Definition
Context Window: The maximum amount of text (measured in tokens) that a language model can process in a single inference call.
A practical guide to context budgets for AI agents. How to allocate tokens across system prompts, tools, retrieval, history, and a buffer in production.
Long context windows haven't replaced RAG. New 2026 benchmarks reveal the cost, speed, and accuracy tradeoffs, and when each approach wins in production.
Context compression reduces AI agent memory usage by 26-54% while preserving task performance. Here's how it works and why bigger context windows aren't the answer.
65% of agent failures come from context drift, not token limits. Here's how context compression keeps long-running AI agents on track.
AI agent memory fails because it's a context engineering problem, not a storage problem. Research reveals three failure modes and what actually works.
84% of developers use AI coding tools, but only 29% trust the output. The problem has less to do with models and more to do with codebase context.
A context window is the total text an AI model can process at once. Learn how they work, why size isn't everything, and what actually affects performance.
Prompt engineering is a dead end. Context engineering — designing what information AI models receive — is replacing it. Here's how to start applying it.
AI doesn't forget because it's broken — it forgets because everything gets crammed into one place. Here's the technical explanation and how to fix it.
Research shows LLMs drop from 95% to 60% accuracy as context grows stale. Here's how context rot degrades AI performance and why bigger windows won't help.