I agree with your take, particularly because of this line in the article:
| the skills that define a strong blindfold chess player are the same as those of a programmer who can thrive behind a Claude Code terminal whilst not reading nor writing any code.
If you're actually not reviewing the outputs, you're just getting a fuzzy description of the state of the chessboard.
But I (and everyone I work with) use Claude Code in a workflow where I -do- review the outputs, or at least I make an honest effort to try. Rather than blindfolded, I think bullet (1-minute) chess is a fairly good analogy for this: you have all the info you need to keep your mental model up to date with reality, but the pace of change is too fast to do a good job unless you have a lot of preexisting chess expertise.
You learn a lot more by reading code than writing it.
So reading the output i believe is an immensely big gift by an LLM, because if you actually take note - and of course know your skills - then ot becomes such a great pal to work with.
I like reading what the LMM gives me, not always, but a lot of times.
It's quite a surprising result: it turns out that there are cases where seeing someone else work through a worked example is more effective than struggling through the problem yourself.
(Obviously it doesn't apply universally, but your "see how ridiculous that sounds?" suggests to me you may not have heard of this before.)
As that link says, this approach is used in Maths textbooks, and yet, as the parent of two kids, I have never come across a single student who is able to pass trig without working the problems.
If reality differs from the results of academic studies, it's not the reality that is wrong.
The worked-example effect doesn't say that worked examples replace exercises. It says that worked examples prior to exercises beats exercises alone.
There's a section on that page about faded worked examples:
> "In order to facilitate the transition from learning from worked examples in earlier stages of skill acquisition to problem solving in later stages, it is effective to successively fade out worked solution steps"
As long as the literature contains insights a reader isn't aware about, reading the literature is low-hanging fruit compared to having to derive all the things yourself.
As soon as the literature no longer contains insights, it becomes more productive to explore mathematics oneself by trial and error.
Organized education will model this on a topic by topic basis: during class you're handed the more valuable insights on a silver platter, during an exam you are prevented from looking at your textbook.
Every time you read a chapter and do the exercises it's a small simulacrum of catching low hanging fruit followed by making sure you can derive similar statements with trial and error for fixing any gaps. The trial and error while you do problems does improve your intuition, but only trial and error is like having every student redevelop the frontier starting from antiquity.
For most of us, writing code is the way to carve out intuition into an artifact. But, I have noticed some people are able to read deeply - and by that I mean, reverse the code to understand the intuition that brought it to life. This is a rare skill and I dont have it, but some do. Not just for code, but also for any book - fiction or non-fiction - some are able to deconstruct the scenarios much better than others, and in that sense understand what they read.
I feel one need to also have developed the intuition by writing lots of code for reading to be really effective.
An an analogy I’m reading a lot of German those days as I’m aiming to become fluent, and it’s very effective to improve only because I spend so much time developing a the intuition by going through the whole grammar, forcing myself to write, forcing myself to speak, etc. Doing only the reading improves your pattern recognition, but doesn’t make you go as deep as one who also writes and speak. If you combine the different aspects they reinforce each other and you progress way faster
> I feel one need to also have developed the intuition by writing lots of code for reading to be really effective.
This is one of the problems young engineers are going to face who rely excessively on AI to generate code. Their intuitions on what constitutes good code will not sharpen, since they are not exercising the tool that sharpens it which is writing code. Intuitions start fuzzy, and incorrect, and gradually sharpen with precise communication of said intuition in the form of writing code or proofs. Reading alone may delude one into a sense of false mastery where intuitions are actually fuzzy, but one thinks otherwise.
a lot of people get stuck, or code up a naive brute force algorithm and call it a day, nothing intrinsically forces a coder that refuses to look at the work of others to write better code.
The 'growth in completed actions runs' graph is interesting. I assume the periodic drops are weekends, so intuitively the floor of those drops corresponds more with hobby/personal projects than people at work. It looks like there's a sharp uptick specifically in that floor since July ish.
Thanks! The population/demographic data is all freely available from the US Census and stored in a PostGIS database (hence the site being US-only for now- if I wanted to make it global, there are global gridded population data sets but they aren't as detailed).
The geography data is all pulled in w/ some long-running background tasks into a rails app (that hosts both draw.city and another site I've shared here in the past - blockatlas.com). To find the pop of place that the user circled, it essentially queries for census blocks whose centroid is fully contained in the area you drew (there is a quicker census-tract-based fallback for huge areas).
Putting demographic data e.g. "% walk to work" onto an arbitrary polygon is a bit trickier, since that sort of data isn't published at the block level. We use census tracts (bigger, neighborhood-sized areas that do have this data), and for partially-contained tracts we compute the fraction of the tract's population estimated to live in the area, and allocate demographic info according to that fraction.
I've been building various geography tools & games, found a fun domain for this one. It's set up as a wordle-like daily challenge, I've backfilled some "past challenges" so there's more than one day to play, and there is also a free-draw mode that tells you population + some census ACS demographic info & points-of-interest data from OSM.
