
12 segments available
What does it mean to “trade margin for moat,” in the AI era – and how are Fortune 500s actually adopting AI today? In this episode, a16z partner Joe Schmidt sits down with Ben Scharfstein, Head of Product, Enterprise Applications at Scale AI, to explore the nuances of forward-deployed engineering and its impact on enterprise AI adoption. They discuss why enterprise AI adoption lagged behind consumer excitement, the roles of integration and UX, and the strategic importance of customization. Key insights include the balance between vertical AI products and custom enterprise solutions, the evolving nature of software services vs. agent-enabled solutions, and the critical role of saying 'no' in AI go-to-market strategies. Timestamps: 00:00 Introduction to Enterprise Customization 00:23 Meet Ben Scharfstein 00:33 Scale's Application Business 01:37 Enterprise AI Adoption 02:27 Challenges and Opportunities in AI Services 14:41 Forward Deployed Engineers 22:04 Balancing Custom Solutions and Internal Teams 25:05 Targeting SMB and Mid-Market Customers 27:59 Building Effective Forward Deployed Teams 32:38 Navigating Industry Expertise and Customer Relations 36:59 Trading Margin for Moat: A Strategic Approach 44:57 The Future of AI and Forward Deployed Teams Resources: Find Ben on X: https://x.com/benscharfstein Find Joe on X: https://x.com/joeschmidtiv Read Joe’s article ‘Trading Margin for Moat’: https://a16z.com/services-led-growth Stay Updated: Find a16z on Twitter: https://twitter.com/a16z Find a16z on LinkedIn: https://www.linkedin.com/company/a16z Subscribe on your favorite podcast app: https://a16z.simplecast.com/ Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.
"The feature set for every company is different and usually that is developed over time and then the next time you see a customer that has it, it's just developed in the platform. And what we're seeing..."
"Ben Shariffstein, thanks for joining the pod. Ben is the head of product for the enterprise application business at scale. So excited to have you on, man. Thanks for joining. >> Yeah, thanks for havin..."
">> It's gonna be super fun. The applications product at scale is one of the best kept secrets in Silic Valley. Maybe just dive a little bit into like what you guys are doing and a little bit behind th..."
"have? Are you going in and doing different types of work? Like what does this actually mean? this enterprise product in the end of the day what we're trying to solve is their problems and the world is..."
">> It's interesting. It's almost as if like these big enterprises, they're saying, hey, like we want AI, like we don't ex know exactly where to turn. And so you guys kind of go out there and you basic..."
">> you know this kind of all leads to this idea of like the for deployed engineer and like what is that and how it's become like you know we just wrote this article about how it's the hottest you know..."
"What's interesting to think about like as you talk through all those decisions you're making is you know trying to find like the right the Goldilock zone of like the right size customer. Um, right. An..."
"extending that though down market like to you know the non-scales of the world right cuz most startups like they're not going out there and selling to the companies that are public today right they're..."
">> Yeah. Do you think the forward deployed team remains inside of these businesses as they scale? Like you know if you just think about the historical example of like Salesforce or service now like a ..."
"they don't have any experience and let's just say you're operating in like some, you know, you you've operated in legal, I think, at at scale or pick a vertical, right, that has like some level of lik..."
"have one question, which is, you know, the title of your post was trading trading margin for mode. >> Yeah. Yeah. >> Right. Do you think that this forward deployed motion is fundamentally low margin? ..."
">> Do you have a like a most controversial take or like a hottest take in AI right now? Yeah, I think that the I would say my hottest take is I think the right way to think about Foundation Labs is th..."