AI Career Boost

AI Career Boost is the world’s first AI-focused career accelerator helping more diverse leaders thrive in business roles for AI and Machine Learning projects. We provided courses, keynote speaking and consulting services.

AI Product Coach and Advisor | Founder | Making AI Careers Accessible

Reforge

Co-created Build & Design Conversational AI for product managers, design and user research leaders, consultants and founders. Understand AI by getting hands-on with this practical course taught by industry experts.

Reforge Partner

Amazon

Built and led a high-performing 26-person team that developed and launched the first Generative AI answers on Alexa, using transformer models (like those that underlie ChatGPT). Led several cross-functional teams of engineers and scientists for one of the world’s top Natural Language Processing research groups.

Principal Product Manager - Technical, Alexa AI - Web Information

International LEAP Network

LEAP is a private exclusive network for members of the #CareerLeap Program: executive leaders, entrepreneurs, and high achievers from around the world who inspire and drive growth and impact on themselves, their work and their communities.

Executive Member

Data|Product|Strategy

Helping clients become data-centric companies by harnessing the power of data at scale. Advising on AI/ML/Analytics use cases, team processes, architecture and change management. Exploratory Data Analysis, Data Quality Evaluations, Skills Gap Analysis, Architecture Reviews, Vendor Research and MVP Development.

Founder & Principal Consultant

PeopleHedge

At PeopleHedge, they are trying to solve the world's foreign exchange rate problems. PeopleHedge helps importers, exporters, credit unions, and community banks with foreign exchange services. Typically, they shave about a hundred dollars off the cost of an average transaction for the bank or credit union.

Corporate Board Member

Elsevier

Elsevier is an information and analytics company and one of the world's major providers of scientific, technical, and medical information. When Elsevier acquired Plum Analytics in 2017, I was responsible for the strategy and implementation of integrating PlumX metrics throughout Elsevier's suite of Research Product tools and publishing platforms, and the expansion of reliable metrics that matter throughout Elsevier's products.

Director of Product Management, Research Metrics

Plum Analytics

Plum Analytics uses modern metrics to help answer the questions and tell the stories about research.
We measure the impact of research online, including traditional measures like citations counts along with new metrics that showcase usage, social media activity or online commentary.

Director, Product Management

Amazon.com

Our team was responsible for analyzing and reporting on retail promotions and discounts run through the Amazon retail websites world wide. We used predictive analytics to highlight poor performing promotions, designing the groundwork for predictive recommendation systems for retail promotions.

Software Development Manager, Promotion Data Analytics

Part of the Amazon Community team, the Reviewer Motivation team's mission is to engage potential reviewers and to motivate them to use Amazon’s Community features in ways that provide helpful, confidence-inspiring content to Amazon shoppers. We aim to make providing product feedback fun and engaging!

Software Development Manager, Social Shopping Technology

Metafor Software

Metafor software was acquired by Splunk Inc. in 2015.

Established a customer discovery process for a new analytics product for data center operations teams. Created a 12-month product roadmap, minimum viable product recommendations and an interactive prototype based on the results of nearly 20 customer interviews and market analysis.

Product Manager - Anomaly Detection as a Service

I help Product Managers break into AI Leadership - no coding required! Ex-Alexa AI Principal Product Manager | Launched 1st GenAI Answers on Alexa | Top 100 Women of the Future Winner | Reforge Instructor | Speaker

Polly Allen has over 20 years experience developing software, building and leading software teams and most recently leading cross-functional science and engineering teams as a Principal Product Manager for Alexa AI at Amazon. Her expertise is focused in natural language use cases, such as search and discovery, natural language understanding and generation, and she led the development and launch of the first automatically-generated summaries of web content on Alexa in 2020. (And yes, it used transformer models like those that drive ChatGPT!)

As a leader in the intersection of Product Management and Machine Learning, she is passionate about DEI in the space and empowering more people to understand, leverage and participate in the field. She is an experienced angel investor and past corporate board member, has advised multiple startups, and speaks on panels and conferences about Product Management, Ethics and DEI in AI. She holds a M.Sc. in Software Engineering from MIT and the University of Victoria, and an MBA from the University of British Columbia.

Polly M Allen

If the future of AI belongs to the builders… what does that mean for leaders? Are we all supposed to become super-ICs now?

Do we need to learn to prompt, prototype, ship, and scale ourselves?Or is there a new kind of leadership emerging—one that knows how to guide builders, not replace them?

🔥 That was the heart of my session today at the Sidebar Spark Conference:
 Lead AI by Building: Driving Impact and ROI.

And WOW—Spark lived up to its name! I spent the day deep in conversation with senior leaders who are trying to answer the same question: How do we lead in an era where our teams are getting closer to the tech stack, the pace is accelerating, and “business as usual” is officially obsolete?

Here’s what we dug into together:
💡 Supporting your builder teams — how to create an AI-first culture where product and engineering can actually ship - inspired by goals that matter.
 🔎 Diving deeper into the tech stack — not to become an engineer, but to remove blockers, ask sharper questions, and accelerate outcomes.
 📈 Owning the right parts of the product, like evaluation — so leaders are driving ROI, not cheering on endless proofs-of-concept that never make it to users.

And honestly?

The best part was reconnecting AI Career Boost alumni and old friends, and meeting new ones who are doing truly exciting work.

Spark was a reminder that the leaders who lean in now—the ones who embrace the builder mindset—will be the ones who shape the next decade of product innovation.

Huge thanks to the Sidebar team for an energizing, beautifully run event - thanks so much for having me Ha Nguyen, Lexy Franklin and the whole Sidebar team!