Happy to answer any questions about the data or the technical side! This only covers US areas at the moment.
Another (semi serious) possible explanation of this is that LLMs were trained on a huge volume of text from Reddit. I wonder if you'd see similar inhuman-looking behavior if you did an iterated prisoners dilemma with a group of Reddit power-users as the participants?
I had the same thought. Also, a significant amount of human knowledge/context/communication is done privately on the internet. Imagine if DMs across all platforms made it into training data...
I think the fun/hobbyist/urbanist answer is that people just like to know facts about where they live, I've spent hours now looking up different places' data. The more commercial answer if I were pitching this as a product is that 'who lives within X minutes of this point' is a big question in CRE site selection etc if e.g. you're deciding where to expand a franchise. The walk-time version is more of a fun demo of the engine than anything else.
Thanks for the feedback! The site (and I suppose this post) doesn't really do much to answer "what's the point?"
I know people who work in urban planning, and they find this also generally interesting because the data and its visualization can be used to identify areas where action is needed in terms of local transit planning.
I'd like to! It'd be pretty straightforward for the parts based on OpenStreetMap i.e. generating travel time areas / points of interest, I'd just need a bigger database. Ingesting global population & demographic data would be a bit of a bigger project since the site is built around US Census territory boundaries at the moment.
It'd definitely something I want to add, but since I'm quite limited in the time I spend on the project, I think it makes sense to keep it US-only for now. Thanks for trying it out!
If you flip through something claiming to be a "book" and immediately see that a majority of pages just contain nonsensical bulleted lists, and furthermore see that chapter titles are printed overlapping with the book title on each page, you can correctly conclude the entire thing is a zero-effort pile of shit without wasting any further time to read it.
I read through a bit of it and it really wasn't all that bad. The only thing that I found to be really problematic were the made up experiences. Clearly hallucinations are still a big problem for LLMs, but if we manage to get rid of those a book like this can really be quite serviceable (a lot of human-written books are badly written so the bar isn't incredibly high, imho).
The creator should really tweak the prompt/process to include automatic review explicitly intended to remove hallucinations. It clearly is already the intent: "Future iterations of this experiment will include AI-powered fact-checking of the content."
I'm looking forward to what the improved version will look like.
Flip through the middle of the book. Nearly every page has either a bulleted list or a numbered list. In several cases, a single list spans multiple pages.
That’s the format of an outline, not a legitimate book.
Is it? Or are 'legitimate' books just too often not concise and structured enough?
I do a lot of personal knowledge management and I use a shit ton of sections and lists in that. Books evolved from the art of telling stories, not from efficiently conveying knowledge. Perhaps we're just way too used for books etc. to an approach that is suboptimal. I know I personally despise news articles and blogs that start with "setting the scene" and are incredibly and needlessly verbose, using thousands of words to say what could be made clear in a single paragraph.
Viewed from another angle: Reading text is inherently serial in nature even though a lot of things are related to each other in a graph. A document with sections with bulleted lists is actually a way to represent a tree, which is closer to a fully unconstrained graph. I would argue that trees like that are much easier to parse than classically written texts.
There is irony here in that I only used some whitespace to add structure, but never used any bulleted lists in this comment.
[...]
I did generate an alternative with Google Gemini 2.5 Pro, but the formatting doesn't work here on HN. It was decent, though!
> I do a lot of personal knowledge management and I use a shit ton of sections and lists in that.
That's because these are notes, not a book. A list-heavy outline format makes sense for notes, as these are summaries that supplement your own memory and knowledge you've already taken in. They're not a sole/primary source of conveying knowledge to others on their own.
> Perhaps we're just way too used for books etc. to an approach that is suboptimal.
If you truly believe books are "suboptimal", I can only suggest that you consider looking inward and do some reflection:
Is the "problem" really with books and long-form writing, which is the dominant form of knowledge transfer across several thousand years of human civilization?
Or is the problem with people's attention spans in the past decade, due to dopamine-fueling social media doom scrolling and AI usage?
Yeah, and the incident details indicate call it "degraded functionality" when it seems broken for everyone across the board. Desktop app, website and mobile app all non-functional.
Oddly, my mobile app still has me logged in and seems to work, but the desktop app switched to its stupid 'oopsy daisy, something not quite right' screen on its own.
| the skills that define a strong blindfold chess player are the same as those of a programmer who can thrive behind a Claude Code terminal whilst not reading nor writing any code.
If you're actually not reviewing the outputs, you're just getting a fuzzy description of the state of the chessboard.
But I (and everyone I work with) use Claude Code in a workflow where I -do- review the outputs, or at least I make an honest effort to try. Rather than blindfolded, I think bullet (1-minute) chess is a fairly good analogy for this: you have all the info you need to keep your mental model up to date with reality, but the pace of change is too fast to do a good job unless you have a lot of preexisting chess expertise.
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