Is T2D3 dead? Is it time for the VC playbook to switch to Q2T1? For years, the benchmark track to unicorn status for VC-backed SaaS businesses has relied on T2D3 growth: triple, triple, double, double, double. Meaning: reach $2M ARR, then grow along a path like this p.a.: $2M -> $6M -> $18M -> $36M -> $72M -> $144M With a 7x ARR multiple, that $144M ARR translates into the coveted $1B valuation. But AI is reshaping the rules. AI startups are now scaling revenue at record speeds—5x faster than traditional SaaS, according to Stripes’ recent data. The appetite for AI solutions across enterprises and SMEs is tremendous. So Q2T1 - quadruple, quadruple, triple. Takes you to $100m ($96m) ARR: $2M -> $8M -> $32M -> $96M Such growth pace motivates a higher multiple (10x) and a hence you end up at a $1bn valuation. This implies a shorter track to unicorn. The bar keeps rising. Will this be the new gold standard?
Are AI margins and FCF similar enough at $100m revenue to justify a similar multiple as traditional SAAS? Asking bc in the ZIRP era we collectively got burned applying SAAS multiples to non-SAAS stuff like grocery delivery, web3, etc
Jerrit Jungmann
4mo
How much of it do you think this is skewed by very few outlier companies? And I think it would be interesting to also understand how long it took each category to reach first revenue, as that where Stripes data starts.
Peter Lindström
4mo
Interesting stats.
Partner | KOMPAS VC
4moI think that the lack of actionable proprietary data is still holding back corporate investment. There is a massive disconnect between CEO's talking the AI talk and the lack of large proprietary enterprise data sets that would allow companies to deploy AI in a really meaningful way. A lot of companies are starting to accelerate investment into their data infrastructure to become 'AI ready' but I don't think the majority of enterprise customers are quite ready yet to support these kinds of growth trajectories.