 And to everyone I met on Wednesday: you absolutely made my day. 🔥
📸 Photos of brilliant humans below. Harsha Srivatsa Nico Posner Shampa Banerjee, PhD Marily Nika, Ph.D Subha Shetty Vanessa Garber Goldie Chan Evan LaPointe Vikash Rungta Arvita Tripati, MBA Jessica McLaughlin Anja Lee Laura Dunn

I help Product and Business Leaders thrive in AI Leadership - no coding required! Ex-Alexa AI Principal Product Manager | Launched 1st GenAI Answers on Alexa | Top 100 Women of the Future Winner | Reforge Instructor

No alternative text description for this image

In 2019, my director at Amazon Alexa set goals the team had no idea how to accomplish.

It felt wrong. People were nervous.

Then he explained the difference between watermelon goals and dragon fruit goals — and it changed how I think about goal-setting entirely.

Watermelon: Green outside, red inside. Looks good, no real impact.
Dragon fruit: Red outside, green inside. Uncomfortable, but transformative.

Steal the framework and revolutionize how your org thinks about innovation and AI goals 👇

I help Product and Business Leaders thrive in AI Leadership - no coding required! Ex-Alexa AI Principal Product Manager | Launched 1st GenAI Answers on Alexa | Top 100 Women of the Future

It's goal-setting season, and I keep having the same conversation with leaders trying to figure out how to set AI goals and build their AI strategy fo

Open article: Watermelon Goals vs. Dragon Fruit Goals: A Framework for Setting AI Goals That Actually Matter by Polly M Allen • 8 min read

Watermelon Goals vs. Dragon Fruit Goals: A Framework for Setting AI Goals That Actually Matter

In four days, it'll be three years since ChatGPT launched. In five days, it'll be three years since I founded AI Career Boost.

(If I could bottle and sell that market timing, I would!)

I could never have anticipated how world-opening, thrilling, and rewarding this journey would be.
Emerson wrote: "It is one of the most beautiful compensations of this life that you cannot sincerely try to help another without helping yourself."

When I started AI Career Boost, I thought the joy would come from doing meaningful work — helping senior product leaders navigate the transition into AI. And it has. But the deeper joy has been watching the people I work with go on to do meaningful, impactful work themselves. That's the real reward.
To everyone who's been part of this journey — thank you for everything you've brought to mine. I wanted to highlight just one project from our recently-graduated cohort of the AI Career Blueprint below (thanks Kirstin Hartos Maurer!)

If you're a product leader looking to make a big impact using AI, I'd love to have you join us. We're heading into 2025 with a Job Search Systems Sprint next week and freshly revamped content in our AI Momentum membership to help you stay ahead. 

Link in comments.

Happy Thanksgiving 🦃

This Thanksgiving, I'm grateful for a project that's deeply personal—and finally ready to share.

For the past several months, I've been building something called the ALS Care Companion: an AI-powered assistant designed to give ALS families instant access to reliable information about benefits, equipment, daily care, and emotional support—24/7, when they need it most.

Why this matters to me: My mom, Rita, was the primary caregiver for two family members who passed from ALS. She's also organized the annual ALS Minnesota Bike Ride since 2013, raising over $127,000 for ALS research. Watching her navigate the overwhelming maze of information while providing exceptional care taught me something important: every ALS family deserves someone like her in their corner. But not everyone has a Rita. This project is my attempt to change that.

Where we are: The platform is live at alscompanion.org. It's a fully functional AI assistant powered by a curated knowledge base built exclusively from trusted government sources and established organizations—including NIH, Social Security Administration, Medicare.gov, and ClinicalTrials.gov to name a few. No random internet content, only vetted sources. In December, I'm opening it up to a small group of ALS families for beta testing and feedback.

What I've learned: This journey has been a masterclass in applied AI. I've iterated through system prompts, built evaluation frameworks, wrestled with RAG architectures, and learned that the hardest part isn't the technology—it's ensuring every response is accurate, empathetic, and safe for people at their most vulnerable.

Gratitude: I couldn't have gotten here without incredible guidance along the way. Thank you to John Cutter for encouraging me to jump head first into AI up-skilling in the first place (that nudge set this whole journey in motion).  Thank you to Polly M Allen and my AI Product Leader cohort—this is my capstone project for that certification, and the feedback has been invaluable. Thank you also to Aishwarya Naresh Reganti and Kiriti Badam for their course on Building Agentic AI Applications with a Problem-First Approach, which gave me foundational skills I'm directly applying here.  

And most of all, thank you to my mom. You're the inspiration behind every feature.

Want to help? I'm looking for people who want to contribute—whether you have ALS caregiving experience, clinical expertise, AI/ML skills, or just want to support the mission. Reach out at kirstin@alscompanion.org.
🔗 alscompanion.org

In the fight against ALS, information should never be a barrier to care.
#ALS #HealthTech #AI #Caregiving #Thanksgiving #BuildInPublic

Open article: ALS Care Companion | Compassionate AI Support for ALS Families by alscompanion.org

ALS Care Companion | Compassionate AI Support for ALS Families

In a planning meeting last week, an engineer said, “We should use AI for this.”
 You asked the simplest question in the room:
 “Why? What business problem are we actually solving?”
Everyone paused.
 Your CTO said, “That’s a great question.”
Here’s what happened:
 Your beginner question was the most strategic one in the entire discussion.
Technical experts often fall into the capability trap — “we could use AI here.”
 But effective AI leadership starts with:
 • What problem are we solving?
 • Is AI the right tool?
 • Will this add value or just complexity?
Your beginner mindset isn’t a liability.
 It’s your superpower, and it’s exactly what AI leadership requires right now.

👉 Want to develop that instinct into a real advantage?
 Join the AI Momentum Membership waitlist. Link in comments.

#aileadership #leadershipdevelopment #productmanagement #aitransformation #techstrategy

I've noticed something about the people who are actually getting ROI from AI.
They're not smarter. (Sorry folks, but you know it's true!)
They don't have better tools. Or more tools.
They just... started. BEFORE they felt ready.
Meanwhile, the people still "researching" are stuck in the same place they were six months ago, with more bookmarks and less confidence.
The difference isn't capability. It's the story we tell ourselves about what we need before we're allowed to begin.
This week's newsletter is about that story — and how to stop believing it.

