Software has been venture capital's core asset class for about 25 years. It needs little capital per dollar of revenue, scales at near-zero marginal cost and produces recurring, predictable revenue that public markets will pay high multiples for. Since late 2022, generative AI has added a second layer on top: foundation-model labs raising tens of billions per round, AI-native applications reaching $100M ARR in two or three years, and a real question about whether the SaaS business model survives its own automation. This section covers the SaaS operating model and its metrics, how software is valued, the AI capital cycle of 2023–2026, and how an experienced software investor tells real durable growth apart from growth that was bought.
What the study covers
- 1Overview: why software fits venture so well
- 2Mechanics: the SaaS operating model
- 3Valuation
- 4Key numbers
- 5The AI capital cycle, 2023–2026
- 6Landmark deals and cases
- 7Pitfalls
- 8How an expert thinks about it
- 9Glossary
Technical exhibits
Worked examples, checklists and case studies included with this study.
SAAS Metrics Worked Example
Eight-quarter ARR bridge for a stylized company: NRR, GRR, magic number, CAC payback, burn multiple, Rule of 40, LTV/CAC and the AI gross-margin penalty, all computed by script
AI Foundation Model Mega Rounds 2023 2026
Round-by-round history of OpenAI, Anthropic, xAI, Mistral, SSI, Thinking Machines and others; compute-for-equity deals; "reverse acquihires"; what it means for ordinary venture funds
Software and AI Diligence Checklist
Practical checklist for Series A–C software and AI-application diligence