Andreas Welsch

Andreas Welsch is an internationally recognized top 10 Agentic AI leader and one of today’s most sought-after thought leaders and keynote speakers for business and technology audiences. With over two decades of global leadership experience, previously as Vice President at SAP, Andreas has helped Fortune 500 companies cut through AI hype to deliver measurable business outcomes.

He is the Founder and Chief Human Agentic AI Officer of AI consulting firm Intelligence Briefing, the best-selling author of the AI Leadership Handbook and The HUMAN Agentic AI Edge, and a leading voice on AI strategy, adoption, and transformation. 

At the heart of Andreas’s work lies a clear value proposition: he helps business leaders understand how to apply AI responsibly, effectively, and profitably by addressing the questions that decision-makers face:

• How do we turn AI into business value, not just experimentation?
• How can we prepare our workforce for AI-driven transformation?
• How can we empower our teams to use AI without creating AI workslop?
• What practical steps can we take to avoid ethical, operational, or financial pitfalls?

Andreas’s keynotes and workshops are known for their clarity, strategic relevance, and deep insight. Drawing from more than two decades in the software industry, he offers real-world frameworks and practical steps tailored to leadership audiences. He introduces leaders to AI agents, leading hybrid teams of humans and AI, and AI-driven business models, explaining not only what’s next, but what matters most and why.

During his tenure at SAP, Andreas accelerated the integration of AI across enterprise applications and positioned SAP as an AI leader. He brings first-hand experience and a global perspective to every business and has been named a LinkedIn Top Voice, Thinkers360's Top 10 Thought Leader in AI, Generative AI, and Agentic AI, The Futurum Group's Top 14 AI Influencer, PEX Network’s Top 30 AI Leader, and SwissCognitive’s Top 50 Global AI Ambassador.

His work has appeared in CIO.com, VentureBeat, InformationWeek, and the American Management Association. He serves on the Editorial Board of the Journal of AI, Robotics and Workplace Automation and as an adjunct professor at West Chester University of Pennsylvania.

For leaders looking for clarity, action, and strategy, Andreas delivers a transformative experience beyond the hype. Follow his “What’s the BUZZ?” podcast and newsletter, “The AI MEMO”, and work with Andreas to turn hype into outcome for your business.

Vice President & Head of Marketing & Solution Management — Artificial Intelligence

Defined GTM and product marketing for Artificial Intelligence (AI) across SAP’s product portfolio, incl. AI Business Services on SAP Business Technology Platform in the context of embedded AI capabilities and intelligent process automation via Robotic Process Automation (RPA) and low-code/ no-code offering. Led global team of product marketers and solution managers

“Is your hand getting tired?” attendees asked.
“You should have a stamp,” others joked. 
But that would circumvent the HUMAN aspect and authenticity. 

For two hours straight, attendees waited in line to receive their signed copy of The HUMAN Agentic AI Edge on launch day yesterday.

I signed each one of the 300 books with:
Stay HUMAN. 
Get AI-Ready.

Sounds great, doesn’t it? But it was the little chats here and there, the feedback on my closing keynote, and talking about the good old days with former colleagues, that added the HUMAN touch.


If you haven’t gotten your copy yet, you can get it on Amazon for a 90% launch discount!


A special shout-out to Paul Kurchina, the mastermind behind the annual “Next Generation SAP Enterprise Architect Community Learning Forum,” master connector, and extraordinary supporter!

#ArtificialIntelligence #AgenticAI #IntelligenceBriefing

I signed 300 books at the big launch this week, but this interaction made an impression on me:

Jade was running the bar and serving customers. When the book line was short, she came over, and I signed a copy for her. She asked about my self-publishing process and mentioned that she has published three books on Amazon. As I was breaking down the banners and stowed them away at the end of the event, Jade came over again. 

“Can I say something?” she asked. 

I was curious, but wasn’t quite sure what was on her mind. 

“Successful people need to hear this, too: I am proud of you!”

I didn’t expect to hear these words.

A dozen thoughts rushed through my head: 
How nice of her to come over to say that. Successful? Proud of ME?

All I could think to say was: “Thank you so much.”

But I’ve been thinking about that interaction and her words for the rest of the week.


Let’s all be a little more like Jade, and be a little more HUMAN. 


