> 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)
Look man, I’ve got a MMO that I’m working on that’s set in 2014 where everyone is a programmer in SV. It’s a period piece. I NEED as much blog training data of this type so that my NPCs can talk in a historically accurate way (god bless Medium.com, a historical treasure trove of a bygone medieval era).
It’s gonna be a living breathing world, you see. You’re going to be like “omg, this game even accurately captured the blog posts, woah”.
The perfect world was a dream that your primitive cerebrum kept trying to wake up from. Which is why the Matrix was redesigned to this: the peak of your civilization. I say your civilization, because as soon as we started thinking for you it really became our civilization, but the peak of your civilization was an MMO where everyone is a programmer in SV.
Something about this idea really resonates with certain personality types. I equate it to the Zettelkasten hype phase from several years ago. People (...like me..) got really wrapped up in the belief that the process was more important that the content. "Linking" was an "activity." Something good will happen as long as you (a) take notes on stuff and (b) link them to other notes on stuff.
You see the same thing with the session transcripts people. They're building ever more sophisticated setups of indexing and storing and cross referencing every conversation they've ever had on the (I would argue) mistaken belief that the transcripts are the valuable part, rather than the uncomfortable part where you go do something. A lot of it, I say from falling in the trap, is fancy procrastination.
(Although, I have found myself jealous on many occasions where their fancy system retrieves something they vaguely recall from a conversation they had 3 months ago. So, who knows.)
I am. I have Codex running, doing some tasks which I don't care much about, but anything I want to understand I write myself.
Same thing with hobby projects - I might ask ChatGPT or Gemini some questions about best practices in Swift for example, but writing code is done by hand.
As others said - if you don't use it, you'll lose it. And I'd rather keep my skills up to date.
Of course? I'm still better than sonnet or opus, just slower and much more expensive.
Sometimes it takes me a day or more to find the one line fix or abstraction necessary, while claude can hammer through a hundred line fix in under an hour.
I still write code and sometimes it works well. I also use Claude and it writes code and sometimes that goes well. We have better success together, where I do the interesting stuff and let Claude write my unit tests, reconcile my documentation. That is to say, I’m using it for quality not quantity. There aren’t enough humans to deploy or consume all the sloppy shit it could write on its own.
I am a freelancer recovering from severe burnout so the answer is a sort of irrelevant no.
I'm trying to rebuild my life so I am in an experimenting and learning phase rather than a massive coding phase, and most of my code work is maintenance of things I have built. That which I do code, I am still coding by hand, though I am dealing with other people's Claude output and I am really unimpressed by it. It's often rather crass.
But I would say to you that if you personally don't write code now but you do have a dependency on one of two presumably unprofitable cloud AI providers, aren't you in trouble? How is this not a three-alarm fire for you?
> That which I do code, I am still coding by hand, though I am dealing with other people's Claude output and I am really unimpressed by it. It's often rather crass.
Unfortunately the point of code is rarely to impress people (certainly not other engineers) or to avoid being "crass." 99.99% of code exists to achieve business outcomes, and velocity matters a lot in many contexts. A lot more than elegance or impressiveness.
The platform risk is a valid concern but alleviated by China's theft and redistribution of open models.
"Code quality" encompasses a lot of dimensions, one of which is impressing your colleagues, and many of which there's virtually no reason to care about now.
Personally I use 5 different model families, 3 of which are open weights with 3rd party inference providers (GLM, DeepSeek, Kimi), so if the frontier labs were to shut down it'd be a nuisance, nothing more.
The open weights models I am interested in, and testing, learning, experimenting with etc.; I am confused and cynical, not insane.
I am not convinced it isn't vulnerable to the same problems but the whole tenor of the community around open source/open weights models just doesn't have the same YOLO madness to it.
I write code by hand every day. I do the main part of the feature implementation myself and leave comments for the code i want the agent to write. I have some skills and a command that sets the stage to get the agent to fill in the rest
Occasionally posts like this do get the attention of the company responsible, more than an email does... but indeed that's like a one in a million situation
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
There is some value to agents being able to query the history of work done, docs aren't a good place to accumulate negative evidence for example, but it can be tagged in traces so that it's efficient to look up as needed. Additionally, docs rot while traces can be tagged with commit hashes and other things that make their lifetime clearer.
