I build AI products from zero to one, and I teach others how to do the same.Over 12+ years, I've taken AI/ML products from proof-of-concept to launch at Amazon, Nike, T-Mobile, and Disney. The work I love most is early-stage: validating ideas, getting executive greenlight, and shipping MVPs that prove value before scaling. At Nike, that approach drove a $100M annual reduction in product returns.I also teach what I build. I co-created and lead the AI Product Management Certificate at the University of Washington, where experienced PMs ship real GenAI products complete with evaluation plans and GTM strategies. Previously, I trained 4 cohorts at Product School.What I bring: the ability to translate messy AI capabilities into clear product value, align technical and business stakeholders, and move fast without breaking trust. I write about AI PM craft at aipmguru.substack.com.I'm currently exploring opportunities to lead 0→1 AI product work at companies solving meaningful problems. I'm especially energized by AI in healthcare and education, though I'm open to any domain where the product can genuinely improve lives. 

Shaili Guru

Hemant Bothra and I are running an in-person workshop where we're going to build something together - in the same room, like the old days.

3 hours. You'll leave with a working tool.

No coding experience needed (you read that right). We'll use Cursor (an AI coding assistant) and walk through everything step by step. If you've ever been curious about "vibe coding" but didn't know where to start, this is it.

Good fit if you're a PM who wants to actually build things, or just someone who learns better by doing than watching.

AI/ML Product Leader | Driving Innovation with AI | PM Mentor and Advisor

Open article: Build Your First AI Tool: ChatGPT Output Cleaner Workshop · Luma by luma.com

Build Your First AI Tool: ChatGPT Output Cleaner Workshop · Luma

Product Manager, Technical Product Manager, and Technical Program Manager with 12+ years building AI/ML solutions that optimize supply chain operations and drive digital commerce innovation. Proven track record delivering $100M+ business impact through predictive analytics, cross-functional leadership, and data-driven product strategy.

🚀 CORE EXPERTISE:
- AI/ML Product Development: Predictive models, machine learning platforms, automation systems
- Supply Chain Innovation: Inventory optimization, logistics analytics, transportation systems
- Technical Program Management: Cross-functional team leadership, engineering roadmaps, system architecture
- Digital Commerce: E-commerce platforms, fulfillment optimization, marketplace operations

💡 PROVEN BUSINESS IMPACT:
- $19M annual cost reduction through predictive AI optimization
- $100M+ revenue generation across AI/ML product portfolio  
- 300K+ containers optimized via supply chain visibility platforms
- 6-day delivery accuracy improvement generating $4.3M revenue
- Led 20+ cross-functional teams spanning engineering, data science, UX, analytics

🔧 TECHNICAL STACK:
Programming: SQL, Python | Cloud: AWS, Databricks, Apache Spark | Analytics: Tableau, PowerBI, Looker | AI/ML: Predictive Modeling, Neural Networks, Decision Trees | Supply Chain Tech: Digital Twins, Simulation Modeling, Transportation Analytics

🌟 LEADERSHIP PHILOSOPHY:
I transform complex technical capabilities into products that solve real business problems. With dual degrees (MBA + MS Engineering) and hands-on experience scaling teams, I bridge the gap between technical innovation and commercial success.

📍 AVAILABILITY: Immediate start available for Product Manager, Technical Product Manager, Technical Program Manager, or Supply Chain Director roles. Open to remote, hybrid, or onsite opportunities.

Seeking organizations where I can leverage deep AI/ML and supply chain expertise to drive product innovation, optimize operations, and deliver measurable business outcomes.

Harsimran Singh

We're all fighting battles that don't show up on a resume.

Three months ago, I was staring at my ceiling at 2 AM, replaying every personal and career mistake I'd made—wondering where I went wrong.

Here's what I've learned: the most valuable currency isn't connections—it's showing up for people.

I used to think "helping" meant big gestures. Writing recommendations. Making introductions to executives.
Then I started noticing something: the people who changed my trajectory weren't the ones with the biggest titles—they were the ones who picked up the phone.

The former colleague who met me for coffee when I was struggling.
  - The LinkedIn connection who jumped on a call with zero agenda.
  - The friend who checked in when I went quiet.
  - They didn't solve my problems. They just showed up. And that made all the difference.