PS: Read or listen to the best-selling The HUMAN Agentic AI Edge on Amazon or Spotify.

#ArtificialIntelligence #AgenticAI #IntelligenceBriefing

📘 NOW AVAILABLE: The HUMAN Agentic AI Edge! 
When AI becomes the next “easy button,” leaders need to set expectations with their teams early. 

Otherwise, low-quality, sloppy results creep in, and performance, skills, and reputation degrade.

Between the triad of standards, guardrails, and readiness lies the real work that leaders need to do now, beyond “giving everyone Copilot etc.”

Let’s face it: team members are not off the hook doing their best work. They never were.

Like a senior manager recently shared with me: “Now, I’m getting all these meeting summaries and action items from my team members. I don’t have time to go through all of them.”

Creating is easy. Filtering and prioritizing are the new bottleneck for most leaders.

In the book, you will find the frameworks, anecdotes, and examples that help you empower and encourage your team to use AI responsibly while remaining accountable and high-performing.


Today is the official book launch together with 500 IT leaders at the Next Generation SAP Enterprise Architect Community Learning Forum—keynote and book signing included.


In case you are not on-site, you can get your copy on Amazon for the special launch offer!


Stay HUMAN. Become AI-ready.

And celebrate the big launch with me!

#ArtificialIntelligence #AgenticAI #Leadership

How do you measure the success of a launch?
Whatever your answer, launch day is intense. 
Whatever your product or service, you prep and prep, and prep…and hope for the best. 

Once the launch is on, market reception and feedback are largely out of your hands.

What applies to software and category launches applies to book launches, too. 

On Wednesday, I was checking the category rankings to see how The HUMAN Agentic AI Edge was moving up in the three categories I selected for the launch. 

But it wasn’t. 

It sat at rank #76 all morning and afternoon.
I was getting nervous. Had I missed to activate even more parts of my network? Was everyone just too busy during the day (or had forgotten about buying the book)?

Was the number of sales not enough to make even a slight dent?

Then, one of my friends texted me. 
“Your book is #3 in the charts!”

I was relieved. At least a little. Viewing the category instead of the book showed the correct ranking. But the question of how many more sales I’d need to make it to #1 was nagging. You just don’t know. 

At dinner, we celebrated the launch together with the other speakers of the Next Generation SAP Enterprise Architect Community Learning Forum. 

By then, the book had moved to #2. Soooo close. So close. 

4 minutes past midnight, it hit the top spot in the “Hot Releases” list on Amazon in Germany—just not in a category. 

I decided to go to sleep and check whenever I’d wake up. #2 wasn’t so bad for launch day. But would other books overtake it tomorrow?

I briefly woke up just before 4am and grabbed my phone. Had anything changed in the past 4 hours??

Yes, it had! #1 in Management Skills…a best-seller!! Satisfaction. Screenshot. Sleep. In that order.

Since then, it has hit #1 in all three categories!
A super successful launch. 


But it’s one of these things that you can’t do alone. Thank you so much for your support and readership! I’m deeply grateful!


(Don’t miss to get the launch promo of $0.99 for the ebook for the next 24 hours: https://lnkd.in/dcKY6biC)


Next up: Keynotes, workshops, and podcasts!

#ArtificialIntelligence #AgenticAI #Leadership

During the launch of The HUMAN Agentic AI Edge, 300 attendees waited in line to get their signed copy. Here’s how quickly 3 hours went by…

In each book, I wrote:

Stay HUMAN. 
Get AI-Ready.

Because in order to become an AI-first business, your team needs to get AI-ready…first.


Since then, many attendees have reached out, and I even met a few IRL this week!

Thank you for the awesome feedback and reviews. If you’ve received or bought a copy, please consider leaving your feedback on Amazon. 

Empowering and encouraging team members to use AI without creating slop is the task of the hour. 

I’m curious: How much AI slop do you receive per day? And what would it take to stop it?

#ArtificialIntelligence #AgenticAI #IntelligenceBriefing

Earlier this week, we had a special pre-launch book signing for members of the Chief Architect Network (CAN) that Grant Ecker leads.

Grant and the CAN community connect Chief Architects and senior IT executives to discuss and learn about new topics (such as Agentic AI) and how IT organizations can both prepare themselves and implement these technologies. Since 2021, the community has grown to over 620 members globally.

