Decision Input Form
Which latency bottleneck should we address first?
Cache OpenAI embedding results to skip repeated API calls for similar queries
Pre-warm database connection pools to eliminate cold-start penalty on first requests
Optimize Neo4j traversal queries to reduce relationship lookup time
What level of monitoring should we implement?
Continue with current LangSmith integration for tracing and debugging
Add a latency/throughput dashboard alongside LangSmith traces
Comprehensive distributed tracing across all services
What's the highest-value improvement to the pipeline?
Add new authority levels or reclassify existing content categories
Enable session persistence so returning users get contextual responses. Redis infrastructure is already configured.
Refine the intent detection model for better routing accuracy
Should we expand the persona retrieval count?
Current count balances context quality vs token budget with no evidence of gaps
More persona context per query, at the cost of ~200 additional tokens
Vary persona retrieval count based on query complexity
How should the pipeline handle sparse retrieval results?
Current behavior: when results < 3, run unfiltered search and add up to 4 tagged broad_match results
When results are sparse, acknowledge the knowledge gap instead of broadening
Use a confidence score to dynamically decide between broadening and declining
Optional. Any context, constraints, or concerns about these decisions.