How to tune agents trained on public data to work better with your private code

I was working in a team of 10 people on a project. We kept running into inconsistency across the codebase because everyone prompted differently and got different results. We tried maintaining a skills.md file to fix it, but it wasn’t great. So I built Decispher (decispher.com) . It's main goal is to automatically capture engineering context from across different platforms and feed it to AI agents. It also records the decisions and assumptions agents make while coding, then surfaces them back to…