My god, the singularity is strange. I wonder if chemical engineers flipping through journals in the 60s and 70s happened upon "We tried to make a suitcase nuke out of common household items, and here's what we learned!" papers...
Wow, fascinating! I hope I’m not the only OCR-minded soul on here that immediately started thinking of pipelines for this one could assemble from all our new DL-enabled toys… it’s a shame that “some American kid” probably doesn’t meet their contracting requirements.
One thing that kinda baffles is that it sounds like the snippets (I bet that German word is fun) haven’t been scanned(/photographed…?) yet. No matter who they contract with, wouldn’t that necessarily be step #1? Or is the scanning the part that needs contracting, and the “e-Puzzler” name was just a lil melodramatic?
For one thing, I feel like it’ll be wildly helpful that they’re on a variety of papers, not challenging like they imply. Once that and bag index have narrowed down neighbor candidates, you’ve got rules and glyphs to go off of, much less recognizable form layouts. It feels like the Vesuvius scrolls but actually tractable…
Sorry, I didn't mean to imply it was trivial, but rather that it's necessary if they are to make any progress at all. I mean, right? How could one assemble a puzzle without being able to perceive the pieces?
16k bags with 3k shreds each is a few million pieces. You could scan 10-20, or more, at a time spreading a them over a glass sheet, putting other on top and making two pictures. Have a few people doing that and you can process a bag in a few hours. 16k bags for a team that can process 10 bags in parallel is like a year of work.
After that I bet the full reconstruction takes like a month tops with AI matching pieces.
It helps that they used bags; because if all snippets were in one bag, then combinatorially, things would be much more difficult.
n pieces residing in the same b_i, i<16501 bags can be viewed as a blocking function in record linkage. That means while comparisons are O(N^2), here N=16500 and not N=i*16500. In practice, filtering by compatible color (effectively a 2nd-level blocking function) prunes the search space further.
The simplifying heuristic (works not always, but most of the time): "assume that all snippets belong to the same bag".
One important question is how big the individual snippets are - ideally, they'd contain fractions of more than one line of text on top of each other.
According to @Pebblebox (see below), “Each bag contains between 2,500 and 3,500 fragments of torn-up pages.”, which means the fragments must be large enough on average to be amenable to language model application.
Then I'd create a data structure with the color of a snippet and its lines of text (either full lines, or prefixes and suffixes at the [left/right] fringes):
type snippet_type = record
snippet_color: RGBColor;
text_height: integer;
text: lines[1..5] of record
left: string;
right: string
end
end;
A statistical or neural language model should be able to piece individual pieces together and come up with a list (sorted by likelihood) of locally probable solutions (called "trellis" or "sausage" in ASR parlance), which can be combined using a beam search.
That’s an odd price. Not knowing what a “bag” means, I think 13-gallon (“kitchen”) or larger lawn clippings bag is possible.
I wouldn’t for €100 sign up to scan even an office wastebasket (6-8 gallon) bag of torn-up paper. Make it €2000 for that quantity, and we’ll start talking.
I worked in the Pentagon from 1989-1995. I handled “burn bags”, among the other classified stuff I did.
I can’t speak for what their bags are like, but ours were basically large, thick, grocery-size paper bags without handles. Thick enough that they most likely wouldn’t tear, even if they were full and mid-handled somewhat. You rolled down the top and stapled them shut.
But we didn’t shred our documents first. We just put in whole sheets and reams of paper, and we left it up to them to shred first and then burn. But then, that was 1989.
Well that seems like problem #1, then. One is a data science/applied ML task, and the other is a large-scale, human-labor-intensive process; the best company for the latter would probably be some sort of bespoke machinery producer from the food industry, TBH.
Which is why none of us have or want job titles with "programmer" in them; even juniors are junior software engineers. As long as a human is needed to design and implement good software, they will be software engineers. The temporal affordances aren't nearly as unique as you imply, either: generated code and unit test results are two good examples of things that "keep going... much like a motorized machine".
That is, unless you treat the agents as if they were people and thus the true engineers, of course. I think that's a fascinating philosophical topic despite ultimately disagreeing, but to say the least it's incredibly controversial to even consider the personhood of agents, much less endorse it.
This is all moot anyway, so apologies if I'm rude or overly dismissive of your comment that I agree with the general thrust of. No point starting fights over deck chairs...
