Like the defensibility and competitive advantage: These concerns exist with most (all?) non-AI startups as well, and they are equally valid. See countless examples of incumbents cloning startups, and using distribution advantage and what's effectively dumping to crush the competition.
(*) Interestingly, prompting ChatGPT with the article title & sub-titles produces almost the same kind of content.
Good lord. I hate these AI copycat companies so much lol.
Here’s a couple of things which could set you apart off the top of my head.
Customers. Having customers is an advantage over the next guy who doesn’t, because now you can start customizing your product for unique needs rather than having a generic crud app.
Custom models. A custom model means some kid can’t just replicate your app easily.
Unique data. Data which is infeasible for another company to acquire or replicate.
Special people. People who will give your startup an edge in creating all of the above.
Midjourney is a great example. An actual valuable product which people pay to use without VC funding.
And companies like context.ai and the thousands of others which are exactly the same have to do this whole monkey dance for VCs.
Nothing ever needed help before blinding signal existed.
Also MidJourney's founder presumably had lots of money from their previous venture-fueled business.
Innovation capital is one thing, but it almost always needs financial capital to lubricate the growth.
Curious to hear some of the answers you used here. User analytics platforms are going to be huge as LLM backed tools start entering production. No doubt that the concept is valuable. But what is to stop DataDog or some other analytics platform from adding LLM analytics?
Perhaps the market will just be large enough that it doesn't matter. And people typically don't switch analytics providers once they're locked in.
The only thing LLM specific in analytics right now is tracking the right REST calls. Most ultra-LLM specific analytics are an anti-pattern if anything: if your agent setup is so convoluted you can't hook up a normal tracing library to it, it's a mess.
That's why 99% of them target Langchain specifically, it's so horribly written that adding basic tracing really is a challenge worth solving. But how long can you bank on the tool of the day just being that terrible?