Alex Lieberman says Tenex started about eighteen months before the recording as an AI-powered development shop.
“we started Tenex eighteen months ago, when we started the business, really, we started as, like, an AI-powered dev shop”
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Alex Lieberman
1 episodes · 15 quoted claims
Alex Lieberman says about half of Tenex's customers are Fortune 2000 companies and half are mid-market firms with 100 to 500 million dollars in revenue.
“50% of our comp our customers are fortune 2,000, and then 50% are mid-market, doing a hundred to 500 million in revenue”
Alex Lieberman says Tenex has about 75 employees, 90% of whom are engineers or AI strategists.
“Today, the business is at, uh, seventy five people, um, 90% of those, uh, employees are either engineers or AI strategists”
Alex Lieberman says the pay gap between Tenex's highest and lowest paid engineers is about four times.
“there's a very wide dispersion in earning capacity between the highest paid engineer at Tenex and the lowest paid engineer at Tenex. It's probably something around four x difference”
Alex Lieberman says Tenex's AI strategists are rewarded for customer retention and growth, which balances engineers' output-based pay.
“where AI strategists are incentivized for, like, customer retention and growth”
Alex Lieberman estimates that about 90% of the enterprises Tenex talks to have rolled out Claude or Codex to employees.
“of the, you know, let's call it a hundred enterprises we're talking to today, 90% have roled rolled out, e- e- either Claude or Codex to their employees.”
Alex Lieberman estimates that about 60% of enterprises have moved on to training and enablement for general-purpose AI tools.
“actually teaching people how to use it, like, training and enablement, which, like, never gets the love that it should get, but is arguably more important or as important as the technology itself. I would say that's at, like, 60%.”
Alex Lieberman says only about 50% of enterprises have rolled out coding agents, well below the 70 to 80% most people guess.
“most people are like, it has to be seventy or 80%. The number is closer to 50%.”
Alex Lieberman says only about 5% of large enterprises have agents in production doing work other than building software.
“the biggest diffusion gap is from, like, raw intelligence to enterprise usage, is agents in production for non-engineering work drops to, like, 5%”
Alex Lieberman says controlling data access with role-based access control has become a nightmare for chief information officers and chief information security officers as employees get AI tools.
“permissioning and, uh, like, RBAC, uh, basically, as every employee in a company has Claude or they have Codex, and they need access to certain data, it has turned into an absolute nightmare for CIOs and CISOs”
Alex Lieberman says he and CJ Hess are generally bearish on AI products built for specific industries or functions.
“we were generally expression expressing an overall bearishness with vertical-specific AI solutions in different functions or industries”
Alex Lieberman argues that replacing software with in-house builds gets harder the further up market a company is.
“the more you move up market in business, the harder the proposition of ripping out and building from scratch gets.”
Alex Lieberman says replacing a system like Salesforce or SAP wrongly could cost hundreds of millions or billions of dollars, which is why he does not see them as at risk.
“where if a company gets it wrong, ripping them out, you're talking about potentially hundreds of millions or billions of dollars.”
Alex Lieberman says Tenex built its own customer relationship management system from scratch.
“even at Tenex, like, we, we like, we built our own, like, CRM from scratch.”
Alex Lieberman argues that rebuilding non-core software only makes sense if the savings justify the ongoing effort of maintaining it.
“is the size of the prize big enough to justify the cognitive load that is going to take from some amount of resource in your company to nurture something that is not core to your business?”