I think it really depends what time of year you go. Zion is beautiful, but when I went it was early in the season and a lot of the popular stuff was closed and it was very crowded everywhere. On the same trip I did all 5 parks in Utah, and I easily rank Zion as my least favorite, even though people seem to love it the most. I would definitely go back though.
In this case it's not basic stuff. You would need to prove that you own the actual bitcoin or transfer it for it to be collateral on a loan. It's the same as spending it.
Adam Back is already a high profile target. Unmasking him as Satoshi doesn't really change that for the guy that founded that company that leads bitcoin core development.
I think good results come from spending a substantial amount of time reading the claude-code documentation and setting up an environment that lets you work in this new paradigm. Asking it a few things, getting poor results, and deciding "it doesn't work when you ask it to correct itself won't get you that far.
I think the biggest case for fine tuning is probably that you can take small models, fine tune them for applications that require structured output, and then run cheap inference at scale. "Frontier LLMs can do it with enough context" is not really a strong argument against fine-tuning, because they're expensive to run.
I think I recall reading about Hendrix that he tried to emulate the sounds of cartoons with his guitar, and then when he was in the army he did the same with trying to reproduce the sounds of fighter jets. Not sure if urban legend, but cool origin story.
I would argue that the ability to crawl and scrape is core to the original ethos of the internet and all the hoops people jump through to block non-abusive scraping of content is in fact more anti-social than circumventing these mechanisms.
I find that even though this isn't standard, that these -cli tools will scan the repo for .md files and for the most part execute the skills accordingly. Having said that, I would much prefer standards not just for this, but for plugins as well.
In my experience all technology has been like this though. We are on the treadmill of learning the new thing with our without LLMs. That's what makes tech work so fun and rewarding (for me anyway).
Define useful I guess. I think the agentic coding loop we can achieve with hosted frontier models today is a really long way away from consumer desktops for now.
I've used chrome devtools mcp successfully to do all kinds of advanced in browser tasks, agents like claude code can write js and inject it into the context in a live browser and do all kinds of neat tricks. I've used this extensively in gemini-cli.
It's pretty chill. I think part of it might be that my context is overloaded with security work, so it doesn't protest this stuff. I also have memories turned on which I don't really keep an eye on at all, and I think having a bunch of stuff in there related to cyber stuff also helps to keep it agreeable with what I'm asking for. Maybe you can hardcode this manually and see if that helps or try to gradually escalate the context by starting a technical conversation and then later on introducing the offensive task you're working on.
I don't think tricky niche knowledge is the sweet spot for genai and it likely won't be for some time. Instead, it's a great replacement for rote tasks where a less than perfect performance is good enough. Transcription, ocr, boilerplate code generation, etc.
Even if it's just for their internal security initiatives it would make sense given how massive they are. Threat hunting via cert monitoring is very effective.
The advice here seems to assume a single .md file with instructions for the whole project, but the AGENTS.md methodology as supported by agents like github copilot is to break out more specific AGENTS.md files in the subdirectories in your code base. I wonder how and if the tips shared change assuming a flow with a bunch of focused AGENTS.md files throughout the code.