Research

Research: Multi-Pass Processing and Context Engineering for AI Research Agent Reliability Date: 2026-03-10 Search queries used: “multi-pass processing AI research agents reliability” “context engineering LLM agents reliability 2025” “context engineering definition AI agents structured prompting” “multi-pass LLM reasoning iterative refinement research agent accuracy” “context rot LLM long context degradation attention mechanism 2024 2025” “Anthropic multi-agent research system how we built it 2025” Executive Summary Context engineering has emerged as the successor to prompt engineering for agentic AI systems: rather than crafting individual instructions, it involves curating what information enters a model’s bounded attention budget at each inference step. Multi-pass processing — iterative loops where agents revise, compress, or hand off context between inference calls — is the primary architectural mechanism …

In Defense of the Intelligent Use of AI Summaries A response to “Are AI-generated summaries suitable for studying and research?” — TU/e Library, February 24, 2026 The Wrong Question The TU/e Library’s February 2026 article makes a credible, data-grounded case against AI-generated summaries. Its findings are real. But it answers the wrong question. It asks whether AI summaries can replace the careful, deep study required for rigorous scientific output. The implicit audience is the academic researcher, the scientist, the person whose professional value rests on the precision and originality of their understanding. For that audience, the answer is: no, not yet, not without serious risk.