I asked an AI to tweak one image. It came back with a completely different picture. I went and figured out why — and it is more interesting than "the AI got confused".
It turns out that platforms like ChatGPT, Claude and Perplexity do not have real memory. Every time you send a message, the entire conversation gets resent to the model — from scratch. It rereads everything, every single turn, before it replies. That is also why the token count keeps climbing the longer a chat runs.
Lost in the middle
Here is the part that actually surprised me. As a conversation grows, the model does not treat every part of it equally. There is a documented behaviour called "lost in the middle" — it pays the most attention to the very start and to whatever is most recent, and quietly deprioritises everything in between.
Nothing gets deleted. It is all still there. The model just stops weighing it as strongly. So an instruction from message 4 can be functionally forgotten by message 20 — even though it is technically still sitting in the chat.
Nothing gets deleted. The model just stops weighing it as strongly.
Why images get hit even harder
Asking for a "small tweak" is not like Photoshop. There is no file being edited. The model rereads the whole chat, writes a brand-new prompt based on it, and hands that to a completely separate image model — which paints a new image from scratch. Every image is a fresh repaint. Guessed. Every single time.
I found this out the hard way making a 3-slide LinkedIn carousel: slide 1 came out perfect, slide 2 had content from slide 1 leaking in, and slide 3 drifted to a completely different theme. Same conversation. Same intent. Three very different results.
The takeaway
The interactive walkthrough at the top of this page lets you watch all of this unfold step by step — from the growing transcript, through the "lost in the middle" effect, to the 3-slide case study. Play with it, then come back here.
The fix is not a better model — it is understanding how the context window actually works, and restating your key instructions instead of relying on the model to "remember" them.