How To Build a Defensible A.I. Startup
- You have access to a proprietary asset (like data) that others don’t have easy access to. In our “write job postings” example, perhaps you have a corpus of thousands of job postings including some outcome scores (as to how well they did). You could use this data to create better job postings. Others don’t have ready access to this data. Note: The a
Dharmesh Shah • How To Build a Defensible A.I. Startup
Protecting LLM products:
(1) Is hard to bootstrap. This already hints to existing customers or you need to get a bunch of your customers to co-develop (insurance model → companies pooling their data to solve a problem they all have). This runs into a bunch of issues: competitive drive of the companies, data privacy and security.
(2) Reserved for existing companies. This is the co-pilot model.
(3) This might be the most sustainable one, but it is also the hardest one. I have not seen anything in that direction yet besides OpenAI.
- How valuable is what I’m doing?
- What makes this hard for others to do?
- Could this get dramatically easier because of what others launch or how the industry evolves?
- If this does get easier, do I have a “Plan B” to create differentiated value?
Note: An early version of this post appeared in my personal blog (still a work in progress). Decided to