Context Engineering

A futuristic robot stands at the center of a glowing blue platform, compacting a flood of purple chat bubbles, logs, and data fragments into a small set of bright structured cubes, while external storage icons on the right show databases, cloud files, archives, and a secure vault, illustrating context compaction and a fast hot path for AI agents.

Context Compaction: Keeping the Hot Path Fast

AI Agent Engineering for Developers, Multi-Agent SystemsBy Sami 19.08.2026 Leave a comment

Most long-running agent failures are context failures, not reasoning failures. This article explains how context compaction keeps the hot path small, preserves recoverability, and turns memory management into an operational policy.

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A friendly futuristic robot manages a compact ring of glowing task-state icons, while blurred transcript panels fade into the background, visualizing short-term state as focused working memory for the current AI agent task.

Short-Term State in Agents: The Working Memory of the Current Task

AI Agent Engineering for Developers, Multi-Agent SystemsBy Sami 22.07.2026 Leave a comment

Short-term state is not a transcript. It is the working memory of the current task. This article explains how clean, structured thread state improves agent focus, reduces context pollution, and makes tool-using systems easier to debug and scale.

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