Author here. I definitely agree that communicating well is a prerequisite to getting decent results. On the other hand:
1. Even if you communicate perfectly, there's no guarantee that the LLM will "behave as instructed" and as you imagined it to. Indeed, the frustration often comes from the fact that you've said something as clear as day, yet the agent takes another path.
2. Part of the value of coding agents is exactly that you don't need to lay it all out perfectly for them. I mean, if I need to give the LLM every little implementation detail, I might as well write the code. Of course, I don't expect it to work off of "I want nice app make money", but I do expect some "intelligence" in figuring out the missing pieces.
> Every sentence says something. Every sentence is important and holds its weight. [...] Also, it makes the post harder (and more boring) to read.
I actually prefer that style of writing! (When it's not AI-generated ofc.) And I also try to use it in my technical blog posts. I usually re-read my drafts asking myself: "Does the reader actually care about this? Is this sentence adding something or is it just fluff?"
And actually I feel like AI text usually produces more fluff, or anyway I notice it more, but I see how it can make the result "robotic and boring".
We sorely need a way to reliably detect AI slop, but unfortunately it doesn't seem possible and it's just getting harder and harder.
Last month I tried my hand at finding a way to tell whether an OSS project is slop or not, based on the amount of "human attention" it received vs the amount of code it contains. The idea is that a 100k LOC project which received 3 days' worth of attention from a human is most certainly slop.
The approach doesn't work very well, though¹, mostly because it's hard to gauge the amount of attention that was given. If I see one commit with +3000 LOC, I can assume it's AI-generated, but maybe you're just the type of dev that commits infrequently.
Maybe we need some sort of "proof of human attention" for digital artifacts, that guarantees that a human spent X time working on it.
I recently ran an experiment where I tried to use _quantitative signals_ (and not _qualitative_ ones) to tell whether something is vibe-coded or not.
My idea was that, if I see that your project is growing 10k LOC per week and you're the only developer working on it, it's most likely vibe-coded.
I analyzed some open-source projects, but unfortunately it turns out not to be so clear cut. It's relatively easy to estimate the growth rate of a project, but figuring out how much time developers worked on it is very error prone, which results in both false positives and false negatives.
I just finished¹ building an experimental tool that tries to figure out if a repo is slopware or not just by looking at it's git history (plus some GitHub activity data).
The takeaway from my experiment is that you can really tell a lot by how / when / what people commit, but conclusions are very hard to generalize.
For example, I've also stumbled upon the "merge vs squash" issue, where squashes compress and mostly hide big chunks of history, so drawing conclusions from a squashed commit is basically just wild guessing.
(The author of course has also flagged this. But I just wanted to add my voice: yeah, careful to generalize.)
Yeah, maybe it's that, though I still wouldn't expect someone to categorize the post as blogspam, even if they just glance at it. (At least according to my definition of blogspam, but I guess each has their own.) But yes, pragmatically I should probably remove the disclaimer.
I gave up on r/programming after an article I wrote (thoughtfully, without AI, even though the content might not have been super interesting) got mod-slapped with a stickied comment "This content is low quality, stolen, blogspam, or clearly AI generated".
Ironically, that comment was added three months after I posted the article, when it was nowhere near the front page anymore, in a clearly automated and AI-driven review.
Oh, interesting, I didn't know about this project, thanks for sharing!
I tried to implement something like this for the search functionality, but ended up going with "old school" lexical search instead.
Mostly because, in my experimentation, vector search didn't perform significantly better, and in some case it performed worse. All the while being much more expensive on several fronts: indexing time (which also requires either an API or a ~big local model), storage, search time, and implementation complexity.
And Superego's agent actually does quite well with the lexical search tool. The model usually tries a few different queries in parallel, which approximates a bit semantic search.
> The intention of this is to reduce hallucination on information extraction, right?
Correct.
> Also, how do you convert your docs / information into JSON documents?
Right now you have to add it yourself to the database. The idea is that you use Superego as the software in which you record your expenses / income / whatever, so the data is naturally there already.
