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Technical Blog Post
Summary
The article explains how the authors inserted TensorZero, an open‑source LLM observability proxy, between Cursor and its language model providers to capture token streams, run evaluations, and experiment with prompts and models for individual users.
Highlights
- TensorZero provides an OpenAI‑compatible endpoint that Cursor can call.
- Routing through TensorZero enables full visibility of tokens and inference data.
- Data is stored for downstream feedback signals such as production metrics or human ratings.
- Cursor sends initial requests to its own servers, requiring a routing workaround.
- Example code and configuration are available in the linked repository.
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Context
Audience
Machine learning engineers and developers building or maintaining AI‑assisted coding assistants
DomainMachine Learning Operations
Formatlong-form article with code snippets
Accessfree online
Topics
Related
TensorZero frameworkCursor AI coding assistantLLM inference logging toolsPrompt optimization techniquesObservability platforms for language models