00:47:01 · Siddhartha Ahluwalia, Varun Badhwar
[00:47:01] S1: Yeah. [00:47:02] S0: What happens if somebody hacks and crashes cars now on the highway? So I think software fuels the world. Um yes, hardware is back again, not dismissing that, but software still fuels the world. And I think any company where the core of your product somehow fits in software, maybe it's not more than 10%, but I think on a base case it should be 10% spent on your overall IT budget for code security as well. Uh maybe take it from a different lens, okay? Most companies I talk to, the engineering teams spend 20 to 30% of their time on just security issues. Follow-ups, bugs, security bug fixes, vulnerability remediation, pen test report. So take that and say, if I can give you back half of that, that economic impact is about 15% of your total payroll cost, fully loaded headcount cost of your engineers. So if I'm gonna do that, arguably if you spend, you know, we're sitting in the Bay Area, so let's talk Bay Area salaries. You're spending $300,000 a year on um an engineer's salary. [00:48:18] S1: Yeah. [00:48:19] S0: If $90,000 worth of their time is spent on security, and I can fix that for $9,000 a year, I think you would happily pay that. [00:48:28] S1: Yeah. [00:48:29] S0: Right. And now is $9,000 a year for that security solve on where you're spending $300 for their GitHub license, you would still pay that if I can create the value connectivity and prove to you that I can give you back $90,000 worth of efficiency. So that's how I think about kind of value-based selling.
00:48:29 · Varun Badhwar, Siddhartha Ahluwalia
[00:48:29] S0: Right. And now is $9,000 a year for that security solve on where you're spending $300 for their GitHub license, you would still pay that if I can create the value connectivity and prove to you that I can give you back $90,000 worth of efficiency. So that's how I think about kind of value-based selling. [00:48:49] S1: And today, um, out of Fortune 500, how many logos would you have? [00:48:54] S0: Look, I think what's interesting about our business is for the reasons we were just having this conversation on like software is the lifeline for tech businesses. Um, a lot of our customers end up started out being the tech companies, companies like DoorDash companies, like the big labs that I can't name here on uh on air. Cursor is a customer, Glean's a customer, Atlassian, MongoDB, Snowflake, Peloton, Robinhood. So I think for us, where we were trying to drive efficiency are the companies that were really manically focused on that. So you know, they weren't your legacy Fortune 500s, if you will. But you know, over time we have several Fortune 500 companies, several of the world's top insurers, financial services. But just as a metric, we focus and fixate less as our claim to success being the Fortune 500, versus we we kind of look at it more as are the world's most prolific software companies, how of those, how many are using an Endor? And that number continues to uh you know go up and to the right.
00:48:54 · Varun Badhwar, Siddhartha Ahluwalia
[00:48:54] S0: Look, I think what's interesting about our business is for the reasons we were just having this conversation on like software is the lifeline for tech businesses. Um, a lot of our customers end up started out being the tech companies, companies like DoorDash companies, like the big labs that I can't name here on uh on air. Cursor is a customer, Glean's a customer, Atlassian, MongoDB, Snowflake, Peloton, Robinhood. So I think for us, where we were trying to drive efficiency are the companies that were really manically focused on that. So you know, they weren't your legacy Fortune 500s, if you will. But you know, over time we have several Fortune 500 companies, several of the world's top insurers, financial services. But just as a metric, we focus and fixate less as our claim to success being the Fortune 500, versus we we kind of look at it more as are the world's most prolific software companies, how of those, how many are using an Endor? And that number continues to uh you know go up and to the right. [00:50:01] S1: And engineering wants to shift faster, always, right? And never been fast as today. And security wants to hold back and slow things down, making sure nothing breaks. So you think that uh the equilibrium has further distorted than five years ago?
00:50:01 · Siddhartha Ahluwalia, Varun Badhwar
[00:50:01] S1: And engineering wants to shift faster, always, right? And never been fast as today. And security wants to hold back and slow things down, making sure nothing breaks. So you think that uh the equilibrium has further distorted than five years ago? [00:50:18] S0: I I think it's a challenge and opportunity. For sure, we're producing more code than ever before. And so the bottleneck is no longer code generation. That's not your constraint. Generation is a solved problem. Everything after that is where the bottlenecks are, security being a major one, quality being another one. Um but yeah, I I think I think as people are moving even faster, now security looks like even slower because of that reason, unless they're retoolable. And and I think this is also a great opportunity because all of the things that were unsolvable security problems, you can now do more efficiently with agents. And so I think the whole idea here at Endor Labs is how do you use a genetic software security solution to keep up and deliver far more effective security programs. [00:51:03] S1: So, how do how do you make uh the engineering team and the secure team work in in uh in the same harmony at the same pace?
00:51:03 · Siddhartha Ahluwalia, Varun Badhwar
[00:51:03] S1: So, how do how do you make uh the engineering team and the secure team work in in uh in the same harmony at the same pace? [00:51:13] S0: Yeah, I think it comes down to the metrics of what what matters to you. It was the example I was giving you on cost efficiency. What matters to the CTO is can they move fast and can they ship fast? No CTO in the world wants to ship an unsafe application, but that's not the core metric. Like I don't know too many engineering teams that are obsessing about security, they're obsessing about speed and quality. And so for us, it's like we always think about Endor and our products called ORE, our platform, eugenic platform. Even actually, the icon of ORE is a bridge. And that's supposed to be a bridge between security and engineering team. Security wants to move fast, we need to give them the tools to move. Uh sorry, engineering needs to move fast, we need to give them the tools to move fast. Security needs to move safe, we need to give them the tools to move safe. The connective tissue is the developers should never get out of their workflow and should have minimal interrupts. So Endor runs where the developers are. Security gets the report where they want it, and that's how we design our interfaces of our product. [00:52:12] S1: We would love to know some of the stories of what went right, some of the visions that went right in Endor and what didn't go right as planned.
00:52:20 · Varun Badhwar
[00:52:20] S0: Um maybe let's actually I want to start with some of the going right versus going wrong dating back to my first startup. Because I think it's you know learnings have begun from there. Um as I kind of touched on briefly before, I have come to realize and appreciate just how important having the right talent is. At CipherCloud, our first company, uh, my co-founder CEO was self-funding a lot of that. And so I think initially, as a self-funded company, we're scrappy about talent. There's a lot of good talent, but very young, early in career talent. And we didn't round that up with the right mix of uh seniority and experience. And I think long term there was just a lot of technical debt in that architecture and that platform. Because yes, we could deliver features really, really fast, but it was hard to understand at what cost and what we were compromising in doing so. So I think that was kind of one of my learnings from there was the quality of talent. I'd rather have fewer people than like earlier and cheaper. Um and I think today, though, that's become easier because you just don't need the same volume of people with AI. You can do a lot more with fewer people. So that was kind of one there. At Redlock, um, one of my big learnings was like when you hire salespeople, hire in pairs. What I mean by that is oftentimes people will be like, oh, I'm hiring my first salesperson. And I always say when you're hiring the first salespeople, what first person, what territory are you gonna put them in? Right, how people on the west coast of US Buy is very different from how people on the east coast of US buy. Uh also, what background do you want somebody to be? Uh, do you want a startup background or is a large company background okay? So, you know, the individual's background matters. And the third thing is with sales, unlike many other functions where like I'll know in the week or two weeks or three weeks if this is working or not, in sales, you may not know for six months, nine months, maybe even twelve months, if it's actually working or not. And if it's not working, is the problem that individual? Is it the accounts you're targeting or your um product? And so at Redlock, I originally started with that following that principle of higher-end pairs. I hired two people, and I'm so grateful I did. I put one person in California, one person in New York.