How OpenAI GPTs are Changing Venture Capital - SVIC Clip

Summary

The transcript discusses the innovative approach of a venture capitalist who leverages AI and GPT to streamline the investment process. They share their experiences with creating custom AI tools to automate various aspects of venture capital, such as deal flow and portfolio support. The conversation delves into the strategic use of AI to identify and engage with promising startups, the challenges of scaling AI businesses, and the evolving landscape of venture capital in the age of AI. The speaker's unique 'build-in-public' philosophy and their use of AI to enhance efficiency and decision-making in their fund are highlighted, offering insights into the future of VC and AI integration.

Takeaways

• 🤖 The speaker is exploring the automation of venture capital (VC) processes using AI, including creating custom GPT models for various tasks.
• 💡 The speaker has developed AI tools to automate parts of VC, such as a VC associate for due diligence and a 'mean DC' for critical analysis.
• 📈 The AI tools are integrated into the speaker's portfolio support, helping to identify potential issues before formal meetings.
• 🔍 The speaker uses AI to streamline communication with founders, allowing for more efficient and less intimidating interactions.
• 📚 The speaker has created an AI from a PDF of documentation to simplify the process of understanding and using a chatbot.
• 🚀 The speaker's approach to building in public has led to deal flow, as it signals interest and attracts founders working on similar ideas.
• 🛠️ The speaker's projects serve as a starter kit and a request for startups, encouraging founders to build upon and improve the open-source prototypes.
• 💼 The speaker has invested in companies that leverage AI for market research and autonomous agents, which align with their interests and expertise.
• 🔄 The speaker's fund, Untapped, focuses on investing in founders who are less familiar with VCs and uses technology to identify and reach out to them.
• 📊 The speaker emphasizes the importance of maintaining the fundamentals of starting a company, such as identifying customers, pain points, and scalable business models.
• 🌐 The speaker is considering the future of AI and its impact on business models, particularly the challenge of creating a sustainable competitive advantage (moat) in the AI-driven market.

Q & A

What are the two sides of building an autonomous venture firm?

The two sides are the technical challenge of automating each piece of the venture capital process and the strategic consideration of how to integrate these automated systems into the firm's operations.

How does the speaker use custom GPTs in their venture capital work?

The speaker has built custom GPTs to automate parts of the VC process, such as a VC associate for handling chats and a 'mean DC' for critically evaluating pitches, thus adding to their portfolio support and decision-making.

What is the speaker's approach to being a 'good cop' and a 'bad cop' in their investment process?

The speaker uses AI to play the role of the 'bad cop' by critically evaluating investment opportunities, while they themselves take on the role of the 'good cop', focusing on building relationships and offering support.

How does the speaker's use of GPTs streamline their interaction with founders?

The speaker has created a GPT that founders can interact with to get initial feedback and sanity checks on their business ideas, which helps founders feel more comfortable and prepared before engaging in deeper discussions with the speaker.

What is the speaker's strategy for signaling their investment interests to founders and colleagues?

The speaker builds and publicly shares projects related to their areas of interest, which serves as a signal to founders and colleagues about the types of opportunities they are looking to invest in.

How does the speaker's 'build in public' approach lead to deal flow?

By openly sharing their projects, the speaker attracts founders working on similar ideas, who then reach out for further discussion, leading to potential investments.

What companies has the speaker invested in as a result of their 'build in public' approach?

The speaker has invested in companies like wo.ai for market research and cognosis and e2b for autonomous agents and developer tools, which were attracted by the speaker's shared projects and interests.

How does the speaker view the role of AI in the future of venture capital and startups?

The speaker believes that AI will continue to play a significant role, but the core principles of starting a company remain the same. They also see AI as a tool that can help founders and VCs operate more efficiently and creatively.

What challenges do founders face in a post-GPT world when raising money for their startups?

Founders must consider the economic feasibility of using AI, especially in terms of inference costs, and how to differentiate their business in a market where it's increasingly easy to build similar products.

What is the speaker's perspective on the future of AI and its impact on business models?

The speaker acknowledges the uncertainty but believes that humans will adapt to AI changes. They think that while AI will make software development easier, human problems and expectations will continue to evolve, creating new opportunities for startups.

What led the speaker to create a new fund, and what is the thesis of the fund?

The speaker was motivated by the inefficiency in traditional VC operations and the lack of diversity in the startups being funded. The fund focuses on investing in founders who are less familiar with VCs and uses technology to identify and reach out to them efficiently.

How does the speaker's fund evaluate inbound deal flow?

The fund uses AI tools to parse and update information from incoming deals, generate memos, and collect data at the top of the funnel, allowing for a more efficient and data-driven evaluation process.