Bifalgorithm post
So essentially, we're now looking for three core things. One of them is data. So we're looking for a proprietary data motor or data that compounds with usage as well. Number two, we're looking for feedback loops. So as typically you'll have in a founding team, you'll have commercial team, you'll have a product team. The customers give the feedback to the commercial team. They will pass it through to product. Products create new features, ship them back out again, and that becomes part of the new product as it develops. Now, because of the pace at which startups are scaling, that feedback loop needs to be faster and more succinct and more accurate than ever before. We're looking at how that loop works. And then the third thing, which is the most important thing that I'm looking for in 2026 in AI startups is around distribution and brand moat. So what we really care about is what makes this business, the one that customers are going to keep coming back to.
So essentially, we're now looking for three core things. One of them is data. So we're looking for a proprietary data motor or data that compounds with usage a…
Ideas in this flowchart
- Core Requirements for AI Startups
- Data
- Proprietary Data Motor
- Compounding Data with Usage
- Feedback Loops
- Commercial Team Receives Feedback
- Product Team Develops Features
- Fast, Succinct, Accurate Loop
- Distribution and Brand Moat
- Customer Retention