LLMs generally have a way to "play a role" (most earlier prompt guides ask you to start with "You are a expert in a "). So maybe if you interact with it by asking questions, it might assume that it knows more than the operator and adopt that attitude?

I switched back to Opus because of this validation quirk. Overall, Fable spent 20% of the time on coding and 80% on validation.

I think using Fable for planning and Opus for execution could be a "best of both worlds" approach (I need to test this more), but for most cases, it's not necessary, and Opus is enough.

It's a very good model, but it comes at a huge premium: not only do the tokens cost more, but the model itself really wants to spend them all. For example, working with React Native, Fable never just says "okay, I did the thing, that's it." It tries to rebuild the entire app from scratch, run the whole test suite, and watch every log and warning.

This is the first time with LLMs I've felt that upgrading to a model isn't worth it, even if my company lets me use it, because all the building / testing was just destroying my machine and its battery, which keeps me from working on other things.

For now, it feels like Opus with ultracode is a better choice (less pollution of the main context, more parallelism in investigations).

I also see some logic flaws. It overlooks the option of going to a major hub to access faster aircraft, rather than hopping on local hubs.

Also, immigration and customs are cleared at the first airport you arrive at in the country, not at the last one.

In some countries, you need to clear immigration even while going to a third country, so 1 hour is not enough to do it.

I mean, there is money to be made. CATL stock (the major producer of EV batteries with 50% market share, with billions of contracts for stationary batteries) rose 48.81% over the last 6 months, for example.

But I agree that news about renewables goes unnoticed. I only see news about renewables because I actively seek out channels and websites that cover it. I wonder if it is because most companies in the industry are Chinese and don't focus on PR in the West as AI companies do.

When COVID hit, I knew a lot of engineers who decided to move to rural areas / small farms, because they could leverage Starlink to work remotely.

Last year, when I asked whether they still liked Starlink, all of them said it was amazing, but they had gotten fiber coverage in their area from a local provider, so they don't use it anymore, or just use it as a backup.

I think Starlink was a huge demand signal that there were people willing to pay a premium for faster-than-radio internet. So, unless they manage to be cheaper and faster than fiber, I don't think there is much of an endgame there.

https://www.youtube.com/watch?v=BzAdXyPYKQo

""If you show the model, people will ask 'HOW BETTER?' and it will never be enough. The model that was the AGI is suddenly the +5% bench dog. But if you have NO model, you can say you're worried about safety! You're a potential pure play... It's not about how much you research, it's about how much you're WORTH. And who is worth the most? Companies that don't release their models!"

Comments URL: https://news.ycombinator.com/item?id=47425060

Points: 1

# Comments: 0

For example, when a designer sends me the SVG icons he created, I no longer need to push back against just using a library. Instead, I can just give these icons to Claude Code and ask it to "Make like react-icons," and an hour later, my issue is solved with minimal input from me. The LLM can use all available data, since the problem is not new.

But many software problems challenge LLMs, especially with features lacking public training data, and creating solutions for these issues is certainly not cheap.

I believe what you wrote here has ten times more impact in convincing people. I would consider adding it to the blog as well (with obfuscated URLs so Google doesn't hurt the SEO).

Thanks for providing context!

And I don't doubt there is malware in Clawhub, but the 8/64 in VirusTotal hardly proves that. "The verdict was not ambiguous. It's malware." I had scripts I wrote flagged more than that!

I know 1Password is a "famous" company, but this article alone isn't trustworthy at all.

Comments URL: https://news.ycombinator.com/item?id=46877072

Points: 3

# Comments: 1

Comments URL: https://news.ycombinator.com/item?id=46872171

Points: 2

# Comments: 1

Comments URL: https://news.ycombinator.com/item?id=46872003

Points: 1

# Comments: 0

Comments URL: https://news.ycombinator.com/item?id=46856722

Points: 73

# Comments: 68

"You have a bug in line 23." "Oh yes, this solution is bugged, let me delete the whole feature." That one-line fix I could make even with ChatGPT 3.5 can't just happen. Workflows that I use and are very reproducible start to flake and then fail.

After a certain number of tokens per day, it becomes unusable. I like Claude, but I don't understand why they would do this.

For engineers aiming to move into management or staff engineering, you can assign them a project at the level they aspire to reach and give feedback once they complete it. For example, for an engineer aiming to be an EM, I expect them to lead not only meetings but also all communications related to this project, while I act as their director. Afterwards, I provide feedback.

It doesn't have to be that extensive right away. You can start small, like asking them to lead a roadmap meeting, and then increase responsibilities as they improve. Essentially, create a safe environment for them to grow.