[deadbabe]

I still don't understand what these freaks are doing running these agents 24/7 on machines. What are they doing? Managing a todo list? You mean crossing items off as you complete them? Research tasks? To do what?

Never really get good answers. There is no killer app. Just bikeshedding.

[artisinal]

Swiping Tinder. It takes about 5000 matches to get a date. It’s easier to just automate it. It automatically adds dates to my calendar, all I have to do is show up. I get a summary of our chat history (well, what the agent wrote to her) in the notes section of the calendar entry and some pointers and talking points for the date.

Maybe I should have the agent also do a background check.

PS: This is a joke, but feel free to steal this idea.

[kurthr]

Any sufficiently advanced satire...

[deadbabe]

Good news about hell: it doesn't exist. Bad news: Humans can pretty much create whatever they can imagine.

[20k]

The future is agents chatting to each other on tinder and automating the initial getting to know you part. I can imagine that while that's going on, we could add like a little text chat box for the humans to chit chat with each other a bit and pass the time, before they can go on a date

[rootsudo]

It works well enough for bumble web, just make sure you have rate limiting..

Then the openclaw WhatsApp module…

Kidding of course.

[mystifyingpoi]

Crap, I totally believed this. We live in a dystopia already.

[artisinal]

Someone apparently made this

https://github.com/Grigorij-Dudnik/TinderGPT

> TinderGPT automates the process of writing and arranging dates with girls on Tinder, enabling you to generate romantic meetings with almost zero effort. Your only role is to like the profiles that catch your eye. After that, TinderGPT comes into the play. It initiates a conversation with the girl, using details from her profile, continues by building an emotional bond and highlighting your attractive traits, and finishes by arranging a meeting and giving you a push-up on your phone with her number.

[hjkl0]

This is not really the same at all. You still have to swipe, the value add here is apparently “building an emotional bond”. Together with the explicit goal of “dates with girls”, this actually feels incredibly nefarious.

[lionkor]

This is a sure way to get girls! Girls love being entirely commoditized and objectified, famously that's a great way to date! /s

[artisinal]

I’m surprised that the author didn’t even refer to them as females.

[kdheiwns]

It seems the main use case is having Claude automatically write blogposts about how great using Claude is, then submit them wherever necessary.

There's lots of news about the billions AI companies spend on data center construction, but it feels like it's not even a fraction of the money they're spending on endless nonstop blogs about how great their app is at doing... things. Things that will never be defined.

[deadbabe]

It really feels to me like this OpenClaw type stuff is the new "I built a static site generator!" type blogs that just post a few articles about how they built their generator.

[leokennis]

Exact same question as you. When the new ChatGPT app dropped it suggested to me to set up a task something like (paraphrased) “every Monday read my Gmail and Slack an make a summary and task list for the week”.

Why would I need an LLM to do this for me? That’s 5 minutes of work max, and doing it gets me in the flow of work again, to see what’s going on and needs to be done.

[phil21]

For a lot of folks summarizing a few days of work email and especially slack chats is way more than 5 minutes. Some work environments do not have great communication hygiene so it can be overwhelming to try to keep up with 500 emails a day and 38 Slack channels.

For the folks I talk to who use a LLM for this that seems to be the case. Takes a huge cognitive load off every morning and saves them an hour or two.

More or less a very expensive band aid over a bad work environment.

I kinda use it the same way in a sense. I have a little skill I run against our (horrible) task management system to summarize things and give me a punchlist to work through sorted by priority. This saves me thousands of clicks to do the same thing in the horrible web UI. A proper system in the first place would be a lot better!

At some point I’ll probably just take that to the next logical step and have the LLM write my own web interface to abstract and replace the horrible one entirely for me.

[croes]

And how can they be sure the summary correct and doesn’t miss anything important?

[phil21]

In such environments everyone is constantly missing things and not replying until they get followed up with.

