Graham McNicoll

Most product teams I talk to struggle to analyze the true impact of any feature they ship, even though they have dashboards. A graph tells you something moved. It does not tell you what caused it, or whether your last release had anything to do with it. That gap is where vibe-driven decisions live. The PM squints at the graph. The trend looks good. The feature ships. Nobody actually knows what moved the number. Controlled experiments close that gap. When you run a test, you can causally attribute an outcome to a specific change. A precise question replaces a vague one: did this feature move my metric, and by how much? That is the difference between interrogating the data and just looking at it. If you're trying to make that shift, send me a DM.