A bit off-topic, but it's interesting how the first thing I check now is whether this is a vibe coded app (which it seems to be) or something that had serious effort put into it.
I mean, "effort" to me in this context is what the creator of $project thinks it is worth their time. Don't you agree? If you want to learn a new computer language yourself, vibecoding will probably not help you. If you want to create something to scratch your itch, and spend time and mental effort in getting it polished, isn't that effort? It is not automatic, even with vibecoding, getting out a good app/site that solves a need in an elegant, functional manner for the user.
I think your last point is the important one. I don't mind vibe coded app if they are polished. But a polished vibe coded app looks like a non-vibe-coded app because of the polishing. The polishing is 95% of the effort. This app here looks fully vibe coded, without much polishing, at least to me.
> It is not automatic, even with vibecoding, getting out a good app/site that solves a need in an elegant, functional manner for the user.
This feels like a vibecoded comment.
To address the "substance" of your "comment": yes, creating a polished product requires effort, but this is not a polished product: as pointed out by numerous commenters, it provides nothing new, and what it does provide is broken. Thus the GP's comment that it is vibecoded slop and not worth taking seriously.
My rhetorical question was broader, because GP comment was a generic one, not specific to this project.
I would ask you to be more mindful in your replies.
It doesn't matter, the answer is the same. Using vibecoding is less effort that not using it, so of late we see a lot of low-effort vibecoding projects, of which this is one. Ergo, vibecoding is an easily-spotted red flag for projects that are not worth taking seriously.
> I would ask you to be more mindful in your replies.
You should take your own advice. Also, don't be a dick.
> It doesn't matter, the answer is the same. Using vibecoding is less effort that not using it, so of late we see a lot of low-effort vibecoding projects, of which this is one. Ergo, vibecoding is an easily-spotted red flag for projects that are not worth taking seriously.
And the whole point of my initial reply was to question the definition of "effort".
> You should take your own advice. Also, don't be a dick.
I think your reply perfectly illustrates the situation.
Not a fruitful discussion anyway, enjoy clicking down arrows.
You're offering a product, not a vibe project, so I disagree.
If vibe coding would lower cost while maintaining quality then this would be a fair argument, but the reality is that its a lazy way and frankly it's not programming.
GP was speaking of the first thing they now check on every new project they find is whether it's vibecoded or there is actual "effort" in it. Hence my comment.
I don't think your Github example is accurate. The vast majority of developers started using git after Github became a thing. They may have used svn or another type of collaboration system before, but not git. And the main reason they started using git is because Github was such massive value on top of git, not because git was so amazing.
My memories are different. Git became amazing on it's own and was a big advantage over SVN. GitHub was "a open source" thing in the beginning. No company here had the idea to host proprietary closed source code on another platform they do not have control over. This eventually became a thing later though and the mindset shifted.
I think you're both right. Post-Github, a lot of Git's adoption came from Github. But Github "worked" because a lot of people were already using Git and Github offered them amazing value, and that initial userbase created a viral effect: People increasingly came into contact with Github via projects hosted there, and those who did not already use Git picked it up as a result of that.
And now many companies do have the idea of hosting proprietary code on a shitty, buggy, closed-source platform they have no control over. Indeed a shifted mindset. Maybe it wasn't shitty, buggy and closed-source enough before.
> And the main reason they started using git is because Github was such massive value on top of git, not because git was so amazing.
Github has always been mediocre and forgettable outside of convenience that you might already have an account on the site. Svn was just shitty compared to git, and cvs was a crime against humanity.
I have to hard disagree on that. I know of many developers personally who were on Source Forge and Google Code before and migrated to GitHub specifically because they offered git
I don't think SVN and Mercurial were more widely used than git before Github became popular, but Github definitely killed off most of the use of those.
Git had already replaced perforce and svn most everywhere I'd seen, before GitHub came along. CVS was still horrible and in a lot, though.
I mean, git was '05 and GitHub was '08, so not like the stats will say much one way or another.
StackOverflow only added it their survey in 2015. No source of truth, only anecdotes.
Lots of people were using svn and mercurial was also coming up around the time that GitHub launched. Both git and GitHub were superior to all the other options but for many people they did the switch to GitHub and git at the same time.