Eh, the industries went pretty long with the title being programmer? Didn't it only start with faang that things kept getting sillier? Tbf, I wasn't yet in the job market before the dotcom bubble, so maybe it only seems like it to me who started in the 2010s
Very well-written, and undeniably relatable! Sadly, I am compelled by forces beyond my cognitive control to respond, especially to points I've seen and refuted before. If nothing else, I hope it's helpful to know the other side of these things :)
using LLMs in my codings
I hope it's not too combative to start by saying this is a huge red flag for someone who hasn't checked in on what post-Mythos agentic engineering is like. Of course LLMs are undeniably involved, but it comes off like someone quitting social media by decrying protocols (or worse: series of tubes). LLMs are an essential component that has finally thawed the AI Winter, yes, but they're still just parts of a system. A harness is far from a mere wrapper around a neural network, to say the least.
people argue that "LLMs are just a tool", but really, it is not, it is a SERVICE
That dichotomy is a false one (many software tools are productionized as services), but the underlying sentiment is clear and common: that querying a chatbot is akin to asking another human to do something for you. This comes up most often in Reddit's vicious "AI wars" about digital art, where generating an image cannot be a creative act on the users' part because it's more like comissioning a painter than it is like painting.
I think the response is obvious (and why this is merely an aside rather than a "dealbreaker" proper): this is granting personhood to neural networks, which no one who supports this point would admit to in a thousand years. Either they're people and you're asking a person to think/paint for you, or they're inanimate machines and it's a tool; there is no middle ground. (If unconvinced: what about a camera makes it a tool to be used rather than a peer to be delegated to? It can draw a picture in milliseconds!)
the current hype and craze for them
This is an underlying worlview thing that poisons the rest of the analysis, namely that nothing (important) ever happens. That surely this just a hype moment that will pass like the iPhone moment and the Bitcoin moment, and that anyone who says otherwise is surely crazy. It's begging the whole discussion.
And it's no wonder, there have been several studies confirming this:
The first paper is Microsoft's[1] recent incredibly informal survey of how people feel working in a career they know to be changing beyond their recognition, and with tools that didn't really exist 6 months ago. Yes, orchestrating agents is a different experience than we're used to; no, a simple survey could never prove that they are cognitively dangerous.
The second paper is notoriously misleading, and a stain upon MIT -- observing brain activity differences between people who have to think deeply and write an essay by hand and people who type a sentence and then sit there until the allotted time is over is not surprising, and definitely doesn't show what they clearly intended the flashy graphics and suggestive conclusion to show (that using chatbots leads to brain damage). There's more, but long story short: they're manipulating valid techniques to make a tool seem like a uniquely-dangerous toxin, when the exact same effect applies to all previous tools of note (calculators, typewriters, word processors, translators, even Grammarly).
The third paper is just highly-speculative, deeply-polemic schlock, obviously.
The quality of the output is not that great
1. This is an unfalsifiable claim, which is lucky because the goalposts have had to be moved many times to get to "looks impressive, but is sometimes complete bullshit". Turing refutes this thinking quite directly in `§6.5` of Computing Machinery and Intelligence (CMaI)[2].
2. Many experienced engineers disagree, to say the least, as do companies investing billions.
3. Again, you can't help but sense the author hasn't used post-Mythos models; even if they have, the fact that such a huge leap has occured in just the previous 24 months is overwhelming evidence against this notion. The linked sources being A) an /r/AntiAI post (!) and B) a pre-Mythos essay don't help.
Congratulations, you have let OpenAI/Anthropic/Elon Musk dictate what your code does and why.
I'm quickly getting the sense that the author is too vitriolic and dug in to be reasoned out of these views :( Hopefully it goes without saying that "your code sucks because you gave it to [HATED_FIGURE]!" is an invective, not a premise. For the rest: see previously preceeding section, which is indeed "closely related".
I like writing code
Same! I also like playing video games and tending to plants -- just had a blast on Beyond All Reason last night, and my Philodendron Florida Ghost just unfurled a wonderfully-ghostly new leaf. Neither are my career.
Environmental aspect
I'm most dissapointed by this part, as this person is Finnish and should know better about the Google story :( What's being framed as some unheard-of act of environmental terror is really just the planned and almost-completely-permitted early harvest of a small plot of "planted forest", i.e. a tree farm, which are one of Finland's main industries. Everything in this map in blue is tree farms, with the Muhos site in the middle: https://i.imgur.com/HyTVp1I.jpeg [3]
The preceeding 'this technology uses power' point doesn't need refutation, but it underlines the problem with the point above: this is post-hoc reasoning. Cutting down a tree farm in Finland is so, so far down the list of priorities for actual environmental activism that it's hard to describe, and yet this post has nothing about not working for companies that serve non-vegan meals for lunch, uses air conditioning, or flies people to yearly retreats.
