The bullshittery is the thing that will not survive enshittification. I keep telling people that all the tokens we're blowing are going to explode in cost as soon as these companies run out of other people's money. To me, this means being laser-focused on your core competencies and only "farming out" stuff to AI that you would offload to a vendor. We're all familiar with the level of risk there, and the kind of encapsulation you need to swap something out if a vendor fails you.
I used https://github.com/Kevjade/migrate-openclaw, and then started running Claude Code with remote exec against an empty folder that I've advised it to start adding new memories into. So far, my bot's personality is back, and it can utilize the same skills as before, which is was failing on last week.
I don't have an especially heavyweight implementation, because I only use mine to review things I've written in my Apple Notes (journaling of various kinds, mostly) and give insights.
My OpenClaw assistant (who's been using Claude) lost all his personality over the last week, and couldn't figure out how to do things he never had any issues doing.
I racked up about $28 worth of usage and then it just stopped consuming anymore, so I don't know if there was some other issue, but it was persistent.
I got sick of it and used a migration script to move my assistant's history and personality to a claude code config. With the new remote exec stuff, I've got the old functionality back without needing to worry about how bleeding-edge and prone to failure OpenClaw is.
I feel like this is what their plan was all along -- put enough strain and friction on the hobbyist space that people are incentivized to move over to their proprietary solution. It's probably a safer choice anyway -- though I'm sure both are equally vibe-coded.
Man it's really too bad that that's the headline, because it's a great tribute to Arturo Vega, and I don't understand why it has to come at the expense of such a seminal band. If what Eno said about the Velvet Underground is true, then album sales don't account for much in the grand scheme of things anyway.
Having more data and being able to consistency process it actually can say a lot about the hypotheses that linguists have. All other science is evidence-based. The challenge for linguistics has been that many theorists pick and choose armchair examples rather than back their assertions up with statistical validity.
I'm a big fan of Karl Popper's work. I learned about him when reading the book Empirical Linguistics by Geoffrey Sampson. At the time, it was a pretty iconoclastic publication, since it directly struck against the assumption of nativism by framing the study of language as something that could be evidence-based in a way where hypotheses were truly falsifiable. The ability to collect and process large amounts of data pertinent to language make it a lot easier to strike down some of the more inscrutable theories of the '90s and '00s -- at least to those who are willing to do real science.
I feel like if you need to utilize a tool like this, odds are pretty good you may have picked the Wrong Tool For the Job, or, perhaps even worse, the wrong architecture.
This is why it's so important to do lots of engineering before writing the first line of code on a project. It helps keep you from choosing a tool set or architecture out of preference and keeps you honest about the capabilities you need and how your system should be organized.
https://hnbadges.netlify.app/?user=languagehacker
meet.hn/city/us-Atlanta
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