In the Vault: Assessing AI Impact vs. Hype with John Stecher of Blackstone

Most financial institutions still bank on software built before the internet, but Jack Henry's CTO, Ben Metz, is leading a quiet revolution to change that. Speaking with a16z General Partner Angela Strange, Metz shares how banks’ historical tech infrastructure and regulatory obstacles have stymied innovation—and how Jack Henry is helping them overcome these challenges. Metz outlines actionable ways startup founders can help smaller community banks leverage artificial intelligence and cloud computing, reshaping the industry at large. Chapter Breakdown:0:47   Backstory 2:15   Community banks and historical infrastructure 4:30   Pre-internet banking & software realities  6:45   Challenges of scaling historical banking tech8:30   Building software & COBOL12:15 Dissecting core banking systems 15:40 How regulatory hurdles impact innovation18:30 Mobile banking and market shiftsT22:45 Integrating AI into banking's foundation 25:30 Digital service core to banking 28:15 Where AI will be integrated first31:20 Advice for fintech founders 34:45 Building a data platform to enable innovation 38:20 Working together: banking & tech startups

a16z Partner Seema Amble talks with MongoDB and Viam co-founder Eliot Horowitz about building sustainable open source software tools. From challenging Oracle to building the de facto cloud-based database management tool, Horowitz outlines MongoDB’s early go-to-market strategies, approach to community building, and enterprise sales motion. This episode provides detailed tips on creating solutions for the developer community, building trust amongst enterprises, and successfully scaling a business supported by the open source community.  01:18-03:42 Why open source is a strategic business decision 3:42:6:03 Product development strategy + making developers’ lives easier6:03-08:24 MongoDB strategy of building community through meetups08:24-10:49 The five-second rule for developer products10:49-13:09 How MongoDB used meetups to fuel growth13:09-15:35 The importance of getting people excited about your product15:35-19:29 MongoDB’s enterprise sales strategy  19:28-20:26 MongoDB’s recruiting strategy 20:26-25:12 Open source customers vs. users, adoption patterns 25:12-27:35 The evolution of enterprise deals and building trust through demos27:35-32:23 Product communication strategies and tactics 32:23-39:37 Managing customers and building long-term relationships39:37-40:16 Outro

a16z Partner Seema Amble connects with Zapier co-founder Wade Foster about the company’s founding and GTM success utilizing a product-led growth (PLG) strategy. Chock-full of actionable insights, this episode explores Zapier’s product strategy, customer experience, and how the team built a sustainable growth engine that enabled them to reach profitability within three years. Foster also provides valuable guidance on brand strategy and how creating an unconventional “weird” brand helped Zapier differentiate from competitors.1:15-2:05      Zapier's origin story2:05-3:13      Initial product idea3:13-5:06      Finding product-market fit and YC5:06-7:43      How Zapier found their early customers7:43-10:15    Strategic approach to identifying services to integrate10:15-13:28  Identifying customer needs and optimizing onboarding13:28-16:10  Developing a scalable customer acquisition strategy16:10-19:07  Guidance on building a successful self-serve product 19:07:23:52  Early pricing experiments and brand evolution23:53-27:04  Early hiring strategy 27:04-29:59  Reflecting on Zapier’s brand identity and product strategy29:59-31:19  Advice for founders regarding customer acquisition and GTM31:19-31:59  OutroPlease 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 Seema Amble chats with Tomer London, co-founder of Gusto, about establishing product-market fit and product discovery. London shares how Gusto, now valued at ~$10 billion with 300,000+ customers, identified early customers who could provide valuable feedback that helped the team optimize the self-service product experience. The conversation explores Gusto's approach to product development, as well as managing and incorporating customer feedback while maintaining a clear product vision.1:18-3:14   Gusto’s founding story 3:14- 4:56  Solidifying a GTM sales strategy 4:56-10:03 Identifying early customers and perfecting the sales pitch10:03-12:45 Working with customers to optimize the product UX12:45-14:31 Engendering trust and finding success with accountants 14:31-16:41 The role accountants planned in Gusto’s success16:41-19:34 Creating a feedback funnel and balancing product vision19:34-22:38 Self-service strategy and measuring success22:38- 23:45 Refining the UX at scale 23:45-25:45 Identifying real-world use cases to inform product strategy25:45-29:52 GTM learnings and advice29:52-30:05 OutroPlease 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.

High-performance compute is the bedrock of generative AI, and if there’s anyone who knows about high-performance chips, it’s AMD CEO Lisa Su. In this wide-ranging conversation with a16z Operating Partner Bob Swan—himself formerly CEO of Intel—Lisa lays out her vision for the evolution of compute within the AI ecosystem, touching not only on raw power and the continuation of Moore’s Law, but also how AMD will support “the right compute for each form factor” for a wider ranges of real-world gen AI use cases. Lisa also shares her perspective on the state of chip manufacturing, how AMD matches their R&D cycles to fast-moving industries, and how partnerships build strong ecosystems. Read more, including a full transcript, here: https://a16z.com/how-to-build-ai-ecos... Time stamps:[00:01:37] Lisa's career in compute[00:04:48] Compute in the genAI era[00:09:39] High performance or multimodal?[00:10:47] Making the genAI ecosystem open[00:14:16] The chip supply chain[00:17:53] Resiliency and the CHIPS Act[00:20:54] How AMD balances long development cycles with short term innovation[00:24:48] Learnings from the hyperscaler market[00:26:54] What being fabless means for AMD[00:31:24] Lisa's advice for startup foundersFind more content from our AI Revolution series on www.a16z.com/AIRevolution. 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.