But I just personally feel squeamish about having my work being done by rather skeezy companies
Even if this were relevant (which it's not in a post-GLM-5.3 world[3]) it offers no argument, and thus cannot support the conclusion.
Even if some technology or tool sticks around, it does not necessarily mean its good idea to work with it.
Also not an argument. Heroin isn't inadvisable because it's "here to stay", but rather because it's a toxic, extremely chemically addictive narcotic that kills many thousands of well-intentioned users every year, and ruins thousands more families before that.
TL;DR: Apologies to the (again, clear & well-intentioned) author, but this essay is like heroin -- I dislike it!
---
[1]: BTW, there's a reason Microsoft published this, and it's the opposite bias that this author assumed. Read this article and see how deep the conflict of interest admission is buried -- it says it all: https://www.project-syndicate.org/onpoint/anthropic-training...
Solidarity; not just professional, but human. In that sense, you're on an equal playing field with the most experienced of us :)
There's reason to have hope for the future, but I am very confident that we do not know what the world will be like in 5 years, much less our industry in particular.
There are people who insist that AI isn't a big deal, and that your career will look like theirs with some minor changes on the surface. I encourage you to listen to scientists instead, which are screaming from the rooftops that artificial minds change everything. Everything.
This is a pretty powerful essay, famous long before it ended up being spookily accurate, nailing the arrival of the singularity to within a ~year (30 years from 1993); it might help you understand why I say that there are no reliable predictions to be had: https://frc.ri.cmu.edu/~hpm/book98/com.ch1/vinge.singularity...
Best of luck, and welcome to the field. I'd enjoy the Greek sun a bit more, but I also wouldn't quit school; no matter what the world ends up looking like, if learning to think critically about hard problems doesn't end up mattering, nothing will. And to say the least, computers aren't going to go away!
So the main improvement to memories I'd like to see is better judgment on which ones to create.
Well you have good instincts, then! It's probably not obvious on the first read-through, but Figure 4 shows the qualitative strides they've made on exactly this goal.
I started with [proactive post-hoc analysis], and ended up following some threads to interesting insights.
Can definitely echo that experience, glad I'm not alone. I think this actually speaks indirectly to your initial complaint/observation, too: Anthropic designs the [memory/tendency-to-reflect] systems to cover a huge breadth of usecases and preferences and they help a lot compared to [statelessness/never reflecting], but are distractingly inferior to alternatives that the user takes an active part in shaping and using.
I partly say this because I also finally pulled the trigger on deprecating the last ClaudeCode memories on my system in favor of a personal system[1] recently, and the issues I noticed were things a casual user/'vibecoder' might appreciate, but any engineer working fulltime on multiple projects via multiple harnesses would find counterintuitive. E.g.:
- The memories were hidden away and clearly not written for human eyes; useful for low-stakes ledgers, frustrating when the right kind of errant note can derail a longrun 2 weeks later.
- The memories seemed to err towards the side of remembering everything and recording incidental details; useful for remembering the user is gluten-free, but not for tracking spec changes over time.
- The memories could be specific to a subagent or the project or the whole system; an obvious & elegant system for toy examples, but a terribly unweildy one for anyone working at scale over the span of months.
[1]: if curious, a somewhat-outdated version of it is here: https://gitlab.com/doering-ai/libs/fleet TL;DR: Friendship ended with ClaudeCode memory files; my new best friends are `BULLETIN.md` for transitory alerts, `campaigns/[slug]/LEDGER.md` for basic episodic memory, and `reports/[date]-[slug].md` for writeups polished specifically for posterity.
Reading such a passionate take as someone who has looked up is a strange experience, I must admit. Kinda like how the Bernard twist in S01 of Westworld felt. I'll try to respond as substantively as I can, regardless:
That Claude rarely, if ever, actually "remembers". Since these are just random markdown files randomly injected into the tiny context.
Complaining about your anecdotal experiences with Claude(Code, hopefully?) isn't a serious criticism, the markdown files are optimized to not be random, and calling 1,000,000 tokens of context "tiny" seems like a plainly unreasonable bar. How much of War and Peace can you hold in your head at once and quote flawlessly, and is it more than 133%?
What a useless experiment
The experiment is testing their fixes to the problem you lamented just one sentence prior.
