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AI

The gap between the demo and production is where homegrown comp tools go to die. That’s why even the companies with the strongest AI engineering talent in the market buy purpose-built comp platforms rather than build. They know the difference between a prototype and a platform.

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Should Your Revenue Team Build Its Own Tools? An Honest Look at the Build vs. Buy Decision
Should Your Revenue Team Build Its Own Tools? An Honest Look at the Build vs. Buy Decision

The era of vibe coding has made building tempting. Here's how to think about it clearly , and why the stakes are especially high when what you're building handles every rep's paycheck.

The 40% Problem: Carl Eschenbach on Why Most AI Bets Fail — and What Smart Revenue Leaders Do Differently
The 40% Problem: Carl Eschenbach on Why Most AI Bets Fail — and What Smart Revenue Leaders Do Differently

Carl Eschenbach has watched more platform shifts than most people have had careers. Thirty-eight years in enterprise technology — from PBX phone systems to VMware's rise from two hundred people to twenty thousand, from Sequoia Capital to the CEO chair at Workday — have given him a particular kind of clarity about what separates companies that transform from ones that merely dabble. We sat down with him at Captivate '26 in Austin to talk about AI, the pressure cooker every revenue leader is sitting in right now, and the single question he says most teams forget to ask before they spend a dollar.

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