Enterprise Document Intelligence [Vol.1 #7bis] - Tobi Lütke and Andrej Karpathy named the practice in 2025. For a single document, each brick emits typed pieces that converge on one LLM call. Corpus, conversation, and tool extensions are follow-up work
The post Context Engineering for RAG : The Four Typed Inputs Behind Every RAG Answer appeared first on Towards Data Science.
Before Tobi Lütke ran Shopify, he learned programming through Germany’s apprenticeship system, the way people have learned trades forever: in a shared workshop, watching people who already knew what they were doing. More recently, describing Shopify’s River, he reached for a related word: Lehrwerkstatt, a teaching workshop where “the whole shop floor is the classroom.”
X has been agog by the numbers around River, Shopify’s Slack-native AI agent. In total, 5,938 Shopify employees worked with River across 4,450 different Slack channels, and River now coauthors roughly one in eight merged pull requests across the company. It’s a big deal, but understanding why it works that way is the most important part.
River can read code, run tests, open pull requests, query the data warehouse, inspect production traces, and sometimes push back on a plan it thinks is bad. Great. Lots of companies will have clever coding agents someday soon. Some already do.
The interesting part is that River doesn’
Enterprise Document Intelligence [Vol.1 #M1] - The thesis behind every architectural choice in this series
The post Amplify the Expert: A Philosophy for Building Enterprise RAG appeared first on Towards Data Science.
June 25, 2026 — Mistral has announced the release of Mistral OCR 4, featuring bounding boxes, block classification, and inline confidence scores alongside extracted text. The model supports 170 languages across […]
The post Mistral Unveils OCR 4 for Enterprise Search, RAG and Document Processing appeared first on AIwire.
Enterprise Document Intelligence [Vol.1 #7C] - One LLM call ranks the candidates with reasons. The output is one typed object your auditor can defend
The post Letting an LLM Pick the Right RAG Page: The Arbiter Pattern at the End of Retrieval appeared first on Towards Data Science.
Enterprise Document Intelligence [Vol.1 #7B] - Retrieval is filtering on structured tables: keywords first, TOC second, embeddings last
The post Anchor Detection for RAG: Parallel Detectors, Then One LLM Call at the End appeared first on Towards Data Science.
Mistral AI released OCR 4 on June 23, 2026, moving from clean text extraction to structured document output. Each block returns a bounding box, a typed classification, and per-page and per-word confidence scores. The model supports 170 languages, runs in a single self-hosted container, and feeds citation-ready inputs into RAG, agentic, and enterprise search pipelines through one API endpoint.
The post Mistral OCR 4 Brings Citation-Ready Structured Output to RAG, Agentic, and Enterprise Search Pipelines appeared first on MarkTechPost.
Enterprise Document Intelligence [Vol.1 #7A] - Stop searching strings. Filter line_df and toc_df. Pick anchors small, expand context large
The post Retrieval Is Filtering, Not Search: A Mental Model for Enterprise RAG appeared first on Towards Data Science.
Enterprise Document Intelligence [Vol.1 #6bis] - Ask one focused clarification, learn the default from the answer, stay silent next time
The post When RAG Users Ask Vague Questions: Clarify Once, Learn the Default appeared first on Towards Data Science.
