“We have some templates and some examples of security review agents in the open source... you can actually incorporate as roles in your harness to then do that end-to-end security review”
“Even if every decision, even if everything is reviewed by a human, you're getting a lot of value... then you can start saying, OK, I'm going to review one in five or one in two even. Right. You've cut your effort by two.”
The Leadership in Insurance Podcast - Insurtech & Innovation · Olivier Lafontaine: Equisoft’s Approach to AI and Insurance Modernisation.
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What was described
Start autonomous agent pilots by reviewing every decision manually, then progressively reduce human review to 1 in 2, 1 in 5, 1 in 10, or even 1 in 100 cases
review every decision → then 1 in 2, 1 in 5, 1 in 10, 1 in 100; effort cut by half
Said nearby on the same subject
“I went away with all of my reviews, 20 years of reviews… I read every one. All the negative reviews. I spent two days looking at them.”
“Authority comes down essentially to what decisions am I choosing as the human in the loop to make? What decisions am I giving to the agent to make? And what decisions can the AI agent never make?”
“Agents can be better at structured extraction than humans… if you have a harness where the agent is not only extracting the information but correcting itself, reviewing its outputs, you kind of get to unbalance that in the favor of perfect accuracy”
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