SignalLabs + BrassRing = Signals of Attention

Did Signal Labs Just Buy HR's Most Beloved Antique? (cough) BrassRing

In this episode of "HR's Most Dangerous Podcast," Chad and Joel sit down with Raj Ronanki, a man whose corporate philosophy stems directly from watching Star Trek in India and who somehow convinced investors to give him money so he could acquire BrassRing a piece of HR software so ancient that 65% of the Fortune 500 are allegedly still paying the bill simply because no one remembers who authorized the original 2002 invoice.  

Jokes? Maybe...

Chad & Joel try to decipher the ultimate tech-bro gobbledygook: "systems of attention," "attention infrastructure," and building a "digital twin of the enterprise". Raj attempts to explain why a newly launched startup with three whole employees listed on LinkedIn decided that buying a 25-year-old software relic was the key to preparing humanity for an AI-agent future.  

Key Highlights & Hot Takes:

• The Star Trek Ethos

• Hiring Bots Like Humans

• The Brass Ring Mystery

• "Nunya Business" Financials

• Solving Boring Compliance

  
  

Will Raj’s "world models" revolutionize workforce management, or did Signal Labs just buy a really expensive digital paperweight? Tune in to find out!  

PODCAST TRANSCRIPTION

Joel Cheesman (00:24.528)

yeah. It's the podcast that New Wave Chick and Social Studies class warned you about. It's the Chad and Cheese podcast, everybody. I'm your co-host, Joel Cheeseman. Joined as always, Chad Sowash is riding Shotgun. As we welcome Raj Ronanki to the show. He's the founder and CEO of Signal Labs. Who the hell is Signal Labs? we're going to get to the bottom of that. Raj, welcome to HR's Most Dangerous Podcast.

Chad Sowash (00:31.214)

I remember her.

Chad Sowash (00:48.358)

We'll get into that. We'll get into that. yes. yeah.

Raj Ronanki (00:53.56)

Thank you, gentlemen.

Joel Cheesman (00:56.216)

So I I'm gonna go on a limb and say a lot of our listeners don't know who you are. we'll get to the signal labs thing in a second, but give us a sense of of virage. What's what's what's the ethos?

Raj Ronanki (01:07.992)

Well the ethos gentlemen is that I'm I grew up watching Star Trek in India. And so that kind of forms the the root of my

Joel Cheesman (01:16.994)

I did not have that on my bingo card. Did you Chad? I did not have Star Trek. Okay.

Chad Sowash (01:20.158)

I did not. No, no.

Raj Ronanki (01:22.538)

So so so that's the root of everything I do in life. what I do at work and my my ethos in life in general is is one of optimism and tech is the utopia. Of course there's always gonna be good and evil in everything, but for the most part I believe that technology is gonna be making humanity progress faster and further and better than before. And that's sort of the the philosophy I've applied to everything that I've done at work, including at Signal Labs, and we'll get into that in a second.

Joel Cheesman (01:52.304)

Good and evil in everything, Chad. Good and evil in everything.

Chad Sowash (01:53.191)

Well, I mean Yes, I mean and who didn't want to hook up with a hot green chick? I mean, seriously. Star Trek, I mean that was it, man. That was it. That was it. Yeah.

Raj Ronanki (02:06.934)

I certainly do.

Chad Sowash (02:13.838)

Okay, okay, cheeseman. okay, Raj. So the out of left field. We haven't we have not heard the name brass ring in a very long time. We'll get to that. so so the the acquisition of brass ring came out of of left field. Joel and I have been in this industry for twenty five years. We grew up with with grass brass ring. so so the question yes, yes. The

Raj Ronanki (02:18.947)

Yeah.

Joel Cheesman (02:31.651)

Mm-hmm.

Raj Ronanki (02:32.962)

Mm-hmm. Yeah.

Joel Cheesman (02:35.299)

And we've covered some weird deals. We've covered some weird shit. This is this is up at the top.

Raj Ronanki (02:38.178)

Mm-hmm.

Chad Sowash (02:42.076)

And and this question comes from the heart. Why the hell did you buy brass ring?

Joel Cheesman (02:45.06)

Yeah.

Raj Ronanki (02:46.133)

Ha ha ha.