Have you noticed how much time we spend preparing to do things instead of actually doing them? With AI tools, it looks like: "Should I use Replit or L

Open article: AI: The Real Reason You Haven't Started Yet by Polly M Allen • 5 min read

AI: The Real Reason You Haven't Started Yet

“AI isn’t replacing teams — it’s removing limits we’ve put up for years.” That’s how Daryl Teo described using AI to give smaller companies capabilities they could never offer before — like full service lines that once required teams of people. Support that runs at all hours, pricing checks across dozens of suppliers, or workflows that used to take hours now shrink into minutes. It's not about job loss, it’s about expanding reach. Watch the clip for the examples that hit hardest.

🎬 Watch the full episode here: https://lnkd.in/geM5343N

#aiproductleadership #futureofwork #aiinnovation #productstrategy

When people worry about “AI replacing jobs,” they're usually missing the real story: most teams aren’t struggling because work is hard; they’re struggling because systems are broken.

In this week’s episode with Sanjay Robson, he makes this point beautifully. His team wasn’t trying to cut roles; they were drowning in outdated processes, compliance reviews, and manual tasks no one had time for. AI didn’t replace people. It replaced the noise so they could finally focus on meaningful work.

What broken system in your org could be an AI win?

🎬 Watch the full episode with Sanjay here: https://lnkd.in/gphg7E4V

#AIProductLeader #ProductManagement #BuildWithAI #AIPodcast #Podcast #TechLeadership

Excited to be speaking to top product leaders in Canada on Thursday, Jan 27th! We'll be discussing 5 important mindset shifts leaders need to adopt to drive impact and ROI when it comes to AI, based on my experience working with thousands of product leaders across North America and my own experience driving innovation and AI adoption at Amazon's Alexa AI. Come ready for an interactive workshop - you'll bring home actionable insights you can start implementing on your team right away!

B2B SaaS product leader working with early stage companies | Driving tech innovation with AI

As a Product Leader do you have questions about AI? Of course you do. We all do. AI is changing how we understand our customers, how we build products, how we manage our work, and how we deliver value.

I am excited about our next Product Leaders Exchange (PLX) event. Polly M Allen will join us to talk about how to drive adoption and impact with AI. I hope you can join us.

📆 On Thursday, November 27 we will be hosting a presentation by Polly Allen focused on how we as product leaders can drive adoption and impact with AI. As the former Principal Product Manager at Amazon’s Alexa AI, Polly Allen led the launch of the first Generative AI answers on Alexa in 2020. In this talk, she’ll explore the five critical mindset shifts that high-impact AI product leaders are making to navigate this new AI landscape.

👉 To see full details about this event and register:

Open article: The AI Mindset for ROI: 5 Shifts to Drive Adoption and Impact · Zoom · Luma by luma.com

The AI Mindset for ROI: 5 Shifts to Drive Adoption and Impact · Zoom · Luma

Excited to be joining my Canadian product folks for great session tomorrow!

Executive coach & advisor | Transformation catalyst | Chief Product Officer

I am excited to be hosting this event with Polly M Allen tomorrow, November 27.     The AI MIndset for ROI: 5 Shifts to Drive Adoption and Impact. 

At Product Leaders Exchange, we are bringing the community of 🇨🇦 Canadian product leaders together to create connections and accelerate growth. 

And to my 🇺🇸 American friends, you are most welcome to join! But I think the priority for tomorrow is 🦃 turkey and 🏡 family and 🙏🏾 gratitude. Enjoy your beautiful day.

#ProductLeadership #AI #Canada

🎉 Blueprint Alumni Spotlight: Meet Courtney Kingsbury— the builder behind Verity

If you’ve ever felt overwhelmed by AI tools (“Which do I choose? Where do I start? Why does every tool promise the moon?”) … this video Courtney created captures that pain perfectly.

And then she does something even better:

She shows what clarity actually looks like.

Her AI Career Boost Blueprint capstone project — Verity — tackles one of the biggest problems I hear from small business owners and product leaders alike: AI is everywhere, but the guidance isn’t. You don’t need 200 tools. You need the right workflow and the right decisions at the right time. With confidence you aren't taking stupid security risks with your data.

This video? 👇 It’s such a sharp demonstration of that!
(It also makes me look way cooler than I am, which I deeply appreciate 😂)

What blows me away is that she built all of this inside our 8-week program — taking a messy, real-world problem and turning it into something elegant and genuinely useful.
💛 Proud coach moment.
 💪 And even prouder to see her stepping confidently into product leadership.

If you’re hiring for a Product Director who actually builds, not just talks about AI…
 👉 Reach out to her. She’s the real deal. 
(Full video link in comments!)

Meet Bob Thompson. Bob has grown his company for the past 30 tears.

He's smart. He's capable.

But right now Bob is terrified.

Joe Sessions explains why small, meaningful AI automations beat big experimental bets. “If you ever find yourself doing repetitive work, that’s your signal. Automate it.” His no-fluff approach to AI adoption reminds us: progress beats perfection every time.

🎬 Watch the full episode with Joe here: https://lnkd.in/g3AKxJ7e

#AIAutomation #AIProductLeader #WorkSmarter #AIForProductManagers #AIBusiness #AIExecution #ProductLeadership

The number of PMs stuck in “which tool should I use?” mode is… a lot. And it’s slowing people down more than any technical skill gap.

Sanjay Robson, said it best: just pick something and start. Replit, Base44, Lovable — none of them matter if you’re not actually building.

The fastest learners in AI are the ones who treat tools like gym equipment. Try one, switch when you outgrow it, keep moving.

Momentum beats perfection every single time.