I’ve been following Grant on LinkedIn for a few years now. So, I was super excited when we first hosted our first event together in December, and when we finally got to meet in person this week.

When AI-generated news and the AI hype make it harder to discern what's real and what's actually working, being part of a community of trusted, human leaders and experts is the way to go.

So here’s a special Friday shout-out Grant and the network!
Give him a follow and maybe we'll see each other at a future event, too.


Love the red tumbler, btw. It goes so well with The HUMAN Agentic AI Edge and the launch-week promo of a symbolic Dollar (or Euro) over on Amazon.


Happy Friday, everyone!


#ArtificialIntelligence #Leadership #Community

“I hadn’t thought about agents as digital employees, yet,” shared a leader with me after attending yesterday workshop, “but it makes sense!”

Let’s get this out of the way for context:
- Approaching agents as digital employees is a helpful metaphor as you define guidelines, guardrails, add processes, but…
- They are still “just software” when it comes to the accountability for their decisions incl legal or ethical aspects (accountability stays with you)

I call it the “Dual-Lens Principle.”

Another attendee rightfully asked who creates the majority of agents in a business today?—IT. 

HR is not at the table. Yet, it’s a major workforce shift and HR can contribute wit that experience. Job descriptions, codes of conduct, rewards, org charts included. IT and HR need to collaborate.

That’s a central point in The HUMAN Agentic AI Edge which participants learned about. Tomorrow is the official book launch, which means you can learn about it, too!


How do you view AI agents?—As digital employees or just another piece of software?


#ArtificialIntelligence #AgenticAI #IntelligenceBriefing

The HUMAN Agentic AI Edge was just covered on Forbes!! Coverage includes the 6 dimensions of the Operating Model you will find in the book.  

When work is no longer a matter of effort, purpose moves into focus.

When AI generates outcomes on par with human results, quality and delivery speed become the differentiating factors.

Ultimately, the question is how you define your value at work when AI can eventually do more tasks that humans do.

The key lies in elevating what makes us unique.
And that’s a core role any leader needs to play. 

How do you define your value at work?


Thank you, Joe McKendrick, for covering a key message of the book in this article!

Don’t miss to get your copy of the best-selling ebook, paperback, or audiobook wherever you get your books!

#ArtificialIntelligence #AgenticAi #IntelligenceBriefing

You've heard me say it time and again:
Your AI agents need high-quality data to deliver high-quality results.

But what does Agentic-Ready Data look like?
And where does that high-quality data even come from when data is rarely current, correct, enriched, or governed.

I can't wait to learn about it from the Precisely team at the Gartner Data & Analytics Summit in Orlando next week at booth # 727. Learn more here: https://lnkd.in/dXhPcGiS

If you're on site, don't forget to join this session:

How a Global Gaming Leader Is Closing the Agentic AI Data Integrity Gap
Monday, March 09, 2026 / 03:30 PM - 04:00 PM EDT (Osceola D)
Paul Bell, Global Head Of Data Trust & Integrity, Entain
Cam Ogden, SVP of Product Management, Precisely

One thing is clear, the highest quality data that is integrated, governed, and enriched is needed for successful AI, automation, and analytics initiatives across the enterprise.

It better be. It has to be.


See you in Orlando!


#ArtificialIntelligence #AgenticAI #Sponsored

If you haven’t gotten your copy, yet, there’s still time to snag the launch price of $0.99 on Amazon today! The HUMAN Agentic AI Edge

graphical user interface, text, application

“What’s new, and what’s real with Agentic AI?” is the big question I’m getting answers to next week in Orlando.

I’ll cover the latest news on site, interview top executives, and talk to customers to get information straight from the source.

One thing is clear:
Large organizations are innovating with Agentic AI. They just don’t talk about it publicly (out of fear to get bad press or backlash). But we need more transparency (not less!), so everyone can avoid the costly mistakes. 

Join me in Orlando for the Gartner Data & Analytics Summit! Leave a comment if you’re going, too.


Still need to register? Use code ‘JOINMEINORLANDO’ to save $450 off registration: https://lnkd.in/duUD-re3
 

PS: Looking forward to catching up with Kate Strachnyi, SCOTT TAYLOR, George Firican, and Ravit Jain.

