Memory vs context window: what your agent remembers

Context = what's in this chat right now. Memory = stored notes your agent reads back next time.

Some examples

• Use context for the current task.
• Use memory (a file, a vector DB) for facts that matter across sessions.
• Don't dump everything into context — it's expensive and noisy.

Try it!

Set up a tiny agent with a memory.md file it reads at start and writes to at end.

Understanding "Memory vs context window: what your agent remembers" in practice: AI agents don't just answer questions — they can do things, like looking things up, writing files, or talking to apps. Your agent forgets between sessions unless you give it actual memory — not just a longer context window — and knowing how to apply this gives you a concrete advantage.

• Design clear agent goals before adding tools
• Define permissions and scope before deploying any agent
• Build in human-approval checkpoints for high-stakes actions
• Understand when to use an agent vs. a simple chat prompt

1. 1Design an agent spec: goal, tools, permissions, stop condition
2. 2Run a simple web-search agent in a sandbox environment
3. 3Instrument an existing workflow to identify where an agent could save time