🎬 Watch the full episode with Sanjay here: https://lnkd.in/gphg7E4V

#AIProductLeader #ProductManagement #BuildWithAI #AIPodcast #Podcast #TechLeadership

What am I thankful for? Being a part of empowering AI-first leaders who build like Courtney Kingsbury. Inspiring work from our AI Career Boost grads!

My husband asked his dev friends to build him an app.

For 15 years.

I did it in under an hour.

I don’t code or program. I’m just a scrappy tinkerer. Junior dev at best.

He wanted alerts for when to open and close the windows based on outside temperature vs his preferred range. Simple idea, but never urgent enough for anyone to actually build.

I used Claude Code. Described what he wanted. Mockup to production before lunch.
15 years of asking. One hour of tinkering.

Here’s the thing: I’ve spent my career translating between engineering and stakeholders. It’s what I’m best at. But I kept hitting a wall. You can only bridge a gap so well when you’ve never stood on the other side.

So I started building. Tinkering. Learning what engineers actually deal with.

Now I get to be the PM and the engineer. And it’s made me better at both.

That’s why I keep doing this. Not to become a developer. To become a better translator.

If you’re looking for a Product Director who actually builds, let’s talk. 

courtneykingsbury.com

Open article: Courtney Kingsbury | Product Director by courtneykingsbury.com

AI won’t solve your workflow gaps if you're still thinking in last year’s playbook. In this week’s episode, Daryl Teo shared how his entire AI shift started with one move: changing the way he approached problems before touching any tools. Instead of jumping into solutions, he asked, “What would this look like if AI were my first teammate?” That simple shift changed everything for him, and it can do the same for any product leader trying to stay ahead. Curious what that looks like in real teams?

🎬 Watch the full episode here: https://lnkd.in/geM5343N

#aiproductleadership #aimindsetshift #aiproductmanagement #techleadership

Vibe coding isn't just empowering a new set of people to be developers. It's enabling them to be a part of building the future.

Need an example? Sarah Hackett 🏳️‍🌈 is building a new AI wedding concierge - and early feedback was that a traditional loveable.dev 'dashboard' view was too overwhelming. This redesign highlights how an art director and creative strategist thinks differently that any traditional 'developer'; instead of being stuck in a paradigm of chatbots vs. web apps, she's thoughtfully looked at how a high end concierge look, behaving and FEEL to the user. Pushing the boundaries and creating new UX patterns - these are some of the changes I'm most excited about!

(and if you have an upcoming wedding, hit Sarah up! She's looking for beta testers!)

Art Director & Creative Strategist | Ex-The Martin Agency, &Walsh + Billie

Vibe coding is super empowering for a non-software engineer but it can take a looooooong time...

This week I created a more conversational homepage.
Pretty happy with it for now. Always more to do!

_________________________________________________________
#buildinpublic #Lovable #NoCode #IndieBuilder #Pinch #UXDesign #VibeCoding

Product and business leaders who want to lead AI at their orgs need to get hands-on. Full stop. It's been an exciting week at AI Career Boost seeing the final capstone projects from our latest cohort of product leaders equipped to lead confidently, by example, in the AI era! Congrats Phillip Fairbrother!!

Product Leader | Driving AI Innovation, Experimentation, and Customer-Centered Growth

Excited to share that I'm a certified AI Product Manager! The AI Product Leader Blueprint from AI Career Boost is a transformative #AI #productmanagement experience, where I gained vital AI skills for real-world applications. Excited for new opportunities in AI #innovation!

I had an opportunity to work with a ton of incredible AI Product Leaders over the last 8 weeks and learn a LOT about what goes into managing Generative AI products. I built prototypes, 'vibe-coded' full products, including multiple chatbots, RAG systems, and agentic ecosystems with multiple AI agents working together to accomplish tasks. I whole heartedly endorse working with Polly M Allen and the folks at AI Career Boost

Feel free to check out some of my work at https://fairbrother.ai/ and let me know what you think! Excited to be part of this new digital frontier. 

Certificate: https://lnkd.in/e2c4M43K

I’m happy to share that I recently obtained a new certification: Certified AI Product Leader from AI Career Boost!  It was a great balance between strategic content and hands-on practice. It's been a solid foundation for navigating practical use cases and understanding the accelerating pace of development in this space.

Unlock Your Early Bird Perks 🔓

Join our newsletter today to unlock exclusive access to course discounts, early bird perks, and other special opportunities. Don't miss out—sign up here: 🔗 https://lnkd.in/g-wzUdTQ

If you’ve been the “go-to person” for 10–15 years, you’re used to competence.
 You’re used to figuring things out quickly.
 You’re used to feeling capable.

So when someone asked you about AI last week and you froze… it felt personal.
 Not knowing things? That’s never been part of your professional identity.

Here’s the truth:
 You’ve had years of practice being good at things, and almost zero practice being bad at things in public.
 But learning AI requires public fumbling, experimentation, and asking questions you’re not used to asking.

Your natural capability, the very thing that built your career, can actually block your ability to learn something completely new.

👉 I unpack exactly why this happens (and how to fix it) in the full video here: https://lnkd.in/gA9Qu_xV

Join the AI Momentum Membership waitlist: https://lnkd.in/gx6p8X8J

#aileadership #productmanagement #leadershipdevelopment #aitransformation #techstrategy

AI Product Builder @ NanoKernel | Generative AI, AI Agents, AIoT, Responsible AI, AI Product Management | Ex-Apple, Accenture, Cognizant, Verizon, AT&T | I help companies build standout Next-Gen AI Solutions

Email:  harsha.srivatsa at connectwithharsha.info | Website: https://www.connectwithharsha.me

I help visionary companies build standout AI Products. 
 
I am a transformative Product and IT Executive, blending innovation with leadership across every role I've embraced. My journey from the technical trenches to the strategic echelons of Product Leadership, Solutions Architecture, and Enterprise Data Strategy has been fueled by an insatiable drive for growth, an unwavering focus on customer success, and a passion for adapting and thriving in diverse organizational landscapes.