Well, I mean, t to to be honest, other than occasionally using Brass Ring over the years, you know, I didn't really know much about the company either. Yeah. And well the the reason we got intrigued by it is as we were talking to some of our customers, and they happened to be in the HR tech space, they just sort of bought up Brass Ring as, hey, this is what we use for recruiting and hiring and talent fulfillment.

Chad Sowash (02:57.072)

Yeah.

Raj Ronanki (03:15.134)

And the context in which we were having that conversation was well, what's gonna happen when you're no longer just filling headcount, but you have to account for for capacity. And you have to think about hiring agents, you know, putting agents, AI agents side by side with humans. And then what if down the road you're you're deploying robots at scale? How are you gonna manage all of that together on one system, on one ledger? And and there it was like

We don't know. Like we are the HR department. We are happy with workday and success factors, Oracle, meh.

Chad Sowash (03:51.591)

Do you think we're gonna hire agents like people though? I mean, this feels more like a contractor business deal than hiring agents like people. I mean, how do you how do you see that happening? Because that's the first time I ever thought of I understand this whole agents working in tandem with with humans, whether they're created in-house or they're they're used by a company like a brass ring or a paradox or a smart recruiters or something like that. but

this whole hiring of agents thing. It's the first time I've ever heard anybody say that. Get get tell talk a little bit more about that.

Raj Ronanki (04:24.974)

Well, I know so Nvidia's see Jensen Wong said I think there'll be like hundred agents to to one human or something along those lines. So it would stand to reason, right? So that if we're creating these these millions, if not billions of agents that eventually and even now they're already on marketplaces like AWS's marketplace, Salesforce's marketplace, you know, ServiceNow's marketplace. So if they're already on marketplaces,

Chad Sowash (04:33.648)

Okay.

Chad Sowash (04:53.564)

Mm-hmm.

Raj Ronanki (04:53.718)

How is that any different than like indeed.com or LinkedIn.com, where essentially people are saying, this is what I do, this is what my experience is, this is what I would like to do. agents probably have a similar spec that says, Hey, here's what I was created to do, here's what I'm good at, here's my track record. Now, if you want to deploy me into your context, tell me a little bit about what I need to do and what systems I need to connect to, and you you sort of go through the, you know, security processes to like like you would a background check and say, All right, you're ready to go.

To deploy them into the workforce.

Joel Cheesman (05:25.433)

Does does brass r does brass ring really have sixty five percent of the Fortune five hundred? And if they do, do those companies know they're still clients of Brass Ring?

Chad Sowash (05:33.508)

Who

Raj Ronanki (05:33.839)

Well, I think many don'ts because it works so ubiquitously and hidden in the seams of HR tech systems. Yeah, and and and when we and when when we reached out to them, they're like, What, wait, we're still paying this bill? Like what are we paying this for? And then, you know, they check with the the HR, you know, tech leaders that are sponsors for the program and they're like, Yeah, this works great. Why would we ever change it? So yeah, there's still absolutely, yeah.

Joel Cheesman (05:42.039)

just been getting a bill since two thousand and two and they're just paying it. Okay.

Chad Sowash (05:45.062)

Yeah. It's what's this brass ring thing?

Joel Cheesman (05:58.916)

So could could be a huge unlock for you, a huge introduction. All right. I I like that Chad started with brass rain because that's where most of our audience are anchored. I'm gonna go to Signal Labs. You laun you launch in April of this year. You have twenty five million in backing from Lightspeed.

Raj Ronanki (06:03.576)

Yeah. Yeah. Yeah. Yeah.

Joel Cheesman (06:21.461)

And and then you buy one of the I don't know, Royal Old Krusty Company. It like it's just really weird. What tell what is up with Signal Labs? What do you guys do? You have some really weird gobbledygook language around systems of attention, attention infrastructure. How do you buy brass ring with twenty five million? Like, help me understand what is Signal Labs and what are you doing?

Raj Ronanki (06:32.142)

Mm-hmm.

Chad Sowash (06:40.152)

yeah.

Raj Ronanki (06:49.762)

Yeah. Well, let's unpack that. So so Signal Labs was formed in in January. That's when we we created the company. but the idea behind Signal Labs is something that's been percolating in my head for, you know, a few years prior to that. It it goes all the way back to when Google wrote the paper, Google Research wrote the paper called Attention Is All You Need, which was famously the paper that led to the this wild dash in the that we're seeing with generative AI and all that's happening with

Joel Cheesman (06:56.59)

Yep.

