Much of what worked in traditional SaaS doesn’t hold true in the AI era. In meeting with hundreds of AI founders building for the enterprise, a few core principles have emerged that are shaping how teams are building and growing in today’s market. - Flashy demos are easy, building substantive products are hard: It takes orchestrating across multiple models, fine tuning, evals, and deep, customer-specific integration to make AI work in production. - 1M ARR isn’t the classic Series A benchmark anymore: AI-native startups are growing faster than their SaaS counterparts, with some hitting 5M ARR in ~9 months. Enterprises now have dedicated AI budgets and CEO-level mandates to buy. - Build costs are collapsing: OpenAI just cut o3 pricing by 80%. Tools like Cursor and Lovable are making it easier for developers and non-technical users to ship full apps. Expect a flood of applications (and potential competitors). - Speed compounds: Product velocity and early brand momentum can snowball into category dominance. Companies like Cursor, Decagon, and ElevenLabs moved fast, landed major customers, and built brand strength before incumbents could respond. - Moats still matter: The winners are becoming systems of record, embedding into workflows, and building deep vertical integrations, especially in complex industries like healthcare and logistics.