Yeah, whilst git was more popular than mercurial, I still think mercurial would have won if bitbucket had a better UI.
It's interesting to me that the only thing that made me vastly prefer using Github over bitbucket is that Github prioritised showing the readme over showing the source tree. Such a little thing, but it made all the difference.
Here’s a copy of a post I made on Farcaster where I’m unconvinced it’s actually being used at all:
I've used OpenClaw for 2 full days and 3 evenings now. I simply don't believe people are using this for anything majorly productive.
I really, really want to like it. I see glimpses of the future in it. I generally try to be a positive guy. But after spending $200 on Claude Max, running with Opus 4.5 most of the time, I'm just so irritated and agitated... IT'S JUST SO BAD IN SO MANY WAYS.
1. It goes off on these huge 10min tangents that are the equivalent of climbing out of your window and flying around the world just to get out of your bed. The /abort command works maybe 1 time out of 100, so I end up having to REBOOT THE SERVER so as not to waste tokens!
2. No matter how many times I tell it not to do things with side effects without checking in with me first, it insists on doing bizarre things like trying to sign up for new accounts people when it hits an inconvenient snag with the account we're using, or it tried emailing and chatting to support agents because it can't figure out something it could easily have asked ME for help with, etc.
3. Which reminds me that its memory is awful. I have to remind it to remind itself. It doesn't understand what it's doing half the time (e.g. it forgets the password it generated for something). It forgets things regularly; this could be because I keep having to reboot the server.
4. It forgets critical things after compaction because the algorithm is awful. There I am, typing away, and suddenly it's like the Men in Black paid a visit and the last 30min didn't happen. Surely just throwing away the oldest 75% of tokens would be more effective than whatever it's doing? Because it completely loses track of what we're doing and what I asked it NOT to do, I end up with problem (1) again.
5. When it does remember things, it spreads those memories all over the place in different locations and forgets to keep them consistent. So after a reboot it gets confused about what is the truth.
i've never had situations where i prompt and had to go out for coffee or a walk or drive. one shotting - your first prompt. perhaps.
but like a person - when the possibility of going off in the wron g direction is so high, i've always had 1 - 2 line prompts, small iterations much more appealing. The only times i've had to rollback would be when i run out of credits, and a new model cant deal with the half baked context, errors, refactoring.
there's an entire cohort on HN who still claim AI is utterly and completely useless despite in your face evidence. Literally people making a similar claim word for word who say that they don't understand the hype that they used AI themselves and it's shit.
Meanwhile my entire company uses AI and the on the ground reality for me versus the cohort above is so much at odds with each other we're both claiming the other side is insane.
I haven't used these bots yet but I want to see the full story. Not just one guys take and one guys personal experience. The hype exists because there are success stories. I want to hear those as well.
You’re correct. Any statement by HN users that something is useless has no value because they say that about useful things too.
Moltbot has the shape of the future but doesn’t feel like it to me. Sort of like Langchain once was. Demonstrated some new paradigm shift but is itself flawed so may not be the implementation that lasts. Time will tell.
The only thing here to say is “put it in a VM and try it”. It’s easy to try.
Yep. But on HN, there's a huge cohort of people saying AI is useless.
Everyone sees the downsides but the upside is the one everyone is in denial about. It's like yeah, there's downsides but why is literally everyone using it?
As a rule of thumb, most people who say things like "X is useless and a waste" or "Y is revolutionary and is going to change everything by tomorrow" when the dust hasn't even begun to settle are stupid, overly-excitable, too biased towards negative outlooks, and/or trying to sell you something.
Sometimes they have some good points so you should listen to what they have to say. But that doesn't mean you have to get absorbed into their world view. Just integrate what you see as useful from your current POV and move on.
I don’t know how you came to that conclusion from my comment. I’m talking about a particular product named OpenClaw, representing a new style of doing work; not AI in general.
I dropped $200 on Claude Max in my personal capacity to test OpenClaw because I use Opus 4.5 all day in Cursor on an enterprise subscription… because it works for those problems.
>I don’t know how you came to that conclusion from my comment. I’m talking about a particular product named OpenClaw, representing a new style of doing work; not AI in general.
Right, I'm saying AI in general is an example of the unreliability of peoples experiences on openclaw. If people are so unreliable about the narrative of AI, I don't trust the narrative of openclaw which on this thread in particular is very negative and in stark contrast to the hype.