Chad Sowash (06:56.828)

Mm-hmm.

Chad Sowash (07:11.024)

Mm.

Raj Ronanki (07:19.552)

Of OpenAI anthropic and the open open weight models across the world. And in that scene, there's always been sort of a kernel there that says, well, if the level of automation sort of increases to the level, you know, where humans have to actually think about what they need to do every day, then what institutions, enterprises, companies need to pay attention to becomes almost what differentiates you.

Given your unique sort of tribal knowledge of a process and a set of systems that allow you to be competitive, then the institutional attention that's directed to which problem should I solve today, which opportunity should I go after today, is perhaps the most important decision a set of leaders in a company can make. So to create that, we essentially called out a new category of software that needs to be created that we call systems of attention.

Chad Sowash (07:53.137)

Mm-hmm.

Raj Ronanki (08:15.34)

And we've got a whole science and IP around how to go create the attention so that if Chad and Joel want to say, what are the three things that I should be working on this morning? We don't have to guess at that. We can use science and AI to go create those three things and put it at the top of your inbox. So that's the very mission of that of our company. And the second part of your question was, well, how does brass ring fit into all of that? So if you think about

Companies now starting to specify missions and objectives for what they want to do versus just hiring 10 people or, you know, filling some butts and seat. Then if you start with the mission of look, this is what I want to get done, then that mission, whatever it happens to be, increase revenue, increase margin, retain more customers, acquire, grow, et cetera, has to be done by a set of people and agents. And we believe that brass ring has the people side of it covered.

Chad Sowash (08:46.14)

Mm-hmm.

Raj Ronanki (09:09.868)

We be we believe we bring a lot of expertise in AI and agentec and how that's going to shape the future of work. So we want to put those two things together and say, look, brass ring becomes the ledger on which all work is managed based on a set of mission parameters as opposed to just purely job specs. And then incidentally, the the the sixty plus percent of the Fortune five hundred that are still on brass ring, we can go talk to them and say, look, is this a problem for you? And if so, we can solve it. And so far, all the doors we've knocked on have said

Chad Sowash (09:31.792)

Mm-hmm. Yeah.

Raj Ronanki (09:39.508)

Absolutely, yes. Come talk to us. You know, we've got a design partnership that we've launched with five of our customers. Mm-hmm.

Joel Cheesman (09:41.975)

All right. How how twenty five million explain to me how twenty five million buys brass ring.

Chad Sowash (09:48.806)

Clearance rack.

Raj Ronanki (09:48.825)

So twenty five million is in fact the contract value that we launched with. So when we launched, we had, you know, a few marquee customers that said we want Signal Apps to be our design partner and come, you know, sort of create this for us out of the gate. So that's the contract value that we launched with. Lightspeed and other investors gave us ten million in seed funding. You know, so you're wondering, you know, how did we make this happen? So it's a combination of cash and stock.

Joel Cheesman (10:10.819)

Yeah.

Raj Ronanki (10:15.368)

And so Infinite, which was which was selling brassing, also made a bet on Signal Labs saying, Yeah, we believe in this future and we believe that this asset, which you know was sort of one of the many things that they worried about, could be front and center in Signal Labs and therefore amplify the value for them.

Joel Cheesman (10:15.799)

Mm.

Joel Cheesman (10:29.433)

Mm-hmm.

Joel Cheesman (10:34.799)

So tur terms weren't disclosed in the PR, but I gotta ask, what were the terms of the deal?

Chad Sowash (10:35.26)

Mm.

Yeah.

Raj Ronanki (10:40.866)

Well, they weren't disclosed for a reason. Yeah.

Joel Cheesman (10:42.031)

I I had to do it. I sorry, Raj, I had to do it.

Chad Sowash (10:42.684)

Which means nanya. Nunya business is what he's saying. so so it in the future of work section on your website, it says the cost of missed signals is skyrocketing. so in the HR space, I mean, what what are the signals that are being missed?

Joel Cheesman (10:49.315)

Nanya, yeah.

Raj Ronanki (10:57.55)

Mm-hmm. Mm-hmm.

Raj Ronanki (11:04.246)

It I mean it's it's like what talent should we be hiring? You know, where is the workforce going to be in five years from now, two years from now, you know, eighteen months from now? all that requires thoughtful planning, ahead of time so that you're saying, Look, you know, these two thousand job categories have to be classified as something else and they're gonna be automated. but those people that are sort of gonna be in those seats are gonna be still super valuable. Yeah, I for one believe that AI will be a net ad to jobs as opposed to a subtraction.

