A one-page model prevents an expensive detour.
Fill this in before choosing Neo4j, Postgres, a graph library, or a managed service. A graph is justified only when the relationship structure changes the answer or the maintenance workflow.
QUESTION: Which commitments are at risk, why, and what should happen first?
SCOPE: One launch project, current quarter
ENTITIES: people, project, commitment, task, decision, source
RELATIONSHIPS: owns, part_of, blocks, supports, evidenced_by
MUST_INCLUDE: owner, due date, blocker, evidence, freshness
MUST_NOT_CLAIM: causality that no source records
BASELINE: direct lookup plus filtered task list
SUCCESS: answer is more complete and still traceableIf the baseline already answers the question, keep the graph as a later experiment. The design canvas is also the boundary that stops an ontology from expanding without a user-facing reason.
Graph retrieval is one tool among several. Use the simplest method that preserves the evidence and answers the question.
| Question shape | Start with | Reason |
|---|---|---|
| What is the current due date? | Direct lookup | A single authoritative field is easier to validate than a relationship query. |
| Which notes are similar to this one? | Vector search | Similarity is the primary signal. A graph may be unnecessary. |
| Which decisions affect this commitment through a task? | Graph | Typed paths and intermediate entities are part of the answer. |
| What changed, who owns it, and which source supports it? | Hybrid | Use structured relationships for joins and text retrieval for the source passages. |
| What are the next three steps in this checklist? | No graph | A document or workflow state is clearer and cheaper to maintain. |
The graph is one layer of the operating brain.
Use the relationship layer to connect current truth, timelines, commitments, decisions, and work items. Keep the surrounding contracts explicit: task truth, rituals, memory ownership, evidence-gated learning, provider routing, and automation state.
Explore Second BrainYour first graph slice
Finish with one question that matters to your work this week. Keep the scope small enough that you can inspect every important edge.
- 01Write the question and the baseline method you would use without a graph.
- 02List five to ten source records and assign stable references.
- 03Name no more than six entity types and five relationship types for this slice.
- 04Add evidence, observed time, confidence, review state, and retirement rules.
- 05Run one query, return the evidence with the answer, and record one likely failure.
- 06Score baseline versus graph, then decide whether to keep, simplify, or retire the graph.
Sources and further reading
The implementation boundaries in this guide are grounded in official documentation. Community posts can suggest questions, but they are not used here as evidence for performance or product claims.
- Microsoft GraphRAG overview: indexing extracts entities, relationships, claims, communities, reports, and embeddings.
- Microsoft GraphRAG query overview: local, global, DRIFT, and basic vector search have different query shapes.
- Microsoft GraphRAG quickstart: an end-to-end indexing and querying path, with cost and small-dataset warnings.
- Microsoft GraphRAG repository: implementation notes, current status, and the warning that the code is a demonstration.
- Neo4j GraphRAG Python API: lexical graph relationships connect documents, chunks, and source context.
Sources checked July 2026. Product capabilities, APIs, pricing, and provider availability can change. Verify the current documentation before implementing a production system.