#GartnerDA #DataCommunity #DataSummit #ArtificialIntelligence #AgenticAI

Agentic AI value does not come from models alone. Instead, quality, trust, and governance of the data behind it are more critical than ever.

To learn more, I spoke with Felix Van de Maele, CEO of Collibra, to discuss why turning AI ambition into real business value starts with one thing: Data Confidence.

Here’s what stood out:

1. AI success is mostly a data challenge
Felix makes the case that enterprise AI is largely driven by the data organizations feed into their models, agents, and use cases. When companies have confidence in their data, they can move faster, generate higher-quality outputs, and drive stronger adoption across the business.

2. Unstructured data is the next big frontier
Most enterprise data is still unstructured, and that creates a major challenge for AI teams. Felix explains why discovering the right documents, identifying sensitive information, and evaluating data quality are essential if organizations want to get better ROI from AI initiatives.

3. More context does not always mean better results
Simply loading every available document into an AI system is not a winning strategy. Better outcomes come from intentional governance of the data and context that agents rely on.

4. Agentic AI raises the stakes for governance
As AI agents begin to take more autonomous actions, accountability becomes even more important. Felix breaks down why organizations need to govern inputs, monitor outputs, and establish the right controls to move AI from experimentation into production responsibly.

If you're tasked with scaling AI in your enterprise, this conversation is a strong reminder that trusted data is the foundation for trusted AI outcomes.


#ArtificialIntelligence #AgenticAI #DataGovernance

Anthropic calls it: Theoretical capability.
You might also call it: Market potential. 

Keep in mind that these are the key industries and occupations that Anthropic is selling to!

So, it’s not surprising for a vendor to picture their product as covering close to 100%(!) of tasks in management, finance, programming, legal, life sciences, and office admin.

The bigger questions are about how to turn theoretical into actual capability:
1) Why is there so much untapped potential?
2) How can organizations close that gap?

Yet, the cause is all around you in your business:
Leaders are asking “We’ve given everyone access to Copilot, Claude & Co., now what?”

Tools have theoretical capabilities.
Humans need actual capabilities. 


Since the summer, I’ve been running cohorts of my “Certified AI Leader” upskilling program.

The four levels of the learning journey cover the basics of using AI assistants, applying advanced prompting techniques, building your first AI agents, and leading your teams through AI-driven change: https://lnkd.in/dq4ayVWX


Prepare your teams expand their actual capabilities. DM me for the details. 


PS: In the meantime, learn how to shape the next generation of AI-ready teams with my new book, The HUMAN Agentic AI Edge.

#ArtificialIntelligence #Upskilling #IntelligenceBriefing

AI agents are only as good as the data behind them.

That’s why I talked to Cam Ogden, SVP of Product Management at Precisely, to learn more about the challenge many organizations are underestimating: whether their data is actually Agentic-Ready Data.

As more companies move from AI experimentation to enterprise agents making decisions on their behalf, the bar for data trust rises dramatically. Cam shares why “AI-ready” and “agentic-ready” are not the same thing, and what leaders need to do now to close that gap.
Here’s what you’ll learn:

1. Why data trust matters more in the age of AI agents
When dashboards fail, teams lose confidence. When agents act on flawed data, the business takes on real operational risk. Agentic AI requires a much higher standard of trust, completeness, and confidence in enterprise data.

2. Where the AI readiness disconnect really comes from
According to the 2026 State of Data Integrity and AI Readiness report (https://lnkd.in/dMm72RbM), co-developed with the Drexel LeBow Center for Applied AI and Business Analytics, many leaders say their organizations are AI ready because they have roadmaps, cloud investments, and executive support in place. But at the operational level, the picture often looks very different, creating a gap between strategy and execution. That’s also why so many organizations are still struggling with data quality, context, and integration.

3. The hidden measurement problem in AI adoption
A major issue is not just whether companies are investing in AI, but whether they are measuring success in a meaningful way. Too few organizations have clear metrics tied to AI outcomes, which makes it harder to prove impact and scale what works.

4. How to close the agentic AI data integrity gap
Leaders need to address six core challenges, spanning siloed data, missing context, stale data, incomplete records, weak governance, and rising cost from untangling these issues. Start with one use case, strengthen the data foundation, prove value, and then scale across the business.

If you’re exploring AI agents in the enterprise, this conversation will help you understand why trusted, well-governed data is becoming a competitive requirement.

