| ▲ | stavros 17 hours ago |
| I hate LinkedIn so much I made a slop cannon for it. I have Claude research a topic and post an extremely LLM slop post about BuSiNeSs twice a week, and of course everyone comments with slop comments and I reply in kind. I immortalised the posts here: https://thinkpieces.stavros.io/ |
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| ▲ | Tade0 17 hours ago | parent | next [-] |
| I second that other comment - this is still above average in terms of LinkedIn content. |
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| ▲ | stavros 17 hours ago | parent [-] | | Damnit. I need to try harder to reach the level of the average poster. Sadly, downwards. |
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| ▲ | isoprophlex 16 hours ago | parent | prev | next [-] |
| My edification is complete and through a process of thought leadership osmosis I have now ascended to B2B sales enlightenment |
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| ▲ | stavros 16 hours ago | parent [-] | | Don't try to increase your B2B sales. Instead, try to realise the truth: there is no B2B sales. | | |
| ▲ | sailfast 2 hours ago | parent [-] | | P2P > B2B. Grow strong relationship pipelines through human interaction and in-person thought leadership. Sponsored by [Conference Facility] |
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| ▲ | gwerbin 17 hours ago | parent | prev [-] |
| Ironically I think these are insightful. If you want to produce true slop, you need to dumb down your topic selection, or have Claude pick the topics. The stuff about the incompatible goals of "data strategy" I think is genuinely useful perspective, for example. |
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| ▲ | stavros 17 hours ago | parent [-] | | Claude does pick the topics! I worry I did too good a job steering it. I found a few of them insightful too, but it doesn't matter, what matters is that they're same old "They were doing a thing. It failed." Claude writing you see everywhere, intensifying the feeling that nobody on LinkedIn has a pulse. | | |
| ▲ | gwerbin 7 hours ago | parent [-] | | On the bright side, if everyone is burning credits mining generic but helpful knowledge out of the LLM training data in bite-size packages, I don't need a subscription of my own! It will be really fascinating to see what happens with the potential for LLM-generated output to become a dominant component of new training data. |
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