A Baconian approach to the mostly Aristotelian corporate AI. And what that means for your business
TL;DR
Large language models are amazing and extraordinary reasoning machines. However, companies need a new breed of systems that can act, observe consequences, and learn from reality as it happens. Large language models are amazing and extraordinary reasoning machines. However, companies need a new breed of systems that can act, observe consequences, and learn from reality as it happens.
Nauti's Take
The distinction has a practical advantage as a planning grid: sorting pilots by whether a system merely answers or also acts and measures the consequences quickly reveals which use cases have a feedback channel at all. The limit is the evidence base, because the piece argues at the level of principle and names neither products nor metrics.
For small teams the first step is to establish what feedback signal an agent actually receives before budget goes into autonomy.
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