Watch and listen how leaders can build the Agentic-Ready Data foundation needed for real AI scale.

#ArtificialIntelligence #DataStrategy #AgenticAI #AgenticReadyData #Precisely

Everyone wants AI agents. But most organizations are still skipping an important step: 

Matching the type of Agentic AI they want to the level of readiness they actually have.

A practical way to think about Agentic AI is in 3 categories:

1. Personal productivity: AI helps an individual draft, summarize, research, or analyze. Accountability is still clear.

2. Operational efficiency: Teams hand recurring work to agents, such as reporting, data checks, or coordination. Review processes start to matter much more.

3. Strategic differentiation: Agents support core processes like procurement, customer support, or financial analysis. This is where scale rises fast, but so does risk.


The mistake many companies make is treating all three the same. It’s a core aspect in my new best-selling book, The HUMAN Agentic AI Edge.

As agent autonomy increases, so must clarity around ownership, permissions, quality standards, and review.

That is why leaders need to look at agents through two lenses at the same time:
- as digital employees that need guardrails
- as just another piece of software that must be governed

Most importantly, human are still responsible. AI can accelerate work, but it does not remove judgment. If standards do not keep pace with adoption, “productivity gains” quickly turn into review overhead, rework, and hidden clean-up.

The better approach:
- Start where accountability is clear.
- Design deliberately as complexity increases.
- Keep human judgment ahead of AI capability.

Wanting AI agents is easy. Using them well is the real work. Read the full guest article on Technical-ly

#ArtificialIntelligence #AgenticAI #IntelligenceBriefing

For the weekend ahead, get some reading or listening in and learn with The HUMAN Agentic AI Edge audiobook how to empower your team to become AI-ready.

You’ll learn about:
- Why professionals need to do a Labor-Shift Check before passing on AI-generated results
- Whether (or when) to view AI agents as digital employees
- How to encourage your team to balance AI-driven efficiency with human judgment 

Why it matters:
At the end of the day, your stakeholders are indifferent about whether your team or its AI created the results. But you’ll hear about it when quality degrades.

Get started today and shape the next generation of AI-ready teams!


#ArtificialIntelligence #Leadership #IntelligenceBriefing

Your biggest AI advantage is a repeatable way for people to use it.

Start a tiered champion program: basic membership and sandbox access, short role-based courses, hands-on prototyping, and named local contacts who connect teams to deployment support. 

Curate short learning paths, keep playgrounds safe, and push pilots that show clear deployment paths so adoption comes from informed users, not guesses.  

Stop confusing speed with scale. Quick experiments teach a lot, but without structure they create waste. Require a simple pilot template (goal, expected benefit, data needs, security checklist, deployment path), run short cycles, and measure outcomes you can act on. Keep governance light but consistent so teams don’t reinvent the same work.  


This is just an excerpt of my weekly newsletter—subscribe to read the latest issue via the link under my name.

Ranked by Favikon as:
↳ #1 AI Creator on LinkedIn India 
↳ Top 10 AI Creators on LinkedIn Globally 

Featured in Forbes and Wired

For 14 years, I've been obsessed with a single question: how do we teach machines to truly see and understand our world?

This quest began at Qualcomm. My 3D reconstruction technology landed in Forbes, and the object tracker I co-designed was used in millions of mobile devices. When someone casually used my work in their palm, I glimpsed what's possible when research meets reality.

At Intel Labs, I immersed myself in creating AI systems that bridge the gap between theoretical potential and practical performance—systems that could deliver sophisticated intelligence within real-world constraints. Today at Valeo, I lead a team of AI experts developing computer vision for autonomous vehicles. We're teaching cars to go beyond simple object detection toward true scene understanding. Each breakthrough is a step toward fundamentally transforming how people and goods move worldwide. We are reimagining transportation.

Since 2019, I've guided teams at NASA's Frontier Development Lab as their Machine Learning Lead. We've tackled fundamental questions about our Sun and understanding it better. Our breakthroughs have since been published in conferences like NeurIPS. 

Along the way, I saw a problem I couldn't ignore.

I watched brilliant scientists—experts in physics and natural phenomena—blocked from leveraging AI. Not by ability. But by clarity. Incredible AI research remained locked behind jargon. 