Now I'm making a different choice:

I'm done waiting until I'm "successful enough" to give back. I'm done assuming people don't need help because they seem fine on LinkedIn.

Because right now, someone is:
    - Questioning their career path at midnight
    - Balancing impossible work demands with family responsibilities
    - Wondering if they're good enough

If that's you—reach out.

Need someone to review your resume? A practice interview? Just need to vent for 15 minutes? I'm here.
Not because I have all the answers. But because people showed up for me when I needed it most.

Comment "here" if you've ever been helped by someone who just listened. Let's normalize asking for support.

#Community #MentalHealth #PayItForward #Leadership #JobSearch #Networking #CareerAdvice  #WorkLifeBalance #Authenticity #CareerGrowth

I spent last weekend watching my family and friends shop through ChatGPT instead of opening Amazon directly.
That's when it hit me, we're not preparing for a future shift. We're already in it.
Target just launched full shopping inside ChatGPT. Walmart partnered with OpenAI for "agentic commerce." Amazon reports customers using their AI assistant Rufus are 60%+ more likely to convert.

The data backs up what I'm seeing around me:
 • 25% of Americans (18-39) now use AI to shop
 • AI-driven retail traffic: up 4,700% year-over-year

While the biggest players race to own this channel, most companies haven't started optimizing for visibility.

The New Reality

 • Target: Full shopping experience inside ChatGPT (multi-item purchases, fresh food, multiple fulfillment options)
 • Walmart: "Instant Checkout" through conversational AI 
 • Amazon: "Buy for Me" now shops 500K+ products on your behalf 

The 5 Critical Demand Areas
1. Capability-to-Cost Mathematics Intelligence per dollar doubles every 4-5 months. The margin opportunity shifts to smarter routing—delivering higher quality at lower cost.
2. Distribution or Death (AEO/GEO) AI agents = fastest-growing commerce channel. Content without structured data and APIs will become invisible.
3. End-to-End Fulfillment & Last-Mile When AI agents compare options, delivery speed and reliability are weighted heavily. Supply chain visibility and last-mile orchestration must be AI-accessible.
4. Identity, Consent & Disclosure Competing protocols (Visa's Trusted Agent vs OpenAI's open integration). Critical question: Who's liable for fraudulent agent purchases?
5. Infrastructure Constraints Goldman Sachs: ~175% growth in data center power demands by 2030. Energy constraints could throttle AI growth—or create opportunities.

The Bottom Line:
Leading supply chain transformation at Nike, building autonomous vehicle systems at Daimler Trucks, and scaling operations at one of the fastest-growing startups across AI, digital transformation, and e-commerce taught me: infrastructure changes compound exponentially, and fulfillment excellence is what separates winners from losers when the playing field shifts.

Walmart CEO Doug McMillon: "For many years now, eCommerce shopping experiences have consisted of a search bar and a long list of item responses. That is about to change." walmart

The window is closing fast. Retailers waiting for 2026 budgets or treating this as next year's problem will find their competitors have already captured the AI commerce channel.

What's your organization doing to prepare for agentic commerce? 

#RetailTech #AICommerce #ProductStrategy #SupplyChain
#AIStrategy #AgenticCommerce #AEO #LLMs #DigitalTransformation #FutureofShopping

Now that the crazy Black Friday & Cyber Monday shopping spree is out of the way, I've been thinking about something bigger.

I've been digging into how companies are actually solving the agentic commerce challenge - and there's a pattern emerging that changes everything.
As a product leader, I'm watching these ecosystem shifts closely because the next generation of customer experiences won't be built by single companies - they'll be built by strategic partnerships that no consumer ever sees but everyone benefits from.

Look at the financial reality of why this is happening.

The Ecosystem Taking Shape:
Retailers + AI Platforms: 
        - Walmart + OpenAI: Instant Checkout agentic commerce
        - Target: Full shopping inside ChatGPT
        - Google Gemini: Agentic checkout, 50B product listings
        - Meta AI: 1B+ monthly users, 29% higher ROAS
        - Amazon Rufus: 60%+ conversion lift
Autonomous Delivery Layer: 
        - Waymo, Tesla, Cruise integrating with retail partners. 
        - Amazon + Walmart testing shared delivery corridors (3 metros)
Infrastructure: 
         - Microsoft + Constellation: Nuclear-powered data centers, 
         - Google: $5B renewable data center investment
         - Meta: Advanced AI infrastructure expansion

