Memorizing session transcripts isn't useful

I remember when OpenAI announced ChatGPT now will remember stuff between sessions. Oh, you mean find random trivia about me and copy paste it between prompts without out my explicit consent.

”compare these three cars. Oh btw I am a data engineer, and my moms maiden name is Joana, and I am allergic to bad poetry. And code should be DRY, I prefer SQL over Python and what’s the most poisonous flower in Scandinavia?”.

I’ve had so much wierd output because context is ”””memorized””” and bleeding into completely unrelated projects and conversations. It’s the first feature I turn off.

Strongly agree here. claude-code’s memory system is occasionally useful but much more often harmful, pulling in obsolete info that muddies the waters about current tasks. I’ve frequently seen Claude’s own memories severely mislead it.

My guess is that has something to do with the training process leaving models unable to differentiate between “what’s happening now” and “what happened before”. Perhaps if making inferences from memories was actually part of the training process things would be different but my sense is that as an inference-time-only feature this just gets the models confused.

This is an annoying problem. It keeps making fake assumptions just because of hypothetical questions I've asked in the past.

It'll assume I own a datacenter and have lots of gpus just because I asked to research things.

My current technique, which seems to have improved maintainability, is to guide Claude to write commit messages specifically focused on "why this was done", "what changed in the theory of operation", and "what changed in the code". Then just reviewing the commits for a file or dir gives it a ton of useful context distilled from the sessions that produced them. Also, making a docs dir with concise .md files explaining the theory of operation and updating them with every commit.

It's because it mostly doesn't matter what you are trying to get the code to do. What matters is what the code does.

Session logs can absolutely be useful, but not when building further. It's just that that the place they slot in is during validation. You know, that place between the markdown plan and CI passing, where there's 800 new lines of code and it all seems sort of fine when you click around?

Session logs can show you what sort of manual validation happened. CI will run the tests you had, and the code will show you what new unit tests were added, but session logs can show you that the agent drove the app with Playwright, or that the agent read and considered the prod config as well as the dev config.

Nothing bulletproof, but not every piece of validation work merits a test in the repo that lives forever. We've gotten a lot of mileage out of re-analyzing the sessions, figuring out where the agent made decisions without asking, and forcing the agent to consider validation for those decisions. That's the sort of thing that's hard to dictate up front but easy to highlight with the session logs.

Isn’t this just a form of the bitter lesson? Our attempts to make engineered context and agents will simply be made obsolete with bigger and better models. Those transcripts are probably extremely useful for lesser capable models, and near unnecessary for frontier ones, maybe?

I agree with the take not to bother with a sophisticated memory system. Anything worth remembering should be in docs, guides, source comments, commit messages or tickets. You don't need another layer, every conceivable granularity is already covered by existing best practices

At the core this is a hardware problem. 1M tokens is simply not enough context to understand a codebase the way a human would understand it. Being able to selectively forget is potentially a very valuable power, but right now it's a substitute for a human's ability to remember the rough shape of something, decide it's uninteresting, and remember that it is uninteresting.

They talk about memory only being useful when guided by a human, I think the proper solution is deeper than that, it probably involves feeding the entire codebase and every agent session into a finetuning of the model, though at that point you might want some guidance to avoid feeding certain sessions into the model. Or maybe not, maybe the bitter lesson applies.

Even with memory off this occurs within a conversation.

It is like an annoying friend, who remembers something from a past conversation, that you have grown and developed from, but they still want to hold it against you.

Strong disagree on this.

I have Claude/Codex keep logs [1]. It's just prompted in my AGENTS.md [0].

> Every session must produce one of: a session log OR a plan, and end with a written summary appended to it. Default to a log; reserve plans for substantive design work.

It's incredibly valuable. For example today I started a few sessions off like this:

- What's the status of my work on Renovate?

- I was recently working on X, find that

- Did we fix the issue with backups? What are the next steps?

- This bug came up again. Didn't we fix it already?

[0]: https://github.com/shepherdjerred/monorepo/blob/main/AGENTS....

[1]: https://github.com/shepherdjerred/monorepo/tree/main/package...

I found that if you allow any low value things into memory, Claude will notice that established pattern and start trying to add low value memories at an ever increasing pace.

Hilariously, I'm working on a Claude Desktop replacement that does all of things. It's the best parts of Claude Desktop, Code, Cowork, and MCP connectors, but uses a client/server design. It's written in JavaFx so it's lightweight, fast, cross platform, and not another damned electron app.

Ideal outcome is this turns into a startup. I think there's a real need for team-oriented AI to avoid siloing of knowledge.

I like the memory system, in general. For reference I'm using mostly Opus 4.8 + Max effort. It will often pull things out of memory that are relevant. Like I'll ask it to come up with a few options I should consider for, say, a self-hosted OIDC provider and it'll say things like "Considering the size of your operations team, this might be a better fit because of X and Y".

Now, I'll agree that this is probably the sort of thing I should put in the CLAUDE.md, but in this case it wasn't on my radar to put that in my CLAUDE.md, so it was nice that it surfaced that.

It does sometimes go awry though. Today I was asking about a problem I was having authenticating, and it said "you may be running into this trusted proxy setting because you put your apps behind an haproxy". That is true of 95% of our apps, so it was worth mentioning, but in this case it was not so I had to correct it. But, I'm glad it mentioned it because if we did have it proxied it could have saved me a lot of time.