Chad Sowash (11:22.778)

Mm-hmm.

Raj Ronanki (11:34.167)

So if every company is is proactively thinking about look, let's say I have ten thousand people working for this company and you know, two thousand of those jobs, the work they do, could be done by AI. Then those two thousand people, what should they be deployed to do? And what skills do they need? How do I retrain them? And then what can we use then to grow the company with that workforce? That's the signal that most people aren't tracking.

They're just reacting to, okay, well, you know, I have to do this riff and lay off five hundred people. Let's put together severance. So it's more more you know, HR is at the far end of the sort of the spectrum of, you know, strategy has been defined, you know, automation and other AI sort of strategies are being implemented. And now you're saying, All right, look, HR, we've got to, you know, right size the workforce, get the work. So that's really just being handed a

Chad Sowash (12:19.952)

Mm-hmm.

Raj Ronanki (12:28.014)

you know, sort of an order to go do something versus being proactive thought partners to shaping, you know, the future of the workforce.

Chad Sowash (12:34.044)

Well, Brass Ring's not going to give you the data on how jobs are evolving. They're just going to show you what jobs are being taken by by AI slash agents slash whatever. What partners are you working with to actually shape that or find those signals so that you can provide the necessary L and D elements so that those individuals who you you don't want to kick out the door, you want to get them shaped and developed into a

Raj Ronanki (12:38.488)

Mm-hmm.

Chad Sowash (13:02.372)

new workers within your organization, where are you getting those signals from? Because again, this sounds like a full ecosystem and there's no way brass ring provides that piece of the signal data signal.

Raj Ronanki (13:13.474)

They don't. Yeah. So so that's where the Signal Labs team complements what Brass Ring does. So we get hired on the front end of a process. And that front end of process could be, look, and if we've got this you know, customer relationship management function that has Salesforce on the front end, we're not growing, we're not retaining our customers. Can you read the signals and tell us how to grow and how to retain our customers?

Chad Sowash (13:18.416)

Mm-hmm.

Chad Sowash (13:29.02)

Mm-hmm.

Raj Ronanki (13:39.191)

So we would go put together a blueprint for all the signals that are necessary in order for a company's CRM system to function at its highest, in order to ultimately achieve the the objectives of a good CRM system, i.e., growth, retention, profitability. In doing that, we have to put a blueprint of everything upstream and downstream of what needs to happen, how the sales teams need to work, you know, what new talent needs to be hired, how the workforce needs to be managed holistically in order to achieve that outcome.

So when we put that blueprint together, you know, browstring has a role to play in managing the workforce, documenting the skills and understanding how the workforce is going to evolve. but they're not doing everything. That's where we're building in the missing pieces to to put that full end to end blueprint together so that our customer get to those outcomes.

Chad Sowash (14:27.142)

That's got to be the hardest part though. mean, we we're hearing guys like Amanda and Altman and whatnot, and they're talking about how things are going to change and how jobs are going to change. They have no fucking clue. They can't tell you what job is going to be created, right? Because they don't know where the data is. They've never been in this space before. Two things, right? So the question is, you take a look at like the government data, that's not going to help because that's all looking backwards, right? Where are you going to find the signals? That's the hard part.

Raj Ronanki (14:30.018)

Mm? Hmm? Hmm? Mm? Hmm?

Raj Ronanki (14:41.006)

Mm.

Hm? Yeah. Yeah.

Raj Ronanki (14:49.876)

Mm-hmm. No. Yep.

Chad Sowash (14:56.412)

If you can find the signals on what I mean, because obviously Altman and Amanda, the guys who have billions of dollars, they don't know where the damn signals are. Where are the signals?

Raj Ronanki (14:56.652)

Yeah.

Yeah. Mm.

Joel Cheesman (15:05.711)

They're gonna find it in the lab chat because they're signal labs. So the lab is where the signal is. Duh.

Raj Ronanki (15:05.846)

Well, I think they're they

Chad Sowash (15:08.25)

Ha ha ha

Raj Ronanki (15:09.678)

That's right. We're we're we're we're we're we're c we're cooking it up right there on on the lab. but no, I think globally the pro the problem is much harder to answer, right? So what is right, the this the US economy has s some fifteen trillion dollars that get paid out in wages, right? So enormous amount of jobs. So we're not here to answer sort of the global job question. We're

Chad Sowash (15:11.42)

now I know. Yeah, yeah.

