Aug 28, 2026 · 1 hr 3 min · 12 segments
Enterprise AI isn't failing because agents aren't smart enough — it's failing at work design. Reejig CEO Siobhan Savage joins Meg Bear and Amy Wilson to reframe AI transformation for the enterprise…
Siobhan SavageGuest
Meg BearHostAmy WilsonHost
One of the things, so Amy and I spend a lot of time being here in Silicon Valley and being in the tech industry.
And what I love about this conversation is the just sort of pulling back to the reality of how this is very different storyline, maybe the same plot, but a very different story arc.
And so what I love about the way that you're approaching it with Rejig is to not only bring forward a path to a transformational approach, but also bringing a data lens to that story so that people can understand where they get their highest leverage and highest value creation along this journey versus just doing these really broad brush things like token maxing or how many agents do we have or counting use cases or whatever, right? This is a real sign of market maturity and I'm just curious, what has been your learning arc along this as you take a data-informed approach with your customers? What are the leading customers discovering on this journey?
The point of being in Silicon Valley and the startups, I'm also the other side of your coin because I'm building a billion-dollar company with 100 people.
And even that, there's a little bit of fugazi in my mind of what's real and what's not.
The one thing that I have seen... to be just kind of crazy about that world as well is like that token maxing thing.
Like whose idea was it to say, here's a leadership board and we're going to celebrate the people that spend the most amount of money in our company because that's the definition of someone who's AI first.
that like and then and here's the thing that's really like actually even more stupid about this situation and then months later everyone shuts it down and then employees get scolded for even doing that and it's like oh my god like it's just mental
It will literally be a book that is written by somebody soon where it's like, here's all the things not to do.
One of the things, so Amy and I spend a lot of time being here in Silicon Valley and being in the tech industry.
And what I love about this conversation is the just sort of pulling back to the reality of how this is very different storyline, maybe the same plot, but a very different story arc.
And so what I love about the way that you're approaching it with Rejig is to not only bring forward a path to a transformational approach, but also bringing a data lens to that story so that people can understand where they get their highest leverage and highest value creation along this journey versus just doing these really broad brush things like token maxing or how many agents do we have or counting use cases or whatever, right? This is a real sign of market maturity and I'm just curious, what has been your learning arc along this as you take a data-informed approach with your customers? What are the leading customers discovering on this journey?
The point of being in Silicon Valley and the startups, I'm also the other side of your coin because I'm building a billion-dollar company with 100 people.
And even that, there's a little bit of fugazi in my mind of what's real and what's not.
The one thing that I have seen... to be just kind of crazy about that world as well is like that token maxing thing.
Like whose idea was it to say, here's a leadership board and we're going to celebrate the people that spend the most amount of money in our company because that's the definition of someone who's AI first.
that like and then and here's the thing that's really like actually even more stupid about this situation and then months later everyone shuts it down and then employees get scolded for even doing that and it's like oh my god like it's just mental
It will literally be a book that is written by somebody soon where it's like, here's all the things not to do.
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