But I'm also working on an "import from csv/json/etc" feature, where you drop in a file and the AI maps the info it contains to the collections you have in the database.
The problem with using markdown for this is that it's unstructured, so when the LLM does calculations on it, extracting data is error prone, you're never sure what exactly gets extracted, and it's then a hassle to verify (like the author had to do).
In my app Superego (https://github.com/superegodev/superego, shameless plug) I use structured JSON documents precisely for this reason, because with a well-defined schema the LLM can write TypeScript functions that must compile. This doesn't guarantee correctness, of course, but it actually goes a long way.
But doing my taxes was a use case I hadn't considered, and it's actually pretty neat! I'll be trying it myself next month (though I'm not looking forward to it).
That would simplify things, but in my opinion that is still too high a hurdle. I'm all about privacy and FOSS, but I don't self-host anything (except for my personal website).
I wish that more apps would instead move the logic to the client and use files on file syncing services as databases. Taking tasks as an example, if a task board were just a file, I could share it with you on Dropbox / Drive / whatever we both use, and we wouldn't need a dedicated backend at all.
The approach has limitations (conflict resolution, authorization, and latency are the big ones), but it is feasible and actually completely fine for lots of apps.
I only use GitHub (and actions) for personal open-source projects, so I can't really complain because I'm getting everything for free¹. But even for those projects I recently had to (partially) switch actions to a paid solution² because GitHub's runners were randomly getting stuck for no discernible reason.
> your methodology would seem to be a reasonable approach/response to get the benefits of this and to shield against the detriments
If you're referring to the sandboxing / isolation of each app, I agree. Plus, the user can change the app quite easily, so if when they spot a bug, they can tell the agent to fix it (and cross their fingers!).
> ensure that a human developer understands the code before committing
Just to clarify: for Superego's app there's no human developer oversight, though. At least for the ones the user self-creates. Obviously the user will check that the app they just made works, but they might not spot subtle bugs. I employ some strategies to _decrease the likelihood of bugs_ (I wrote a bit about it here https://pscanf.com/s/351/, if you're interested), but of course only formal verification would ensure there aren't any.
Correct. Admittedly, graphic design is not even my passion, so there's probably lots of room for improvement. But at this point I've grown accustomed to the friendly face. :D
Yes! That's more or less the angle I'm going for. I mean, I don't aim just yet for Emacs-levels of malleability, but at least for something where you can create some useful day to day personal tools.
> It is hard, today, to explain exactly what Lotus Notes was.
Whenever I try to explain what it does to a non-tech person, I'm met with confused looks that make me quickly give up and mumble something like "It's for techies and data nerds". I think to myself "they're not my target audience".
But I actually would like them to be, at some point. In the 90s "the generality and depth of its capabilities meant that it was also just plain hard to use", but now LLMs lower a lot the barrier to entry, so I think there can be a renaissance of such malleable¹ platforms.
Of course, the user still needs to "know what they need" and see software as something that can be configured and shaped to their needs which, with "digital literacy" decreasing, might be a bigger obstacle than I think.
Question regarding the pluggable js engine: I have an electron app where I'm currently using QuickJS to run LLM-generated code. Would edge.js be able (theoretically) to use electron's v8 to get a "sanboxed within electron" execution environment?
Oh, interesting perspective. I'm Italian, but from an Alpine valley not far from Austria, so I don't know what I should prefer. :D
But joking aside, putting it like that I'd think I'd prefer the German/Codex way of doing things, yet I'm in camp Claude. But I've always worked better with teammates that balance my fastidiousness, so maybe that's my answer.
1. Even if you communicate perfectly, there's no guarantee that the LLM will "behave as instructed" and as you imagined it to. Indeed, the frustration often comes from the fact that you've said something as clear as day, yet the agent takes another path.
2. Part of the value of coding agents is exactly that you don't need to lay it all out perfectly for them. I mean, if I need to give the LLM every little implementation detail, I might as well write the code. Of course, I don't expect it to work off of "I want nice app make money", but I do expect some "intelligence" in figuring out the missing pieces.