From Fortune 50 giants to agile startups, my path has been marked by over 8 groundbreaking product launches and more than 20 transformative project deliveries. At the heart of these achievements lies a deep-seated belief in the power of innovative thinking, strategic execution, and the magic of collaboration across domains and disciplines. My mantra? Value creation, operational excellence, and nurturing talent are the cornerstones of my transformative leadership.

My commitment to thought leadership has led me to author a book on Big Data, secure several patents, and contribute to the knowledge pool with articles and papers featured in renowned journals, blogs, and media channels. Dive into my insights on LinkedIn and Medium at https://harsha-srivatsa.medium.com/

Education is an ongoing journey for me, enriched by formal degrees in Engineering, Math, Computer Science, and Management, alongside continuous learning from prestigious institutions like MIT, Stanford, Kellogg, and IDEOU. This foundation empowers me to lead at the intersection of technology and business, navigating the complexities of AI, IoT, Cloud Platforms, and beyond with ease and insight.

My commitment extends beyond the professional realm. As a High School Educator with Microsoft's TEALS Program, a Master Gardener certified by University of California, a mentor for immigrants through Upwardly Global, and a volunteer with the Coast Guard Auxiliary, I believe in giving back, sharing knowledge, and supporting communities.

I am seeking a Senior IC AI Product Manager role at established AI-focused companies. 

I am a believer in the transformative power of technology, education, and community service. Let’s connect, collaborate, and create impact together.

Harsha Srivatsa

🚀 I’m excited to announce my new book:
 The AI Product Builder’s Troubleshooting & Diagnostic Guide

AI is entering a new era—one where reliability, governance, and production excellence matter far more than demos or prototypes. After  working and talking  with AI teams, founders, and enterprise leaders, I noticed a consistent pattern:
AI doesn’t fail because the model is weak.
AI fails because the product around it isn’t ready.

This book captures the diagnostic frameworks, templates, scorecards, heatmaps, playbooks, and troubleshooting patterns I’ve seen transform AI initiatives from unstable pilots into production-grade systems.

Inside, you’ll find:
🔍 The Seven Bridges Framework for the pilot → production gap
 🧩 The AI Value Stack for maturity diagnostics
 📊 Templates for PRDs, Model Cards, HITL workflows, and EvalOps
 🚦 Release Gate flows for safety, quality, reliability, and FinOps
 🔥 Troubleshooting guides for RAG decay, drift, model volatility, and cost spikes
 📈 Heatmaps, scorecards, and governance cycles for ongoing improvement

If you’re an AI PM, AI engineer, AI Solutions architect, or a Product Leader building AI that must work reliably in the real world—this guide is for you.

👉 If you would like a free e-copy of this book, please fill out this form and I will send it you. 
https://lnkd.in/gTNYrbCd

#AIProductManagement #AIProductBuilder #AIProductDevelopment  #AIDiagnostics #AIReliability #AIGovernance

AI Product Lead @ NanoKernel | Generative AI, AI Agents, AIoT, Responsible AI, AI Product Management | Ex-Apple, Accenture, Cognizant, Verizon, AT&T | I help companies build standout Next-Gen AI Solutions

Thanksgiving 2025…

For me, it’s not about the food, the shopping, or the holiday itself. It’s about the occasion—and the sentiment of pausing to say thank you.
This Thanksgiving, I’m giving thanks for the people who have touched my life, the places that have shaped me, and the possibilities that make life purposeful.

Thank you to two amazing people I met recently—Polly M Allen and Nico Posner —who filled my heart and soul with joy.

Thank you to the beautiful Bay Area that my wife and I have called home for 2+ decades.

Thank you to SFO, my City of Possibilities, where I discovered—and continue to build—my passion for creating AI products.

Thanks for being part of my life journey and for reminding me, in big and small ways, how rich my life becomes when I experience gratitude and share it.

#ThanksgivingGratitude #PeoplePlacesPossibilities #AIPM

Senior AI Product Leader | Generative AI, AI Agents, AIoT, Responsible AI, AI Product Strategy | Ex-Apple, Accenture, Cognizant | I help companies build, debug and launch standout AI products

I had the fabulous opportunity to meet the "Oprah of LinkedIn" - personal branding guru Goldie Chan


Awesome session on personal branding at the Sidebar Spark Summit. 

"Show up without showing off" is an awesome takeaway from the talk by Goldie.

I am continually fascinated by the recent LLM Council project by Andrej Karpathy. I now consider the LLM Council as both a Gen AI Design Pattern and an application building block. The possibilities for building innovative applications seems to be quite a lot. 

The LLM Council pattern embodies the principle that N models > 1 model when properly orchestrated. Instead of relying on a single AI to answer your question—with all its biases, blind spots, and hallucination risks—what if you assembled a "council" of diverse AI models to debate, critique, and synthesize a superior answer?

Today, as I was working on a PRD, I had the Aha! moment to explore the application of LLM Council Pattern to PRD reviews and rapid iteration and improvement. 

We all know this: the real gaps in a PRD show up after sprint planning – during engineering review, in QA, or (worst) in production.

I came up with an application concept: PRD Review Council – an AI “board of PM advisors” powered by the LLM Council pattern that reviews my PRD before it ever reaches sprint planning.

Here’s the idea 👇
Instead of a single AI doing a generic review, my PRD (generated the classical way or via ChatPRD)  goes to a council of AI personas inspired by product thought leaders – think Jackie Bavaro (clarity & strategy), Melissa Perri (outcomes over output), Dan Olsen (PMF & lean experiments), Janna Bastow (roadmaps & process), Claire Vo Vo (AI-native PM & agents). 
Each one reviews the PRD from their own lens and surfaces issues, questions, and suggestions. 

