The emergence of large language models (LLMs) and artificial intelligence has undoubtedly transformed the tech landscape, but the true potential for new businesses lies in what we might call the “second layer” of AI implementation. While many startups are merely creating wrappers around existing LLM capabilities, the real opportunity exists in developing specialized integrations and applications that address specific industry needs and business challenges.

This second layer opportunity requires a deep understanding of both AI capabilities and real-world business problems. It’s not about inventing use cases to shoehorn AI into every possible scenario, but rather identifying genuine pain points within industries and leveraging AI to create tailored solutions. This approach mirrors the evolution of Enterprise Resource Planning (ERP) systems, where the true value emerged from customization and integration rather than the base technology itself.

The future of AI in business lies not in the pursuit of artificial general intelligence (AGI) or humanoid robots, but in the hands of “integrators” who can bridge the gap between raw AI capabilities and specific business needs. These integrators will need to combine technical expertise with industry knowledge to create AI solutions that deliver tangible value. While this may not generate the same buzz as more speculative AI ventures, it represents a more sustainable and practical path forward for AI startups looking to make a real impact in the business world.