>I dropped $200 on Claude Max in my personal capacity to test OpenClaw because I use Opus 4.5 all day in Cursor on an enterprise subscription… because it works for those problems.
The comment wasn't directed at you personally. I'm just saying I want to see counter examples of openclaw succeeding, not just examples of it failing. Frankly on this thread there's Zero success stories which I find sort of strange.
>There's people saying AI isn't living up its hype / valuation, I don't see many saying "utterly useless".
There's more people saying AI doesn't live up to the hype. The people who are saying it's utterly useless is still quite large on HN. It's just that most of them are midway through changing their story because reality is smashing them in the face.
>And there's plenty who worship at the altar of Claude.
I mean who doesn't use it? No one claims it's perfect or a god of code. But if you're not using it you're behind.
The problem with those opinions is they add next to nothing, and they often have the least experience with the things they're critiquing.
Those of us who want to explore what people are doing have to wade through piles of comments saying the same thing, with very little difference from comment to comment.
That said, the opinion is quite valid. I think many people will continue to have no use for agents.
Disclaimer: Haven't used any of these (was going to try OpenClaw but found too many issues). I think the biggest value-add is agency. Chat interfaces like Claude/ChatGPT are reactive, but agents can be proactive. They don't need to wait for you to initiate a conversation.
What I've always wanted: a morning briefing that pulls in my calendar (CalDAV), open Todoist items, weather, and relevant news. The first three are trivial API work. The news part is where it gets interesting and more difficult - RSS feeds and news APIs are firehoses. But an LLM that knows your interests could actually filter effectively. E.g., I want tech news but don't care about Android (iPhone user) or MacOS (Linux user). That kind of nuanced filtering is hard to express as traditional rules but trivial for an LLM.
But can't you do the same using appropriate MCP servers with any of the LLM providers? Even just a generic browser MCP is probably enough to do most of these things. And ChatGPT has Tasks that are also proactive/scheduled. Not sure if Claude has something similar.
If all you want to do is schedule a task there are much easier solutions, like a few lines of python, instead of installing something so heavy in a vm that comes with a whole bunch of security nightmares?
> But can't you do the same just using appropriate MCP servers with any of the LLM providers?
Yeah, absolutely. And that was going to be my approach for a personal AI assistant side project. No need to reinvent the wheel writing a Todoist integration when MCPs exist.
The difference is where it runs. ChatGPT Tasks and MCP through the Claude/OpenAI web interfaces run on their infrastructure, which means no access to your local network — your Home Assistant instance, your NAS, your printer. A self-hosted agent on a mac mini or your old laptop can talk to all of that.
But I think the big value-add here might be "disposable automation". You could set up a Home Assistant automation to check the weather and notify you when rain is coming because you're drying clothes on the clothesline outside. That's 5 minutes of config for something you might need once. Telling your AI assistant "hey, I've got laundry on the line. Let me know if rain's coming and remind me to grab the clothes before it gets dark" takes 10 seconds and you never think about it again. The agent has access to weather forecasts, maybe even your smart home weather station in Home Assistant, and it can create a sub-agent, which polls those once every x minutes and pings your phone when it needs to.
I have a few cron jobs that basically are `opencode run` with a context file and it works very well.
At some point OpenClaw will take over in terms of it's benefits but it doesn't feel close yet for the simplicity of just run the job every so often and have OpenCode decide what it needs to do.
Currently it shoots me a notification if my trip to work is likely to be delayed. Could I do it manually well sure.
But this could be done for 1/100 the cost by only delegating the news-filtering part to an LLM API. No reason not to have an LLM write you the code, too! But putting it in front of task scheduling and API fetching — turning those from simple, consistent tasks to expensive, nondeterministic ones — just makes no sense.
Like I said, the first examples are fairly trivial, and you absolutely don't need an LLM for those.
A good agent architecture lets the LLM orchestrate but the actual API calls are deterministic (through tool use / MCPs).
My point was specifically about the news filtering part, which was something I had tried in the past but never managed to solve to my satisfaction.
