What AI Exploit Benchmarks Actually Tell Us About System Architecture Recently, researchers at Anthropic published a study showing autonomous AI agents discovering and monetizing real software failures in simulated environments. The headlines made it sound... AI Infrastructure 08/12/2025
The Hidden Architecture Behind Dense Vector Search (and Why It’s Hard to Scale) Most people think dense vector search works like this: embed your documents store the vectors run cosine similarity Done. This is the biggest misunderstanding in... AI Infrastructure 27/11/2025
The Hidden Complexity Behind Scaling Dense Vector Search A systems-level explanation for engineers, architects, and anyone building RAG, search, or agent infrastructure. Dense retrieval looks clean on paper. You take an embedding model,... AI Infrastructure 26/11/2025
Distributed Vector Search: How Real Vector Databases Scale Beyond One Machine Why dense search becomes a routing, sharding, and distributed-systems problem Vector search looks simple when everything fits on one machine. It becomes a different discipline... AI Infrastructure 25/11/2025
The Write Path in Vector Databases (It’s a Distributed Systems Problem) (Where Dense Search Becomes a Distributed Systems Problem) Most content about vector databases focuses on the glamorous part: fast queries, clever indexing, tight cosine similarity... AI Infrastructure 24/11/2025
How Vector Databases Fail (And What Architects Must Design For) The Hidden Failure Modes of Dense Vector Search, ANN Indexes, and RAG Infrastructure Most engineering teams learn this the hard way: vector databases don’t fail... AI Infrastructure 23/11/2025
Hybrid Retrieval: The Architectural Backbone Behind Reliable AI Systems Most AI failures don’t happen inside the model. They happen one layer earlier — in retrieval. If your RAG system, copilot, or agentic workflow is... AI Infrastructure 22/11/2025