Xav
@xav_db
🇬🇧 22 | sf | building @hlx_db (yc x25)
Starting on what will likely be a multi year project, to create the fastest and most lightweight graph database available. I’ve been using AWS Neptune for the past 3 years and it’s a pain to use, slow for development, and is slow to startup. Don’t even get me started on gremlin😂
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you can just do things
Starting on what will likely be a multi year project, to create the fastest and most lightweight graph database available. I’ve been using AWS Neptune for the past 3 years and it’s a pain to use, slow for development, and is slow to startup. Don’t even get me started on gremlin😂
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context engineering is always key with llms this literally would not be possible without rag (with @hlx_db) — the AI would be producing numerous errors. going to try kimi for faster results shoutout @puttasync and @rohanganapa for the advice