There had to be a better way to get the message across. So, Gradient Ascent was born. In it, I break down complex AI concepts for engineers, product leaders, CEOs, and investors making critical decisions shaping our future. Their response has been humbling.

Outside the lab, I'm an award-winning nature photographer and enjoy illustration and music. These pursuits fuel my creative approach to problem-solving.

✍️ Subscribe to my newsletter for insights that transform technical AI jargon into actionable understanding: newsletter.artofsaience.com

———
Note: All opinions are my own and do not reflect the opinions of my employer

Sairam Sundaresan

You don’t need 100 tutorials.
Just these 8 videos on AI agents:

1. LLM Introduction: 
https://lnkd.in/gN8sv7Q5
2. LLMs from Scratch: 
https://lnkd.in/gJt-SQj2
3. Agentic AI Overview (Stanford): 
https://lnkd.in/gk4GKdxa
4. Building and Evaluating Agents: 
https://lnkd.in/ghBiVjdF
5. Building Effective Agents: 
https://lnkd.in/g_m78sid
6. Building Agents with MCP: 
https://lnkd.in/gAzBzr3W
7. Building an Agent from Scratch: 
https://lnkd.in/g9GR9b9F
8. Philo Agents: 
https://lnkd.in/gnxRq9n9

♻️ Repost to help someone master AI
➕ Follow me, Sairam, for AI engineering that works

Want to learn the basics first? Check this out: https://lnkd.in/giV_N6KU

AI Engineering Leader | Author of AI for the Rest of Us | I help engineers land AI roles and companies build valuable products

Think you’ve mastered Claude?
You haven’t seen what it's really capable of.

This open repo has 450+ real Claude skills
Not just prompt templates, but actual workflows across Claude, Claude Code, and the API.

Ready-made examples:
🔸 Dev & code
🧪 playwright, TDD, sub-agent workflows, iOS simulator

🔸 Document mastery
📄 docx, pdf, xlsx, markdown → EPUB

🔸 Research & writing
📝 brainstorm, summarize, auto-cite

🔸 Data & analysis
📊 CSV insights, root-cause tracing

🔸 Security & systems
🛡️ forensics, threat hunting, metadata

450+ skills. 
25+ categories.

Everything repeatable. 
Everything customizable.

Still pasting prompts?
You're 5 steps behind.

Check it out: https://lnkd.in/evYkUYiw

♻️ Repost to help someone learn AI the right way
➕ Follow me, Sairam, for AI engineering that works.
-----
Join 26k+ readers from Google, Meta, Netflix, and over 160+ countries worldwide: https://lnkd.in/gZbZAeQW
Learn the basics first: https://lnkd.in/gTQyc_fi

Stanford just made a $200,000 AI education free.
The same lessons that built Silicon Valley are now on YouTube.

📚 Here's your map to go beyond prompting and start building real AI systems:

1️⃣ CS221 – Artificial Intelligence
Foundations of AI: search, reasoning, planning, decision-making
🔗 https://lnkd.in/gM9ndUCf

2️⃣ CS229 – Machine Learning (Andrew Ng)
Supervised/unsupervised learning + deep dive into algorithms
🔗 https://lnkd.in/gDc9siUC

3️⃣ CS230 – Deep Learning (Andrew Ng)
Neural nets, CNNs, RNNs, and best practices for deep models
🔗 https://lnkd.in/guaavVdk

4️⃣ CS231n – Deep Learning for Computer Vision
Neural nets, CNNs, Generative Models, and VLMs
🔗 https://lnkd.in/gVJZ-xMq

5️⃣ CS229M – Machine Learning Theory
The math and proofs behind ML - for those who want to really understand
🔗 https://lnkd.in/gFBCyuCU

6️⃣ CS234 – Reinforcement Learning
MDPs, Q-learning, policy gradients, and agents that learn by doing
🔗 https://lnkd.in/gVvz87Hc

7️⃣ CS224U – Natural Language Understanding
Semantic analysis, dialogue systems, language meaning
🔗 https://lnkd.in/gRsWMfA6

8️⃣ CS224N – NLP with Deep Learning
Transformers, embeddings, and modern NLP architectures
🔗 https://lnkd.in/gQdFAZXM

♾️ New to AI? Start here:
 https://lnkd.in/gTQyc_fi

🎯 Why this curriculum matters:
• Not just tools, real understanding
• Theory and application from world-class professors
• Build instead of just using
• Go deeper than 95% of "AI experts"

You're one click away from learning real AI.
Which course are you starting with?

