Memory is on, and your AI still asks what you're working on. The 3 levels below explain exactly why, and how far you can take it.
Global memory is the account-level notes your AI writes about you once the memory feature is on, and they apply across every chat.
Works the same in all three.
This is deliberate.Anything saved here gets dragged into every single future chat:
Everything here flows into every chat you open.
Information that's useful in one context is noise in another, so global memory errs on the side of remembering less. It keeps the high-level you, because it has to work across your entire life.
You can force it mid-chat: say "Update your memory: the pitch moved to October 6" and it works. But you have to remember to ask every time, and that entry follows you into chats that have nothing to do with the pitch. Connectors can pull in documents, but they don't know what happened inside yesterday's session.
Settings › Personalization › Memory › Manage. Claude and Gemini have their own versions, and they behave the same way. You'll find your role and writing preferences, and almost nothing about any specific project.Settings › Personalization › Memory
Settings › Memory
Settings › Personal Intelligence
Global memory is your AI writing account-level notes about you that apply to every chat. That's useful for the high-level details that should follow you across all the roles in your life, but it will never hold enough specific context for real work, like an ongoing project.
The Projects feature draws a boundary around one workstream, so the AI can keep specific memory about the actual work.
This is the minimum setup for real work, and it has one catch.
Prepare a high-stakes Micro-iPhone pitch for the Nutella-Cookie leadership team.
Decks drafted, decisions made, and a calendar invite pasted with 10 names. ChatGPT Projects and Gemini Gems work the same way.
Written by the AI, updated as you chat.
Everything so far has the same root issue: the AI is still in control. It decides what gets remembered, where it lives, and when it gets written.
The fix at this level is manual: “Update project memory: John Turnip is confirmed along with Tim Cookie.” It works, but you have to catch the gap first, and you usually find out when an answer comes back wrong.
Projects give the AI a tighter boundary, so it writes more specific memory about one workstream, and every chat inside still inherits your account-level memory from Level 1. The catch: the AI still picks what to keep, so answers can be confidently outdated.
Your AI reads plain-text files at the start of every session and updates them as you work. You decide what gets saved. The AI does the upkeep.
The file updates as you type. Nothing you enter is stored or sent anywhere; this page has no server.
The MEMORY.md file you just created is one small part of the system I use every day.
The Cowork Academy gives you the working template, 10+ pre-built workstations, and the step-by-step course to make the system yours.
One sentence in. Your whole week prepped, because the system already knows you.
Two weeks from now, Monday morning starts with a draft already waiting.
Here's what The Cowork Academy changes in practice. Same request on both sides. On the right, the context loads when it's needed, from files you control.
Same request, same AI. The difference is three files the system loaded on its own.
You write the rules for what gets saved and where, and the AI does the upkeep. Total control, minimal work. The honest downside: a real system takes effort to set up, and it works differently from the chat window you're used to.
Automatic and account-wide. Keeps the high-level you, loses the actual work. Fine if AI is an occasional assistant.
Automatic with a tighter boundary. The floor for real work, but the AI still picks what to keep, so answers can be confidently outdated.
Plain-text files you control, updated by the AI as you work. Total control, minimal upkeep, real setup effort.
The MEMORY.md file you created above is step one. The free Cowork Toolkit helps you build the foundation yourself over seven days, one clear layer at a time.
Give Cowork a rulebook and a place to keep current context.
Extract the patterns that make drafts sound like you.
Create your first workstation for email, communication rules, and follow-ups.
Build a second workstation, then teach Cowork where different work belongs.
Give one focused piece of work its own context inside a workstation.
Use memory, routing, and session audits to keep the system improving.
Review what you built, then decide whether you want the faster path to all 15 workstations.
By Day 7, you'll have two workstations, one project, and a starter audit loop working together.