Then a “chairman” persona inspired by Marty Cagan pulls it all together: synthesising the feedback into one coherent review with: 
* An executive summary of readiness
* Critical gaps that block development
* High-leverage improvements to problem, outcomes, scope and risks
* A short list of concrete next steps for the author PM

Under the hood, PRD Review Council uses an LLM Council-style workflow: multiple models/experts in parallel, cross-review of each other’s feedback, and a final synthesis step that optimises for completeness, coherence, and practical actionability – not just clever comments. 

Why this matters:
* Catch most structural gaps before sprint planning
* Reduce back-and-forth PRD revisions with engineering, design and leadership
* Turn every PRD review into a mini coaching session from multiple “schools of PM”
* Build a repeatable, high-quality PRD review ritual even in lean teams 

I’m exploring this both as a real product idea implemented with Google AI Studio and as a reference app for multi-LLM “council” architectures. 

If you’re a PM or product leader who struggles with PRDs that get shredded late in the process, I’d love your take:

👉 Would you trust (and use) an AI PRD Review Council like this? What would you want it to catch every single time?

#ProductManagement #AIProductManagement #LLMCouncil #GenerativeAI #ProdMgmt

We now have a menu of LLM platforms and frontier models. 

OpenAI, Google DeepMind, Anthropic, Perplexity, xAI, Mistral AI, DeepSeek
and others keep shipping new model releases, each with fresh claims about features and performance.

But a practical question remains: which model should I use for which task, purpose, and outcome? How do we look beyond leaderboards and hype, and relate these models to day-to-day, pragmatic work?

I found comparing frontier LLM platforms like ChatGPT 5.1, Claude 4.5, Grok, Perplexity, and Gemini quite difficult because they are complex products, not just models on a chart. I needed a structured way to map their distinct strengths, risks, and task fit so I could confidently route work to the right tool.

So I adapted Andrej Karpathy’s “LLM Council” idea — a multi-model debate plus chairman synthesis — to systematically evaluate each LLM platform.

The result is a practical view, for each platform, of:
* Strengths
* Watch-outs
* Tasks well suited
* Tasks better routed elsewhere

The adapted LLM Council process:
-> Multiple frontier models independently assess a target platform to avoid early anchoring.
-> They anonymously critique and rank each other’s answers to surface errors and nuances.
-> A “Chairman” model, overseen by a human, synthesizes the debate into a consensus verdict.

The Council’s one-sentence report snapshots:
> ChatGPT 5.1 – A top-tier generalist with adaptive reasoning that excels at explaining concepts, agentic workflows, and acting as a conversational copilot.
> Anthropic Claude 4.5 – The “deep thinker” for complex coding, heavy document analysis, and long-horizon reasoning, especially when paired with Artifacts.
> Perplexity – A web-native “answer engine” built for deep research and fact-finding, rather than long-form creative writing or storytelling.
> Grok – Best for real-time social trend analysis and sentiment tracking, with a spicy tone and direct access to X data.
> Google Gemini – A multimodal powerhouse that integrates with Workspace and uses massive context windows to analyze video, large codebases, and Drive files.

Comment “Council” if you’d like the full breakdown and report.

The attached slide deck captures and summarizes the key findings.

Doing this exercise gave me a much clearer mental model of which LLM platform to use for what, and how to route tasks to the best-fit model for the outcomes I care about.

#AI #GenerativeAI #AIProductManagement #FrontierLLMs #AIEvaluation #AISafety #LLMCouncil #ProductManagement

Evaluating LLM Platforms with the LLM Councils

Sharing a personal spirit lifting milestone from ResearchGate. 

Glad to know that people are reading my published paper. Inspired by my mentor Aman Chadha and by his stellar publishing record and portfolio. 

This path to publishing preprints and getting reads / citations is to get into the groove of original ideation, thinking about problems - solutions, and putting high quality written work. This effort with ResearchGate is a start; I aim to work and uplevel myself to be worthy of acceptance into "prestigious" journals - arXiv, IEEE, ACM etc. It is hard but I am motivated to do whatever it takes to get to that level.

🚀 Book Release Announcement - Nov 21 2025! 

I’m excited to share that my book AI Product Builder’s Troubleshooting & Diagnostic Guide is now complete and in final refinement. It will be released on Nov 21, 2025 and sent directly to everyone who signed up. 🙏

If you’d like to receive the e-copy, you can still join the list here:  👉 https://lnkd.in/gz2mVPe6

Earlier announcement: https://lnkd.in/ga5Qd9vy

💡 What makes this book different
To make this a practical, usable manual for real-world AI teams, I tried several first-of-its-kind approaches:
• Each chapter is exactly one page — sharp, concise, and built for busy AI builders

• TL;DR + Bottom Line — know the “why” and “what to do” instantly

• A unified visual synthesis of the entire book

• Multimodal chapter experiences:
  🎥 ~8-min video explainers
  🎧 Dialog-style audio versions
  📘 Detailed text + visuals
 
Designed to support every learning style.

🛠 Why I wrote this
AI Product Builders don’t need more “how to build a RAG app” tutorials.
We need guidance on:
 ✔ debugging failures
 ✔ diagnosing drift
 ✔ preventing cost explosions
 ✔ hardening AI for real production
 ✔ governing responsibly at scale

A mentor summarized it perfectly:
“This isn’t just a book — it’s an intervention… You’ve addressed the ‘Pilot Purgatory’ problem every VP of AI feels right now.”


📘 What this book aspires to be
A living operational manual that unifies Product + Engineering + AI implementation realities.

A playbook to help teams:
 • cross the pilot-to-production gap
 • debug with clarity
 • apply diagnostic hardening
 • evaluate, govern, and scale with discipline

After launch, I’ll also release templates, guides, Miro boards, and walkthrough videos to make the playbook even more actionable.

This work is dedicated to every AI Product Builder striving to build their “Aha!” product — responsibly, reliably, and at scale.

