AI Workflow Automation with Personal MCP server
Engineering managers operate at the intersection of numerous information streams, leading to significant context-switching overhead and potential loss of critical information. This post outlines the design for a context-aware AI assistant, orchestrated by the Gemini CLI, to solve this problem. We will explore two solutions: a short-term workaround using a command-line bridge and the recommended long-term solution involving a dedicated local server.
AI Workflow Automation for an Engineering Manager
The life of an engineering manager is a constant exercise in context switching. Between processing a flood of emails, keeping up with Slack channels, managing Jira tickets, reading Confluence pages, and preparing for one-on-one meetings with notes in OneNote, the mental overhead can be staggering. The core challenge isn’t just managing tasks; it’s about maintaining and retrieving context across a dozen different platforms, often in parallel.
Agentic Features for Codehub: Engineering Metrics Intelligence (part 2 of 2)
Enhancing Codehub application with agentic capabilities can transform it from a static reporting tool into an intelligent engineering insights platform that proactively helps teams improve their performance and productivity.
See also Agentic Features for Codehub: Engineering Metrics Intelligence (part 1 of 2)