Is the SaaSpocalypse Over?

In this episode

Craig talks with Aaron, who built DocsBot, an AI customer support agent that's almost four years old, about what AI is really doing to SaaS. Aaron shares DocsBot's numbers: slower growth and fewer new customers, but more revenue per customer and lower churn after narrowing in on the right customers. They also get into what it costs to run an AI product, how to choose and switch models, and the AI tools Aaron is excited about next.

Topics discussed

Growth in the AI era: new customer acquisition is down year over year, but revenue per customer is up 20% from last year

Finding the ideal customer: talking to customers, cancellation surveys, and pointing AI agents at all of the product and Stripe data, after reading Jason Cohen's book Hidden Multipliers

Signal density: why founders with only a handful of customers struggle to draw conclusions

Where customers come from now: organic search, AI search, referrals, conferences like WordCamp, and an agency partner program

Why big companies move slowly: and why that makes larger customers stickier

Churn to DIY: churned customers citing AI or their own custom solution went from 1.6% to 13%, and most weren't a good fit anyway

Pricing around token costs: from bring-your-own-key to included usage to AI credits

Evaluating new models: why letting customers edit their system prompt makes evals hard, and a classifier that behaved differently on GPT-5.4

Choosing models: balancing cost, speed and quality instead of reaching for the newest model