Long sessions rot quietly, well before any token limit is reached. Here’s why, and how to govern your context in Claude Code.
Most coding agents treat prompt construction like retrieval: gather more files, add more context, hope the model figures it out. But that approach breaks down fast.
The article discusses how context engineering is evolving and outlines practical ways data scientists can incorporate the newest guidelines into their everyday work. It explains the importance of adapting to these changes to improve model performance and relevance. The piece offers actionable steps for integrating context engineering into typical data science workflows.
The article argues that AI agents face a context typing issue rather than merely a lack of context. It explains how flattening instructions, memory, evidence, and tool outputs into a single string erases semantic boundaries, and presents a lightweight, zero‑dependency Python runtime that preserves these boundaries, tracks provenance, and rejects invalid transformations before they reach the model. The post details the implementation, testing, and the guarantees and limitations of this approach.
The article discusses the appropriate contexts for using Claude Code versus Codex, two coding agents. It explains the strengths and ideal use cases for each tool, helping readers decide which agent to employ for specific programming tasks. The post provides guidance on selecting the most suitable coding assistant based on the nature of the work.
The article titled "Why Claude Code Time Estimates Are Poor" discusses the challenges and shortcomings of using Claude, an LLM, for estimating code development time. It highlights how these estimates can be unreliable and offers insights into improving communication when working with LLM programming tools.
Enterprise Document Intelligence [Vol. 1 #7bis] - Tobi Lütke and Andrej Karpathy named the practice in 2025.
Balancing context capability against cost, speed, and data The post Long Context vs. Short Context Model: When Does a Long Context Model Win?
Enterprise Document Intelligence [Vol. 1 #9bis] - Your RAG isn’t hallucinating, it’s answering the wrong context faithfully.
Enterprise Document Intelligence [Vol. 1 #7bis] - Tobi Lütke and Andrej Karpathy named the practice in 2025.
Enterprise Document Intelligence [Vol. 1 #7bis] - Tobi Lütke and Andrej Karpathy named the practice in 2025.
Maximize your efficiency with Claude Code The post How to Efficiently Prompt Claude Code appeared first on Towards Data Science .
arXiv:2607. 00692v1 Announce Type: new Abstract: Long-horizon LLM agents accumulate tool results, files, plans, and user constraints that are too structured to be treated as a disposable text suffix.