Mayank Yadav

LLMs aren’t good enough yet for the general public to use it for shopping… but they’re getting dangerously close. When AI cracks commerce, traffic behavior will change faster than most businesses are ready for.👇

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I wrote about how product managers should deliberately decide which features should be built to an A grade and which ones should be built to a B or even only a C grade. Making the resource tradeoffs to optimize business outcomes is a core job of product management, and building every capability to an A grade is a poor use of scarce resources. https://lnkd.in/gTXBfNYE

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I stopped by the NYC Founders Club meetup last night to chat with AI founders about monetization. Lots of folks wanted to understand what is the "winning" strategy to balance acquisition, growth, and healthy margins. Stripe interviewed 2k businesses and we are sharing out the results today. Our data shows that AI companies adopt hybrid pricing models (subscription plus usage) and change their prices ~2x more frequently than others. For the full set of trends, check out our report: https://lnkd.in/eReqAfkG

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Excited to share my conversation with Marc Baselga and Ben Erez on the Supra Insider podcast. We went deep on one of the biggest shifts happening in product leadership right now: why many experienced PMs and product execs are returning to individual contributor (IC) roles in the AI era, and why that’s not a step back, but a strategic leap forward. Other topics we discussed: -- Why the leverage equation has changed—and how managing AI agents now rivals managing people -- The critical importance of hands-on credibility in AI-native companies -- Why great PMs in the future will blend product, design, analytics, and frontend execution -- What it takes to deliver real customer outcomes (not just launch features) -- How to evaluate breakout companies—and what founders often get wrong when hiring product leaders I also shared my thoughts on: -- Joining the right company: mission, trajectory, talent density, and founder courage -- Crushing it as a “super IC”: the power of speed, ownership, and infectious energy -- Transitioning from product leader to GM or founder with the right mindset If you’re navigating your next chapter in product (or just trying to stay sharp in the AI-native world), I hope you’ll find this useful. Episode links: Spotify: https://lnkd.in/gK48PFWK Apple: https://lnkd.in/gmT265BY YouTube: https://lnkd.in/gtr4RAKd Substack: https://lnkd.in/gM38FSWc

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I was CPO at Blend before their $4 billion IPO. We rejected the “forward deployed engineer” Palantir model that everyone is copying now. Here’s why: Blend could have followed the forward-deployed engineer approach. Both our CEO and CTO were early Palantir. They'd seen it work. Instead, we built a SaaS product with core components. Move fast, iterate, use data to learn. Not custom code for every client. That Palantir model is having a resurgence. Now Sierra, Decagon, and others are hiring forward-deployed engineers. But it’s not the right approach for every company. It’s fundamentally the wrong answer for Assembled’s customers. Here's what we understand about support teams and why we’re not going the forward deployed route: Customer Support teams are used to getting no resources and no support. On the surface, you'd think they'd be excited about engineers building custom solutions. "Finally, someone's offering us developers!" The reality is support teams are terrified of getting help they can't afford to keep. Support teams are wary because they know the math. They don't have budget for expensive, scarce resources. At some point the shoe drops. The engineers disappear when priorities shift. And custom solutions break. Support is left holding the bag with something they can't maintain. They're resource-starved by design. The idea of a dependency on resources they can't control is terrifying. So instead, the goal should be to give support teams the ability to manage, change, and solve their own problems. Not dependencies on engineers they can't keep. Smart, competent people who teach them to do it themselves. Palantir wasn't even a product company for years. They were a custom development shop with reusable components. Show up, build something bespoke, maybe extract learnings. That's not scalable for any but the largest support teams who need sustainability. Forward-deployed engineers are the new shiny object. I wasn’t a fan of it at Blend. And I’m not a fan today either. What I see in the customer support space is that teams need empowerment, not dependency. I want the teams we work with to be able to say: "I love that you’re partnering with me. And I love that I can do this myself too." That's the difference between building a product and building a consulting practice.

