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On the one hand, people like Sam Altman have been talking about potential problems from AI systems up to and including the destruction of humanity for years now.

On the other, we are supposed to be ok with OpenAI deciding to move fast and break things? Cut them some slack because they are a lab?

Previously on HN: https://news.ycombinator.com/item?id=49864306

These types of taxes are common and logic is simple, you have capital gains that accrued during the time you were tax resident in Germany. By rights the taxes on those gains are due to the German state. So you need to do a deemed disposition and pay the relevant taxes.

I had to do the same when moving country and it’s right.

If the user doesn’t perceive/value the measured improvements in quality or availability, then it is legitimately sameish.

Just because it can be measured doesn’t mean it matters.

For one off tools, sure. For ongoing tools, either they are right after the first implementation and you use them for years. Alternatively, you need to maintain them and they decay until you discard them.

You also need to be ok with your tool to do task A (you had an agent build) to work different from my tool to do task A (I had an agent build). Meaning we can’t reliably compare the output from those tools.

Unless this impacts net income, it's just theater.

Tech bros thinking because they're good with computers they're experts at everything.

Could this be that the AI companies are seeing progress slow down and need to seed a narrative to explain it? Not clear from outside.

Could it be to slow down burn before an IPO to juice profitability projections? More plausible.

Kind of hard to take the frontier labs at their word.

That‘ll happen when you don‘t have meaningful data protection laws.

Because America can’t be trusted.

...or bankrupt... I'm told it's 50:50, but only a 30% chance of that

Maybe cutting their prices another 80% will get them to 2 billion?

We've seen this playbook with social media - be nice and friendly until they let you get close enough to stick the knife in.

It's really quite amazing that people would actually hook an AI company up to data that actually matters. I mean, we all know that they're only doing this to build a training data set to put your business out of business and capture all the value for themselves, right?

It's as if the social media companies don't recognize they are the problem and that the world worked perfectly fine before social media.

MBP M4 Max 64MB - haven't measured the tokens/sec, feels slower than Claude, but not unbearably

It's not yet perfect, my sense is just that it's near the tipping point where models are efficient enough that running a local model is truly viable

I'm using small - works well for its size

In other news, been using Devstral 2 (Ollama) with OpenCode, and while it's not as good as Claude Code, my initial sense it that it's nonetheless good enough and doesn't require me to send my data off my laptop.

I kind of wonder how close we are to alternative (not from a major AI lab) models being good enough for a lot of productive work and data sovereignty being the deciding factor.

I've been coding professionally for almost 30 years. I use Claude Code heavily, even for larger features. To get that to work half-decent, you have to take on a PM/Tech-lead role, you're no longer a senior engineer.

For large pieces of work, I will iterate with CC to generate a feature spec. It's usually pretty good at getting you most of the way there first shot and then either have it tweak things or manually do so.

Implementation is having CC first generate a plan, and iterating with it on the plan - a bit like mentoring a junior, except CC won't remember anything after a little while. Once you get the plan in place, then CC is generally pretty good at getting through code and tests, etc. You'll still have to review it after for all the reasons others have mentioned, but in my experience, it'll get through it way faster than I would on my own.

To parallelize some of the work, I often have Visual Studio Code open to monitor what's happening while it's working so I can redirect early if necessary. It also allows me to get a head start on the code review.

I will admit that I spent a lot of time iterating on my way of working to get to where I am, and I don't feel at all done (CC has workflows and subagents to help with common tasks that I haven't fully explored yet). I think the big thing is that tools like CC allow us to work in new ways but we need to shift our mindset and invest time in learning how to use these tools.

Aren't executives just responding rationally to the current environment? Right or wrong, the broadly speaking, the current thinking is that GenAI will be super impactful. Which means there is a lot of risk to be seen as underinvesting in GenAI, even when the ROI isn't there. Until the hype dies down and there is a broad, practical understanding of the value of GenAI, I don't see how it could work anyother way.

I'm unsure how strange this is. As a Canadian, when I left the country I had to undergo what's termed a deemed disposition - i.e., pretend you sold all your assets and then pay the relevant taxes on the net gains you've enjoyed to that point. This includes proposing a value for any companies that are not publicly traded. See: https://www.canada.ca/en/revenue-agency/services/tax/interna...

That said, I still approach it with the assumption that Claude Code is just mashing its fists on the keyboard and that there needs to be really strong, in-loop verification to keep it in line.

I used to use Cursor and just deal with the slow requests for most of the month because it was the most affordable way to leverage an agent for coding, but I didn't find it so much better than Cline or Roo. When I first tried Claude Code, it was immediately clear to me that it worked better, both as an agent and for me, but it was way too expensive. Now with the $200/mo. Max plan, I couldn't be happier.

I've spent a lot of hours vibe coding with sonnet 3.7 thinking and I'm not seeing anything in the article that jumps out at me as being different from my experience.

After spending some time vibe coding, I think this article is pretty accurate in that it aligns with a) how poor AI agents work in practice and b) the fact that non-coders are expecting magic from AI (which to be fair is what the AI companies are promising with all of their hype).

Where I have found vibe coding as an approach really shine is if I need to write some sort of quick utility to get a task done. Something that might take an hour or more to slap together to solve some menial task that I need to do on a bunch of files. Here I can definitely throw it together quicker than manually and don't care if it is messy code.

Larger, more complicated apps that are meant for production are painful to try to get AI tools to build. Spend so much time prompting the AI to get the task done without breaking something else that I doubt I'm any faster than just hand coding it alongside a co-pilot

You mean the memos all over LinkedIn about how companies can reimagine and automate their customer experience to better instrumentalize customers to hand over their money while removing the need to actually interact with said customers?

Who cares what businesses do, what I want is an AI agent I can point to a business with my goal (e.g., be relentless in either negotiating my cable bill down by 25% and if after 30 days you fail, cancel my subscription) and have it do it.