To, to answer the question you've asked.

To answer the question.

But they're not, not every token's actually equal.

And you know, if you've used a really advanced model like 5.6 from, from OpenAI, you'll know actually, wow, the code it writes is a lot better than the previous model.

So it's not exactly the right analogy, and that's the thing is actually I think what we're seeing is for a lot of tasks, it turns out these frontier models from OpenAI and Anthropic are actually just better than these open weight models.

And I think it's important for the labs in the United States for any-- If you just think about what do you want from a model, you might want it to be fast for some tasks.

... who don't know?

Yeah.

Are you seeing some of the changes in how things are billed, how enterprises are spending start to impact the legacy players? What does it say about sort of where we are in the cycle right now?

There is a ton of uncertainty right now.

I love the CEO of IPM.

I believe in that company.

But I think the market right now, there's almost contradictions.

You have all this excitement about AI and token maxing.

And the CFO has said, who the heck's buying all these tokens? What's going on with our token bill? And then on the other hand, you have a lot of people saying, where's the value from this AI? The approach that we at CIRA and others are taking, I think, is roughly the answer.

How does that fit into, I guess, both the Frontier Labs strategy and growth, and then the opportunities on the software side where you're also playing?

Yeah

... from Spanish, Mandarin, Tagalog, you know, like, go down the list, really, really expensive to do.

Now you can do it at scale.

Each new language, the marginal cost is effectively zero.

And then the other part of it is, for good reason, as I said, there's just a, a really high compliance bar for technologies to be available.

And as a consequence, if you look at, you know, what waste management, or just pick any private company, they can go off and get the best of breed solution for any given technology problem they have.

That is not something all federal agencies can do.

Hmm

[laughs]

Yeah.

One wasn't...

I, I had the same question I didn't get to.

I was like, "What are you doing that you need two?" But that's the whole thing.I, you know, I think this is really interesting, and I think it's really giving people direct access.

You know, one of the things you can do in Sierra is you can ask questions like, "Hey, what is irritating people about our returns policy?" Kind of those qualitative questions that would previously maybe require a focus group.

The agents in the Sierra platform will actually sample conversations, look for low CSAT conversations, use large language models to synthesize actually what's going on, and give you a report like ChatGPT Deep Research.

... to Sierra at all? Do they move the needle? Uh, you know, d-- I, I'm curious what role you think they play in, like, a truly elite enterprise GTM.

Why is it that the managers trying to implement GenAI often feel like they're banging their heads against a brick wall?

When a technology is new, whether it's the mainframe or the PC or eventually the advent of the Internet, there's not a lot of off-the-shelf solutions to leverage that technology.

So, you know, when mainframes and PCs came out, a lot of companies had to build everything from scratch....

And then the first generation of software companies essentially amortized the research and development costs of building that software across thousands or hundreds of thousands of clients, which is just rational.

So you end up where, you know, every company in the world built their own, and then you transition to, you know, licensing software from these software vendors.

And then the internet comes out, and there was an article in Wired in nineteen ninety-seven, ninety-eight, that time period, and it was about a set of banks that were spending between twenty and fifty million dollars to make their websites transactional, which, if you read the article, basically meant adding a login form, so you could actually see your stuff and not just like information about the bank.

Which is something a, you know, someone who goes to a coding boot camp could do in a weekend, or now with tools like Codex and Cloud Code, you can do just by prompting.

Mm-hmm.

You still think that companies need to be able to do this.

It may be true.

Uh, you know, it's interesting.

I think it's very hard to predict the second-order effects of the marginal cost of software development going down, um, so dramatically, but it's interesting.

So I was, uh, for our, uh, first customer conference at Sierra, I was doing research, and I was looking up in the Wayback Machine old Wired articles, and I found one from, I think it was 1997, and the article was about banks failing to launch websites with login forms and spending tens of millions of dollars with consulting companies, and how hard it was to go from read-only to enabling someone to log in to, like, check their balance.

It's trivial now.

You could vibe code that probably during the course of this podcast.

But we're-- for the sake of this thought exercise, we're just burning it down and starting from scratch.

But do you think, talk to me about that.

I have such a nuanced point of view on this, because it is decidedly not simple.

Uh, so broadly speaking, I really like the spirit of founder mode, which is just having deep founder-led accountability for every decision at your company.

Um, I think that that's how great companies operate, uh, and when you, you know, proverbially make decisions by committee or you're more focused on process than outcomes, um, that produces all the experiences we hate as employees, as customers.

