Ship faster in a codebase nobody fully remembers

Past a certain size, no single engineer holds the whole system in their head — and neither does any AI assistant grepping it one query at a time. Graphify builds the map once, as an on-device knowledge graph, so both humans and assistants can ask structural questions and get structural answers.

The problem: tribal knowledge doesn't scale

Platform teams inherit the questions everyone else can't answer: what actually depends on this shared module? Which services touch this schema? Why does changing a "small" utility keep breaking distant teams? The answers live in a few senior heads and an architecture wiki that stopped being true two quarters ago. Meanwhile every engineer's AI assistant rediscovers the codebase from scratch, reading whole files into context — slow in a monorepo, expensive at team scale, and blind to anything that isn't a text match.

How the graph helps

One command per repo builds the graph on-device: bundled tree-sitter grammars parse 36 languagesinto nodes and edges taken straight from the AST, with every edge carrying a confidence tag — EXTRACTED for parsed facts, INFERRED for model-connected context like docs and schemas, AMBIGUOUS for dynamic dispatch the parser couldn't resolve. The mechanics are on the concepts page. Three things fall out of that for a platform team:

• An onboarding map that's generated, not maintained. The build emits an interactive graph.html and a GRAPH_REPORT.md naming the natural communities in the code, the god nodes everything depends on, and the surprising connections worth knowing. New engineers get the diagram the wiki promised — derived from the actual AST. See the onboarding use case.
• Blast radius before the change, not after the incident. "What breaks if I change this?" is a multi-hop question, and the graph answers it by traversal: graphify query for everything touching a symbol, graphify path for the exact chain between two points, graphify prs to put open PRs in context of the communities they land in. Commands are in the docs.
• One retrieval layer for every assistant. Engineers use different tools; Graphify installs as a skill or MCP server in 17 of them — Claude Code, Cursor, Codex, Copilot, and more (full list) — so the whole team's assistants query the same graph instead of each grepping its own picture.

What it won't do

Graphify won't enforce anything. The open-source core is a map and a query engine — it informs assistants and engineers; it doesn't block merges or gate CI. Teams that want the graph at the merge gate — verification checks, graph-aware review, running in their own VPC — that's the Enterprise layer, and it's in early access, not GA. And if your repos are small enough to read whole, you don't need any of this yet.

Rolling it out

Because the core is a local CLI with no server, account, or telemetry, there's nothing to procure to try it: one engineer runs it on the monorepo today (quickstart), and adoption spreads repo by repo. Git-hook integration keeps the graph rebuilt as code changes, so the map stays as fresh as the last commit rather than the last documentation sprint.