Phyllipe Medeiros
11 posts

Phyllipe Medeiros
@Phyllipecm
just another engineer trying to build startups. 2x ICPC world finalist ex SWE L7 @ Facebook


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why i avoid graph databases the question: "is knowledge graph rag production ready? should we use it?" the answer: after 10 years in ml, i stay away from graph databases. every company i've seen go into the graph world moves back to sql within 4-5 years. the issues are real: hard to hire talent (easier to find postgresql experts) schema definition creates endless debates without clear best practices most use cases need only 1-2 traversals, not complex graph operations even facebook's "graph" was actually a large mysql database. the only company that truly needs graph databases is linkedin for 3-5 degree friendship calculations. even for microsoft's document graph approach - i'd rather use fine-tuned embeddings. a graph is just an adjacency matrix, and fine-tuning can get you close to that similarity definition without the operational complexity. start with your data: let specific use cases justify graph complexity rather than choosing technology first. graph might be 2% better, but traditional approaches working well means that 2% rarely justifies the maintenance cost.

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@lucianodiisouza Minha experiência a grande maioria dos programadores hoje em dia usa **menos** comentários que o ideal. Quando perguntados sobre isso, eles falam que aprenderam que assim é clean code. Mas se você olhar o código deles é o contrário de clean, um mistério atrás do outro. Contínua

"utiliza código limpo e bem comentado" eu falo ou vocês falam?

