Most AI product firms are founded and grown in a similar way.
It usually goes something like this:
Founder(s) develop a hypothesis about how AI might improve a particular business result
Money is raised, an initial team is built, and a beta product begins development
Initial prospect conversations make it clear that the firm is wrong about it's go-to-market hypothesis (almost no firm gets premonition right, per von Moltke's famous quote), and they need to recalibrate their hypothesis to consider what they've learned about:
The motives of stakeholders
The current state of IT and data infrastructure of prospect firms
The workflows their product impacts
Where budgets do and do not exist within prospect firms
This usually leads to a phase where the startups has dozens - maybe hundreds - of haphazard conversations across industries, groping to find someone who might use their product. They tell prospects about their product ("hammer"), and hope the client ...
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