A quick orientation if you’re new here: this sits in the meta-arc — the stretch of posts about how I actually work with AI day to day, once the story stopped being about my own transformation and started being about the mechanics that make it sustainable.
Let me tell you something that took me an embarrassingly long time to understand.
Every time you open a new conversation with an AI, you are a stranger.
Not a returning customer. Not a familiar face. A complete stranger, walking into a room with someone who has never met you, has no memory of your previous conversations, and knows nothing about you except what you’re about to tell them.
It doesn’t matter that you talked for three hours yesterday. It doesn’t matter that you built something together, or had a breakthrough, or finally found the right way to explain the thing you’d been trying to explain for weeks. Open a new conversation and you’re starting from scratch.
The old conversation still exists — you can go back and read it. But the new conversation has no access to it. Every new chat starts fresh, knowing nothing of what came before, unless you deliberately bring that context with you.
This is not a bug. It’s not an oversight. It’s just how it works.
And while there are YouTubers, training courses, academies and even university degrees that cover this — if you’re working through AI on your own, the only one who can guide you through what to do is your AI. Or, for this current moment in time, me.
The context window
Here’s the technical reality, explained without the jargon.
Every AI conversation happens inside something called a context window. Think of it as a desk. Everything on the desk — every message you’ve sent, every response you’ve received, every document you’ve shared, every piece of context you’ve established — is visible and active while you’re working. The AI can see all of it. It shapes everything that comes back to you.
Your office is hot-desking. You’re finished for the night, and tomorrow you’ll need to find a new desk.
When you start a new conversation, the desk is empty. Not because your previous work was lost — it’s still in the old chat, readable, retrievable by you. But the new conversation can’t see it. You have to decide what comes with you and bring it yourself.
This is why the AI that felt like it knew you yesterday seems to know nothing about you today. It isn’t being difficult. It isn’t forgetting. It only ever had a desk, and today’s desk is new.
One more thing worth knowing
Sometimes the AI will start producing — enthusiastically, generously, at length — in a direction you didn’t intend, or simply going on far longer than you need. You don’t have to wait for it to finish.
You can interrupt.
Claude has a stop button. Use it. It’s not rude. It’s exactly the kind of taking-charge we talked about in “Taking charge of the runaway AI”]. The AI is working for you, not the other way around.
What projects do — and don’t do
If you’re using Claude specifically, you may have discovered Claude Projects — a way of organising conversations around a particular topic or purpose.
Projects help. They let you upload documents that stay available across sessions — instructions, notes, reference material, handover documents. Every new conversation in a project can see those uploaded files. That’s genuinely useful.
But here’s what projects don’t do: they don’t give the AI access to your previous conversations. You might have three or four chat sessions running different parts of the same project — and none of them know what the others have been doing. The chats themselves aren’t shared. Each new conversation still starts fresh.
This matters more than it might seem. If you’re building something across multiple sessions, and each new Claude is working without knowing the ground rules established in the previous ones — that’s a recipe for confusion. Not disaster. Just a lot of unnecessary reconstruction.
The solution is simple, but it has to be deliberate: save your key documents — your project instructions, your handover notes, your ground rules — to the project space. Upload them. Make them available to every conversation that needs them. That’s the only bridge that works.
I built my first four apps using Sonnet 4.5. I’m now working with Sonnet 5.0 for everyday work, with Opus 5.0 available for more complex tasks. Each model, each session, each new chat — a stranger, until you introduce yourself. The uploaded documents are how you make the introduction.
The handover document
This is where it gets practical.
If you’ve had a productive session — built something, worked something out, established context that you’ll need again — the most useful thing you can do before you start a new conversation is ask the AI to produce a handover document.
Not a summary. A handover. The kind of document you’d give to a colleague who was picking up your work while you were away. What was decided. What was built. What the current state is. What needs to happen next.
Download that document. Save it. Upload it to your project space — so every future conversation in that project has access to it. And at the start of your next session, reference it. Tell the new Claude where things stand.
It’s not seamless. It requires a habit. But it works.
If you want the other half of this — not the mechanics, but what’s actually at stake emotionally when a session ends, and what I capture beyond just the handover — that’s “Don’t Let the Window Close”. This post is the how. That one’s the why.
Why this matters for how you work
The context window limitation sounds like a frustration. In some ways it is.
But there’s another way to look at it.
The reconstruction cost matters more than it looks. Studies on interrupted work consistently find it takes upward of twenty minutes to fully refocus after a switch, not because the task itself is hard, but because part of your attention stays stuck rebuilding the mental model you just lost. That’s not a developer problem or an office problem. It’s exactly what happens every time you open a fresh AI chat with no handover and try to explain, from memory, what you were doing three sessions ago.
Every AI conversation is a clean slate. No accumulated misunderstandings. No half-remembered context that’s slightly wrong. No conversation history that’s grown so long the AI has started losing track of what was decided three hours ago.
Fresh desk. Every time.
The handover document means you control what carries forward. Not the AI’s imperfect memory of a long session. Your deliberate summary of what matters. The decisions you want to keep. The context that’s genuinely relevant.
You’re not at the mercy of what the AI remembers. You decide what survives.
That’s not a limitation dressed up as a feature. That’s actually how a well-run project works. At the end of every phase, you document. You hand over. You start the next phase with a clear brief.
If you’re like me, you’ve been doing this your whole career.
You just didn’t know you’d need to do it here too.
The practical checklist
Before you start a new AI conversation on an ongoing project:
Ask for a handover. Tell the AI to produce a summary of what was built, decided, or established — enough for a new session to pick up without losing the thread.
Download the file. Anything the AI produces lives only in the session. If you don’t download it, you may not be able to find it again easily.
Upload key documents to your project. If you’re using Claude Projects, uploaded files survive between sessions. Your handover document, your key reference material, your project instructions — these belong there, not just on your local drive.
Start new sessions with context. Don’t assume the AI remembers. Give it what it needs. Paste in the handover. Upload the relevant file. Spend two minutes at the start so you don’t spend twenty minutes wondering why it doesn’t know what you’re talking about.
Use the stop button. If the AI is heading somewhere you didn’t intend, or producing more than you need — interrupt it. That’s what the button is for.
The desk clears every time. You decide what goes back on it.
The AI doesn’t forget you. It never knew you. The knowing is something you have to bring.
Sandi is a Melbourne-based problem-solver, crisis-averter, and translator of the technical into the human. She spent decades being the person everyone called when something was broken, confusing, or just needed explaining properly — earning a reputation that preceded her wherever she went. Now she’s channelling that same instinct into AI: making it accessible, practical, and genuinely useful for people who think it isn’t for them.