Happy Sunday and welcome to the weekend edition of InsideAI! I'm Rob May, CTO at Dianthus. As a reminder, I'm slowing things down here and at the end of the year will move to write at Investing in AI, so, go sign up there if you want to continue following my thoughts. The main reason for the move is that, in the 6 years I've been writing about AI, it has matured to the point where I don't see much of a need to give you news and commentary. There are now many people doing that, and I want to focus more on something that is different. The new newsletter focuses on the investment side of AI - what do we look for in business models and markets? It will be more ad hoc - 2-3x per month, but deeper and more focused. I'll write another 6 newsletters or so here before end of the year, then sign off.
For today's topic though, I want to point you to Michael Dempsey's excellent piece on the Curiosity Phase of AI. What I like about this piece is Michael shows why this is in some ways the best time, and in other ways the worst time, to start an AI company.
Now that AI has started to proliferate into specific industries with real value creation, the curiosity is growing even stronger, with people looking to either dismiss this still imperfect (but pretty damn good) technology, while others wondering how they can use AI to do their job better.
For those shipping narrow products and side projects, this particular time in the market is amazing. It allows for a robust top of funnel of users who might pay a small amount to try what you’ve built, or at a minimum who will happily share it on the internet and generate 15 minutes of fame for your work.
For those building long-lasting products and turning those into companies, this is a dangerous time to operate.
I've seen a lot of what Michael describes in my AI investing. Most importantly, this idea that sometimes the early users are the worst users - tirekickers who are willing to spend a small amount of money to try something out but ultimately churn and aren't valuable long term. Here is his advice for companies building now:
The pace of innovation means having the time to see validating data will be nearly impossible, and thus teams must build ahead of feedback loops from scaled user data. Because of this, feedback loops must have tighter timelines, experiments must be cut off faster, and likely teams must build in a more speculative manner, in an effort to skate to where the proverbial puck is going, before others do so.
But really, this is awesome so go read the whole thing.
Thanks for reading.
@robmay
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