How AI Is Transforming Governance and Workflow Automation in the Enterprise - with Tsavo Knott of Pieces

**Daniel Faggella** (0:12)
Welcome everyone to the Emerge AI in Business Podcast. Today's guest is Tsavo Knott, CEO and co-founder at Pieces. Pieces is an AI memory platform that captures and structures context across the tools organizations already use, giving teams shared visibility into institutional knowledge, decisions and context, so nothing important gets lost. Tsavo joins Daniel Faggella, Emerge CEO and Head of Research on today's episode to examine how AI is reshaping individual contributor roles and the operational realities come with teams working across broader surfaces of work. He explains how fragmented context scattered across tools and personal systems is slowing execution and why enterprises need a unified substrate for capturing and retrieving the day-to-day details that drive decisions. Today's episode is sponsored by Pieces. According to Edison Research, 79% of Americans listen to online audio monthly, an estimated 228 million people. Podcasts offer a rare opportunity to capture 20 plus minutes of attention with VP plus leaders in America's largest enterprises. Emerge reaches 1 million listeners every year. Learn more about how these conversations drive pipeline for AI solution providers. Download our media kit at emerge.com/ad1.
That's enerj.com/ad and the number one. Now the conversation with Tsavo.

**Daniel Faggella** (1:50)
So Tsavo, welcome back to the show.

**Tsavo Knott** (1:52)
Dan, thanks for having me. How are you doing?

**Daniel Faggella** (1:54)
Doing well, man. I'm glad to be able to dive in. AI has moved exceedingly fast in these last 18 months or so, since we've had a more long-form conversation. I kind of want to open up with a bigger picture dynamic around sort of teams, AI, productivity, communication, and let you take this where you'd like to take it, but I'm going to frame it this way. When you look at teams that are using AI now to sort of do knowledge work that involves a lot of context, whether it's in marketing, whether it's in supply chain, whether it's in development and engineering, what do you see as the most common current hurdles with kind of the LLMAI tools we're using today?

**Tsavo Knott** (2:31)
Yeah, you know, Dan, we've touched on this before, maybe in a prior episode, but I think one of the biggest hurdles that we're seeing out there is this transition of the old individual contributor into the new individual contributor, where they're not particularly working on a specific thing, and they're a specialized contributor to the overall effort, but they're becoming more of a Swiss Army knife. And I'm sure that you've talked about this concept of, you know, the Swiss Army knife individual within a company starting to wear more hats, solve different problems across a variety of surface areas. And I think the biggest thing is that with AI and with agents, people have the capability now to not only solve a particular task in their domain that they're perhaps comfortable with, faster and with a higher level of efficiency, but they're also able to switch over and cross over to other different domains, right? So I think one of the biggest things is that people are moving away from, and they'll have to move away from this concept of me, myself, and my work, to me, myself, and the delegation of work to a variety of sub-agents or agents to accomplish a variety of tasks. And so I think probably the largest hurdle that's quietly going on in companies right now is everyone is becoming a PM, in a sense, right? A PM over a series of agents, a series of specialized or generalized agents to accomplish tasks. And so I think that's the biggest thing is context switching is a side effect of this broader capability that individuals now have in this world of AI. So I think that's the biggest thing is just people are doing more across more surface areas.

**Daniel Faggella** (4:08)
Yeah, there's a few. So you're touching on, I actually haven't heard it framed this way, but I'm going to put the related and collected ideas on the table, see what your response is. You're talking about old individual contributor model to new individual contributor model. I would agree there's a sea change happening, and many companies are already there, but they haven't labeled it. They're just noticing work shift. Few ways that I've almost been like mentally conceiving of this and that have come up in other conversations with a data robot, a Google Cloud, other leaders we've had on. What is sort of like this notion that departmentally, so company-wide, maybe there's a big meta brain, but it's definitely made of sub-brain components, not unlike the brains you and I have, where sales department, whatever, everybody working in sales is working to close their deals, but they're also working to add context into a bigger system. So it could be, so now when the sales manager's like, okay, well, where do we stand after the last call with the Walmart account? They can just ask the system in like 85, maybe 95% of the time, get all the detail they need, including the exact parts of the conversation of what came up, just kind of snap in front of them.