Finding and backing companies that can reach escape velocity is the name of the game over here at a16z Growth—but picking those winners is far from easy. David George, head of the a16z Growth fund, sat down with the I/O podcast to discuss his mental models for growth-stage investing, what it really takes to go public, where AI is today and where it’s headed, and more. [00:03:19] What makes Andreessen Horowitz different[00:08:29] David's mental model for investing[00:18:23] Focusing on inputs, not outputs[00:26:52] What constitutes a growth company?[00:29:14] David's three investing frameworks[00:36:45] How to measure the ROI of R&D[00:42:15] What it takes to go public today[00:46:43] AI: market structure and infrastructure vs. application layersTo read a transcript of this conversation, click here. 

In this conversation with a16z general partner David George, Scale AI founder and CEO Alexandr Wang discusses the three pillars of AI—models, compute, and data—and how creating abundant data is core to the evolution of gen AI. With Scale’s work across enterprise, automotive, and the public sector, Alex is also building the critical infrastructure that will allow any organization to use their proprietary data to build bespoke gen AI applications. In addition to talking about frontier data, Alex also shares his learnings from the growth of Scale, his approach to leadership, and what he thinks growth-stage founder/CEOs tend to get wrong about hiring.  Read more, including a full transcript, here: https://a16z.com/frontier-data-foundries-alex-wang-scale-ai/Timestamps: [00:00:58] How frontier data will change gen AI [00:08:47] Are big tech companies over-investing in AI? [00:14:39] Where the best AI businesses will thrive [00:17:05] How enterprise businesses are approaching AI adoption [00:19:50] What does the next phase of gen AI products look like? [00:23:23] Alex's approach to scaling Scale [00:25:36] The founder fallacy [00:30:12] MEI and how Alex views talent acquisition

a16z general partner David Haber talks to John Stecher, Chief Technology Officer at Blackstone, where he advances cutting-edge technology, heads up innovation investing, and advises the firm’s investment teams and portfolio companies. The conversation covers how he decides whether to build tech in-house or partner with startups, what qualities he’s looking for in early stage companies, and how he sees AI impacting real estate, credit, energy, and ecommerce.0:00-1:05 Intro1:06-3:55 Changes in finance x tech over the past 2 decades3:56-5:06 Investing in "themes" across asset classes5:07-7:00 What the CTO role entails 7:01-9:00 "Build it" vs. "buy it": trade-offs9:01-11:57 Advice for early stage companies11:58-16:37 Ways Blackstone is incorporating generative AI16:38-17:46 How AI changes the role of an analyst17:47-21:04 Gen AI's impact on private equity, real estate, credit, more 21:05-22:54 How Blackstone will evolve over the next five years22:55-23:26 OutroPlease 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.

a16z general partner David Haber and fintech partner Marc Andrusko talk to Tim Karpoff, the Global Head of Strategy at Citi, where he guides the bank’s core focus areas, as well as future investment in emerging tech like AI. The conversation covers the shifting landscape of banking policy and regulation, the increasingly important role startups are playing in partnership with big banks, and where Tim disagrees with the zeitgeist when it comes to the adoption of AI in financial services.0:00-1:05 Intro1:06-2:28 Navigating bureaucracy2:29-4:26 What "chief strategy officer" entails 4:27-8:18 Citi's role in the banking ecosystem8:19-9:16 Fallout from the 2023 banking crisis9:17-13:10 Citi's revised risk controls and tech investment13:11-14:59 How Citi works with startups15:00-20:00 Citi's future: AI and regulation20:01-23:33 What people get wrong when it comes to AI 23:33-24:12 OutroPlease 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.

Waymo co-CEO Dmitri Dolgov joined a16z general partner David George to discuss how Waymo is using genAI to help them build safer, sustainable, and more accessible transportation. In the conversation, Dmitri talks about the potential of embodied AI, the value of simulations and building training data, and his approach to leading a company focused on solving the challenges of building AI that can navigate the real world.[00:01:22] The early days of autonomous vehicles[00:05:27] Layering genAI into traditional AI/ML[00:09:42] The value of simulation[00:15:56] The hard part about integrating AI in autonomous systems[00:22:45] AI in the real world[00:28:47] Where does Waymo go from here?[00:37:21] Dmitri's learnings from hard problemsThis conversation is part of our AI Revolution series, which features some of the most impactful builders in the field of AI discussing and debating where we are, where we’re going, and the big open questions in AI. Find more content from our AI Revolution series on www.a16z.com/AIRevolution.