- 1 hour ago
LinkedIn is finally moving against AI slop, Claude is opening the door to self-hosted private compute, and the tech jobs market is still showing strong demand despite a tough hiring environment. In this weekly tech, data, and AI commentary, the focus is on how platforms and professionals are adapting to low-quality AI content, privacy concerns, and shifting job trends.
The discussion starts with LinkedIn’s effort to detect automated comments and low-quality posts, including new ways for members to flag content that feels inauthentic. From there, it breaks down Claude code running on your own infrastructure, where sessions can stay inside your network, connect to internal services, and keep source code and build artifacts under your control. The episode closes with a look at CompTIA’s tech jobs report, including strong employer demand for software engineers, systems engineers, data analysts, and AI skills.
Created for viewers interested in tech news, AI commentary, LinkedIn updates, Claude code, privacy-focused AI tools, and the latest tech jobs report. It’s a useful listen for developers, data professionals, software engineers, and anyone tracking AI in the workplace and the future of tech hiring.
The discussion starts with LinkedIn’s effort to detect automated comments and low-quality posts, including new ways for members to flag content that feels inauthentic. From there, it breaks down Claude code running on your own infrastructure, where sessions can stay inside your network, connect to internal services, and keep source code and build artifacts under your control. The episode closes with a look at CompTIA’s tech jobs report, including strong employer demand for software engineers, systems engineers, data analysts, and AI skills.
Created for viewers interested in tech news, AI commentary, LinkedIn updates, Claude code, privacy-focused AI tools, and the latest tech jobs report. It’s a useful listen for developers, data professionals, software engineers, and anyone tracking AI in the workplace and the future of tech hiring.
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LearningTranscript
00:00Hello everybody and welcome back to our weekly video where we cover everything that's been
00:03happening in tech, data, and AI. And in this week we don't have a ton to cover but there are
00:08a few
00:08really interesting things to look at today. The first thing is that LinkedIn is finally taking
00:13some steps to counteract some of this AI slop that is everywhere on the platform. This right
00:18here is Harry and I'm going to butcher this last name but it's Srinivasan. He is the chief product
00:23officer at LinkedIn and so he is talking a little bit about what they're trying to do. He says right
00:29here, AI slop is a top priority for all of us. We really care about this and people come to
00:34LinkedIn
00:34to connect with real people and share their real perspectives, ideas, and expertise which is
00:39in my opinion 100% true. I don't really like coming on LinkedIn and I post and I get lots
00:46of just AI
00:47responses. I do not like them. They are not really engaging to me, right? These aren't real people who
00:53are actually giving their feedback. It's just you can tell immediately that it's AI slop. Now I'm just
00:57going to give you one example. This is a post I made several days ago just about a silly story
01:03about a printer that wasn't working in an old office. True story. I wrote it and within minutes
01:09there were already comments like this and people like it. I don't really understand why. It says
01:14the no one complained they just figured it out part is the real story. I mean anytime it starts out
01:20like
01:20this it's it just sounds like AI. Maybe this person really took their time to write this out
01:27and write it just like this but I'm telling you it I can spot it in a fraction of a
01:32second whether
01:32it's AI or not and there are ones like this where they're just like random channels or stuff on
01:37LinkedIn and these aren't real and so this is what they're talking about. Now it's not just comments
01:42although that's where I personally see it the most. It's in just people auto commenting. They're
01:47basically summarizing saying hey AI write a nice response to this on LinkedIn and they give the
01:51same generic output every time but it's also posts. It's posts as well of people just posting random
01:57AI slop that is just garbage and so they are working on several different things and one of the things
02:02right here is they're in beta version for this right now but you're going to be able to take a
02:07look at a post take a look at a comment and you're going to be able to report it and
02:10say hey this seems
02:11like AI slop ironically most likely what is happening on the back end is you're just training
02:16their AI in order to detect the AI better. That's probably all we're doing. It is possible some
02:23better system because LinkedIn is you know a pretty good network overall so they're going to have things
02:28like machine learning systems in place to detect these things so it's possible it's not AI. I'm just
02:33saying it would be really ironic if we are just training an AI system on the back end for it
02:38to then
02:39detect AI while we keep identifying this as AI. I just think it'd be ironic that's all I'm saying.
