Eliminate an average of 3 repeated context-setting discussions per week and cut onboarding time for new developers by 30%.
~1 hr
Saved / wk
Medium
Setup
AI-Assisted
AI
Every time a pull request is merged on GitHub, a Make automation extracts the PR description and reviewer comments, then writes a structured decision record to Kumbukum. Your team's AI tools instantly know why that code choice was made. Future AI sessions stop repeating old debates.
~1 hr
Saved / Week
Some setup required
Setup Complexity
AI Status
Destination
Step 1: Connect your GitHub repo to Make using a webhook that fires on pull request merge.
Step 2: Set up a Make scenario to extract the PR title, description, linked issues, and key review comments.
Step 3: Format the extracted data as a decision record and POST it to your Kumbukum shared library via API.
Step 4: Post a summary message to your team's Slack channel so everyone knows a new decision was logged.
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Kumbukum is an open-source, team-shared memory layer that connects your notes, decisions, emails, links, and Git context to Claude, Cursor, ChatGPT, and any MCP-compatible tool. Instead of re-explaining your project background at the start of every AI session, your team's full knowledge library is already there. It includes an Email Command Center that reads incoming email against your shared library and drafts context-grounded replies automatically.
Kumbukum serves as an AI-readable memory store for engineering decisions. Make extracts context from each merged PR and writes a structured record to Kumbukum. Future AI sessions in Claude, Cursor, or other tools can query that library so they already know why past code choices were made — without anyone re-explaining.