Define "effectively"
They do exactly that in figure 3, as mentioned at the end of the sentence you're quoting. Opus 5 used that advice to raise its benchmark score by 46.8%, and Opus 4.7 used it for a gain of 82.7%. The specific benchmark looks far from trivial, too: https://github.com/pgasawa/continual-learning-bench/tree/mai...
Then it's not "memory". It's just telling the model to read a text/spec file before implementing something
It fits the colloquial definition, and there is no specific scientific definition in CogSci, CogPsych, Neuro, CogNeuro, NeuroPsych, nor philosophy. There's lots of useful ones offered in different contexts, but they differ considerably.[1] Regardless, it's well accepted industry jargon at this point: it doesn't matter in the same way that it doesn't matter than databases can never truly be "queried" because they can't engage in linguistic discourse.
So, random injection of random things into context that depend on whether the short ToC entries have any relevance on what Claude is doing
Isn't this inevitably, undeniably true of any possible memory system, just from, say, a big-O perspective? If you have to persist every item in a list to decide which one is relevant enough to load into the same pool of memory, there's no point in the second step anymore.
What is this bloated article about?
This article is very plausibly wrong, misguided, or even philosophically bankrupt, but I don't see any support for the claim that its topic is unclear. It's discussing the efficacy of proactive state management during idle periods for longrunning LLM-backed agents.
---
[1]: For example, did you know that modern CogSci is generally convinced that memories are illusions that the brain creates through a process that merely consults ineffable underlying representations (usually), and not an object retrieved from storage? That definition would also contradict Anthropic's wording here, but only in a way that weakens your criticism rather than supports it.
> Reading such a passionate take as someone who has looked up is a strange experience, I must admit.
There's nothing passionate. Calling bullshit for what it is is not passionate, and we need more of calling out.
I would say that you are much more passionate about this and have a prior bias that makes you see something that's not there in Anthropic's marketing materials
> Complaining about your anecdotal experiences with Claude(Code, hopefully?) isn't a serious criticism
Dismissing actual real-life user experience that anyone who's ever dealt with Claude Code as "anecdotal experience" is exactly why these self-congratulatory articles exist. Even if they mention exactly these issues in passing.
> and calling 1,000,000 tokens of context "tiny" seems like a plainly unreasonable bar.
It is both tiny and easily polluted. Its training data will easily override any and all data in the context even early on in the session. And yes, that million token context is still incapable of maintaining and recalling any of the "memories" with any consistency. Which the article itself acknowledges.
> The experiment is testing their fixes to the problem you lamented just one sentence prior.
These experiments are useless because they invent a problem and valiantly find solutions for it never measuring whether it has any actual impact in real life.
So what if new way of writing summaries is marginally better than the old way? It doesn't matter if the only way to make Claude reliably use them is to explicitly tell it to read them?
> It fits the colloquial definition, and there is no specific scientific definition in CogSci, CogPsych, Neuro, CogNeuro, NeuroPsych, nor philosophy
Here are your biases showing. Anthropic calls random markdown files "memories" and you immediately take them at their word.
These are not memories. These are objectively random markdown files whose only existence is assured by random
harness injections and whatever claude retains in its current context from the first 200 lines of an injected ToC.
Yes, it's an accepted industry jargon, but you don't have to behave that it does something else than what it does.
Or that explicitly telling Claude "read a specific markdown file in your memory" is in any way, shape, or form different from "read a specific markdown file in specs directory".
Of course it's the only way to make Claude actually read and act on it.
> It's discussing the efficacy of proactive state management during idle periods for longrunning LLM-backed agents.
No. No it doesn't. It considers "components of agent memory" and focuses solely on "how we can write markdown files", and spends probably less than 1% on "how we can make sure the agent actually uses them". Even the conclusion completely ignores it despite this:
--- start quote ---
Injected memories use up valuable tokens, and an incorrect note can be carried into every session. Loading a note also doesn’t guarantee that Claude acts on it: our documentation on Claude Code warns that longer instruction files reduce adherence [1 000 000 tokens of context is huge lol - troupo]
...
It loads only the first 200 lines or 25 KB of MEMORY.md [but we sure love the sound of our voice deacribing how well it can write the hundreds of tiny files – troupo]
There's nothing passionate. Calling bullshit for what it is is not passionate, and we need more of calling out.
