AI Investment Landscape - The AI sector is expected to generate numerous trillion-dollar businesses [1][52] - Venture firms recognize the need for scale to effectively operate throughout the private market lifecycle [2] - A significant portion of venture funding is concentrated in a small number of top AI deals, with the top three LLMs potentially raising $100 billion in a six-month period [2] - AI is seen as a foundational element for the future of vertical SaaS, enhancing data models, connectivity, and marketplace capabilities [2] - AI solutions are increasingly impacting labor budgets, not just technology budgets, opening up a multi-trillion dollar market [3] Investment Strategies & Considerations - Investment decisions are focused on the future margin profile of companies, considering potential for significant capital expenditure [1] - Venture firms are willing to be small investors in potentially very large companies, accepting dilution in exchange for exposure to generational companies [1] - The pace of innovation is rapidly compressing, favoring teams that can iterate quickly [1] - Efficiency still matters, with a quantified trade-off between growth and efficiency, especially at mid-stage scale (around $50 million ARR) [5] - The industry is seeing a shift towards consumer-like growth rates for enterprise businesses, with some companies reaching $100 million in ARR in 18 months [5]

So, what is Generable and is that even a word. Well, yes, it is. Generable is an easy way to let the model generate structured data, using Swift types The macro generates a schema at compile time, which the model can use to produce the expected structure. The macro also generates an initializer, which is automatically called for you when making a request to a session.So then we can generate instances of our struct. Like before, we’ll call the respond method on our session. But this time pass the generating ...