Chad Sowash (15:21.829)

Yeah.

Raj Ronanki (15:34.831)

We're at we're here to answer the much more local question of what happens to jobs as it relates to specific processes within the enterprise or with the collective of all and all processes within an enterprise. So we can take that and we can study that. Then we can say, look, for a billing process or accounts receivable process, a holistic finance you know function, we can say, look, what is what should this look like? What combination of AI, you know, humans, in some cases robots?

How do they all need to come together to fulfill this process to its objectives? What quality, what SLAs, what parameters, et cetera? Then you can sort of say, okay, this is how everything changes within that context. Absent that context, it's a much larger, more global problem, which people that have billions of dollars in the bank are going to go try and figure out. But we're solving it at a much more macro level with very defined sort of outcomes within a matter of weeks, as opposed to a global research project.

Joel Cheesman (16:33.423)

What's been the rollout to the brass ring clients been like? Historically, this is not a real innovative, progressive group of companies and people. Like my f my assumption would be this shit would scare the hell out of most of them. So how have you sort of slow rolled this? What's been the messaging? What's been the feedback from the brass ring folks?

Chad Sowash (16:42.074)

Yeah, yeah, they're on brass ring.

Chad Sowash (16:47.267)

Yeah.

Raj Ronanki (16:54.904)

Yeah, look, it's first of all it's been there was some trepidation, you know, as brass ring has been, you know, sold you know, a few times, as you both know. And and so they were like, Here we go, one more change and what is this gonna mean and what what do we have to change? And you know, so the first thing we did as we went out to to do the rounds with our customers is let them let them know that look, if you're happy with what you're getting, that'll continue to be the case. We're not changing the the core promise of what brass ring is gonna deliver.

Chad Sowash (17:24.304)

Mm-hmm.

Raj Ronanki (17:24.782)

And but as we had that conversation, they were like, you know what, if you did these four things better, we'd be much happier. Right. So it was like, okay, what are they? And one of the things, incidentally, was compliance. You know, we want to understand all of the compliance requirements locally, globally. you know, well but but but but look, but we can solve compliance with AI. You know, and why hasn't it been solved before? Because they're

Joel Cheesman (17:42.147)

Like I said, innovation. Yeah.

Chad Sowash (17:42.758)

God. my god. Dude, I mean

Yeah.

Raj Ronanki (17:54.317)

Literally millions of documents you have to sift through to figure out what applies to any one client, any one zip code, and sort of localize those compliance requirements. Well, fortunately with techniques we can use, we can ingest all of that and efficiently kind of create the compliance requirements for every client and make that available. So nothing sexy. We're gonna go do things like that. And then there are a few that are like, okay, so what else are you gonna do? So that's when we were talking about look, there's a future coming, even if you talk to your

colleagues down the down the aisle on strategy or tech or or finance or or anything else. They're all talking about AI. Everyone's talking about partnerships with the Frontier Labs. They've they've got thousands of people working on AI. So where's this all gonna go? Look, you know, HR's gotta get in front of this and lead the way as opposed to sort of being on the back end, you know, taking orders. So that's that conversation absolutely perks some years. Others have a roll of the eye, if you will, but you know, definitely

you know, interest in what we're doing. And as evidenced by, I can't name the customers just yet. Hopefully we can have them on the show in a few months to talk about what we're doing. But the the design partnerships have started to take place and we're kicking off the work and there's a release that's planned in October. It's called Marina. That's going to be the first of a future work release where those five design partners are going to shape what we build and how we roll it out.

Chad Sowash (18:58.938)

Yes.

Chad Sowash (19:08.497)

Mm-hmm.

Joel Cheesman (19:15.855)

And how about the employees on this? I mean, according to LinkedIn, you have a whopping three employees. maybe there's more that aren't on LinkedIn, I don't know, or LinkedIn's wrong. I mean, Brass Ring is not huge, couple hundred people, but what was the like, what? These guys are buying us? Like, I know we've been bought and sold over the years, but what? Was that a was that a a tough conversation?

Chad Sowash (19:16.272)

Yeah.

