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Eric Vishria - A Decade of Lessons Investing in Software & Hardware - [Invest Like the Best, EP.486]

Eric Vishria discusses the evolving landscape of investing in software and hardware, emphasizing the importance of scalable infrastructure in AI and the nuanced role of traditional companies in rapidly changing markets. He shares insights on the complexities of hardware investing, the potential of AI, and the necessary traits for successful partnerships in venture capital.

Summary

In a recent episode of 'Invest Like the Best', Eric Vishria delves into lessons learned over a decade of investing in both software and hardware, particularly in the context of AI advancements. He highlights that while traditional companies may struggle with AI models, new players are likely to thrive, illustrating this with examples like Fireworks and Sierra. Vishria discusses how the cloud computing landscape has evolved; contrary to early predictions of AWS dominating all, a variety of specialized companies have emerged, showing the market's expansiveness. He argues that AI adoption in enterprise settings is growing but requires significant infrastructure to effectively manage these technologies.

Vishria reflects on the necessity of adaptable product development in the AI era, where understanding both customer problems and the capabilities of models is essential. His experiences with Cerebrus illustrate the long journey of hardware development, emphasizing that success in this field demands significant patience and ingenuity due to physical and logistical challenges. Furthermore, he offers insights into public market dynamics, explaining that going public not only provides increased trust and capital but can also reveal operational transparency to stakeholders.

Lastly, Vishria stresses that understanding market dynamics and varying levels of demand for AI capabilities will dictate which companies emerge as winners and which do not. Despite potential hurdles in sectors like healthcare and robotics, the overarching sentiment is one of optimism about the integration and utility of AI technologies across industries.

About this episode

My guest today is Eric Vishria, a General Partner at Benchmark.  Eric has spent his career in software and cloud, and few people know the history of these markets as well as he does. What makes him special is his ability to use that history to make sense of today.  We discuss what the rise of AWS teaches us about AI, what he has learned from investing in Fireworks, Sierra, and Cerebras, and how the criteria for winning have changed for founders and investors.  Please enjoy my conversation with Eric Vishria. For the full show notes, transcript, and links to mentioned content, check out the episode page ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠here⁠⁠⁠⁠⁠.  ----- Become a Colossus member to get our quarterly print magazine and private audio experience, including exclusive profiles and early access to select episodes. Subscribe at ⁠colossus.com/subscribe⁠. ----- ⁠Ramp’s⁠ mission is to help companies manage their spend in a way that reduces expenses and frees up time for teams to work on more valuable projects. Go to⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠ramp.com/invest⁠⁠ to sign up for free and get a $250 welcome bonus. ----- Trusted by thousands of businesses, ⁠Vanta⁠ continuously monitors your security posture and streamlines audits so you can win enterprise deals and build customer trust without the traditional overhead. Invest Like the Best listeners get a special offer of $1,000 off Vanta when you go to ⁠vanta.com/invest⁠.  ----- WorkOS⁠ is the infrastructure B2B and AI-native companies use to sell to enterprise. It covers everything enterprise security requires: SSO, SCIM, RBAC, Audit Logs, AI governance, and more. Trusted by 2,000+ fast-growing companies, including OpenAI, Anthropic, Cursor, and Vercel. ----- Rogo is the AI platform for finance. They're building agents for Wall Street that are trained to understand how bankers and investors actually do work: from diligence and modeling, to turning analysis into deliverables. To learn more, visit rogo.ai/invest. ----- ⁠Ridgeline⁠ has built a complete, real-time, modern operating system for investment managers. It handles trading, portfolio management, compliance, customer reporting, and much more through an all-in-one real-time cloud platform. Visit⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ridgeline.ai⁠. ----- Editing and post-production work for this episode was provided by The Podcast Consultant. Timestamps: (00:00:00) Welcome to Invest Like The Best (00:02:20) Learning the World Through Fireworks (00:05:42) AWS Was Going to Eat Everything (00:07:40) The Zero-Sum Thinking Trap (00:09:01) Comparing Cloud and AI Adoption (00:11:03) Becoming Enterprise's AI Sherpa (00:13:05) Building Sandcastles (00:14:55) The Return to Being Technical (00:17:13) The Shifting Competitive Frontier (00:22:10) Why the Old Playbook Fails (00:27:53) Energy as the Binding Constraint (00:29:38) The Cerebras Story (00:37:57) The Virtue of Productive Naivete (00:39:19) What Robotics Still Needs (00:45:58) What Makes a Great Board Partner (00:51:13) Raising A Growth Fund (00:55:39) What the Big Winners Taught Him (00:57:37) Hard Work Versus the Hole-in-One (00:58:38) The Best Reasons to Go Public (01:01:09) Debates Inside Benchmark (01:02:16) What If It All Works (01:03:35) What Geoff Hinton Got Wrong

Key Insights

  • Vishria notes that the performance difference for AI models between companies like Fireworks and traditional cloud providers can be significant, showcasing the complexity of running these models effectively.
  • He emphasizes that successful investing requires understanding the jagged edge of AI capabilities and having the technical acumen to navigate product development in this dynamic landscape.
  • The evolution of AWS demonstrates that expectations of a single company dominating the cloud space were misguided; instead, a diverse array of companies can thrive simultaneously.
  • Enterprises are more receptive to AI technologies than they were to cloud adoption a decade ago, indicating a shift in mindset towards the opportunities AI presents.
  • The investment landscape is increasingly characterized by high valuations and larger capital requirements, leading firms to consider growth equity as a viable avenue for returns.
  • Vishria describes the importance of being nimble in the investment approach, adapting to changing market dynamics rather than adhering strictly to traditional models.
  • He shares lessons from Cerebrus, where the path to hardware success is fraught with challenges, revealing that innovative hardware investments require deep understanding and long-term commitment.
  • Going public offers companies a new avenue for trust and capital, transforming their operations and relationships with investors and customers.
  • Vishria argues that the current AI landscape is not a zero-sum game; various sectors can grow and thrive rather than competing for a finite pool of resources.
  • He critiques deterministic views regarding job displacement due to AI, using radiology as an example where managerial and operational realities complicate predictions about workforce changes.
  • The growth of AI and demand for intelligence necessitate increased energy resources, affecting the development and deployment of technology companies reliant on these capabilities.
  • Finally, Vishria emphasizes the value of partnering closely with entrepreneurs and understanding their vision to foster successful outcomes.

Topics

AI InfrastructureCloud ComputingRoboticsVenture CapitalHardware InvestingMarket Dynamics

Transcript

Ramp is the only platform built to make your finance team leaner, faster, and better, saving businesses 5% annually on average so you can stay focused on growth. Ramp customers grew revenue 3.2 times faster than the average American business. Visa, Vercel, Cursor, Stripe, Notion, 11Lab, Shopify, and 70,000 other businesses all run on Ramp. Mine does too, and so should yours. Learn more at ramp.com slash invest. OpenAI, Cursor, Anthropic, Perplexity, and Vercel all have something in common. They all use WorkOS. To achieve enterprise adoption at scale, you have to deliver on core capabilities like SSO, SCIM, RBAC, and audit logs. Instead of spending months building these mission-critical capabilities yourself, you can just use WorkOS APIs to gain…

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