So that sort of thing is already normalized. An LLM is unlikely to be worse than a human. There is no accountability either way since everyone is failing at the task, it really doesn’t matter much if your or your bot misses a few percentage points of high priority items. You will probably be vastly outperforming your peers who are doing it manually.

[lionkor]

This is very much just laundering not giving a shit through an LLM so you can blame it after the fact.

[moron4hire]

Because then OpenAI can read your emails and project communications and eventually build a model they will sell as an automated consultant. The CEOs will uncritically eat it up just long enough to cut the footing out from the industry. Once everyone is used to the sorry state of software, nobody will be able to imagine putting people to the task anymore and we'll have the new world order that Altman and Theil have been talking about creating.

[fooster]

I think you need to open your mind to the possibilities? For example:

- scanning logs for errors and

- opening issues which are then auto-triaged and

- PRs are opened for them and auto-reviewed and

- merged (and deployed).

This workflow alone is immensely powerful, and takes alot of burden off the team.

[airstrike]

> This workflow alone is immensely powerful, and takes alot of burden off the team.

ITSM those unsupervised workflows are essentially an attempt at purported productivity in the near term at the expense of meaningful incremental long term burden for teams.

The only ostensible benefit is in the eyes of the AI-psychotic tinkerer, who knows no better, or in those of the clout-chasing developer farming likes on their LinkedIn posts.

[fooster]

Really they're not. But it seems you have decided that you, above all, know best.

[airstrike]

I started my post with "it seems to me" precisely because I haven't decided that I know best.

[hjkl0]

> The only ostensible benefit is in the eyes of the AI-psychotic tinkerer, who knows no better, or in those of the clout-chasing developer farming likes on their LinkedIn posts.

Truly open minded

[airstrike]

I'm open minded, I just haven't seen evidence to the contrary. Speaking as someone who's spent an ungodly amount of time in claude code

[closeparen]

A company at the scale to benefit from this almost certainly has some kind of development sandbox environment and/or periodic job runner that's integrated into its environment and maintained by a team, not random Mac Minis.

[lionkor]

None of these are things I want or need in the product I maintain with a team, there's really no point to any of this unless you run a vibe coded SaaS (?)

[fooster]

You want your team spending their time fixing these simple errors? The secret sauce is in the triage. We've adopted solutions alot like this, and now our team spends its time on much more meaningful work.

[dingaling]

Why are the errors occurring, though? That's what boring analyse-and-fix addresses, through familiarity, recognition of patterns and "hang onnn..." moments.

It's like your AI agent is just plugging the leaks in the dyke each time, instead of fixing the architecture of the dam.

[fooster]

There are many sources of boring predictable errors which nonetheless are easy to miss and easy to fix. API validation errors for example.

[lionkor]

Yes, I want my team to be deeply familiar with the codebase and every single little bug that needs fixing both trains them and let's them learn a little bit more about the codebase.

They can use agents. Like, team members don't need to be replaced, they can simply use agents when they deem it useful. If they see a trivial bug,they can put their agent on it and go work on something else meanwhile.

[theshrike79]

Your non-vibecoded non-SaaS application never has errors?

[lionkor]

It doesn't have a central stream of logs if it's running on an isolated system without internet, so while there are errors, you can't have a 24/7 Claude looking at it. At my previous role, similar issue, you can't put Claude 24/7 on a PC with patient data on it. Just not happening.

[troupo]

> scanning logs for errors

famously a good job for a tool that takes 10-50k logs to run out of context and forget what it's doing.

[fooster]

Not really? Imagine for example looking for http status code 500 in an api log over the past hour. The nice thing here is it doesn’t matter if you get them all because it’s reoccur (or not).

[troupo]

> Imagine for example looking for http status code 500 in an api log over the past hour.

1. On a blog that no one visits maybe?

2. It's called a grep

3. For bigger projects it's called sentry

[fooster]

Dude, really open your mind and stop arguing mindlessly. We're using this to great success on a serious sass product with hundreds of thousands of users. I'm not some AI influencer, or blowing smoke.

