JSON hurts at scale. Protobuf cuts payload size by ~72%, reduces CPU overhead, and enforces typed contracts. However, it needs careful schema management.
The new context layer connects to existing SQL databases and builds a governed, model-agnostic foundation for AI agents running on live operational data, in weeks rather than years.
Learn how to build a production-ready multi-agent AI framework in Python that improves reliability, reduces hallucinations, and scales enterprise LLM workflows.
Build a safer Python API client with timeouts, selective retries, exponential backoff, jitter, and better handling of rate limits and temporary failures.
Fetch AQI data from IQAir, store it in Neo4j, then visualize it with pydeck, Leaflet and R, plus Cypher queries showing what graph-native analysis looks like.
A Java UDF that runs sentiment analysis directly inside the Neo4j database engine — no external APIs, no application-layer round-trips, callable from any Cypher query.
Use Docker to create a local lakehouse environment that mirrors production, while improving data engineering workflows, Spark testing, and CI reliability.