The open-source Eval Pyramid Starter, a provider-neutral TypeScript harness for testing LLM and agent systems, enables engineers to clone a repository and run offline evaluations with deterministic gr…
An agent that passes 75 out of 100 test runs has a 75% pass@1 rate, but reliability depends on the product: pass@k (at least one success in k tries) yields 98.4% for k=3, while pass^k (all k succeed) …
In a new blog post, engineer and former SDET professional introduces the 'eval pyramid' for testing AI agents that behave nondeterministically, arguing that traditional testing methods remain relevant…
Retrieval-augmented generation (RAG) fixes the knowledge cutoff, lack of private data access, and hallucination problems of large language models by using an embedding model to retrieve relevant docum…
A transformer architecture becomes a large language model through training on trillions of tokens, using residual connections to enable deep networks, tokenization to split text into manageable units,…
Engineers can now understand the transformer architecture behind large language models through a plain-English guide that explains how words become vectors, layers move points, and attention mechanism…