Readit NewsThanks for sharing!
Edit: sigh, I should probably run my comments through ChatGPT to avoid being downvoted. I like this, I share my enthusiasm. I like the uselessness of it, meaning the uselessness of making a floppy disk in 2025, not the lack of educational value. Sheesh.
Inverted indices were not used as they worked poorly for “an ordered list of words” (as opposed to a bag of words).
And this doesn’t even start to address the ranking part.
Wikipedia [1] links to "Jeff Dean's keynote at WSDM 2009" [2] which suggests that indices were most certainly used.
Then again, I am no expert in this field, so if you could share more details, I'd love to hear more about it.
[1] https://en.wikipedia.org/wiki/Google_data_centers
[2] https://static.googleusercontent.com/media/research.google.c...
I suspect that well-engineered projects with plenty of test coverage and high-quality documentation will be easier to use AI on, just like they're easier for humans to comprehend. But you need to have somebody with the big picture still who can make sure that you don't just turn things into a giant mess once less disciplined people start using AI on a project.
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But then my wife sort of handed me a project that previously I would have just said no to, a particular Android app for the family. I have instances of all the various Android technologies under my belt, that is, I've used GUI toolkits, I've used general purpose programming languages, I've used databases, etc, but with the possible exception of SQLite (which even that is accessed through an ORM), I don't know any of the specific technologies involved with Android now. I have never used Kotlin; I've got enough experience that I can pretty much piece it together when I'm reading it but I can't write it. Never used the Android UI toolkit, services, permissions, media APIs, ORMs, build system, etc.
I know from many previous experiences that A: I could definitely learn how to do this but B: it would be a many-week project and in the end I wouldn't really be able to leverage any of the Android knowledge I would get for much else.
So I figured this was a good chance to take this stuff for a spin in a really hard way.
I'm about eight hours in and nearly done enough for the family; I need about another 2 hours to hit that mark, maybe 4 to really polish it. Probably another 8-12 hours and I'd have it brushed up to a rough commercial product level for a simple, single-purpose app. It's really impressive.
And I'm now convinced it's not just that I'm too old a fogey to pick it up, which is, you know, a bit of a relief.
It's just that it works really well in some domains, and not so much in others. My current work project is working through decades of organically-grown cruft owned by 5 different teams, most of which don't even have a person on them that understands the cruft in question, and trying to pull it all together into one system where it belongs. I've been able to use AI here and there for some stuff that is still pretty impressive, like translating some stuff into psuedocode for my reference, and AI-powered autocomplete is definitely impressive when it correctly guesses the next 10 lines I was going to type effectively letter-for-letter. But I haven't gotten that large-scale win where I just type a tiny prompt in and see the outsized results from it.
I think that's because I'm working in a domain where the code I'm writing is already roughly the size of the prompt I'd have to give, at least in terms of the "payload" of the work I'm trying to do, because of the level of detail and maturity of the code base. There's no single sentence I can type that an AI can essentially decompress into 250 lines of code, pulling in the correct 4 new libraries, and adding it all to the build system the way that Gemini in Android Studio could decompress "I would like to store user settings with a UI to set the user's name, and then display it on the home page".
I think I recommend this approach to anyone who wants to give this approach a fair shake - try it in a language and environment you know nothing about and so aren't tempted to keep taking the wheel. The AI is almost the only tool I have in that environment, certainly the only one for writing code, so I'm forced to really exercise the AI.
People start developing protocol, standards and overengineering abstractions to get free PR and status. Since AI hype started we have seen so many concepts built upon the basic LLM, from Langchain to CoT chains to MCP to UTCP.
I even attended a conference where one of the speakers was adamant that you couldn't "chain model responses" until Langchain came out. Over and over again, we build these abstractions that distance us from the lower layers and the core technology, leaving people with huge knowledge gaps and misunderstanding of it.
And with LLM's, this cycle got quite fast and it's impact in the end is highly visible - these tools do nothing but poison your context, offering you less control over the response and tie you into their ecosystem.
Every time I tried just listing a list of available functions with a basic signature like:
fn run_search(query: String, engine: String oneOf Bing, Google, Yahoo)
it provided better and more efficient results than poisoning the context with a bunch of tool definitions because "oooh tool calling works that way".
Making a simple monad interface beats using langchain by a margin, and you get to keep control over its implementation and design rather than having to use a design made by someone who doesn't see the pattern.
Keeping control over what goes into the prompt gives you way better control over the output. Keeping things simple gives you a way better control over the flow and architecture.
I don't care that your favorite influencer says differently. If you go and build, you'll experience it directly.
I've seen a lot of influencers suggest "100% assembly", "JavaScript only", "no SQL", which seem quite similar.
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For those commenting in the latter category, it might be worthwhile to read a bit about the underlying technology and share your insights on why it does not deliver.
In a way it is somewhat similar to people writing demos for old computers using emulators. Still great fun, but using these tools it doesn't take a village to make one floppy disk. With modern hardware you are apparently able to pull this off on your own. That would have been almost impossible in the 1980s, when these floppy disks were popular.
I probably worded it badly, but I really enjoy these efforts, and I would never be able to do this myself, even if I had a shed with all those tools!