The source of errors can be whatever you like. Sentry, grep, whatever. Its not the point. The point is that many of these errors are real issues, and can be fixed automatically and safely by agentic systems. It really saves time, and work by our team leaving them to actually concentrate on the thing that delivers real value.

[troupo]

You started with "scanning logs for errors" with LLMs which is one of the most stupid things could do with LLMs on a "serious SASS product with hundreds of thousands of users" (aka logs easily in gigabytes to hundreds of gigabytes per minute).

But now it's suddenly not "we use LLMs to scan logs for errors", but "we use actual tools to find erots in logs, but then just hand them off to an LLM and hope for the best".

As in "let's repeat what @troupo said but pretend it somehow goes against what @troupo said" lol

[mystifyingpoi]

None of this requires running it 24/7.

[theshrike79]

So someone has to be in the office to press the "observe logs" button every 5 minutes?

[mystifyingpoi]

Alerting on level=ERROR doesn't require agentic monster systems burning tokens constantly.

[theshrike79]

No, but the agentic monster system can have the relevant code checked out, manuals and runbooks analyzed, the error investigated and a fix proposed by the time the on-call engineer gets up from bed, grabs a Red Bull from the fridge and logs in to their work computer.

Then they have a starting off point to see if the agent was correct or not. If not, they lost maybe 2 minutes of reading. If yes, they can go "yea, push the fix and monitor", put down the Red Bull and go back to bed.

[greggsy]

I set it up out of curiosity a few months ago and realised I had no requirement for it whatsoever.

I’m actually very time-poor, so figured it could help be clawed back time doing… what exactly?

[vessenes]

Let me guess -- in your day job you don't manage people. I have agents parsing messages, building out document sets, evaluating existing document sets, one is currently fixing a giant backlog of bugs and feature requests for a multi year personal coding project, one is exploring some ideas on speeding up inference at the edge..

If you put yourself in a position where you need more leverage (technical or operating) I think you might find you get some value.

[deadbabe]

Given all the automation you do, it sounds like you don't really manage people either.

[theptip]

If you can’t think up enough coding projects to keep an agent busy in the background that’s a skill issue on your side.

[lionkor]

I am aware this is likely sarcasm, but in case it isn't, what do you gain from doing side projects this way?

[theptip]

No sarcasm, I am completely serious.

I don’t have time for much leisure coding these days. I do have time to kick off a few tasks in the morning to progress my many side projects. Nothing public / oss, just code that I find useful/interesting like home automation, content pipelines, games, etc.

There are a bunch of cases where remote control from iOS onto a Mac Mini is simply nicer than using iOS Claude Code sandboxes.

It’s the same pattern as you (hopefully) apply at $dayjob. If you are not defining a /goal and letting your agent crank you are not making full use of the models’ capabilities.

[lionkor]

Well I am fully of the opinion that LLMs can help in software programming, it's not something that I feel provides any value unless it has a human in the loop. The overhead of having to figure out if the agent did a good job, if the agent is actually done or not, and if the thing it built is shit or not, is worth simply avoiding by having a human in the loop.

So I wouldn't agree that the agent should be cranking out code all the time, in fact that seems more like a waste of resources compared to the work it creates. But I do understand home automation software can be very one-off and simple. But then again, a properly programmed home automation suite doesn't need a SOTA model to modify it, I think.

[troupo]

On all projects I've run any of the models they:

- infinitely duplicate any and all code, helpers and components

- infinitely duplicate CSS (because they duplicate components)

- continuously write code like "read the entire db into memory and run a filter function on retrieved data"

- continuously write code like "call db with multiple queries for each element in a list"

- etc. etc.

Why the hell would I ever want to run them unsupervised?

[ronbenton]

Have it work down my jira tickets while I’m sitting on the porcelain throne