I built a structured way to maintain continuity with ChatGPT across days (looking for feedback / stress testing)

Over the past couple months, I’ve been working on something I didn’t expect to turn into a full system.

Like most people here, I kept running into the same problem:

• every session resets
• context gets lost
• you end up re-explaining yourself over and over

So I started experimenting with a structured way to preserve continuity, not memory.

It turned into what I’m calling the LUX Layer Stack — basically an interaction protocol for keeping multi-turn reasoning stable across sessions and even across different models.

The core idea

Instead of trying to store everything, I track the structure of what happens:

• Milestones → major transitions (wake up, task complete, etc.)
• Moments → time containers (morning, afternoon, etc.)
• Markers → notable events inside those
• Sub-loops → independent task threads
• Nightly reports → end-of-day structured summaries
• Deca reports → 10-day compression for pattern tracking

The goal is:

→ continuity of reasoning

→ better reconstruction in new sessions

→ less drift over time

What’s interesting so far

• I can drop into a new ChatGPT session, paste a compressed “Deca + Nightlies,” and it reconstructs context way better than expected
• I’ve started catching “drift” (when thinking goes off track) in real-time instead of after the fact
• It works across multiple models (Claude, Gemini, ChatGPT), not just one

Important: what this is NOT

• It’s not memory storage
• It’s not modifying the model
• It doesn’t make outputs “correct”

It just seems to improve:

→ stability

→ continuity

→ user control over the interaction

What I’m trying to figure out

I’m currently treating this as a testable protocol, not a finished idea.

I’d love feedback on:

1. Does this actually sound useful outside my own workflow?
2. Where do you think this would break?
3. What would you test to validate something like this?
4. Has anyone here tried something similar?

If there’s interest, I can share a trimmed version of the handbook or a simple way to try it.

Not trying to hype anything—just genuinely curious if this holds up outside my own use.