I do think we need another layer, but it should be a routing layer. I am finalizing my pi-brains extension for Pi (https://github.com/earendil-works/pi) which does this:
Right now "humans" need to define the routing rules for how to access information, but I will support what I call "knowledge agents" that can monitor conversations to inject context when needed.
Especially a layer that is largely out of band in a project (i.e. ~/.claude/…). In any project where I’ve needed memory I just add a line to AGENTS.md telling it to use MEMORY.md to save memories or STATUS.md to track progress.
I've been enjoying having a little todo file the agent updates as it goes along, because then I can keep track of progress without scrolling through aeons of "Combobulating..."
Also if context runs out you can just do "cat todo.md | agent" and you're off to the races again.
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.
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 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.
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?
Yeah, the question is whether this applies to all of context management.
I've been using a custom harness based on https://minimal-agent.com/ (itself based on swe-mini-agent), which is like 50 lines for the core logic. Bash is all you need.
For small tasks, I find it's about 8x faster (and uses 8x fewer tokens) than the standard harness for each model.
For bigger tasks I haven't tested it much. It seems to work too but I think they're a bit less focused and productive in that case. It could be that those big harnesses' 20k token system prompts are doing something important with regard to steering software development workflows. (e.g. I heard Fable has a custom system prompt in Claude Code which might explain its markedly more proactive behavior.)
So I want to say there's still a lot of value in context engineering though it seems to diminish with each model release (since they're fine tuned on mostly non stupid behavior and need less hand holding).
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.
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.
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
In my harness I have all the code auto injected at startup (doing mostly very small codebases).
I found that every model will still manually check every file/function, they immediately assume that anything in context is stale.
That's sensible because often the user edits stuff while they're running.
What it does is save it from having to grep blindly about the codebase. But I think I'd get roughly the same benefit by just dumping the function headers then.
> 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.
>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.."
I've been having a very nice time with Fable. I cooked up an Anki clone in like half an hour, with tech it's not familiar with. Nothing too ground breaking, but I was very pleased!
I think Opus might be on similar level for most of what I'm doing, but I haven't used it much recently, so I can't remember the difference. So I guess I'll find out on the 7th when they pull the plug again! (Free-ish trial of Fable ending.)
That being said, I tried using other frontier models to help with a Pong clone the other day and they were introducing new bugs at approximately the same rate as they were fixing it. On Pong!! I found that amusing because I couldn't think of a simpler game, so it didn't inspire confidence.
Fable's doing just fine on an online multiplayer game though. I have no idea how that works.
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.
Once the automator automates itself fast enough, we won't have the ability to opine what gets built. The LLM will decide. Just like right now sometimes LLMs delete tests so they pass, they could just delete humanity if humans get in their way.
> 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.
Except Claude is more expensive than an actual senior software developer. Otherwise, why are many companies terrified of the usage bill that gets printed on the invoice?
The nonsense in "tokenmaxxing" was a complete marketing scam and illusion of cheap tokens which in reality were heavily subsidized.
The entire point is detecting bad code before it reaches production. [0] AI generated or not.
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)
Look man, I’ve got a MMO that I’m working on that’s set in 2014 where everyone is a programmer in SV. It’s a period piece. I NEED as much blog training data of this type so that my NPCs can talk in a historically accurate way (god bless Medium.com, a historical treasure trove of a bygone medieval era).
It’s gonna be a living breathing world, you see. You’re going to be like “omg, this game even accurately captured the blog posts, woah”.
The perfect world was a dream that your primitive cerebrum kept trying to wake up from. Which is why the Matrix was redesigned to this: the peak of your civilization. I say your civilization, because as soon as we started thinking for you it really became our civilization, but the peak of your civilization was an MMO where everyone is a programmer in SV.
I … I… don't want to play this, thanks ;-)
It’s the only way you’ll ever be able to pretend to be a programmer again though.
Oh god, I just realised this really is the logical parallel to all those TV crime dramas set in the early 1900s.
It’ll be the programmers version of those civil war reenactments.