#AIProductManagement #AIProductBuilders #AILifecycle

I am thrilled to announce a collaboration with my friend Sevanne Calle on upleveling ourselves in Physical AI! 

To start off, we have created a newsletter titled "Physical AI Dispatch" 

Issue #1 is now live: “Why Physical AI Matters Now.”
In this first issue, we break down:
* What I mean by Physical AI (beyond the buzzwords)
* How it will reshape work, industries, and everyday environments
* Why now is the time for AI Product builders, AI leaders, and AI practitioners to upskill and get ready

If you’re curious about the intersection of AI + Robotics + AIoT + Edge Infrastructure, or you’re an AI builder, product leader, engineer, or operator who wants to ride the Physical AI wave,  I’d love for you to follow along.

🔔 Subscribe to Physical AI Dispatch to get future issues, deep dives, and practical frameworks straight in your inbox.
[https://lnkd.in/gubSgEYB]

We’re entering a moment where AI is no longer staying in the digital world.
It’s stepping into the real world — into devices that sense the environment, robots that move with purpose, machines that can help us in hospitals, farms, factories, and even in our homes. This shift can change industries, careers, and lives.

But right now, most people only understand “software AI”: LLMs, chatbots, copilots.

Physical AI is the next wave — and most people are not prepared for it.

Over the past months, I’ve become convinced that Physical AI — AI embedded in robots, machines, vehicles, and devices that can sense, decide, and act in the real world — will define the next decade of innovation. From logistics and manufacturing to healthcare, energy, agriculture, and smart cities, we’re already seeing early signs: autonomous robots, intelligent fleets, warehouse automation, hospital logistics, and more.

I want to prepare myself now for that shift — to think deeply about:
* How we design Physical AI systems that are helpful rather than harmful
* How we blend AI, robotics, AIoT, and edge infrastructure responsibly
* How Product, Engineering, Operations, and Policy need to work together to make Physical AI safe, reliable, and truly human-centered

👉 So please join us in the journey of this exciting new world of possibilities and potential from Physical AI. 

#PhysicalAI #Robotics #AIoT #AIProduct #FutureOfAI

I have been using the new Slide Deck generation feature in Google NotebookLM and its pretty awesome - provided you give it some clear and good instructions. 

Here is a sample slide deck generated for Chapter 2 - The Pilot-to-Production Bridge in my book The  AI Product Builders Troubleshooting Guide.

The AI Product Builder's Guide - Chapter 2 Slide Deck

🚀 It’s here! I’m excited to officially release my new book:
 “AI Product Builder’s Troubleshooting & Diagnostic Guide”

Today, I’m releasing Version 1 - the first edition of what I hope becomes a living, evolving manual for AI Product Builders everywhere.

🔗 Download / Access the book:
Formatted PDF (recommended for visuals):
https://lnkd.in/gQAqvWNY

Living Google Doc (always up-to-date):
https://lnkd.in/gguqQTEH

📝 Suggest updates / fixes / improvements:
 👉 Feedback Sheet: https://lnkd.in/g7x622X8

💡 Why I wrote this
AI Products don’t fail at the model stage—they fail at the system stage. Drift, bad data, fragile pipelines, unclear governance, cost explosions, missing guardrails — these are all diagnosable and fixable patterns.

This book is the operational guide I wish my AI team(s) had:
On How to debug, diagnose, harden, evaluate, govern, and scale AI systems that must survive real-world conditions.

🚀 What makes this book unique: 
I designed this book with several first-of-its-kind features:
✨ Each chapter is exactly one page
 Clear. Sharp. Built for busy AI Builders.

✨ TL;DR + Bottom Line on every page
 No fluff. Immediate clarity.

✨ A unified visual synthesis in each chapter. 
Each chapter content synthesized into one artifact.

✨ Integrated multimodal learning
 For every chapter, you can choose to:
 🎥 Watch an ~8-min explainer video
 🎧 Listen to a dialog-style audio version
 📘 Read the text + visuals

✨ Living manual — continuously updated
 The Google Doc will remain the source of truth.
 I will track updates in a public change log and release refreshed versions frequently.

🛠 How you can use the book
Use it as your:
 • Production hardening checklist
 • Pilot-to-Production playbook
 • Evaluation & guardrail reference
 • Incident response guide
 • Governance + FinOps alignment tool
 • Workshop toolkit for AI maturity

My goal: help teams escape “Pilot Purgatory” and build reliable, safe, cost-aware, trustworthy AI systems.

A mentor who read this book earlier, captured it well:
“This book isn’t just guidance — it’s an intervention. It tackles the exact pain point every VP of AI is wrestling with right now.”

🌱 Your feedback matters
This is Version 1 — the beginning.
 Please use the feedback sheet to propose:
 • Fixes
 • Improvements
 • Clarifications
 • New chapter ideas
 • Real-world cases
I’ll review every submission and integrate improvements continuously.

🙏 Final note
I’d be grateful if you could:
 💬 Share this post
 📤 Forward the book
 🏷️ Mention it to teams who need it
 📚 Use it in your org’s AI processes

Thank you for your support — this book is dedicated to every AI Product Builder striving to build their “Aha!” product responsibly and at scale.

#AIProductManagement #AIProductBuilders #AILifecycle

What happens when AI’s hunger for power, water, and land collides with the limits of our planet – and the patience of our communities?

We’re already seeing the early signs: grid constraints, water stress, local moratoriums on new data centers, and growing scrutiny from regulators and citizens. 
At the same time, we’re racing to build an AI++ world – where AI is deeply intertwined with IoT, edge, robotics, and cyber-physical systems.

To make that future possible, we don’t just need more  power or more AI infrastructure.

We need to have a clear vision for the Future of Data Centers, And We need Resource-Responsible AI so that we invest and build in that AI infrastructure rationally. 

