𝗲𝘀𝘀
Perfect for instant API access without managing infrastructure.

🔸Download from Hugging Face one of the supported Kimi K2 architectures
🔸Import Kimi K2 via Custom Model Import from S3 or SageMaker.
🔸Deploy as a serverless endpoint with InvokeModel.
✅ Integrated with Guardrails, Knowledge Bases, Agents — and you only pay per use.

🧠 𝗘𝗖𝟮 / 𝗞𝘂𝗯𝗲𝗿𝗻𝗲𝘁𝗲𝘀 — 𝗗𝗜𝗬 𝗠𝗼𝗱𝗲
For the builders/AI Engineers who want bare-metal control.

🔸 Choose the appropiate instance: g5.2xlarge, p3.2xlarge , p4d.24xlarge...
🔸Launch on GPU EC2 instances or manage clusters via EKS.
✅ Total flexibility, manual scaling, and deep system tuning.

📘 For full step-by-step setup, follow the official AWS guides for each method, they’ll walk you through from container to inference.

Also you can always ask Perplexity for a detailed step by step implementation. I did it and works great!

Build now!!!

#ai #genai #aws

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