I find no arguments against solar. I can put it everywhere and has no moving parts. Once storing is solved, perfect.
But wind?? Huge nature areas are destroyed by beton fundaments, rotors break, and just in germany was a scandal lately about recycling, as the first structures need to be renewed.
Wind power does seem to be generally not quite as good as photovoltaic solar power. But yeah every source of electricity has some downside. I don't have any good reason to care more about the possibility of rotors breaking or how to recycle the turbines, than I do about the possibility that a natural gas peaker plant might suffer a mechanical failure.
It's not like other forms of power generation don't have similar problems. Solar PV cells lose efficiency and need to be replaced. Nuclear has very long term storage concerns. Coal and natural gas plants have finite expected lifetimes before the whole plant needs to shut down.
A person that is expressing something a lot of real people are feeling. AI is churning out this terrible UI / graphic desing that looks the same, gives aways is just vibe coded slop and is VERY ugly.
Huh? I think the press in germany was never as free as it is now. A lot of new publications and competition. And that Trump is not reflected critically, nope, i do not agree.
ChatGPT or CoPilot were awesome products at the time. I do not use them anymore these days. But to me it felt never like i was abused. And Investment into companies is what it is, a risk. But the results remain forever, whoever wins.
Yeah, have the same sentiment towards Twitter before it has been bought by Mr. Musk. You were always close to being banned. And the American government was colluding. I don't like the tone on X now, but hey, no one silences me, and that is awesome.
How was the US Gov colluding? My recollection of the twitter files was it largely blew out of proportion (for non-tech aligned audiences) that Twitter received tips from CISA regarding misinformation/disinformation and Twitter decided whether to take action on accounts, sometimes they did, sometimes they didn't.
A group of whistleblowers tried to come forward about twitter before Elon bought it. There were entire departments dedicated to suppressing certain ideas and trends, while amplifying others.
Realistically this is something you need to do to some degree. I mean, you probably want to silence the "kill yourself" part of twitter and want to amplify the "please don't kill yourself" part.
Regardless, I think it's fairly clear that twitter is as manufactured as it ever was.
To my believe there was not a goal to write good code. The goal was maintainability and to keep it simple, so that people understand. People come and go, you constantly get to see foreign code and you have to do something with it.
Anyways, i see the maintainability hell coming onto us. I still wonder how i organize this with AI. I definitly do not want to touch it what is written by AI.
I think the industry-wide hope is that AI manages the AI-written code, but it’s unclear whether that’s actually going to work out in practice. Right now, my experience is that is dicey. I’ve had AI mess up a codebase to the point where I threw it away and restarted. Maybe I was doing it wrong, though, in that I was looking at the code and was increasingly horrified by the slop. I get the feeling that in this new world, we’re supposed to ignore how the sausage is made and just focus on the final outcome.
IME AI-native engineering requires a lot of infrastructure to make it viable. Teams who are just opening up cursor and putting it on "auto" and trying to one shot features may get stuff that works but is indeed slop.
Since the beginning of the year, I've been spearheading a low-stakes AI-native project (an internal tool). No one's written a single line of code. And we've learned so much from this experience. The first rule was our product manager, who is technical but isn't typically in the weeds, needs to be able to one-shot prompts with cursor auto. And so many rules stem from there, from e2e tests to ensure he doesn't break stuff, to custom linters to ensure that code lives in the right place, to architectural spec sheets so the LLM doesn't try to do raw DB queries from the client.
We're still not there, but we're getting closer and learning and improving every day.
I think the folks who are vibe coding a lot either aren't working in a team, or they are omitting the fact that they have spent a long time building harnesses to ensure the LLM doesn't run amok.
And I think the people who hate vibe coding are likely just asking Claude Code to do X without using Skills that have opinionated ways to do X.
All that said, I don't think we should ignore how the sausage is made at all. Part of what makes me able to move quickly in this project is knowing where stuff lives. I may not understand the line-by-line code, but if I know where to look to find out why I'm missing data that's in the DB, I can move a lot faster than if I have no idea what's going on in the codebase. Then when I find the problematic file or function, I can ask the LLM why it's like X and tell it it should be like Y.
Cool. Are you restricting the AI to be very focused on a function or an architectural blocks that is envisioned, or are you giving it more freedom? I seem to have less slop when I really constrain things, but that takes a lot of work (e.g., specs) and dialogue with the AI (“focus on X, now let’s design block Y,” etc.).
I give it freedom but with the predefined restrictions. I use a plug-in called Obra Superpowers. Whenever I want to start on a block of work, whether it's a ticket or if I just want to tackle tech debt, I start with the brainstorm command. I say something vague like "implement X" or "last time i tried to vibe code Y, Z happened. I don't want that to happen again. Let's improve the harness."
It'll ask follow questions, which I answer, then generate specs that I manually review. If it looks good, it'll generate a plan. If not then I'll give it feedback.
When the scope of work is well-defined (ie my boss says users should be able to do Y) then this process is fairly seamless.
When it's not well-defined then it does take a bit longer and more dialogue as you said. But because everything is documented and written down, we have a pretty good feedback loop (boss asks why it works like X, I can look at the generated spec/plan, or ask the AI to, to understand why).
Ok, so it’s constrained by specs, but you dialog with the AI and have it create the specs. I should try that. I’ve been creating my own specs and having it work from those and then iterating, but that’s not exactly quick and I find myself thinking, “At this rate I could do it faster myself.”
Yeah definitely agreed. I'm lucky I'm that my boss is willing to invest in this little experiment so the point isn't "can we do this faster manually" it's "how can we build our AI infrastructure such that it can actually be faster."
And also, I'm taking care of my infant daughter while working so my workflow is often "launch an AI agent from my computer while she's asleep, review plan on my phone while feeding or napping the little one, approve it and execute it" so it's often running when I'm not really in a mental space to be thinking deeply.
I use tailscale and mullvad vpn for a list of exit nodes i can choose from to work around restrictions, but also bad routing.
Like, when in asia and the route is to europe, sometimes it adds weird hops, while when i use an exit-node in Japan, i know, i have perfect routing to Japan and from there perfect routing to europe.
But the Mullvad VPN exit nodes often runs into problems like cloudflare blocking. So i am looking for alternative, not well known providers for exit-nodes.
Sometimes i even dream of sending my europe traffic via the internal aws network via regions, but hey...
> Sometimes i even dream of sending my europe traffic via the internal aws network via regions, but hey...
It's more work, but you can definitely do this. Inter-region traffic still carries egress charges though, so be aware of that in advance. This is a very common pattern in enterprise networking when building cloud-based SDWAN topologies: branch a,b,c connect to hub-1 in us-east-2; branch d,e,f connect to hub-2 in us-west-2; dc1 connects to hub-1 in us-east-2; dc2 connects to hub-2 in us-west-2; services in dc1 and dc2 can reach each other for DR and clients in branch f can reach services hosted in dc1.
Underlying all of these SDWAN technologies is essentially basic site-to-site VPN tunnels. Most still use IPSEC, although Wireguard is also used sometimes.
The only tricky part is the inter-region routing, and this can be managed largely within AWS using Transit Gateways (TGW), for a price, for more of a price AWS even makes it easier with Cloud WAN: https://aws.amazon.com/cloud-wan/
Basically if you just link your VPCs in each region with the appropriate routing policies, you can just connect to your preferred VPN server in each region and ultimately get routed correctly. This is what companies with cloud-based SDWAN do for providing SASE services to end-user clients.
I hope not. I am in general fine with Ads for content, even with profiling to what i listen and so on. But if you pay for subscription to get no Ads and still you get Ads from Spotify, then it is plain stupid.
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