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Had such a great chat with Vivien Lin! She brought so much wisdom and vivid insights to the conversation: 1. We're trying to work with our users, when they make money we make money. We try not to stand on the opposite. 2. From the start we decided to exit China market. We never touched US users. It's all because we are quite self-disciplined and self-regulated. 3. We consider whether this product or whether a feature can truly solve the problem for the user. 4. From 2018, 2019 is always put our top priority to think about how we bring more new user to the crypto industry. It's not like competing the existing user with other exchange. 5. Ideally, the final product should be you don't need to worry about what functions sit in what page. You just go to the AI or the AI assistant to tell him what you want. 6. The difference in the roadmap between crypto and traditional finance is rooted in how the industry got originated. For traditional finance, banking and payment that's naturally where finance comes from than lending than trading. At crypto, the very first need where the industry originated is mining. 7. I think, we are still in a very precious time window especially for exchange it to become a sort of mega platform in near future. 8. My suggestion is always be open minded - open minded to the technology, business model and even all those new ideas. 9. My suggestion to everyone, even if you are a legal, you are a product manager or you are in the operation team, is to study programming, learn how to code. 10. The slides always tell the good stories but you need to get down to the details to understand what's happening. 11. Before all those regulations put into place there has to be someone familiar with how possible the regulation is going to be implemented in the future and we can get prepared beforehand. 12. Without one major hack exchange cannot be a mature exchange. 13. If I know what they are doing I can read their code, I can get a very direct sense about the quality of the project instead of really looking at the powerpoint. Watch the full session here: https://lnkd.in/dGhbXdwr BingX

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We'll learn a lot more about today's outages over the next couple of days as we start to get post mortems from the different platforms that were impacted. But it was interesting to see that traffic on our PNIs to GCP were not impacted uniformly with big traffic drops in LAX, ORD, SEA, SJC and DFW, but increases in traffic in FRA and AMS as customer services failed over. This highlights the important of proper DR planning with a minimum of multi-region and ideally multi-cloud.

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Very soon, Commerce merchants on any e-commerce platform (e.g. BigCommerce) will be able to drive discovery and sell directly across Google's surfaces like Google AI Mode and the Gemini app. Agentic commerce is here and Commerce is perfectly positioned to help merchants sell more on Google's Agentic channels. For years, Feedonomics has been sending quality catalog data to Google Merchant Center, which is a core enabler of UCP. BigCommerce has been at the table with Google providing feedback on the UCP design, sharing the commerce expertise to help drive better discovery and conversion across Google's surfaces. You can see Commerce is becoming the commerce later for the agent economy. Thank you to Samantha Kahn, Aatish Motwani and the Product, Engineering and Marketing teams at Google Shopping for the collaboration and partnership. Commerce is changing. Sharon Gee Tom Arbesser-Rastburg David Chin David Aland Luke Eller Patrick Edelman Kushal Khatri Adam W. Nick Kostohryz Michaela Weber Matt Crawford Keith Karlick

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One of the most impactful product roles out there right now. If you've ever wanted to shape the infrastructure behind how millions of people get their groceries, this is it.

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Oh🚀 Big news: Beekeeper is merging with LumApps to launch the first all-in-one, AI-powered Employee Hub, connecting EVERY employee, whether they’re at a desk or on the frontline. I can't believe what a journey these past 9 years have been - it has truly been a privilege to enjoy every single day working with our team! Along the way we grew Beekeeper from a small Swiss startup to an international scale-up, growing our team 10x while 100x-ing our revenue. I so proud of what we have been able to deliver and the great work our product and engineering teams have done. It has been an honour to lead our Engineering, DevOps and Support teams from our Series-B to our merge with LumApps. Together, we’ll give 7 million users in 2,000+ companies a single home for comms, knowledge, and day-to-day tools, from HQ updates to shift swaps, right on their phones. A huge thanks to Cristian G., Flavio Pfaffhauser, Andreas Slotosch and Daniel Sztutwojner who kicked-off this journey 12 years ago, creating an amazing place to work every single day. I’m thrilled to be part of this next step working alongside Elie Mélois, Sébastien Ricard, Sébastien BOULLE, Kees de Vos, Filip Wieladek, Omar Moling, Daphne van den Brule and our amazing product & engineering teams to create a new European software powerhouse. Dive into the full story ➡️ https://lnkd.in/dGC88MKP #FrontlineSuccess #EmployeeSuccess #AI #FutureOfWork #Beekeeper #LumApps #WorkplaceTransformation

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Some recently launched, cool Gen AI use cases powered by Michelangelo :) ✨ AI-powered insights that summarize reviews, auto-generate menu descriptions, and enhance food photos. #AI #MLplatform #Ubereats

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