AI startups today are growing at breakneck speeds — faster than almost any previous generation of tech companies. But growth alone doesn’t make you Google. In fact, some of the fastest-growing companies are also the most fragile. So how do you tell apart the category leaders in the making from the ones about to hit a wall? The answer lies in **defensibility** — your startup’s ability to survive competitive pressure over time. In previous tech waves, defensibility often came from scale, embedding, brand, and network effects. Those still matter, but in the AI era, things move too fast for traditional defenses to hold on their own. You need a **layered strategy** that matches today’s pace, while setting up for tomorrow’s advantage. See: [[7 Powers]] | [[The Deep Tech Growth Cycle is different]] ### Think Like a Castle Builder Your AI company should resemble a **motte-and-bailey castle**: - The **bailey** is your fast-moving outer defense: distribution hacks, brand momentum, early user acquisition, and speed to scale. - The **motte** is the deep, harder-to-build core: network effects, embedding into workflows, and switching costs that make it nearly impossible for customers to leave. Early-stage growth happens in the bailey. But as competition intensifies, you need to fall back into your motte. Great companies time this transition perfectly. **Google did it. Groupon didn’t.** ### What I'm thinking about for the AI startup era #### 1. **Speed wins the start, but layering defensibility wins the war.** Modern defensibility is sequential. Start with velocity — grow fast, distribute widely, and grab attention. Then layer in deeper defenses like embedded workflows, collaborative memory, and network effects. Don’t wait until it’s too late. #### 2. **Network effects still rule — they just look different in AI.** AI-native network effects are emerging: - **Personal utility loops**: co-pilots that learn from your data - **Hub-and-spoke dynamics**: platforms that promote winners asymmetrically - **Agent-to-agent networks**: AI systems that collaborate autonomously These effects are subtle, compounding, and sticky. Winning companies build them in early — even if the value only shows later. See: [[Autonomous AI Agents - The rise, potential and challenges]] #### 3. **Brands and distribution are no longer soft advantages — they’re foundational.** In a sea of similar tools, **trust, clarity, and emotional preference** are your edge. Strong distribution gives you momentum; a strong brand makes people stay. ## So What? If you’re building in AI, design your roadmap with **defensibility sequencing** in mind. - **Early stage:** focus on distribution, velocity, and brand. Fight in the bailey. Move fast. - **Mid-stage:** watch for signs of copycats or plateauing growth — that’s your cue to build the motte. Embed deeply, create switching costs, and engineer network effects. - **Long-term:** as the AI stack matures, the winners will be those who *earned* the right to slow down — because they built defenses too strong to topple. > Don’t just sprint. **Sprint toward your castle.** [[Defensibility Principles MOC]] | Ref original article on NfX [here](https://www.nfx.com/post/ai-defensibility)