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.