--- title: "The 4 Questions Startups Should Ask Themselves about Building with Generative AI" description: "Discover 4 crucial questions startups must answer when building with AI. Learn how Goldman Sachs projects AI will drive 300x more GDP growth than PCs did." categories: ["AI","trends","startups"] keywords: ["venture capital","generative AI","startups","AI trends","Theory Ventures","Tomasz Tunguz","SaaS","technology content","GDP growth","cloud computing"] ai_summary: "Key questions startups should ask when integrating generative AI, including considerations for market competition and technical depth." date: 2023-04-07 lastmod: 2026-07-30 canonical_url: https://www.tomtunguz.com/generative-ai-saastr/ author: "Tomasz Tunguz" --- There are 4 questions a startup should ask themselves about building a startup that uses generative AI. I presented those questions & my views on their answers at [Saastr's Workshop Wednesday](https://www.saastr.com/workshop-wednesday/). I had a blast putting this deck together. I started with a few sentences, uploaded them to [gamma.app](https://gamma.app) to outline the presentation, popped over to [Midjourney](https://www.midjourney.com/home/?callbackUrl=%2Fapp%2F) to generate images along the story line, & published it in [IA Presenter](https://ia.net/presenter). The [video is here](https://www.youtube.com/watch?v=xiYzzLe9BAs). The last slide contains the prompts for the images in the presentation. The narrative is : AI is a massive platform change that Goldman Sachs projects will increase GDP 300x more than the PC. GS estimates a 1.5-2.9% increase to US GDP, doubling GDP growth, net of 7% job loss. The PC increased GDP by 0.006%, according to NBER That alone should turn heads. There are 4 questions startups should ask themselves about building with generative AI. 1. Layer : application, platform, or infrastructure? In the cloud, AWS, Azure, & GCP have created about as much market cap as all the top 100 B2B & B2C publics built on cloud (Netflix, ServiceNow, AirBnb, etc). But there are 100 applications compared to 3 infrastructure vendors. 2. Market : how to compete with incumbents? Startups have negative time to launch in many markets with Adobe, Microsoft, & Salesforce launching Gen AI enabled software in weeks. 3. Moats : how to develop competitive advantage? Competing on algorithms is possible but hard. Access to proprietary data provides a moat. Usage & distribution, like in classical SaaS, are likely the most sustainable & repeatable. Enterprise readiness will be an essential : ensuring buyers are safe from legal & compliance risks. 4. AI Depth : what level of technical sophistication to bring into the company? Startups can integrate with a plug-in, build a prompt-tuning engine (a little model on top of a bigger model), or develop & train their own models. Each subsequent choice is more expensive, but provides a deeper moat. It's likely startups start at plug-ins & then move down with scale that affords more usage & more capital to invest. If you're building in the space,[I'd love to hear from you](https://twitter.com/ttunguz).