Raj Ronanki (19:40.429)

Not really. You know, at first they they thought they were buying us, and then we clarified that we were we well yeah yeah exactly. So but at the the end of the day it's it's it's just good people. they happen to be in a town that's just a hundred miles or so from where I grew up in India. their their HQ is in Bizag, in a in a in in a state called Andhra.

Joel Cheesman (19:41.453)

Okay.

Ha ha ha ha.

Chad Sowash (19:46.524)

You don't buy me, I buy you.

Joel Cheesman (19:49.005)

That's what I thought when I read it. Like, wait, is that headline right? Okay, they're buying okay. All right.

Raj Ronanki (20:10.494)

And so I could speak the language and sort of understand the roots of the culture of where you know that team was grown up. But very quickly it became about look, what can we do? And you know, for whatever reason, for the last ten years or so, there's been a lack of a vision and a lack of enthusiasm about what they were doing, because they were literally just harvesting what they were doing as opposed to thinking about what the future is. And so what we laid out was look, this is what we want to do. Are you guys ready? And my God, the first town hall we did, we had all

Joel Cheesman (20:25.604)

Mm-hmm.

Raj Ronanki (20:39.202)

The entire gameplay base, people are on occasion, whatever, they made time, showed up. And, you know, we said, right, look, this is how it's gonna work. That this isn't some spec we need to go create for you and you tell us what you're gonna do. It's just like here's the broad ambition, get to work. Like what should we work on? That's right. So that's exactly right. Nineteen ninety nine, the original internet era.

Joel Cheesman (20:54.287)

We're back, baby. We're back. Partying like it's 1999 at Brass Rang.

Chad Sowash (21:00.827)

Yeah.

like a little prints, baby. Yeah. Y2K. yeah, so that's a great Mo Green move, by the way. we don't you don't buy me, I buy you. so your website also says the data exists, the system to act on it doesn't. Have d did you see the data inside brass ring before you actually bought it?

Raj Ronanki (21:26.803)

no. Well the c the confidentiality requirements you know precluded us from from doing that. Yeah, yeah.

Chad Sowash (21:30.621)

Well, and here's and here's why I'm asking because job descriptions, garbage data, resumes, garbage data. They're both they're both unstructured, they're outdated data points. And then there's disposition codes, which provide hundreds of millions, in your case, probably billions, of garbage and bias signals. And you talk about compliance, bias scales very quickly. And then you scale that problem for how many companies that you guys support.

Raj Ronanki (21:35.532)

Mm? Mm. Garbage. Yep. Yep. Yep.

Chad Sowash (22:00.694)

you scale that problem. And they all have different hiring processes, they have different disposition code data, they all even have different ways of collecting the data. And I haven't even mentioned what the waves of fake candidate bots profiles that are out there, just garbage. So as you talk about signal and we and we hear about it all the time.

It is so hard, especially in these systems, to be able to discern between what is good and what is bad data. How are you guys going to be able to do that? I I magic is is the easy word, but there's tons of data. How can you guys grind on something like that and even understand what's good, what's bad, what can possibly be used?

Raj Ronanki (22:54.262)

Yeah, we should we should have had you on our diligence team chat on on the data quality. So all right, let's let's talk. there there we go. no, but what's what's interesting about this is that we're not as interested in the literal data of the job descriptions and the the job spec the you know the the disposition codes, even you know, the resumes themselves as much as we are in the

Chad Sowash (22:57.999)

Yeah.

Joel Cheesman (22:58.755)

He he's for sale. He's for sale. He'll he'll take your money.

Chad Sowash (23:01.308)

Depending, depending, yeah.

Raj Ronanki (23:22.306)

the singular act of the signal of you're hiring someone and the number of people you're hiring. And and then on the the flip side, what is the outcome of that hiring? How many people left? And how long did they stay? How effective were they in that? Right. So that data is available. And that's that's what we think is gold here. Because what we want to figure out is like what is causing people to hire? And

Chad Sowash (23:38.513)

Uh-huh.

Chad Sowash (23:49.969)

Mm-hmm.

Raj Ronanki (23:50.915)

what is that outcome gonna look like twelve months from now, eighteen months from now? And is what they're hiring for should should it even be a human? And and that's what we want to start the dialogue with with the hiring teams saying, look, yeah, you're hiring these five programmers for this company. Are you really the the job spec says you need to know, you know, Python and Java and and and whatever.

Chad Sowash (24:09.456)

Mm-hmm.