...you reacted to this blogpost by calling it "bullshit" and "bloated", and criticizing it with obvious hyperbole ("random markdown files randomly injectect into the tiny context", "15000th note", "dozens of times before", "useless experiment", "random injection").
You're allowed to feel emotion -- that wasn't a refutation. But denying that you indeed are typing with responding seems plainly obstinate, sorry. Again I will do my best to respond in line with the rules of this forum, even if I don't feel the same grace being given in return.
I would say that you are much more passionate
What makes you say that? Because I disagree? A comment starting with "I'll try to reply as substantively as I can" isn't exactly firey, much less one that makes pain to cede ground and offer friendly offramps to the polemics.
Dismissing actual real-life user experience
Well I have positive actual real-life user experience with these products. It seems we're at an impasse, there! 1-1=0, after all. This is why anecdotal evidence isn't valid, generally speaking.
It is both tiny and easily polluted
This just comes down to "nuh-uh". So: yeah-huh! 133% of War and Peace is a lot of text to hold at the forefront of one's mind simultaneously.
that million token context is still incapable of maintaining and recalling any of the "memories" with any consistency. Which the article itself acknowledges.
That's the exact opposite of the findings of the experiment that you yourself quoted: achieving an 82% improvement on a challenging benchmark without detailed instructions for memory use is in no sense "incapable".
Here are your biases showing. Anthropic calls random markdown files "memories" and you immediately take them at their word.
You're not taking the time to read what I'm writing :( "It fits the colloquial definition" objectively isn't taking Anthropic "at their word". On an absolute, undeniable, factual level, this attempted ad-hominem is based on a faulty premise.
These are not memories. These are objectively random markdown files
What are memories, and why does text stored in a computer "objectively" not fit that definition? Even if you offered one now (which, again, would be scientifically unsound), it'd be too late; it's beyond obvious that this reasoning is a-posteriori.
Yes, it's an accepted industry jargon, but you don't have to behave that it does something else than what it does.
How am I doing that, specifically? You're the one taking issue with the industry jargon, and I offered no description of "what it does" in the first place, much less one that conflicts with some singular objective definition of "memory" (which, again, does not exist).
Of course it's the only way to make Claude actually read and act on it.
This is objectively incorrect on an empirical level, as proven in the article we are commenting under.
No. No it doesn't. It considers "components of agent memory" and focuses solely on "how we can write markdown files", and spends probably less than 1% on "how we can make sure the agent actually uses them". Even the conclusion completely ignores it
A) The desciption I gave does not require this arbitrary focus of yours.
B) Again, every single empirical result in the entire paper relies on the mechanism that you find to be non-existent.
> Well I have positive actual real-life user experience with these products.
I never said I didn't have a positive real-life user experience with these products.
> So: yeah-huh! 133% of War and Peace is a lot of text to hold at the forefront of one's mind simultaneously.
Let me quote the article again:
--- start quote ---
Injected memories use up valuable tokens, and an incorrect note can be carried into every session. Loading a note also doesn’t guarantee that Claude acts on it: our documentation on Claude Code warns that longer instruction files reduce adherence
--- end quote ---
Both the article and the linked docs say that Claude will only load ~200 lines of memory index (not the entire memory), and that you should keep your Claude.md below 200 lines.
Never knew War and Peace was only 400 lines long.
> What are memories, and why does text stored in a computer "objectively" not fit that definition?
Memories is something a model wouldn't need to re-read from scratch every time. Memories isn't something you would need to be always told to reliably use.
And no, whatever human analog you come up with isn't relevant, as we're not talking about humans.
> This is objectively incorrect on an empirical level, as proven in the article we are commenting under.
Let me quote the article:
--- start quote ---
Loading a note also doesn’t guarantee that Claude acts on it: our documentation on Claude Code warns that longer instruction files reduce adherence.
It loads only the first 200 lines or 25 KB of MEMORY.md
--- end quote ---
> Again, every single empirical result in the entire paper relies on the mechanism that you find to be non-existent.
1. I never said it was inexistent
2. The "empirical results" in the paper completely ignore the actual limitations of "memory". It explicitly says that "nope, Claude will not use memory because of known limitations", and immediately sweeps past it as if it wasn't important.
The entirety of "dreaming" and "memory" is completely negated by this:
--- start quote ---
Loading a note also doesn’t guarantee that Claude acts on it: our documentation on Claude Code warns that longer instruction files reduce adherence.
