I'm not sure how well it works in programming. It helps in brainstorming and for a developer working in an area in which he is not advanced. There is a claim it works very well in crypto implemented in Rust with full test coverage and after human developer provided all the main interfaces. It is plausible. Most crypto code is opensource and easy to test so AI can work very well essentially rewriting the code it was trained on into Rust.[1]

But on the other side there is that study that did show that developers working on a code base they know well are quicker without AI despite thinking they were quicker with the AI.[2] And if AI is helping that much then where is all the showelware (additional software which should be on the market since it is so easy to write software now with AI help).[3]

Also llm-stats.com show that the best coding score has Claude Mythos Preview. The value is 57. I'm not sure how to interpret it but if that means that 100-57 = 43% of the output has some bugs then it is pitiful and would explain the missing "showelware".

[1] https://slashdot.org/comments....
[2] https://metr.org/blog/2025-07-...
[3] https://mikelovesrobots.substa...

OK, I get it. It is really bad when the fuel starts boiling.

Anyway some shippers transport gasoline cars without a problem but refuse to transport electric vehicles because when they start burning then they are screwed. With gasoline cars they can seal off the deck, flood it with nitrogen and cool the walls from the outside. With electric vehicles, nitrogen will not help. If temperature from the first burning vehicle rises enough to start internal fire in batteries of other vehicles then it is likely the whole ship will burn and sink.

Isn't the goal to use foam? Cooling is not important. Preventing oxygen access is. I'm not a firefighter. I have only seen them to use foam on a burning gasoline car.

I tried this for fun. Only some free models. The results:

Copilot: John David Allsup
Gemini: MaxTokenHalt? Something went wrong. Not sure what.
Duckduckgo GPT 5 Fast: Richard Kaye
Duckduckgo Claude Haiku 4.5 Reasoning: MaxTokenHalt
Qwen 3.6 27B Reasoning (locally run without internet access): David J.

That is true only for power-split e-CVT hybrids which is a lot of them, maybe most but not all of hybrids.

You know it is easier to put out gasoline fire than lithium battery fire, right?

Natural gas price will rise when data centers increase consumption. Producers will increase their production as natural gas price goes up. That is basic economics. Therefore more CO2 will be generated from natural gas.

Also the summary notes that data centers use less efficient gas turbines because more efficient are not currently available in the required numbers. Again more CO2 because of sudden data center buildup.

How can you claim that it is possible for some tool to find all the bugs if you cannot know that the tool found all the bugs?
You cannot claim a tool found all the bugs without a proof that the tool found all the bugs.

Just tell the AI to write the IDE! Sure the best AI can do it for less than $ 60B.

This is not a problem for very low earth orbit.
Lifetime vs Orbital Height Ballistic Coefficient m/(Cd*A) = 166.67 kg/m^2
mean lifetime @ 400 km initial height is 110 days, maximum is 7 years

Maybe in about 90% if you are lucky. That still leaves about 10% error rate which is way too much.

Depends on the definition of "bases". Passing test suite does not show your program correct. And if your test suite is also AI generated then you are again at the problem whether the tests themselves are correct.

Vibe error detection goes nicely with vibe programming. That being said, experienced programmers have a talent to detect errors. But detecting some errors here and there is far from full code review. Well, you can ask LLM to do it as well and many proposals it provides are good. Greg Kroah-Hartman estimates about 2/3 are good and the rest is marginally somewhat usable.

Nothing goes as nicely as discussing with LLM. The longer you are at it the more askew it goes.

My point is that 25k LOC a month (god forbid a week) is a lot. It may look working on the outside but it is likely full of hopefully only small errors. Especially when you decide that you do not need to human-review all the LLM generated code. But if you consider e.g. lines of an XML file defining your UI (which you have drawn in some GUI designer) to be valid LOC then yeah. 25k is not a big deal. Not all LOCs are equal.

Mod UP!

Kinesis Advantage is good enough. I started to use it around 2002. Then switched to custom builds: K80CS and later K84CS.

Split space bar is better than a standard one but it is only a poor start to separated thumb clusters which provide somewhere from 6 to 9 easily reachable keys per thumb.

Check out e.g. K80CS layout. That is a custom build and there are many similar (and from my point of view slightly worse) custom keyboards in the community. People mostly do not want to build their own keyboard. They can get a usable commercial alternative which is not too bad. There are more of them, e.g. Kinesis Advantage 360.

A split keyboard with thumb clusters is the most important feature. If it is contoured then even better.

It is dispatch-able if you overbuild cooling to 100% of thermal power.

Most reactors build cooling only to about 50% of thermal power. They do it since they assume they can always sell at least 50% of electrical power to grid. They assume this since they can lower price to zero (and out compete others) when needed. They can afford this since nuclear fuel is only about 2% of the overall costs. So there is no serious problem to waste fuel into heating the environment around the plant ... provided that they do not cool in a local river only which they cannot overheat without killing the river life.
Look at nuclear electricity production in France around summer solstice. You will see that it fluctuates quite a lot.