02:45Now there is some good news it says on comments alone every day we're now catching hundreds of
02:49thousands of automated comment attempts and have blocked billions of other automation attempts
02:55posting at scale slop in the last couple months alone. Now I am not shocked by this because there is
03:00so much opportunity here to very easily get rid of just so much junk. I'm glad they're at least making
03:06progress towards this. It also says that they're ramping up a series of new and improved classifiers
03:11that identify if a post is AI slop or generally low quality content. So even if you aren't using AI
03:18if
03:18your content is just not good right you're just writing random junk and it doesn't sound good it's
03:23not you know good grammar or it just sounds like AI. It is possible that they're just going to classify
03:29it as low content and not show it to a lot of people which I'm okay with. I'm fine with
03:34it if you're not
03:34putting a lot of effort into your posts if they're not actually good posts that people want to read
03:39I'm okay with them getting identified in this way and then just not being shown. That's okay. And then
03:44right here it says we are ramping up the ability for members to tell us if they believe a post
03:48or
03:48comment seems like AI slop. Slop is hard to define and the definition changes but they're tuning their
03:53models to make their better feet. So this is what we were talking about earlier. I think this is great
03:57but again this is purely done by people right. They are identifying this by you and me saying hey this
04:03is
04:03AI slop. There's a lot of ways this could go right. A lot of ways this could go wrong. We
04:08will see how
04:09this plays out but giving people at least the ability to be like hey I don't like this. I don't
04:13want to see this type of you know comment because I'm pretty sure it's AI. I think that's a good
04:18thing
04:18overall. And one thing I do like and this is because I post a lot on LinkedIn is for anyone
04:23who shares
04:23content will test a way to privately flag in your analytics dashboard when members feel your post may
04:29have come off as inauthentic or heavy use of AI. So this is good for somebody like me because if
04:36I'm
04:36making posts and people are flagging it in droves that it's AI well then maybe I'm just bad at writing
04:41and I need to get better at it. That's fine with me. Maybe I'll need to work on this. But
04:45it at least
04:46gives people the opportunity to say hey people think my stuff is AI the way I'm writing or the way
04:51I'm creating
04:52it seems like it's AI. Maybe I shouldn't write like that anymore. That doesn't mean you have to change.
04:56Just means that that's part of your algorithm now. You need to be aware of this. The next big news
05:00is that Claude code can now run its own compute. Now if we come right down here it says this
05:08is in
05:08public beta but you can self-host environments where you can run Claude code sessions on your own
05:14infrastructure. Now just at a high level this is amazing because up until now you cannot do that.
05:20And so everything that you were doing had to go through actual Claude code. And with this change
05:26here are some of the reasons why you'd want to self-host. One is that sessions run inside your
05:31network and can reach internal services databases and registries without exposing them to the public
05:37internet. So everything can be run on your local computer never having access to the internet which
05:43means you can't really accidentally mess things up. Now once you connect back to the internet if you have
05:49you know bugs and issues in your code or you know API keys or whatever it is then yes it's
05:55still going
05:55to you know mess things up. But if you're doing everything locally and you don't need to connect
06:00to the internet you are good. And that is a huge huge benefit of doing something like this especially
06:05if you're already in the Claude code ecosystem or that's kind of part of your workflow. You can also
06:09pre-install compilers SDKs and internal CLIs in your environment so every session starts ready to build.
06:15Now this is awesome just because again you don't have to go through and make all these connections
06:20and kind of log into all these different things. You can have all of those things already pre-done
06:25on your computer so you don't have to then again configure everything when you want to go and work.
06:31And lastly your source code and build artifacts stay on the infrastructure that you control.
06:36I think this is just the way that AI is going to be moving a lot in the future especially
06:41for
06:41professionals who are working on you know things that maybe you don't want to be sharing with the
06:46outside world really sensitive data some proprietary code. People want control over what they are sharing
06:52and what they're not sharing and some of these things are really private. They don't want to
06:55accidentally you know share all these things but it happens a lot. And so that piece of things especially
07:01for you know newbies and just people getting into AI they don't know all these different things.
