Tech Leader Talk

There are a handful of genuinely useful data points - the 45/40/15 deal-sourcing breakdown, the Rule of 40 explanation with worked numbers, and the dry powder figure with context - but they are surrounded by substantial filler, host affirmations, and generic VC platitudes like 'be passionate and build a great product.' The ratio of novel ideas to padding is low for a 37-minute episode.

“about 45% of our investments come inbound...40% of it's outbound...about 15% of it is sourced by the data science team”

“the market shifted from growth to capital efficiency...the rule of 40 takes revenue growth and then adds to it the EBITDA margin”

The data-science-led sourcing workflow (SIMBI companies, momentum scoring across hundreds of thousands of firms) is modestly differentiated from standard VC talk, but virtually everything else - passion, great product, cyber/AI themes, Rule of 40 - is recycled from the standard VC playbook with no contrarian framing or first-principles reasoning.

“we affectionately call these companies Simbi Companies, which is a complicated acronym that stands for companies you might be interested in”

“the data science doesn't really care whether it's a cyber company or a cloud company. It just thinks that the momentum of that company relative to everything else...is much better”

Mark Sherman has genuine practitioner credentials - ran software banking at Robertson Stevens taking Siebel and BEA public, GP at Battery Ventures where he backed Coupa at $20M pre-money through an $8B exit, and 11 years running Telstra Ventures with 90 investments and 17 unicorn-milestone companies. This is a real operator, not a podcast circuit thought leader, though the episode does not fully exploit his depth.

“I led the investment in Coupa which I invested in at $20 million pre money valuation and their getting bought right now at 8 billion”

“we backed 88 companies actually it's now it's up to 90...17 of those have generated unicorn milestones”

The episode delivers a solid cluster of concrete data points - named portfolio companies (Corvus, CrowdStrike, Auth0, Coupa, CyberGRX, Cohere, Singular), specific fund figures ($350M raised, $100M+ deployed), the $300B industry dry powder figure, and the sourcing percentage split - though many claims about how data science works remain vague and no customer metrics or growth trajectories are shared.

“we just raised a $350 million fund and we've invested, let's just say a little over $100 million of that fund thus far”

“our data science guys basically grabbed him by the collars and said, hey, there's a company called Corvus which is bubbling up...particularly relative to the 28 other companies that were in that space”

The host largely restates what the guest just said, offers affirmations ('Yeah, yeah it does,' 'Okay, all right, that makes sense'), and asks pre-telegraphed softball questions ('What do you love most about the work?'). There is no meaningful pushback, no probing of tension between data science and gut feel, and no follow-up on how the SIMBI scoring has actually performed versus manual sourcing.

“Yeah, yeah it does. So it helps. I could see if you didn't have the data analysis tools to do a lot of that, to automate a lot of that, that would be a huge human capital investment”

“Okay, all right, that makes sense”