♻️ Repost to help someone learn AI the right way
➕ Follow me, Sairam, for AI engineering that works.

Join 26k+ learners from Google, Meta, Netflix, and other top tech companies and level up your AI skills for free at Gradient Ascent: https://lnkd.in/gZbZAeQW

The tech landscape just shifted. Again. 
Here’s a resource stack to future-proof your career:

📹 Videos:
1. LLM Introduction: https://lnkd.in/gN8sv7Q5
2. LLMs from Scratch: https://lnkd.in/gJt-SQj2
3. Agentic AI Overview (Stanford): https://lnkd.in/gk4GKdxa
4. Building and Evaluating Agents: https://lnkd.in/ghBiVjdF
5. Building Effective Agents: https://lnkd.in/g_m78sid
6. Building Agents with MCP: https://lnkd.in/gAzBzr3W
7. Building an Agent from Scratch: https://lnkd.in/g9GR9b9F
8. Philo Agents: https://lnkd.in/gnxRq9n9

📚Books:
1. AI for the Rest of Us: https://lnkd.in/gTQyc_fi
2. Understanding Deep Learning: https://lnkd.in/g4xgvu_q
3. Building an LLM from Scratch: https://lnkd.in/g2YGbnWS
4. The LLM Engineering Handbook: https://lnkd.in/gWUT2EXe
5. AI Engineering: https://lnkd.in/gpfQSMCQ

🗂️ Repos
1. GenAI Agents: https://lnkd.in/gvfAc-9H
2. Microsoft's AI Agents for Beginners: https://lnkd.in/gK8MiVfv
3. Prompt Engineering Guide: https://lnkd.in/gJjGbxQr
4. AI Agent Papers: https://lnkd.in/gfKQ82Fs

🗺️ Guides
1. Google's Agent Whitepaper: https://lnkd.in/gFvCfbSN
2. Google's Agent Companion: https://lnkd.in/gfmCrgAH
3. Building Effective Agents by Anthropic: https://lnkd.in/gRWKANS4.
4. Claude Code Best Agentic Coding practices: https://lnkd.in/gs99zyCf
5. OpenAI's Practical Guide to Building Agents: https://lnkd.in/guRfXsFK

📜 Papers
1. ReAct: https://lnkd.in/gRBH3ZRq
2. Generative Agents: https://lnkd.in/gsDCUsWm.
3. Toolformer: https://lnkd.in/gyzrege6
4. Chain-of-Thought Prompting: https://lnkd.in/gaK5CXzD.
5. Tree of Thoughts: https://lnkd.in/gRJdv_iU.
6. Reflexion: https://lnkd.in/gGFMgjUj
7. Retrieval-Augmented Generation Survey: https://lnkd.in/gGUqkkyR.

🧑‍🏫 Courses:
1. HuggingFace's Agent Course: https://lnkd.in/gmTftTXV
2. MCP with Anthropic: https://lnkd.in/geffcwdq
3. Building Vector Databases with Pinecone: https://lnkd.in/gCS4sd7Y
4. Vector Databases from Embeddings to Apps: https://lnkd.in/gm9HR6_2
5. Agent Memory: https://lnkd.in/gNFpC542
6. Building and Evaluating RAG apps: https://lnkd.in/g2qC9-mh
7. Building Browser Agents: https://lnkd.in/gsMmCifQ
8. LLMOps: https://lnkd.in/g7bHU37w
9. Evaluating AI Agents: https://lnkd.in/gHJtwF5s
10. Computer Use with Anthropic: https://lnkd.in/gMUWg7Fa
11. Multi-Agent Use: https://lnkd.in/gU9DY9kj
12. Improving LLM Accuracy: https://lnkd.in/gsE-4FvY
13. Agent Design Patterns: https://lnkd.in/gzKvx5A4
14. Multi Agent Systems: https://lnkd.in/gUayts9s

📩 Newsletters
1. Gradient Ascent: https://lnkd.in/gZbZAeQW
2. DecodingML by Paul: https://lnkd.in/gpZPgk7J
3. Deep (Learning) Focus by Cameron: https://lnkd.in/gTUNcUVE
4. NeoSage by Shivani: https://blog.neosage.io/
5. Jam with AI by Shirin and Shantanu: https://lnkd.in/gQXJzuV8
6. Data Hustle by Sai: https://lnkd.in/gZpdTTYD

Don’t fear the agents replacing everyone else.
Learn to build them and own the advantage.