07:06That is a great use case you know just having that kind of boilerplate AI. But for professionals
07:12who are using this for their work and it could cost them a lot of money to mess this up
07:17this is a
07:18fantastic thing. You're going to see a lot of startups going this way. I just think for you know your
07:22average
07:23AI user they're not going to care about this at all. But for developers and software engineers even data
07:28engineers people are working really heavily with these AI systems and this is a big big change.
07:33Lastly I want to touch on the job market. This is from CompTIA. I'll leave a link in the description
07:39but it basically just summarizes some of the information from the Bureau of Labor Statistics.
07:44And if you've ever been on the Bureau of Labor Statistics website it's not the easiest to read. I mean
07:49I went
07:49through and read it but then if I want to show it to you it doesn't read like it does
07:53in this article and so I
07:54just pulled up this article. But basically the technology sector expanded by approximately 3,700 jobs in July.
08:00That's not a lot. So that's not great. But there is some other data in here that I think is
08:05pretty
08:05interesting. It says employer demand for new tech talent remains strong with nearly 603,000 active job
08:12postings nationwide and across all industry sectors. If we look right down here it says demand for
08:18artificial intelligence AI skills remained significant with nearly 14,000 job postings in July alone
08:25seeking AI and machine learning expertise. At the same time employers sought out talent for established
08:30tech roles at a much greater scale including software engineers with 46,000 job postings, systems engineers
08:37with 34,000, tech support specialists at 24,000, and data analysts at 18,800. So there still is a
08:45lot of
08:45demand for these jobs. There's a lot of job postings. What I have anecdotally been seeing and I
08:52absolutely want to you know make a full video diving into the data on this. Anecdotally I have been seeing
08:57that there are a ton of job openings but there are so many people applying to a very small number
09:03of
09:03these job openings that it's really difficult right. So especially the remote jobs you're going to see
09:0910,000 people apply for a handful of remote jobs that are available whereas the local ones are going to
09:15get like 50 applications and that's purely just because they're local. They're most likely not going to be
09:20making as much money and so people don't apply to those as much. Anecdotally like I said I have talked
09:27to so many people who have gotten jobs in the past year where it hasn't been the best job market
09:31and the majority of them I would say 75 percent of them have said that the jobs that they got
09:36were
09:37local jobs or ones that they had to move to be in person for. They were not remote jobs. So
09:41if you're
09:41just starting out I highly recommend taking a look at your local jobs or somewhere where you can move
09:46to be local. If I'm living in the middle of the mountains in North Carolina or South Carolina
09:52and there's Charlotte you know and there's Charlotte North Carolina which is a big you know
09:57metropolitan city and there's lots of jobs there then I can apply there and if I get a job then
10:02I
10:02can just relocate very easily just several hours and so if you are living even within a vicinity
10:06where you are open to moving I highly recommend it. Now that is all we have for this week. I
10:12think
10:12the LinkedIn stuff is great. I genuinely think it's a big problem on the platform. I think they're aware
10:18of it and that is a really good thing is just being aware of it. I myself get so frustrated
10:24when
10:24I have 20 comments on a post and you know 15 of them are AI. It just isn't fun as
10:30a creator to try
10:32to interact or parse through which ones are AI slop and which ones are actually real people who I want
10:37to connect with because that's kind of a big reason why I post because I like talking to people. I
10:43like
10:43connecting with people but when most of them are just people using some AI system to auto comment
10:48it's just not fun. That doesn't excite me. So I am glad that they're taking this you know really
10:54seriously. That's kind of the biggest thing or the biggest takeaway from you know this week is that
10:59they're at least trying all right. Not every platform is going to be great at it or get it 100
11:03%
11:04but they're at least trying and identifying it. The code thing with Claude is amazing. I think this
11:10is long overdue. I'm glad it's happening and I'm glad that we can all now benefit from keeping things
11:16internal instead of having to keep everything connected to the internet and expose you know
11:20privacy things that we don't want to have you know accidentally slip out there. And so those are all
11:25really good things. I hope you learned something from this video. I am releasing these every single
11:30week. So if you like this type of content be sure to like and subscribe and I will see you
11:33next week.
11:44I'll see you next week.