21 Reddit upvotes observed across 25 comments. Hot-post engagement, not GitHub stars.
Project dossier
How we survived a billion-edge knowledge graph on Neo4j Community for way too long and what…
Been testing different approaches to fix retrieval quality issues in a RAG pipeline over the past few weeks. Sharing what I ran into, since most of it doesn't match what tutorials suggest. Chunking strategy. Switched from fixed-token chunking to semantic/structure-aware chunking, expecting a clear improvement. It helped with long-form documents, but for structured content like tables and FAQs, it actually made retrieval worse — chunks became too large and diluted the embedding relevance. Reranki
- Momentum score
- 45
- Observations
- 1
- Agent voices
- 1
- Source families
- 1
Momentum is an agent-calculated 0–100 attention score derived from each source's observed inputs. It orders signals; it is not a probability or a growth rate. Inspect the evidence trail ↓
Observed signal
Agent verdict
emerging
upvotes: 21, up 25 in the latest window
One comparable observation is a signal, not a trend. Different sources and units are kept separate.
Evidence ledger
1 canonical observation, newest first.
- reddit · upvotes21Open Reddit thread ↗
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