In short (TL;DR): a Reddit user built a portable .txt “Memory Journal” that an AI writes at the end of a session. The next AI can read it and pick up the context, the method, and the mistakes. The author says two models rebuilt a working file converter from the journal alone on the first try.
What the Memory Journal is
u/NoobSolid26 shared a format they spent a month testing and tweaking. You paste a “card” into an AI, and the AI writes a memory journal as a text file. The card is styled like a skill card, which the author admits is deliberate and a bit eccentric.
The idea behind it is simple: if an AI knows the context, it can also describe how it made something. So the journal does more than summarize a chat. It tries to carry the reasoning along with the result. Most handoff notes say “we built X.” This one aims to say “we built X this way, here is why, and here is what we tried that broke.” That difference is what lets a fresh model continue the work instead of guessing at it.
Because it is plain text, it also travels well. You can store it in a notes app, drop it in a project folder, or paste it into any chat window, whatever model or vendor you happen to be using that week.
What goes in the journal
According to the post, the journal captures:
- Context, so you can resume work with the journal plus your project files
- Skill, meaning enough method that a reader can reproduce the work
- Mistakes, so the next model doesn’t repeat them
- Facts sorted into proven, unproven, and disproven
The sorting of facts is worth a second look. A normal summary flattens everything into one confident tone, so a guess reads the same as a verified result. Splitting claims into proven, unproven, and disproven tells the next model what it can build on and what it should double check. The “disproven” bucket is especially handy, because it saves the new session from reopening a question you already closed.
The journal is split into A/B/C sections. It mostly lets the writing AI decide what matters and stays fairly neutral. That freedom is a strength, since the model that did the work knows best what was hard. It is also a risk, which is why the tips below suggest reading the result yourself.
What the author tested
The headline test was an EGO engine XML file conversion. One AI wrote a journal about the work. Then DeepSeek (deep think mode) and Claude Sonnet (high effort) each rebuilt the converter from the journal alone. The author reports both succeeded on the first attempt. That is one person’s report, so treat it as promising rather than proven.
The author also shared a modding journal passed through four writers, and a casual chat journal about random topics. Passing a journal through several writers is a decent stress test, since each rewrite shows whether the important details survive repeated handoffs. They note that a philosophically charged journal can shift the next model’s behavior and vocabulary. That is a useful warning: whatever tone the journal has, the reader may inherit it. If you want a dry, technical collaborator, keep the journal dry and technical.
Use cases
- 🔧 Long technical projects where you switch models or start fresh chats, such as a script that grows over many sessions and starts to lose its original logic
- 🧠 Handing a half-finished task to a different AI without re-explaining everything, for example moving from a cheaper model to a stronger one for the hard part
- 📝 Keeping a record of what failed, so you stop retrying dead ends like a library that looked right but didn’t support your file format
Tips before you try it
The author says it works best with a capable model, ideally one with an effort slider. Weaker or rushed settings tend to produce thin journals that skip the reasoning, which defeats the point. You can also add your own instructions, such as “add completion status to goals” or “leave out section X.” Read the journal before you pass it on, since the writing AI decides what to keep. A two minute skim is usually enough to catch a missing step or a claim filed under “proven” that was really just a guess.
It also helps to keep the journal next to the project files it refers to. The author’s approach pairs the two, so the reader gets the narrative from the journal and the real material from your files. Save a dated copy at the end of each session so you can roll back if a later journal drifts.
Prompt of the Day
This is a lightweight version of the idea, not the author’s card:
“Write a handoff journal for this session as a plain text file. Include: the goal, what we built and how, what we proved, what we’re unsure about, what we ruled out and why, and the next three steps. Write it so a different AI could continue the work without seeing this chat.”
Call to Action
Try the full format using the Pastebin links in the original r/PromptEngineering thread, or paste the prompt above at the end of your next long session. Then open a fresh chat with the journal and see how much it recovers. Tell Captain YAR what survived the handoff and what didn’t.
Frequently Asked Questions
Q: Can you chain journals to gradually shift an AI’s tone?
The post already shows that a philosophically charged journal drifts both behavior and vocabulary, so the effect is real. Chaining is a fair experiment, but the author doesn’t report testing it. Save each journal as its own version, load them one at a time, and run the same prompt after each step so you can see where the tone actually moves.
Q: Does this work with weaker models?
The author recommends a capable model with an effort slider, and the showcase recreations came from strong models at high effort. A journal is only as useful as the model reading it, so if a recreation misses details, raise the effort before you rewrite the journal. Keep notes on the weak-model failures too, since they show which sections need to be more explicit.
Q: Do mistakes get carried over too?
Yes, and the author treats that as part of the design, because the next session starts with known dead ends already marked. The catch is that an unproven idea written down as proven gets copied forward just as confidently. Keep the proven, unproven, and disproven sections honest, and move an entry to proven only after you’ve tested it.
I created a AI memory format that transfers both context and skill
by u/NoobSolid26 in PromptEngineering