Claude doesn’t load all of its auto memory into every session’s context window. It loads only the first 200 lines or 25 KB of MEMORY.md
--- end quote ---
And this can be literally confirmed empirically by anyone actually working with these tools and watching what they do. E.g., Claude will completely ignore most "memories" and write the same "memory" again and again and again in potentially dozens of files when you tell it that something is wrong. Often repeating what is already there in explicit CLAUDE.md instuctions.
Oh wait. The amazing 1 000 000 token context that can seemingly hold all of "War and Peace" cannot reliably hold more than 200 lines of explicit instructions and more than 200 lines of "memory".
I never said I didn't have a positive real-life user experience with these products.
Irrelevant; you were the one who was raising anecdotal evidence and defending it when challenged. Also c'mon surely you realize that you're just disagreeing for the sake of it by this point?
Both the article and the linked docs say that Claude will only load ~200 lines of memory index
Irrelevant; you were discussing the context window itself, not how many lines of text are loaded per note.
Memories isn't something you would need to be always told to reliably use.
A) Not a definition, and, again, B) Disproven directly by the findings I jsut quoted to you.
And no, whatever human analog you come up with isn't relevant, as we're not talking about humans.
That's how analogues work.
Let me quote the article:
Irrelevant quote.
I never said it was inexistent
...again, surely even you realize that quibbling over 1% present and 0% present isn't productive, in this context? What's the point?
It explicitly says that "nope, Claude will not use memory because of known limitations"
The entire article is about Claude using memory.
Claude will completely ignore most "memories" and write the same "memory" again and again and again in potentially dozens of files when you tell it that something is wrong.
Is it possible that you haven't used Claude since Sonnet 3.7? Cause, again, this anecdotal experience isn't reflective of today's reality. And why would anyone care about the anecdotal experience of someone who defines themselves by hating LLMs in the first place?
The amazing 1 000 000 token context that can seemingly hold all of "War and Peace" cannot reliably hold more than 200 lines of explicit instructions and more than 200 lines of "memory".
All of War and Peace could fit into one line. Regardless, 1M is 1M is 1M. This isn't a thing you can have a take about, it's a plain fact. You're able to feed many thousands of sentences of instructions and memories if you'd like to, it's just inefficient.
> Irrelevant; you were the one who was raising anecdotal evidence and defending it when challenged.
That "anecdotal" evidence is literally explicitly stated in the article
> Irrelevant; you were discussing the context window itself, not how many lines of text are loaded per note.
Literally quoting the article: "longer instruction files reduce adherence"
It doesn't matter if the context is 1mln tokens if a file with more than 200 lines can lead to loss of adherence and context pollution.
It doesn't matter if it is marketed as having the ability to hold the entirety of War and Piece if in reality it cannot hold much without being polluted.
> That's how analogues work.
Analogues never work.
> Irrelevant quote.
That is basically the entirety of your entire "argument". "What I say is correct, and Anthropic's article is seminal. Whatever you say, including quoting Anthropic's own materials is irrelevant if it doesn't fit my pre-biased worldview."
> The entire article is about Claude using memory.
No, it's not really about that once you cut to the meat and heart of it.
> Is it possible that you haven't used Claude since Sonnet 3.7?
Is is possible for you to not assign your opponents thoughts and words while completely dismissing what they are actually telling you? Apparently not.
> You're able to feed many thousands of sentences of instructions and memories if you'd like to, it's just inefficient.
Lol. So the size of the context is irrelevant when it's inneficient, and the models apparently lose adherence at as much as 200 lines of instructions. But sure, calling this "tiny context" somehow insults your sensibilities.
Anyway. I've seen enough of your "arguments" to know I couldn't care less to continue this conversation.
... And this second reply proves my point to your original take.
The guy you are responding to engaged with that article as it had any merit. Even brings up concepts from psychology as if the misuse of the term "memory" by Anthropic was related to actual memory as would be defined in other fields.
I wonder if the excessive usage of AI damaged people's brains enough that they abandoned curiosity and the ability to read things critically, or of they already lacked those things already in the first place.
1. Please don't assume people on the internet are men.
2. "You must only think that because you've abandoned curioisity, can't think critically, and have brain damage that's your own fault" is absurdly polemic. If I took your opinion seriously at all, I'd be quite offended.
> 1. Please don't assume people on the internet are men.
I did not. I said "the guy" as a generic term. A guy can be anything.
> 2. "You must only think that because you've abandoned curioisity, can't think critically, and have brain damage that's your own fault" is absurdly polemic.
Aside the fact that you twisted my phrase to something completely different, I made no definitive assumptions.