The agent's job in the end for a morning briefing would be:
- grab weather, calendar, Todoist data using APIs or MCP
- grab news from select sources via RSS or similar, then filter relevant news based on my interests and things it has learned about me
- synthesize the information above
The steps that explicitly require an LLM are the last two. The value is in the personalization through memory and my feedback but also the ability for the LLM to synthesize the information - not just regurgitate it. Here's what I mean: I have a task to mow the lawn on my Todoist scheduled for today, but the weather forecast says it's going to be a bit windy and rain all day. At the end of the briefing, the assistant can proactively offer to move the Todoist task to tomorrow when it will be nicer outside because it knows the forecast. Or it might offer to move it to the day after tomorrow, because it also knows I have to attend my nephew's birthday party tomorrow.
I spun up an Debian stable ec2 vm (using an agent + aws cli + aws-vault of course) to host openclaw, giving it full root access, and I talk to it on discord.
It's a little slow sometimes, but it's the first time I've felt like I have an independent agent that can handle things kind of.
The only two things I did were 1. Ask it to create a Monero address so I could send it money, and have it notify me whenever money is sent to that address. It spun up its own monerod daemon which was really heavy and it ran out of space. So I had to get it to use the Monero wallet instead, but had to manually intervene to shut down the monerod daemon and kill the process and restart openclaw. In the end it worked and still works.
2. I simply asked it "@ me the the silver price every day around 8am ET" and it just figured out how to do it and schedule it. To my understanding it has its own cron functionality using a json file.
3. Write and host some python scripts I can ping externally to send me a notification
I've had it done other misc stuff, but ChatGPT is almost always better for queries, and coding agents + Zed is much better for coding. But with a cheap enough vm and using openrouter plus glm 4.7 or flash, it can do some quirky fun stuff. I see the advantage as mainly having control of a system where it can have long term state (like files, processes, etc) and manage context itself. It is more like glue and it's full mastery and control of a Linux system gives it a lot of flexibility.
Think of it more as agent+os which you aren't getting with raw Claude or ChatGPT.
I've done nothing that interesting with it, it's absolutely a security nightmare, but it's really fun!
One significant advantage over Claude/ChatGPT is that your own agent will be able to access many websites that block cloud-hosted agents via robots.txt and/or IP filters. This is unfortunately getting more common.
Another is that you have access to and control over its memory much more directly, since it's entirely based on text files on your machine. Much less vendor lock-in.
I couldn't really use OpenClaw (it was too slow and buggy), but having an agent that can autonomously do things for you and have the whole context of your life would be massively helpful. It would be like having a personal assistant, and I can see the draw there.
I have no idea. the single thing I can think of is that it can have a memory.. but you can do that with even less code.
Just get a VPS. create a folder and run CC in it, tell it to save things into MD files.
You can access it via your phone using termux.
You could, but Claude Code's memory system works well for specialized tasks like coding - not so much for a general-purpose assistant. It stores everything in flat markdown files, which means you're pulling in the full file regardless of relevance. That costs tokens and dilutes the context the model actually needs.
An embedding-based memory system (letta, mem0, or a self-built PostgreSQL + pgvector setup) lets you retrieve selectively and only grab what's relevant to the current query. Much better fit for anything beyond a narrow use case. Your assistant doesn't need to know your location and address when you're asking it to look up whether sharks are indeed older than trees, but it probably should know where you live when you ask it about the weather, or good Thai restaurants near you.
Yeah, I don't get it either. Deploy a VM that runs an LLM so that I can talk to it via Telegram... I could just talk to it through an app or a web interface. I'm not even trying to be snarky, like what the hell even is the use case?
Okay, but most of the time you can't prompt your AI to successfully debug you out of problems if you don't understand code. Or when you do the AI will solve the problem in a way that creates a dozen more cascading problems an hour later. I've also been coding for 20 years now and I feel like my coding skills are just as important now as they were 10 years ago. Without them I'd never be able to use AI effectively.
The only exception really are greenfield apps like "create a toy todo app demo" or "scaffold this react project" but that's like 0.001% of real world engineering work.
True, but it very much depends on the domain and complexity of stack you're working in. For a lot of crud type dev work the problems are common to many and AI will have no trouble.
Captcha is a completely useless system trivially solved by many agents and services. The only thing captcha does is annoy humans. I do agree with the problem, but I don't know what a solution would look like outside of government identification.
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