Raj Ronanki (24:17.73)

Well, guess what? Cursor and you know, cloud code and you know these tools do most of that. So are you really gonna need programmers to do it, or are you gonna need senior level sort of QA people to QA the code that the AI is creating? And rather than five programmers, do you really need one s super senior programmer? And is that really what needs to happen? So that's the dialogue that we wanna have. And what the browsering data shows is whether it's noisy and and of poor quality, that's all true.

But it's got like twenty-five years of those signals across right, across a hundred and seventy countries. So you go mine that. Like why did th someone hire someone in in ninety-eight? What happened in two thousand two? What happened in two thousand ten? All these these technology waves that have happened in the last twenty-five years have a correlation to to how jobs have shaped and changed and evolved. So that's what we're looking to understand, as opposed to look, you know.

Chad Sowash (24:50.116)

I know Yes.

Raj Ronanki (25:13.996)

Joe Smith has here five years of experience and, you know, blah blah blah, and is applying for this position here in this company. That's interesting, but not as relevant to to what we're building for the future.

Chad Sowash (25:25.092)

And you know that

Joel Cheesman (25:25.113)

Chad, I don't want anything from nineteen ninety eight that I was doing to come back to light. Raj, what going to to venture partners, when I was when we report on this and I looked at, you know, their portfolio has eightfold personio. I know I'm sure you don't have a opinion on why they didn't buy if brass ring was for sale. Now I think that makes more sense. If the if the press release had been eightfold buys brass ring, I can

Chad Sowash (25:28.892)

That's a bad signal. That's a bad signal.

Raj Ronanki (25:35.971)

Yeah.

Raj Ronanki (25:41.902)

Mm-hmm.

Joel Cheesman (25:53.795)

I can square that circle. will you guys be doing anything with Eightfold Personio? We have a conversation on the show that we, you know, there are pre-chat GPT companies and there are post chat GPT companies. Both of them are in the pre. You're in the post. Just curious your opinion. Like, are you are you the next wave of those companies? Do you think you'll work or partner with them or businesses like them?

Raj Ronanki (26:10.498)

Mm-hmm. Mm-hmm.

Joel Cheesman (26:20.772)

Just general thoughts on that relationship and how you're in sort of their their circle.

Raj Ronanki (26:26.114)

More partnerships, Joel. You know, so so so we we don't necessarily think of ourselves as a HR tech company. future work happens to be, you know, one of the areas that we want to solve for, but it's one of three areas that that we're focused on. And so when it comes to the to the rest of the HR tech ecosystem, you know, I think it's really we believe that a partnership approach where we're putting together kind of different best of breed kind of point solution and assemble the orchestration around it.

Joel Cheesman (26:33.858)

Interesting.

Raj Ronanki (26:55.632)

that's really our core interest, as opposed to necessarily expanding into, you know, more and more, you know, deeper HR tech capabilities per se.

Chad Sowash (27:06.498)

It one of the words that you said earlier that made Joel almost run out of the room was compliance. this, I mean, a lot of the we and we talk about it, the boring stuff is where business gets done. And you take a look at some of the big names, Workday, Eightfold, just talking about Eightfold, talk about a higher view, talking about a lot of these big systems that are getting nailed for compliance because of scaling or

Raj Ronanki (27:12.301)

Uh-huh.

Raj Ronanki (27:17.236)

Mm? Mm?

Mm, mm? Yep.

Chad Sowash (27:36.147)

decision shaping versus you know AI decision making, those types of things. you you mentioned that as like one of the number one ways you guys can can actually go after some of these problems, which I agree with a hundred percent. is do you think that's where your first product set lands is to be able to say, okay, there's tons of AI out there. We're gonna be we're gonna be the signal to tell you when it's going right and when it's going wrong.

Raj Ronanki (27:37.742)

Mm-hmm.

Raj Ronanki (27:43.918)

Mm.

Raj Ronanki (28:02.302)

Exactly right. And and the the the root basis of all of that is is one of the signals for that is the compliance rule set, right? you can do this here. The EU AI Act is is, you know, going live shortly, so you can do certain things in the EU, but you c you you can't do certain things in the EU and you can in in the US and China's a free for all. So how do we, you know, track all of that, right? So that that's really I think one of the the reasons why the boring stuff, you know, the compliance stuff also excites us.

Chad Sowash (28:09.628)

Mm.

