One Line
The excerpt highlights the importance of building systems of intelligence powered by AI in order to create new moats and remain competitive in the business world, as AI becomes the enabling technology of this moment.
Slides
Slide Presentation (7 slides)
Key Points
- AI technology is exciting, but the fundamentals of business building remain the same.
- The value of an application lies in its ability to deliver value through workflows, data integration, brand/trust, network effects, scale, and cost efficiency.
- Startups that can build systems of intelligence have a huge opportunity in the business world.
- AI tools have potential in various industries and can be used to build systems of intelligence in enterprise products.
- Combining different datasets and systems of record is important for creating value.
- Systems of engagement act as interfaces between users and systems of record, and can be powerful businesses.
- Deep tech moats can still be built around IP and hard engineering problems, but AI is becoming a shallower moat.
- Startups need to focus on building systems of intelligence powered by AI to create new moats and remain competitive.
Summary
491 word summary
The excerpt discusses the importance of building sustainable businesses in the age of AI. It emphasizes that while AI technology is exciting, the fundamentals of business building remain the same. The value of an application lies in its ability to deliver value through workflows, data integration, brand/trust, network effects, scale, and cost efficiency. Companies that can build systems of intelligence must also master go-to-market strategies. The article suggests that the new moats in the business world are the old moats, and that AI-driven systems of intelligence present a huge opportunity for startups. These systems can create a virtuous cycle of data, improving models and tailoring products for each customer. The article also highlights the potential of AI tools in various industries and describes how enterprise products can use AI techniques to build systems of intelligence. It discusses the importance of combining different datasets and systems of record to create value. The excerpt concludes by mentioning the role of systems of engagement as interfaces between users and systems of record, and how they can be powerful businesses. Foundation models are essential for unlocking value and understanding across all systems of record. It is still uncertain whether the future will lean towards a few large models or a market of smaller models. Systems of record, such as CRM and HCM, are the backbone of enterprise systems. Full stack companies offering SaaS applications are favored in the market, as technology becomes an invisible component of a complete solution. Deep tech moats can still be built around IP and hard engineering problems. However, in an era of cloud and open source, deep technology is becoming a shallower moat. AI is becoming the platform technology of today, potentially disrupting the hierarchy among incumbents. Startup founders should attack legacy player moats while building their own defensible moats. Switching costs, brand and customer loyalty, high switching costs, deep tech/IP/trade secrets, network effects, and economies of scale are all important moats to consider. The balance between models with trillions of parameters and smaller models is yet to be determined. Microsoft, Google, and Facebook are examples of companies with powerful moats. Startups today need to focus on building systems of intelligence powered by AI in order to create new moats and remain competitive. The value captured by traditional economic moats, such as big cloud platforms and open source alternatives, is being disrupted. Open source technology has historically shifted value to adjacent layers in the stack, reducing the dependence on proprietary systems. However, the new wave of AI models can potentially shift power back to startups, allowing them to leverage both open source and proprietary foundation models. Large language models like GPT-4, PaLM2, and LlaMA are examples of how AI is becoming the enabling technology of this moment. Startups and existing companies that incorporate generative AI into their applications can benefit from this development. The ability to adapt and incorporate AI is crucial for businesses to build sustainable and profitable models.