Context type
Persistent
Graphify saves graph artifacts instead of relying only on a temporary prompt window.
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Graphify
graphify.homes
Persistent assistant context
AI coding assistant context that persists
AI coding assistant context should survive beyond a single prompt. Graphify converts code, documentation, PDFs, diagrams, screenshots, and transcripts into persistent graph artifacts that assistants and engineers can revisit across reviews, debugging sessions, and refactors.
Graphify outputs
graph.html
graph.json
GRAPH_REPORT.md
Graphify stores inspectable artifacts so codebase knowledge can be reviewed by humans and reused by AI coding assistants.
Inputs
Multimodal
Code, docs, PDFs, diagrams, screenshots, transcripts, and rationale can sit in one graph.
Workflow
Ask later
Teams can query the same graph after the first build, review, or handoff.
What makes AI coding assistant context persistent?
Persistent context is stored outside the chat session as structured artifacts. Graphify keeps graph.html for visual review, graph.json for tools, and GRAPH_REPORT.md for human-readable explanations.
- Use graph.json as durable machine-readable project memory.
- Use GRAPH_REPORT.md to align humans and assistants on architecture.
- Use graph.html to inspect relationships before asking follow-up questions.
How does Graphify handle multimodal context?
Graphify is designed for messy engineering context. It can combine source code, technical docs, PDFs, diagrams, screenshots, transcripts, and rationale into one connected map.
- Keep non-code artifacts connected to the implementation they explain.
- Preserve design intent alongside files and symbols.
- Reduce repeated setup work when a new assistant session starts.
Which assistant workflows benefit most?
Persistent context is most useful when the assistant must reason across modules, compare old and new architecture, or explain a system to someone who did not build it.
- Repository onboarding for new engineers or new assistant sessions.
- Architecture review before changing central modules.
- Debugging handoff after an investigation identifies connected risk.
Related Graphify guides
Continue through the Graphify topic cluster with pages that explain assistant context, architecture review, documentation, and graph-based codebase understanding.
Codebase knowledge graphs for AI assistants
Learn how codebase knowledge graphs connect source files, docs, diagrams, and rationale so AI coding assistants can answer with structure.
Repository architecture review with Graphify
Use Graphify for repository architecture review by surfacing dependencies, subsystem clusters, graph centers, and unexpected cross-file links.
Graphify vs Vector RAG for codebases
Compare Graphify and Vector RAG for codebases across structure, persistent context, multimodal inputs, and architecture review workflows.
Turn this concept into a real project graph
Start from the use cases page or upload a project ZIP to build a graph that your team can inspect and reuse.