How Ecosystems Win (The 5 Critical Areas):
1. Capability-to-Cost: Shared data centers + smart model routing = 60-80% cost reduction
2. Distribution: One API across ChatGPT, Gemini, Claude, Meta AI = instant visibility
3. Fulfillment: Waymo/Tesla/Cruise fleets = 15-30 min delivery standard
Identity: Single protocol = authenticate once, shop everywhere
4. Infrastructure: Joint nuclear data centers = 10× capacity vs solo build

The Financial Reality:
Building alone: $3.1-7B investment, 5-10× ROI by 2030 Ecosystem approach: $400-700M investment, 12-18× ROI by 2030

The Bottom Line:
Leading supply chain transformation at Nike, building autonomous vehicle systems at Daimler Trucks, and scaling AI-powered e-commerce at Crumbl taught me: market share goes to whoever delivers the experience consumers prefer, not who builds the most infrastructure.
 
What I'm tracking as a product leader:
The retailers joining these ecosystems in Q1 2026 will deliver experiences that shift purchasing habits permanently. I'm watching how they solve cross-platform integration, autonomous fleet coordination, and real-time inventory visibility at scale.
By 2028, consumers won't choose retailers—they'll ask AI assistants who default to ecosystem members delivering in 15-30 minutes with 95% reliability.
 
That's not a technology shift. That's a market share shift.
Is your organization building toward this consumer experience, or optimizing last generation's shopping journey?
#RetailTech #AICommerce #SupplyChain #DigitalTransformation #AutonomousDelivery #ProductManagement #ArtificialIntelligence #Ecommerce #ProductLeadership #FutureOfRetail #LastMileDelivery #AgenticAI #TechInnovation #LogisticsTech #ProductStrategy

Waymo launching non-autonomous ride service in new cities might look like a step backward.

From a supply chain, logistics and infrastructure view? It’s actually a masterclass in “manual-first, automate-when-it-scale” execution.

Here’s why I think matters right now:

1. This is a scaling supply chain challenge, not just an AI triumph.
Robotaxis don’t scale like software—they scale like any network of physical assets: local ops, charging depots, depot supply chains, skilled service teams, and city-by-city compliance. By starting with human drivers, Waymo seeds market demand, gathers granular trip data, and learns urban logistics in real time—so AV fleets and infrastructure land exactly where the economics make sense.

2. Waymo’s California-first isn’t by accident, it’s an accelerator.
Regulatory stress test: If you’re cleared to run 24/7 freeway rides and airports in CA, every other market is easier.
Demand density: San Francisco + LA mean max utilization—airports, nightlife, high friction and high expectation.
Ultimate “real-world” lab: From unpredictable traffic to the infamous curb wars, if an AV can thrive here, it can fly in any city. This learning advantage compounds as Waymo moves national.

3. Customer experience is where the ops rubber hits the road.
These network effects ripple outward:
Broader coverage, fewer “no AV available” moments
Freeway driving unlocks faster, longer, cross-metro rides
Greater consistency, less “is tonight’s driver good… or not?”
Higher trust: CA’s regulatory bar means every ride must deliver
Frictionless airport and urban pickups—fundamental after dark or when you’re late

4. Question comes Why now? Because the next AV land grab is already unfolding.
By pre-staging in 2025 the hiring, mapping, building local partnerships - Waymo is setting the rails for a multi-city, full-autonomy wave in 2026. The interim manual layer is the world’s quickest “market tuning fork” like de-risking rollout, building loyalty, and funding the march to fully autonomous networks.

To anyone who has scaled automation in First-mile, warehouses, DCs, or last-mile: this is the playbook—
     - Start manual to stabilize demand, ops, and trust
     - Layer-in autonomy after the network is humming
     - Reap margins and network effects as machines scale

A question for the experts:

Will “hybrid” human + AV fleets become the norm in mobility, or is this just a fleeting bridge to the age of true autonomy?

#SupplyChain #Logistics #Waymo #AutonomousVehicles #CustomerExperience #TechStrategy #FutureOfMobility #AI

For now, human drivers will operate the vehicles, but the company hopes to roll out autonomous service in all three cities as soon as next year.

Waymo adds non-autonomous ride service in trio of US cities

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