Replit Agent · Replit
Build a practice tool for sales calls with AI buyers
A go-to-market leader at Replit with no coding background used Replit Agent to build a simulator where reps practise cold and discovery calls against AI buyer personas and get scored.
What they did
In his first two weeks on the job he described the tool to the agent in natural language and had it running in under two hours. The simulator scores reps against sales frameworks such as MEDDIC or Sandler and gives coaching notes after each call.
How it went
He expects it to shorten new rep ramp-up from about three months to under two weeks.
Worth knowing
The ramp-up figure is an expectation, not a measured result, and the story is published by Replit about its own employee.
Try it with Replit Agent
Build a web app where a salesperson can practise calls with an AI buyer. Let me pick a persona from <your buyer types> and a call type such as cold call or discovery. After the call, score the rep against <your sales framework> and list three specific things to improve, quoting the moments from the transcript.
We wrote this prompt from the case. Replace the parts in angle brackets with your own details.
What this label means: Vendor says
The maker describes it on its own site or launch post. It shows what the product is meant to do, with no independent result.
Real cases of AI agents at work, from every major agent, each linked to where it was first reported. Rewritten in our own words, most with a prompt you can try. These are not Wize customers.