Short conversational transcript (YouTube #shorts) featuring Jason M. Lemkin discussing a stair-step approach to deploying agentic AI: start with simple, broad, easy use-cases to win early, build internal confidence, then iterate to more complex agents. Emphasizes crawling→walking→running, choosing minimal training tools, and learning from an early successful deployment that automated qualification and sales tasks.
Learning for folks that watch. I didn't know this at the time. Stair step it. So the fact that we went from Delphi, a horizontal agent which basically can self ingest your content with no training like you do need to, but it's the least amount of training of the tools in our stack. Start easy, start broad, get a win under your belt. Even if you started with say qualified, I'm not total qualified expert start for the simplest use case. Okay. Because if you fail with your first agentic thing, not only will it is it frustrating, you won't know. You won't know. You just won't know. Because we had the early win that that was better than expected. Like our general digital. Jason could do some sales, it could do some qualification and it would start to say, you know what Craig, you're not big enough for Sasser annual this year don't come. That was like great for us. Like it would do it on its own. So we gained confidence and if you can stairstep this stuff, you will build confidence by your second, third agent or deployment. And we didn't intend but that's what we ended up doing. That's how even us were successful. We stair stepped.
I think every company is probably a little bit different but like the stair step we always talk about, you got to, you got to crawl, walk, run. Everybody like sees the prize of like I'm going to be sprinting and you're like whoa, you know, where do I start? And you got to get the quick win. You got to build the confidence internally.
