I’ve been working on an agent that tracks leadership changes at mid-market SaaS companies and turns them into potential outbound timing signals.
The basic idea is pretty simple: when a company brings in a new sales leader, there’s often a period in the first few months when they’re reviewing the existing stack and deciding what needs to change. So the goal is to catch the hire early.
The data comes through the Coresignal API and then gets scored based on things like the role, company size, and how the person’s previous career moves line up. I’ve also been using their MCP during development, mostly for digging into career histories without having to build another query layer. n8n handles the workflow around it.
The part I’m still trying to get right is how much weight to give the secondary signals. Some combinations seem meaningful, while others don’t tell you much on their own.
For anyone who’s built something around leadership changes or intent signals, how did you handle the scoring without making the model too rigid?
submitted by /u/snowingbol
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