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:
/ a16z
Find a16z on LinkedIn:
/ 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.
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:
/ a16z Find a16z on LinkedIn:
/ 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.