I Sold My AI Startup Before Revenue: Here’s What Investors Missed — And Founders Shouldn’t
Nobody is talking about this: the best AI returns aren't coming from ChatGPT wrappers—they're coming from founders solving model and infrastructure problems.
Why it matters
A contrarian take on AI startup investability from an angel investor who exited pre-revenue. The piece argues that foundational AI (models, infrastructure) will create more long-term value than application-layer products, offering a strategic framework for how founders and investors should think about positioning in the AI economy.
The key facts
9 to knowAuthor: Alexander Kardos-Nyheim, angel investor
Thesis: Deep technical challenges (model/infrastructure level) > application-layer products
Context: Author sold AI startup before revenue
Type: Guest commentary on investability criteria for AI startups
Source: Crunchbase News
Author: Alexander Kardos-Nyheim (angel investor)
Core thesis: Long-term value in foundational AI (models, infrastructure) > application-layer products
Context: Author sold AI startup pre-revenue
Focus: Investment evaluation framework and due diligence questions for AI founders/investors
Go to the source
Crunchbase Newsnews.crunchbase.com
Publisher excerpt: The greatest long-term value in AI will come from companies solving deep technical challenges at the model and infrastructure level rather than application-layer products built on existing AI platforms, writes angel investor Alexander Kardos-Nyheim. In this guest commentary he shares processes and…