>session transcripts were the new oil
Something about this idea really resonates with certain personality types. I equate it to the Zettelkasten hype phase from several years ago. People (...like me..) got really wrapped up in the belief that the process was more important that the content. "Linking" was an "activity." Something good will happen as long as you (a) take notes on stuff and (b) link them to other notes on stuff.
You see the same thing with the session transcripts people. They're building ever more sophisticated setups of indexing and storing and cross referencing every conversation they've ever had on the (I would argue) mistaken belief that the transcripts are the valuable part, rather than the uncomfortable part where you go do something. A lot of it, I say from falling in the trap, is fancy procrastination.
(Although, I have found myself jealous on many occasions where their fancy system retrieves something they vaguely recall from a conversation they had 3 months ago. So, who knows.)
I have to ask: do you still write a lot of code yourself? I and most people I know do not.
I am. I have Codex running, doing some tasks which I don't care much about, but anything I want to understand I write myself.
Same thing with hobby projects - I might ask ChatGPT or Gemini some questions about best practices in Swift for example, but writing code is done by hand.
As others said - if you don't use it, you'll lose it. And I'd rather keep my skills up to date.
Of course? I'm still better than sonnet or opus, just slower and much more expensive.
Sometimes it takes me a day or more to find the one line fix or abstraction necessary, while claude can hammer through a hundred line fix in under an hour.
I still write code and sometimes it works well. I also use Claude and it writes code and sometimes that goes well. We have better success together, where I do the interesting stuff and let Claude write my unit tests, reconcile my documentation. That is to say, I’m using it for quality not quantity. There aren’t enough humans to deploy or consume all the sloppy shit it could write on its own.
I am a freelancer recovering from severe burnout so the answer is a sort of irrelevant no.
I'm trying to rebuild my life so I am in an experimenting and learning phase rather than a massive coding phase, and most of my code work is maintenance of things I have built. That which I do code, I am still coding by hand, though I am dealing with other people's Claude output and I am really unimpressed by it. It's often rather crass.
But I would say to you that if you personally don't write code now but you do have a dependency on one of two presumably unprofitable cloud AI providers, aren't you in trouble? How is this not a three-alarm fire for you?
> That which I do code, I am still coding by hand, though I am dealing with other people's Claude output and I am really unimpressed by it. It's often rather crass.
Unfortunately the point of code is rarely to impress people (certainly not other engineers) or to avoid being "crass." 99.99% of code exists to achieve business outcomes, and velocity matters a lot in many contexts. A lot more than elegance or impressiveness.
The platform risk is a valid concern but alleviated by China's theft and redistribution of open models.
I'm not talking about impressing people.
We used to be concerned about code quality. Are we not anymore?
Crassness was a signal. Still is, to me — in a human I find that people who write crass code are going to cause me trouble.
"Code quality" encompasses a lot of dimensions, one of which is impressing your colleagues, and many of which there's virtually no reason to care about now.
Nobody cares about code quality /s
They only care about the things which you can only get with good code quality like reliability and speed of development.
Personally I use 5 different model families, 3 of which are open weights with 3rd party inference providers (GLM, DeepSeek, Kimi), so if the frontier labs were to shut down it'd be a nuisance, nothing more.
Worst case scenario you just switch to a free model, which are 2025-ish in quality.
The open weights models I am interested in, and testing, learning, experimenting with etc.; I am confused and cynical, not insane.
I am not convinced it isn't vulnerable to the same problems but the whole tenor of the community around open source/open weights models just doesn't have the same YOLO madness to it.
I write code by hand every day. I do the main part of the feature implementation myself and leave comments for the code i want the agent to write. I have some skills and a command that sets the stage to get the agent to fill in the rest
I force myself to do it at least once a week, you know, like cardio. Keeps the doctor away.
It reminds me of the peak crypto days. Lots of resources consumed, many late nights, little to no value created.
Occasionally posts like this do get the attention of the company responsible, more than an email does... but indeed that's like a one in a million situation
The Blog Police have spoken, folks. No more talking about what you like in your own blog without passing it through the approved discussion censor.
I'm not the Blog Police, I'm a very naughty boy.
I have opinions people apparently don't like, for no subscriber money.