♻️ Repost to help someone master AI
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Zero to RAG in 2026?
This roadmap will save you 100+ hours.

5️⃣ Videos
↳ Start here to understand what RAG is, how it works, and how to use it.
🔸 What is RAG: 
https://lnkd.in/gYVF6CfT
🔸 How to use RAG: 
https://lnkd.in/g-953k9V
🔸 CMU Advanced NLP (RAG): 
https://lnkd.in/gFXF6DZV
🔸 Stanford Transformers V3 RAG: 
https://lnkd.in/gnvPbU7X
🔸 RAG from Scratch: 
https://lnkd.in/gibgTsz5

4️⃣ Papers
↳ These shape how you think about the RAG landscape.
🔸 The RAG paper: 
https://lnkd.in/gW8ee2q6
🔸 RAG Survey: 
https://lnkd.in/ggAxtnwn
🔸 Self RAG: 
https://lnkd.in/gpbpyxqj
🔸 Corrective RAG: 
https://lnkd.in/gaHS3yhS

3️⃣ Repos
↳ Amazingly curated resources that save time.
🔸 RAG Techniques: 
https://lnkd.in/g2ZHwZ3w
🔸 Awesome RAG: 
https://lnkd.in/g4ppP4-H
🔸 Another Awesome RAG: 
https://lnkd.in/g3meT_ns

2️⃣ Courses
↳ Hands-on, guided courses on RAG that are worth your time.
🔸 Deep Learning AI's RAG : 
https://lnkd.in/gKCUaN7G
🔸 RAG with Langchain: 
https://lnkd.in/gEhQJ3RC

1️⃣ Newsletter
↳ Read for everything in and around AI engineering and research.
🔸 Gradient Ascent: 
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Bonus 
↳Need to learn the basics first? 
🔸 Start here: 
https://lnkd.in/giV_N6KU

Don’t just learn RAG. 
Context is power.
Build with it.

♻️ Repost this to save someone 100+ hours of research
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80% of ML system design interviews fail
On the same 7 question types.
Here are the traps and how to answer them right 👇

1️⃣ Predict Netflix Watch Times
Problem: New users and shows → sparse data
❌ Trap: Jumping straight to regression on watch hours
✅ Better: Use popular-show baselines, then layer personalization as data grows

2️⃣ ETA for Maps
Problem: Needs to run fast, at global scale
❌ Trap: Designing complex ML pipelines first
✅ Better: Start simple (distance ÷ speed). Add ML for traffic, incidents, freshness

3️⃣ Spotify Artist Recommendations
Problem: New artists lack data, heavy users skew results
❌ Trap: Relying only on collaborative filtering
✅ Better: Blend “users like you” with “songs like this one,” and plan for cold start

4️⃣ Detecting Bots
Problem: Bots adapt quickly, data is imbalanced
❌ Trap: Optimizing for accuracy and stopping there
✅ Better: Monitor drift, retrain often, include evolving signals

5️⃣ Fake News Detection
Problem: Text is noisy and easy to manipulate
❌ Trap: Using only text classifiers
✅ Better: Combine article content with who shares it and how it spreads

6️⃣ Instagram Feed Ranking
Problem: Ranking shifts user behavior long-term
❌ Trap: Optimizing only for engagement
✅ Better: Balance clicks with quality signals (reports, time spent, wellbeing)

7️⃣ Toxic Tweet Classification
Problem: Language is subjective and imbalanced
❌ Trap: Focusing only on a single metric (F1/accuracy)
✅ Better: Calibrate outputs, check bias, use human review for edge cases

💡 Pro Tip: These interviews aren’t about the “best model.” They test whether your design survives production.

👉 Learn ML System Design. Use FLASH40 for 40% off: https://lnkd.in/gqTrvsuS

♻️ Repost to help someone land their next AI role
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---
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The Battle

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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);}Andreas Welsch's LinkedIn Performance

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