Chad Sowash (28:31.238)

Mm-hmm.

Joel Cheesman (28:33.432)

What's what's next? Are we gonna should we expect more acquisitions in our space? You mentioned going into other industries. Is there some connection to all of them? Like what's what's the future hold? What sh what what what PR will we be looking at from Signal Labs in the next six to twelve months?

Chad Sowash (28:50.544)

Listening.

Raj Ronanki (28:52.002)

wow. Okay. So and now I'll be tracking your show. so really, really entertaining. Yeah, so the the main thing you're gonna, you know, sort of one is the October release arena. we're gonna be doing a lot of PR on that, and that's gonna we're gonna get into to why customers should care, what is it gonna do, and there's some really cool innovative things we're doing and how to how to construct that particular release. beyond that, you know, we're getting into

Joel Cheesman (28:52.856)

And we'll be watching, by the way.

Chad Sowash (28:54.446)

Yeah.

Joel Cheesman (28:57.408)

Mm-hmm.

Chad Sowash (28:57.667)

Yeah.

Joel Cheesman (29:05.37)

Mm-hmm.

Raj Ronanki (29:20.096)

a post LLM world, you know, so you said pre, you know, GPT, post GPT. I think there's a there's a post LLM world that's that's upon us. And that world is about how do all of these you know fantastic AI capabilities get applied in the real world. You know, so Jan Lakun, you know, the former chief AI scientist from Meta, you know, and others have have you know jumped on this this notion of world models, which is model the physical 3D world and then apply AI into that.

Chad Sowash (29:25.19)

Mm-hmm.

Raj Ronanki (29:49.369)

So for example, if you were to go to Target down the street, and if some company had modeled the entire Target store and is every hour says, look, move these products around. chats stopping by, so stock up on popcorn on the exit aisle or whatever this preference may be. So those level of dynamic configurations, avocado toast, love it. Very, very California of you, my friend. so that that level of simulation can happen in real time.

Joel Cheesman (30:08.344)

Avocado toast, I think, is his his preference. Yeah.

Raj Ronanki (30:18.816)

And the reconfiguration of the physical world can happen in real time, and that's what they're betting on. and our view is that there's a corollary to that in the enterprise world. So if we can model all the enterprise data and sort of keep it sovereign to every enterprise, whether it's it's Disney or Walgreens or it's it's IBM, their data can be modeled and we can create a digital twin of that company where you can do lots of simulations.

And and that's really the world that that's coming in the next few months, if not sooner. And a lot of what Signal Labs is going to be doing is is building out world models for certain problem types that we're interested in, starting with workforce management. And we're also gonna do healthcare productivity. that's a topic we should talk about at some point. And enterprise resilience, which goes back to you know the compliance angle, sort of modernizing global risk and compliance. We wanna build

So the entire knowledge structure and the world model around those topics, then we'll take those models and then intersect it with any company's data. And together, so we're gonna reimagine the intelligent stack of of enterprise and hopefully you know, create some sovereign AI for the enterprises.

Chad Sowash (31:33.678)

I know.

Chad Sowash (31:37.308)

Of all the applicant tracking systems of all the small towns and all the worlds, Raj, you picked brass ring. congratulations, I guess. I so so Raj, if if somebody wants to reach out to you, maybe connect with you, where would you send?

Raj Ronanki (31:37.612)

Yeah.

Raj Ronanki (31:46.562)

Thank you.

Raj Ronanki (31:52.93)

No. Raj at signallabs dotai. you can also go to our website at www.signallabs.ai and you can find us on LinkedIn and and Twitter and all X guests these days and all the other social media platforms.

Chad Sowash (32:04.666)

Really appreciate you coming on, man. Thanks.

Joel Cheesman (32:04.716)

And by the way, it it it takes Cajones to come on the show. He reached out after we talked shit and he wanted to come on and explain it. So cheers to you, my friend. Chad, you heard it here first. Systems of attention, attention infrastructure for the enterprise, and the fourth layer, the fourth layer of enterprise software. Whatever the hell that all makes, we're gonna unfold it in the coming months and years. Another one is in the can, Chad. We out.

Chad Sowash (32:08.956)

Of course. I love it.

Raj Ronanki (32:16.024)

Thank you.

Chad Sowash (32:21.25)

Word models, world models.

Chad Sowash (32:26.822)

That's a cake.

Chad Sowash (32:32.433)

We out.