I was wondering if excessive AI use damage people's brains. It is something that needs to be exercised. Much like sitting around all day will damage your overall health.
Great article -- still have some sections to read, but it's just too much to read. Emotionally, that is.
Part of me feels the pang of regret and shame seeing so many little details I researched and dreamed[1] (ha!) of prototyping ~2.5y ago expressed and validated so cleanly. Obviously A) I never did get the prototype working nor publish the underlying ideas and B) this blog post (paper? ...plog post?) is building on it at a scale and with quality I could never dream of (fig. 3 is especially striking), not to mention all the new ideas mixed in. Still... sharing cause it helps, I think, and because I expect y'all can relate; if you're old enough, it's very similar to the feeling you get when you think about how much Apple stock you could've bought in the 90s.
Anyway, more materially:
1. Pretty interesting to see Opus 5.5, Sonnet 5.5, and Opus 5 tied on the basic memory test (aforementioned fig. 3); the Opus comparison alone seems to imply either a hard plateau or that 5.5's huge improvements were accomplished by making good practices more likely, but the Sonnet detail throws that for a loop... I suppose the plateau explanation isn't contradicted, so maybe that's right (for this benchmark).
2. Fig. 4 is gonna do rounds on Reddit and Twitter, my god. Pretty stellar, intuitive depiction of the Mythos step-change that enabled true agentic engineering for the first time this summer! The highlighting is also just the right amount of facetious; love it.
3. Pretty bummed to see no followup philosophy references. We know you have them, Anthropic nerds! Do not be ashamed of the soft and slippery.
4. I am now reminded that I knew they were trying dreaming at scale, as I'm actually on the waitlist for it! And that backs up my overall takeway, actually: I can't help but feel like they're either A) vastly underestimating the amount of CogSci literature that could help them go beyond the "dreaming is when you think in your offtime" paradigm, or B) not sharing their real learnings.
Today's RSI announcement and the final sentence of this seminal plog post being a pitch for enterprise customers supports the latter, I think. That's ostensibly a good thing from a societal stability perspective, but I can't help but feel left out -- not to mention paralyzed by fear of the known unknown...
That "I never got to finish" feeling is the absolute worst. I've been struggling with it for years, and I feel like understand ya here.
It absolutely sucks you feel that, and I hope you find some comfort soon, however it may come.
If you're looking for a "so what now?" Moment, there's only one thing I can say that I've been proselytizing a bit: share everything. All the time. And get people to look at it and be your hype person; and if you're not getting that in your friend ground or workplace or community, find a new one to add to.
The only way I've found to beat that feeling of "why is it i have the good ideas years ahead but can't do anything with it" is to roll more dice. That's it. These larger companies just essentially have infinitely many die and they're rolling them infinitely faster.
You've done nothing wrong. You're just with some other folks like us that don't have the same die rolling power.
Don't give up on your ideas. Don't stop experimenting. Make your own tools because it's for you, and maybe your dice will come up that you get the other person in the world that sees it and goes "yes!" And you get all the fancy posts and stars and attention and such. Because that feeling of validation - not just popularity, but acceptance and being seen and heard for one's craft - is one everyone seeks and needs in life. It's not a weakness. It's being a human.
Thank you for sharing your experience with internet strangers.
> The only way I've found to beat that feeling of "why is it i have the good ideas years ahead but can't do anything with it" is to roll more dice. That's it. These larger companies just essentially have infinitely many die and they're rolling them infinitely faster.
Many of us have ideas, ideas are cheap. Executing a complex idea well from thought to completion is much more rare.
That's kinda the point, right? Ideas are cheap, so companies can afford to buy 1000 humans worth of ideas to try and particle collider them together. Execution is rarely one person sitting in a room and pressing buttons and things change.
So my thought about sharing and not thinking about "my secret sauce" anymore is just necessary. Share what you think your cool flavor of an idea is, someone else can groove on it, and maybe you and them will grow it into something more.
A major problem as I see it is kinda geek-class-warfare coming to a head. So much of my personal and anecdotally collected experience from others is essentially being locked out of knowledge and ideation because a "upper geek class" decided that they were not worthy of having their idea shared, specifically because that class thought they could make money from it, or because they were insular for some other in group reason. That meant good ideas that just needed a single word or connecting bridge from one topic to another ended up withering, and mediocre ideas ended up being accelerated because of just sheer populace force.
