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@jack and @roelofbotha published an essay this week with a contrarian answer to the most important question in tech right now: what is AI actually for. Their point of view resonates with how we're answering this question at @Standd_io.
Most companies are trying to figure out how to use AI to move faster through their existing workflows. But Block poses a more interesting question: what does a company look like when AI stops being a tool for efficiency gains and becomes the infrastructure through which a company operates? The essay is worth reading in full for their nuanced take on this.
What strikes me reading it is how much further this thinking can go. Block is applying this idea to how a company coordinates. We're applying it to how a company sees the world.
At Standd, we built from a simple observation: private market investors have traditionally been forced to develope expertise reactively, looking closely at something when circumstances demand it. Our autonomous agents do the inverse. They watch continuously, generating inferred signals about portfolio companies that don't exist in any database and that no one explicitly asked them to find. These signals inform proactive research and action. And they feed Standd PI, our world model, which builds causal understanding of markets, sectors, and positions over time. What the system develops is a documented point of view about markets, risk, and opportunites — one that compounds and deepens with every passing quarter.
The firms that define the next decade of private markets won't necessarily be the ones with the fastest analysts or the most deal flow. They'll be the ones that combine a winning strategy with a compounding data advantage — one that develops iteratively over time, until the gap between what they know and what everyone else knows becomes very hard to close. That's what becomes possible when AI stops being a tool people pick up and put down, and starts being the infrastructure through which a company sees the world.
jack@jack
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