Memory & Context (2026)

Memory and context tools decide what an AI agent knows at the moment it acts. Some give agents long-term memory that persists across sessions and tools; others index a codebase into a queryable map, or compress tool output and documents so more useful information fits into the context window. For coding agents in particular, better context often improves results more than a stronger model.

Consider where memory is stored (locally, in your repository, or in a hosted service), which agents and editors it works with, and how it decides what to keep and what to forget. For context compression, check how much it reduces tokens on your own workloads and whether answers stay accurate. Prefer tools that keep proprietary data local when your code or documents are sensitive.