I’ve pulled together my research, thoughts, and field notes into a publication: 
📘 “The Future of AI Data Centers – Creating Resource-Responsible AI for an AI++ World”

Links to the booklet and slide deck in the comments. 

In this publication I explore:
* How AI data centers differ fundamentally from traditional cloud infrastructure
* Why power, water, and cooling are becoming design constraints – not afterthoughts
* A set of principles and scorecards for building Resource-Responsible AI across the model lifecycle
* Patterns for AI-native architectures spanning edge, micro data centers, and hyperscale
* The role of regulation, risk, and “social license to operate”
* Future scenarios and a practical roadmap for teams who want to act, not just admire the problem

If this topic resonates with you – whether you’re in AI/ML, cloud, data centers, sustainability, or policy – drop a comment or DM  🙌

#AIDatacenters #ResourceResponsibleAI #SustainableAI #AIInfrastructure #AIoT #EdgeComputing #AIArchitecture #AIProductLeadership

An update to my earlier post announcing the upcoming release of my book titled "AI Product Builder's Troubleshooting Guide" 
https://lnkd.in/ga5Qd9vy

Today I want to introduce a key concept in the book - Seven Bridges. 
I am so much fascinated by the term. 
Seven Bridges of Konigsberg is a classical mathematics / computer science problem. 
Seven Bridges Road is a beautiful song by The Eagles. 

In AI Product Building, The Seven Bridges diagram maps the chasm and the critical transition gaps between pilot success and production scale. It connotes the difference whether an AI project is destined to Pilot purgatory or whether it makes it a successful Production GTM. It is a diagnostic model identifying the precise failure points where AI projects fracture during scale-up. Each bridge—Data Readiness, Model Robustness, Infrastructure Scalability, Operational Maturity, Governance Readiness, Organizational Alignment, and Business Value—represents a critical handoff where assumptions break, ownership blurs, and risk compounds. Looking at an AI Project from the Seven Bridges lens can help cross the chasm to a successful AI project. 

For this book, my content creation approach has been: 
- Generate a text document with concepts, principles, visual artifacts, practices etc. 
- For each chapter, I have created a companion video explainer to amplify and explain the contents in 8 mins or less
- And an audio overview with two hosts discussing and debating the insights and nuances. 

In short, a multimodal approach to convey what I want to share. 

As an example, here is the content for Chapter 1: 
Text: https://lnkd.in/g6hdBiWn
Video Explainer: https://lnkd.in/gaEhUa2u
Audio overview: https://lnkd.in/gYXEt-j5 

I hope you like to content creation approach and formats. Let me know in comments. 

#AIProductManagement #AIProductBuilder #AIProductDevelopment

Thrilled to share that my new research paper is now available on ResearchGate: “Agentic Swarm Intelligence Applied to AIoT Agent Coordination: A Domain-Agnostic Framework for Multi-Agent Coordination, Task Allocation, and Human-AIoT Workflow Delineation.”

This work brings together Swarm Intelligence, multi-agent systems, and AIoT to answer a key question: 
How do we coordinate AIoT agents while keeping humans safely and meaningfully in the loop? 

The paper introduces the AIoT Swarm Coordination Map (ASCM), an extended RACI-A responsibility model, and a Human–AIoT Workflow Canvas that practitioners can apply across manufacturing, energy, smart cities, logistics, and more.

If you’re interested in and exploring Multi-agent systems, AIoT, edge intelligence, or Human-AI teaming, I’d really value your read, critique, and suggestions for future directions.


#AIoT #AgenticAI #SwarmIntelligence #MultiAgentSystems #EdgeComputing #HumanInTheLoop #AIArchitecture #EdgeAI

Going From Vibe Synthetic Multimodal Data Creator to a Vibe  Synthetic Reality Creator! 

Today I got access to https://lnkd.in/gQvPJ5Kz World Labs
World Labs (the startup founded by Dr Fe-Fei Li https://lnkd.in/gMiebVzw Fei-Fei Li
Marble 3D World creation platform. And I am blown away by the possibilities. 

If I can think / imagine a scenario, I can now create  Synthetic Reality Worlds. The possibilities for AI Products with Visual Intelligence, Robotics training, and simulation-first design feel enormous.

With Marble + Veo3, it’s becoming possible to go beyond  synthetic multimodal images and videos… and instead construct entire 3D, physics-aware simulation reality worlds. 

This has so much potential for AIoT systems, robotics, and digital twins.

This is a game changer. This has so much value for my work. 

Imagine designing scenarios that are hard, dangerous, or impossible to capture in the real world:
 🔥 fire and explosion events
 🪖 battlefield and high-risk environments
 🤖 humanoid robot training scenes
 🏥 hospital digital twins
 🌆 smart-city anomaly simulations

Instead of creating the data, we create the reality with the data! 

My first experiment was to use WorldLabs Marble to generate a 3D panorama of a battlefield scenario as it would appear for an autonomous drone as it surveys the battlefield scene for sitrep and damage assessment. I then used to panorama snapshots to create a realistic battlefield scenario video. 

Early results are promising. See the generated video attached and the panorma screenshots in the comments. 

If you’re building in digital twins, simulation, robotics, or AIoT, keep an eye on this space.

Synthetic Reality is coming fast.

#AI #SyntheticData #Simulation #AIProductManagement #AIoT #Robotics #DigitalTwin #AgenticAI #Marble #Veo3

A TGIF moment! Thankful to meeting and collaborating with awesome people like Ronny Ashar .

It is an awesome feeling for me when you can have meaningful connects even though we are thousands of miles apart and we can find something that we are both passionate about. 

Ronny and I have had deep and thoughtful discussions about Sustainable AI recently. Which led me to the formulation of the concept of Resource Responsible AI. 

I am really proud of Ronny for getting the AI Ethics practioner certification from Stanford. Looking forward to continuing this awesomeness in 2026.

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