Eoghan McCabe

You know, the reality is that adoption of new technology takes far longer than we always imagine. We were the first to come out with an AI agent that would do customer support for you, like actual conversations with customers and closing tickets. We now have, forgive the fucking pitch, we now have the highest performing AI customer service bot.

You look at everything that's on the market, they can't resolve tickets at the rate we can. The average resolution rate of our bot is now approaching 50%. How is that, Owen?

You look at everything that's on the market, they can't resolve tickets at the rate we can. The average resolution rate of our bot is now approaching 50%. How is that, Owen?

You look at everything that's on the market, they can't resolve tickets at the rate we can. The average resolution rate of our bot is now approaching 50%. How is that, Owen?

Yeah, it's all the existing data sources. With intercom, it's your historical conversations that your human reps are also having. But what's really interesting and what's key to understanding how AI is going to develop, and we can go back to your questions if I manage to remember, is that building domain-specific AI systems requires a phenomenal amount of work on top of these LLMs.

Yeah, it's all the existing data sources. With intercom, it's your historical conversations that your human reps are also having. But what's really interesting and what's key to understanding how AI is going to develop, and we can go back to your questions if I manage to remember, is that building domain-specific AI systems requires a phenomenal amount of work on top of these LLMs.

Yeah, it's all the existing data sources. With intercom, it's your historical conversations that your human reps are also having. But what's really interesting and what's key to understanding how AI is going to develop, and we can go back to your questions if I manage to remember, is that building domain-specific AI systems requires a phenomenal amount of work on top of these LLMs.

Of course, yes, over a decade or two, the LLMs will get powerful enough that they will disrupt away all of these detailed intricacies that we've built. But Finn, our AI agent, for example, is the product of over 100 unique experiments to figure out how exactly to understand customer questions and resolve tickets. There's patented components to it.

Of course, yes, over a decade or two, the LLMs will get powerful enough that they will disrupt away all of these detailed intricacies that we've built. But Finn, our AI agent, for example, is the product of over 100 unique experiments to figure out how exactly to understand customer questions and resolve tickets. There's patented components to it.

Of course, yes, over a decade or two, the LLMs will get powerful enough that they will disrupt away all of these detailed intricacies that we've built. But Finn, our AI agent, for example, is the product of over 100 unique experiments to figure out how exactly to understand customer questions and resolve tickets. There's patented components to it.

I think there are somewhere around seven different LLMs intricately connected together. There's homegrown AI, and just a lot of very detailed prompt engineering and massaging to make it highly effective at closing tickets. When we first released our AI agent, the average resolution rate was in the high 20s.

I think there are somewhere around seven different LLMs intricately connected together. There's homegrown AI, and just a lot of very detailed prompt engineering and massaging to make it highly effective at closing tickets. When we first released our AI agent, the average resolution rate was in the high 20s.

I think there are somewhere around seven different LLMs intricately connected together. There's homegrown AI, and just a lot of very detailed prompt engineering and massaging to make it highly effective at closing tickets. When we first released our AI agent, the average resolution rate was in the high 20s.

So that's the rate at which it successfully closes tickets when it gets involved in the conversation. And now, like I said, it's approaching 50%. I think Zendesk is still high 20s. And so it just takes a long period of time and a lot of work to build all of the functionality on top of the LLMs to make them really, really great at these domain-specific things.

So that's the rate at which it successfully closes tickets when it gets involved in the conversation. And now, like I said, it's approaching 50%. I think Zendesk is still high 20s. And so it just takes a long period of time and a lot of work to build all of the functionality on top of the LLMs to make them really, really great at these domain-specific things.

So that's the rate at which it successfully closes tickets when it gets involved in the conversation. And now, like I said, it's approaching 50%. I think Zendesk is still high 20s. And so it just takes a long period of time and a lot of work to build all of the functionality on top of the LLMs to make them really, really great at these domain-specific things.

That's why these AI application companies are going to win. That's why they're going to become so big, because I don't think, at least in the next five, 10 years, that any of the AI labs are going to build all the domain-specific stuff.

That's why these AI application companies are going to win. That's why they're going to become so big, because I don't think, at least in the next five, 10 years, that any of the AI labs are going to build all the domain-specific stuff.

That's why these AI application companies are going to win. That's why they're going to become so big, because I don't think, at least in the next five, 10 years, that any of the AI labs are going to build all the domain-specific stuff.

Yeah, I think that's right in the fullness of time. And again, if you held on to your stock in fax companies, you'd be crushed. But for the first 10 years, you would have made a fucking fortune. So in technology, it's all about timing and it's all about waving success of growth cycles and riding the trends in that moment in time. And then you must reinvent yourself and kill yourself.