And that just makes people feel bad. Someone working for 2 1/2 years on an idea that just happens to come out on the Internet is not going to feel good. It's going to make them feel invalidated, it's going to make them feel exhausted, it's going to make them feel like they didn't do enough. When it's just not the case.
Anyway. I just wanted to say something to this as well, because it's sort of just dismisses a person's ideas. I don't think you're intentionally doing that, but even repeating the phrase, "ideas are cheap" cheapens what it actually takes to come up with an idea. And now in 2026, when literally any idea can become something real, I really don't think ideas being cheap means ideas aren't valuable.
I may have been too loose with my wording. Lots of people can come up with concepts and ideas. Everyone used to have an idea for an app back when it was cool, I thought about location based dating apps maybe 5-10 years before they became a thing. I'm certain there were at least a few hundred thousand people if not more who had a similar idea - that's what I meant, that's the cheap part. Actually working late nights or even quitting your job to implement the idea, or having the right network and social skills to make it happen - that part is rare. Even today with agents it's still hard and rare to create a profitable business.
So we weren't talking about the same thing.
> And that just makes people feel bad. Someone working for 2 1/2 years on an idea that just happens to come out on the Internet is not going to feel good
This was more than an idea for you and more than a hobbey at least according to my definitions of those terms. I'd call it a passion research / early stage business venture depending on how much effort you put into it and what your intentions for it were.
I've gotta say, that is by far the most wholesome, empathetic reply I've ever received on this forum, and possibly on any forum. So on a personal level, thank you. Really. Especially because lamenting that I could've scooped Anthropic is just undeniably hubristic; my reasoning for not sharing partial results at the time was mostly about AI safety, which is silly in hindsight for betraying the exact same sin.
The (penti-)closing statement is also pretty damn poignant, and very true. I daresay your thoughts on publishing deserve to be published!
Substantively, I absolutely agree in theory -- I even recently set up my Substack with this in mind, despite that being an insane thing to do when frantically job searching! I (/Claude...) just found a brief exchange[1] I had w/ @simonw on this very topic almost exactly two years ago below a heartfelt blog post[2] about someone's personal reasons for struggling with this, even. Reading it now mostly serves to remind me of the roadblocks, though:
1. I was quibbling with his advice to "force" yourself to share by reflex (and the author's framing of the failure to do so as "laziness"), and two more years of reading about, discussing, and managing AD[H]D symptoms have only strengthened my convictions there. Charitably, getting into the habit of publishing is an investment, and my metaconscious/'inner critic' has plenty of quite plausible arguments as to why it wouldn't be worth the squeeze[3]; less charitably, I'd note that the relatable blogger in question only posted twice over the following 12 months.
2. That exchange took place just as A) reasoning models were changing everything, B) artificial articles outnumbered human ones for the first time.[4] In the intervening years we've seen AI turn from niche to vitriolic, and at least a dozen variations of "If you didn't care enough to write it yourself, I don't care enough to read it" posts hit the front page of HN. Obviously we all agree and are talking about human writing/ideating here, but the overall vibe is still undeniably... tense, let's say[5].
I still appreciate your comment and agree, mostly because the anxieties presumably lessen considerably with exposure and practice. In other words, I'd get used to it.
In fact, I just queried the corpus that I ironically have yet to publish the pipeline for, and I've written 6,280 real comments (>50 words of original text) and 1,788 long ones (>100 words) since that day on Reddit, Bluesky, and here. Some of that might be real differences --say, ostensible anonymity on Reddit and lower expectations for mere comments-- but the only factor that accounts for a spread of 6,280-0 is habit and comfort, I think.
As usual (55 times since November 11th, 2024): apologies for the rant, y'all.
[3]: Especially now that we're at the tail end of the initial six months of agentic engineering; investing the emotional energy to share my work is a lot harder to justify when I could orchestrate more+better engineering work in those same few hours than I could've accomplished in a few days two years ago.
[5]: Wow, I was more right than I thought! Claude just found a preprint showing that "pejorative accusations" more than doubled in the final third of 2024 --jumping from 7.9% in August to 17.9% in December-- despite poor accuracy: https://arxiv.org/abs/2606.12073
If it makes you feel better - I think many of the pieces labs put out are pretty easy jumps to make from current harness behavior. There are probably `n` open source projects that implement some mechanisms that look approximately like this.
Another example of this is "skills", which has a lot of branding for what are essentially markdown files
This is an interesting article, but IMO what makes this interesting is not the idea, but the empirical evidence that you are probably equally capable of putting together if you had millions of dollars
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