I specifically disabled claude memory in a project because it kept writing down thigns to memory that didn't need to be in memory, including severly wrong statements that then would confuse it later. At some point it got re-enabled automatically which had me ask claude itself to "turn it the fuck off" by which it promptly figured out that both ("autoMemoryEnabled": false, "autoDreamEnabled": false) are necessary and need to be at the user home settings, not in a project override (which is what I had with the original setup that eventually got ignored by a CC update).

I agree with other commenters here, if anything is worth being rememebered, it will be in code comments, git commit messages, CLAUDE.md or other formal documentation. The auto memory system just causes confusion and leaves stale and outdated information written down.

Its an interesting thought experiment as well, I originally thought that having the model write down memory files by itself would be a nice addition, but after playing around with it, it became clear to me that good as an idea turns out bad in practice because the model can't correctly gauge what deserves being stored as a memory.

The only times I found the memory feature useful are in "projects" I created myself.

In a project my questions are usually revolved around the same topic. Having context carried across threads actually make a lot of sense.

In the general mode where I'm expecting models to be *stateless*, having memory is very annoying.

The top of my ~/.claude/CLAUDE.md:

> Don't turn a one-off or area-specific comment into a durable memory without my explicit confirmation. You have a history of over-indexing on one-offs, and those memories end up getting cited to override well-tuned skills.

I'm not sure how well this take will age.

Its certainly true at the moment, but give it 10 years and we might have systems that are much cheaper and much better at context management than they are now.

(Apologies to anyone who is under the impression that we were very likely going to be at the singularity in 10 years time. Possible != very likely)

I must admit lingering long since retired 'memories' are currently one of the biggest pitfalls of the setup. Wiping all 'memory.md' often leads to better sustain.

Thats interesting, but what was the methodology?

is the conclusion really that its just more important to create proper artifacts from any tricks that got the llm to understand the code better?

is the tool for searching the history just bad?

> I believed this so strongly that my company built an entire product around this concept. I used to tell folks that "session transcripts were the new oil," that they were more valuable than the code itself.

This is infuriatingly common wrt talking/writing about how to use AI effectively. All of the "this is how you write an AGENTS.md" and "you need to talk to it like X to optimize it". Like sure, you can believe that as much as you want but unless you provide some evidence you can keep your shitty CLAUDE.md to yourself and don't pollute the whole company's git repo, thanks.

Those small, random items that pop-up later on in conversation actually make the experience feel better. But that's just my own personal experience.

I have this in my global CLAUDE.md after being annoyed by all the random crap memories.

> Don't start generating an auto-memory entry before asking me. Ask first, write only if I confirm — no speculative drafting.

No more crap after this.

Incidentally I don’t recall Opus 4.8 asking me once in the past few weeks. Older models did ask semi-frequently.

There's a lot of valuable information in there, its' too noisy.

t once had to tell claude 3-4 times to stop assuming the state of a system was the way it kept iterating it was cause it was in it's memory. I repeatably told it to otherwise and it just never updated it's memory and instead kept referencing it's memory about the state of a particular system

Blog posts like this just blow me away.

> I believed this so strongly that my company built an entire product around this concept. I used to tell folks that "session transcripts were the new oil," that they were more valuable than the code itself.

> […]

> We don't really write code by hand anymore.

Honestly, isn't this just influencer spam? What possible value is there in reading about people who used to have products, but no longer write their own code, complaining about the inscrutable prediction machine they have handed that job and their livelihoods to?

Like, if you have complaints about the thing, perhaps you should address them to your supplier directly. None of your readers can help, and nobody's magic folk solution to your problem is better than yours.

And there are so many of these sorts of posts. Are we not entirely cooked?

(I think I have concluded that if people writing about AI aren't writing about interesting things they have achieved with small, local LLMs — which for clarity I am fully interested in reading - then I'm done reading. This whole blogging-about-cloud-AI genre is just weird and irresponsible now)

Settings > Capabilities > "Generate memory from chat history"

Toggle it off and never think about it again.

I mean, it’s pretty clear the people who work on Claude Code aren’t actually looking at what they’re implementing. The thought behind this feature seems like it goes nowhere beyond “oh wouldn’t it be nice if Claude could remember things about you? Ok Claude go implement this” and nobody bothered to see if it was useful or helpful.

>We have found zero performance benefit on SWE tasks when agents have search access to their previous transcript sessions

I refuse to believe this is true. The ability for an agent to find information from before a compaction is incredibly useful. At compaction time it's impossible to know what exactly may be still needed.

There has been this slow transition inside me, as someone who likes to not touch the AI as much as possible, where I've gone from skeptical and argumentative about it all to starting to just feel sad for all the Claude et al heads. Like, this is such a ridiculous house of cards you have to deal with all the time, which isn't even directly concerning the task at hand, presumably. Like you're cooking yourself a meal but its just nuking a burrito and then still somehow needing to wash the dishes for an hour.

Not that this isolated article is super damning or anything, but the accumulated set of all these reports has left me only empathetic, I think, of these other devs. Like, I just want to tell them, "it can be ok, it doesn't need to be like this.."

non-deterministic system behaves non deterministically. in other news, water is wet.

The author says

>> We don't really write code by hand anymore.

The software world is very close to building a super intelligent senior software developer. Companies like this will ask all the best things a software engineer does automatically. Now claude will add it into the coding agents itself.

Damn, I didn't see this coming.

Its first the build the intelligent builder. We will figure out what we want to build later.

Edit: Before more people take it seriously. This is sarcasm. I don't wish this.