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Engineering

3 posts on engineering.

When an image pipeline fails silently: a disk-quota postmortem

A listing page said "48 photos" above a grid of blank tiles, and every layer underneath it, from encoder to cache to queue, had reported success. The account had hit its disk quota, the image encoder wrote nothing and said it had worked, and the cache filed the empty result as truth. Here is the whole chain, and the four changes that shipped the same morning.

Graph RAG vs vector RAG: when the graph earns its keep

Vector retrieval answers the question of what resembles this text, while a graph answers what is connected to it, and the two fail on different questions. The benchmarks say the difference is large on relational questions and close to nothing on lookups, which makes this an accounting decision rather than an architecture debate. What each one costs, the hybrid I actually run, and how to decide before you buy an index.

The questions similarity search can't answer

The assistant on this site can find anything that resembles your question. It cannot yet follow a chain of facts spread across three notes. Why that failure is structural, what a knowledge graph actually is, and how I plan to wire one into the studio's retrieval without tearing out what works.

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