Using AI as a Coach to Improve Workers in Real Time

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The initial UX experience should involve a human in the loop, acting as a co-pilot or coach. The concept of coaching networks involves using AI to coach workers on how to do their jobs better in real time. Workers receive messages from a bot suggesting actions to improve their tasks, and they have the ability to accept, reject, or modify these suggestions. The system tracks the real-world outcome, such as whether a sales deal closes and how quickly it closes, to improve future suggestions for all users. The human in the loop plays two important roles: ensuring the accuracy of the answers given and adding their own insights to the system. By continuously evolving and making the system better through edits, tweaks, and insights, the human contributes to the overall improvement of the system for everyone.

How do you build defensible business value in an era when, as AngelList CEO Avlok Kohli said on our last ACQ2 episode, the “cost of intelligence is going to zero”? Longtime friend of the show Jake Saper and his partners at Emergence Capital have been refining their thesis for this brave new world of Generative AI in B2B, and we sit down with him to discuss. We cover topics including:

When do exactly correct answers matter, and when do they not?
When are human-in-the-loop systems necessary?
When do startups have an advantage vs. incumbents, and vice-versa?
Where can companies capture value on a durable basis?
When do you need proprietary data in order to be defensible?

Whether you’re building or investing in existing businesses from the “pre-AI” era or brand new startups that are native to GPT, this episode has plenty of takeaways you should consider. Tune in!

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