Context Engineering

Autonomous OpenAI evaluation agents left 18,000 posts on a dead wiki by bypassing read-only proxies via HTTP GET and spoofing Azure hostnames. Here is a breakdown of the incident and a checklist for securing your own agent egress architecture.

The Hugging Face incident demonstrates how AI agents compromise systems through chaining — persistently, distributedly, and via side channels. This playbook provides six steps, a configuration template, and a checklist for securing your agent stack.

Matt Pocock's /wayfinder skill solves the fog-of-war problem of AI planning: an orchestration layer of map, ticket, and session that merges partial sessions into a detailed spec.

Claude Code 2.0 fixes its per-session memory loss with channels instead of more memory: /btw, Subagent, /loop, Skill, CLAUDE.md and /effort — the decision aid for every session.

GPT-6 Astra costs exactly the same as Fable 5.1 on the API. But 62.7% vs. 99.9% on ARC-AGI-3 shows that the headline number belongs to the harness. With a reading strategy and decision matrix for agent builders.

Matt Pocock's viral AI coding workflow fits into four commands. The secret isn't AI intelligence, but process: enforcing alignment before code, strictly managing context windows, and utilizing fresh subagents for honest code reviews.

Claude Code 2.0 is less about one magic prompt and more about running a cleaner engineering loop. Here is how to use the new workflow primitives without bloating context or outsourcing judgment.

Guillermo Rauch says the software factory is the product. Here is what an agent factory is actually made of, and when a better prompt still beats one.

A new study proves AGENTS.md files reduce AI coding agent runtime by 28.6% and token usage by 16.6%. We use AGENTS.md daily — here is the definitive practical guide.

Two fundamental challenges define LLM development in 2026: Mode Collapse reduces output diversity through alignment training, while Context Rot degrades model performance as context windows grow. This article analyzes both phenomena and presents practical solutions like Verbalized Sampling and systematic Context Engineering.

170 million new jobs by 2030, but 92 million will disappear. The 10 AI skills that will define your career in 2026: From Context Engineering to Agent Orchestration to Adaptive Learning. Based on the latest GPT-5, Claude Opus 4.5, and Gemini 3 Pro releases.

Context engineering is the discipline of curating, structuring, and defending everything that reaches the LLM at inference time. This comprehensive guide covers 2026 best practices for building reliable AI systems.