You know, that's the proverbial DMV, right? You know, it's like process over outcomes.

Um, and then similarly, uh, you look at the disruption in all industries right now because of AI, you know, the companies that will recognize where things are clearly going to change, like everyone can see it.

It's like a s- you know, slow motion car wreck.

How do you use that at work?

Oh.

... extensibility model they developed.

Here's the big picture.

I mean, if you just think of any consumer brand, uh, every new platform brings distribution channels, right? The, uh, you know, mobile had app store, the web had portals and then search.

In the age of AI, it's agents, it's ChatGPT, it's Gemini.

A lot of our customers are thinking about, what do we want our presence to be on our own properties? What do we want our presence to be when people are starting from ChatGPT? We think just the world of channels are changing now.

It's going from chat and phone and your website, to chat and your phone and your website.

Hmm.

Like, it's, it's very satisfying.

Well, I appreciate you saying.

And you know, it does all have to start with the product though, you know, 'cause certainly I would say-My guess is, the way I think of Sierra is, we have the best product, but because we have a founding team that's sort of been there and done that, we're not, like, a hugely risky bet, you know? We know how to work with large companies.

We're not gonna show up and be learning from, you know, first principles how to engage with a large bank or a large health insurance company.

And that's a unique value proposition, because right now, most of the incumbent technology platforms, their products don't really work.

And so, you really want to use a best of breed product right now, and I think our value proposition is we are a best of breed, I believe the best of breed product in this space, but we also know how to, like, work with complex companies.

You know, we're gonna show up with as many people necessary to help you be successful, as opposed to just throwing a product over the wall and saying, "Good luck to you." And, uh, so that I think, I, you know, certainly our reputation helps, but at the end of the day, it's the quality of the product that really matters here.

Uh, h- how'd you land on that and w- uh, what does it say about the, the usage of that fund, how in capital intensive your business is, the state of the markets right now? Just take me through the, the thesis for the round.

So, what is unique about how you work with a customer versus, like, how you would have done it at a, at another company before?

I'll start with our business model because I think it helps answer your question, which is, um, one of the things that we do differently than traditional software companies at Cyra is we charge only for outcomes.

So, for most of our customers, that means when the AI agent autonomously resolves the case that you called about or chatted in about, there's a fee for that.

And if the agent has to transfer to a real person, it's free.

Uh, we really like this as a business model, and I think it will become the standard business model for agents because, uh, the word agent comes from agency, and the principle of it is some degree of autonomy.

And, uh, I think most of the most sophisticated agents will actually start and complete a task, whether it's generating a new lead for your sales team, or solving a customer service inquiry, or, uh, doing a legal analysis, uh, for an antitrust review, whatever it might be.

And if an AI agent isn't just helping a person be more productive but actually accomplishing a task, why not just pay for a job well done? Uh, and if you look at most of your companies, the, if you have a job where the outcome is measurable, like sales, you tend to pay a commission, right? There's not, uh, just a salary.

(laughs)

What mindsets or habits or just ways of working have you worked on building in yourself that you think have most contributed to you being successful in such a variety of roles and levels?

Yeah.

It's actually something I am proud of.

I, I like the fact I've worn different hats.

It's actually amusing when I meet colleagues that I've known from one of those jobs, they'll often think of me through the lens of that job, you know? And so, uh, you know, I'll go to meet folks from Facebook, and they think of me largely as an engineer.

They'll-- If I meet folks from Google, they think me largely as a product, you know, person.

At Salesforce, you know, a lot of the folks there interacted with me as like a, for lack of a better word, a suit.

Mm-hmm.

How did that change how you went about integrating that company into the Salesforce culture?

I'll talk abstractly and I'll talk to you about some specific acquisitions, too.

But first, I, I think I tried to approach it with more empathy, um, and more realism.

You know, uh, one of the nuanced parts about acquisitions is there's the period of, um, doing the acquisition, there's sort of the period, uh, after you've decided to do it and doing due diligence, and then there's the period when it's done and you're integrating the company, and sort of the period after.

One of the things that I have observed is that while a company's doing acquisitions, often the part of deciding to do it is a bit of a mutual sales process.

Um, uh, you're trying to find a f- fair value for the company and, and there's some back and forth there, but at the end of the day, there's usually some objective measure of that, um, influenced by a lot of factors.

But, but there's some fair value of that.

How do you use that at work?