Key Takeaways

  • Jason Lemkin outlines the investment bull case for Clay at a $7 billion valuation and Linear at a $2.5 billion valuation based on agent-native adoption.
  • Autonomous software agents consume 10 to 100 times more data and run go-to-market workflows 24/7 without human fatigue.
  • Rory O'Driscoll highlights that the entire enterprise buying process is shifting from human procurement teams to automated systems that evaluate tools programmatically.
  • Software volume is exploding, with engineering teams producing 100 times more features that require developer tracking tools like Linear to manage human-agent coordination.

When Software Buyers Stop Being Human

Lemkin noticed something strange about his own team's software stack: his autonomous agents refused to use anything other than Clay. “I will tell you I've changed my mind and our agents will only use clay now for real,” Lemkin said. “They will use nothing but clay. And so as we move from AEO and GEO and whatever yo to agentmade decisions the fact our agents would only use clay that I think it's a BF deal.”

For decades, enterprise SaaS companies won by pleasing human managers. They built glossy interfaces, hired armies of outbound sales reps, and sponsored conference booths. That playbook dies when the user and the buyer are both software. As O'Driscoll noted, “the puck is agents buying software, not humans buying software. That's the zoom out comment here, right?”

When agents make the call, they pick products on cold metrics: API response times, structured data formats, reliability, and clean execution. Clay wins because autonomous scripts can parse its outputs and trigger enriched workflows without getting stuck in human-centric interface bloat.

The 100x Usage Multiplier

Human sales development reps get tired. They work eight hours a day, send fifty customized emails, take breaks, and make manual data entry errors. Software agents do not stop.

“It turns out when agents can run these GTM motions, they will consume 10 to 100 times more usage than humans ever could,” Lemkin explained. “They can run GTM around the clock.” This dynamic turns traditional per-seat SaaS pricing upside down. A platform priced on consumption or API calls sees its revenue curve hockey-stick when an agent executes thousands of pipeline queries an hour.

The same surge applies to product development. Software teams using automated coding tools are generating code at unprecedented volume. That output creates a massive project management bottleneck that older issue trackers cannot handle.

“Linear is the clear winner,” Lemkin argued. “They have built an agentic product first that allows the fact that we are building 100 times more software and that means 100 times more features than ever before. Humans cannot keep up with it and humans still have to work with agents.”

The 2x2 Matrix That Decides SaaS Valuations

Lemkin evaluates modern enterprise tools on a simple grid: output quality on one axis, agent friendliness on the other. Legacy platforms struggle on both fronts because their architectures were designed around human clicks rather than machine readability.

"They are agentfriendly," Lemkin said regarding Clay. “Why do my agents nag us to use clay? Because it's the most agent friend. If you have a 2 by two of agent friendly and quality of output, it wins the 2 by 2.”

Valuations of $7 billion for Clay and $2.5 billion for Linear look steep under legacy software metrics. But if software consumption multiplies by 100x and machines select the tools, the winners in each category will capture value at rates traditional SaaS never reached.

What to Do With This

Audit your product's API surface this week by running a test script to execute your three core user workflows without opening your web UI. If an autonomous script hits rate limits, messy JSON payloads, or auth friction, prioritize refactoring those programmatic endpoints before building your next front-end feature.