AI Features
topic on 3 shows · 7 statements across 7 episodes
the Official SaaStr Podcast 
the a16z Podcast 
20VC
7 statements about AI Features, every show
Zinman: Monday.com's early AI features were superficial sugarcoating
“We built some AI features, but like you said, I call it we sprinkled some AI dust on top of our product. So essentially we didn't know what to build. So we built a way for people to be, build formulas using AI. We built AI blocks, AI columns, but essentially i…”
Lemkin: SaaS companies adding minor AI features will be irrelevant in two years
“You're going to go out of business and you're not going to fail because your customers are going to renew, but your growth is going to fall so far that you become irrelevant in two years.”
Cannon-Brookes: Some Atlassian AI features are 1,000x cheaper to run today
“Some of our features are a thousand times cheaper to run than when we introduced them today.”
Simionato: Exploratory AI product features cannot be forecasted with upfront business cases
“When you build instead an exploratory AI feature on Evernote, you don't have a business case because you don't know how many people will use it. You can guess, but it's different.”
Figma Designer: AI Features Only Ship After Passing Perfect Output Evals
“So for every feature that we built, we set up these little tests. Where we have the expected perfect outputs and we compare, we then compare that expected perfect outputs to the AI outputs. And we do that for every change. And only when the expected outputs is…”
Olivia Moore: Incumbents fail in AI by avoiding platform cannibalization
“Where a lot of the incumbents get stuck is they can't really cannibalize or put their existing product or platform too much at risk. And so they tack on AI features versus, like, reimagining what the experience would look like.”