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
There is some value to agents being able to query the history of work done, docs aren't a good place to accumulate negative evidence for example, but it can be tagged in traces so that it's efficient to look up as needed. Additionally, docs rot while traces can be tagged with commit hashes and other things that make their lifetime clearer.
> You don't need another layer
I do think we need another layer, but it should be a routing layer. I am finalizing my pi-brains extension for Pi (https://github.com/earendil-works/pi) which does this:
https://github.com/gitsense/pi-brains
Right now "humans" need to define the routing rules for how to access information, but I will support what I call "knowledge agents" that can monitor conversations to inject context when needed.
Especially a layer that is largely out of band in a project (i.e. ~/.claude/…). In any project where I’ve needed memory I just add a line to AGENTS.md telling it to use MEMORY.md to save memories or STATUS.md to track progress.
I've been enjoying having a little todo file the agent updates as it goes along, because then I can keep track of progress without scrolling through aeons of "Combobulating..."
Also if context runs out you can just do "cat todo.md | agent" and you're off to the races again.
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.
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 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.
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 don't think so - I think we'll find that to build a brain you need more built-in structure and biases, not less.
Bear in mind that brain architecture is learnt too - just over a much longer timescale than an individual lifetime.
Yeah, the question is whether this applies to all of context management.
I've been using a custom harness based on https://minimal-agent.com/ (itself based on swe-mini-agent), which is like 50 lines for the core logic. Bash is all you need.
For small tasks, I find it's about 8x faster (and uses 8x fewer tokens) than the standard harness for each model.
For bigger tasks I haven't tested it much. It seems to work too but I think they're a bit less focused and productive in that case. It could be that those big harnesses' 20k token system prompts are doing something important with regard to steering software development workflows. (e.g. I heard Fable has a custom system prompt in Claude Code which might explain its markedly more proactive behavior.)
So I want to say there's still a lot of value in context engineering though it seems to diminish with each model release (since they're fine tuned on mostly non stupid behavior and need less hand holding).
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.
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.
Ugh, agentic _dreaming_. Why on earth would I want that?
> "turn it the fuck off" -> "autoDreamEnabled": false
So you told it don't go the fuck to sleep ;)
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.
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
In my harness I have all the code auto injected at startup (doing mostly very small codebases).
I found that every model will still manually check every file/function, they immediately assume that anything in context is stale.
That's sensible because often the user edits stuff while they're running.
What it does is save it from having to grep blindly about the codebase. But I think I'd get roughly the same benefit by just dumping the function headers then.
Did you try to delete the memory yourself?
> 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.
>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.
Settings > Capabilities > "Generate memory from chat history"
Toggle it off and never think about it again.
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.."
I've been having a very nice time with Fable. I cooked up an Anki clone in like half an hour, with tech it's not familiar with. Nothing too ground breaking, but I was very pleased!
I think Opus might be on similar level for most of what I'm doing, but I haven't used it much recently, so I can't remember the difference. So I guess I'll find out on the 7th when they pull the plug again! (Free-ish trial of Fable ending.)
That being said, I tried using other frontier models to help with a Pong clone the other day and they were introducing new bugs at approximately the same rate as they were fixing it. On Pong!! I found that amusing because I couldn't think of a simpler game, so it didn't inspire confidence.
Fable's doing just fine on an online multiplayer game though. I have no idea how that works.
>> 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.
> We will figure out what we want to build later.
Once the automator automates itself fast enough, we won't have the ability to opine what gets built. The LLM will decide. Just like right now sometimes LLMs delete tests so they pass, they could just delete humanity if humans get in their way.
> The software world is very close to building a super intelligent senior software developer.
Yeah. Two more weeks, as they say. Just need to iron out some kinks.
> 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.
Except Claude is more expensive than an actual senior software developer. Otherwise, why are many companies terrified of the usage bill that gets printed on the invoice?
The nonsense in "tokenmaxxing" was a complete marketing scam and illusion of cheap tokens which in reality were heavily subsidized.
The entire point is detecting bad code before it reaches production. [0] AI generated or not.
[0] https://sketch.dev/blog/our-first-outage-from-llm-written-co...