It’s Hacktoberfest. Here’s what 4 real merged PRs actually look like.
A contributor walks through four merged Graphify pull requests, covering PHP routes, Kotlin annotations, Python imports, and contributor documentation.
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A contributor walks through four merged Graphify pull requests, covering PHP routes, Kotlin annotations, Python imports, and contributor documentation.

Why Graphify’s growth points to a broader need for shared business context, ontologies, and knowledge graphs as companies adopt AI agents.

An overview of Graphify’s codebase-to-graph workflow, parser improvements, and how structured context helps coding assistants reason across files.

How code graphs support cross-file reasoning, with a look at Graphify’s parser updates and developer adoption.

A hands-on review of Graphify with Claude Code, covering repository exploration and the trade-offs in a daily development workflow.

A solo developer’s workflow combining OpenCode, Graphify, and Cloud Run for coding and deployment.

An introduction to turning project folders into knowledge graphs that coding assistants can query.

A repository-level test of Graphify’s code index, including exploration costs, benchmark context, and practical limitations.

A review of Graphify’s local parsing, adoption trade-offs, and what to evaluate during a trial on your own codebase.

A walkthrough of using Graphify knowledge graphs with Kiro to reduce repeated codebase reading.

A quick-start guide to installing Graphify and giving coding agents a reusable map of a repository.

An overview of Graphify’s folder-to-graph workflow and how it fits into Claude Code and other coding tools.

A comparison of three code graph tools, exploring their architectures, benchmarks, and suitable workflows.

A guide to choosing between CodeGraph and Graphify for code navigation and AI agent context.

An introduction to local codebase graphs, repository exploration, and the privacy considerations of indexing a project.

How a structural code graph helps an assistant follow calls, imports, and dependencies across a repository.

A practical introduction to graph retrieval, with a Graphify and Antigravity setup walkthrough.

One developer’s account of using Graphify with Claude Code on a large codebase and measuring token usage.

A setup guide for connecting Graphify knowledge graphs to Claude Code and Codex.

A walkthrough of building a project map before asking Claude Code to explore the codebase.

An iOS project walkthrough showing how a code graph exposes dependencies and helps guide Claude Code.

A setup combining Graphify and code-review-graph to keep repository context available to coding agents.

A guide to installing Graphify and querying codebase structure from popular AI coding assistants.

A Spanish-language installation and usage guide for Graphify with Claude CLI on Linux and WSL.

A look at local parsing with tree-sitter and navigating the resulting graph without model calls.

An overview of Graphify’s code knowledge graph, local setup, and coding-agent integrations.

A Japanese-language introduction to building a codebase graph and reducing repeated exploration by coding agents.

A hands-on comparison of Graphify, grep, and vector retrieval on an infrastructure repository, including where each approach falls short.

A mobile development team shares how persistent codebase graphs help Codex find relevant files and resume work across sessions.

A practical guide to setting up Graphify with coding agents, tracing repository relationships, and understanding its limitations.

An examination of stale knowledge graphs, unreliable update hooks, and the monitoring needed to catch drift in production.

The ideas behind Graphify’s rise, from Karpathy’s persistent knowledge bases to graphs that connect code, documents, and images.

A hands-on account of testing Graphify in Claude Code and addressing gaps in a persistent codebase-context workflow.

A comparison of five alternatives to Graphify for organizing codebase context and working with Claude Code.

A comparison of Headroom, Caveman, and Graphify for developers evaluating their AI coding workflow.

A closer look at the token-savings claims circulating around Graphify and AI coding assistants.

An examination of how code graphs, portable knowledge, and vector retrieval address different context problems.

A framework for choosing a codebase knowledge tool based on a team’s needs, beyond headline token benchmarks.

A critical look at stale graph context, deleted symbols, and the maintenance needed to keep coding-agent knowledge reliable.

An account of trying to measure Graphify’s effect on Claude Code usage and encountering gaps in attribution and analytics.

An introduction to giving Claude Code reusable repository context instead of starting each session from scratch.

A walkthrough of Graphify’s origins, how it builds a graph from a folder, and how to start using it.

An overview of Graphify’s local parsing, relationship provenance, and shared repository context for AI coding assistants.

A tour of Graphify’s assistant skill, graph queries, and team workflows for navigating code, schemas, and documentation.

A look at Graphify’s shared MCP server, PostgreSQL introspection, and graph updates for teams working across coding assistants.