Personalization is a ranking problem — architecture makes it work
Every product team is chasing the same moment: The user opens a page and thinks, this understands me. A shopper The post Personalization is a ranking …
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Why retrieval quality is becoming the defining challenge in AI agent architecture
Agentic systems usually have two jobs: Build context, then use that context to produce an answer or action. Many failures The post Why retrieval quali…
Why AI retrieval and ranking need more than vector search
A recent GigaOm CxO Decision Brief explores how AI retrieval architectures are evolving beyond flat vector databases as organizations combine The post…
From Jupyter Notebook to production: How to ship AI systems that actually work
Moving from experimentation to production in AI requires a transformation of mindset, architecture, and engineering discipline. There’s no API w…
AI retrieval at scale is becoming a systems problem, not a tooling problem
AI retrieval has moved well beyond embeddings and vector search. Early retrieval architectures focused primarily on semantic similarity. Still, produc…
JFrog report recaps a tumultuous year in supply chain security
Calendar year 2025 not only broke records for code package proliferation; it also redefined the foundational architecture of the software The post JFr…