The rebuttals I always get are “I want you working on something that I can’t pay another company for”. I think it sounds good, but in the long run we always end up a budget conversations and head count limits because we spend so much money on external services and software we should just build.

Every company ever has this problem.

But now with AI. The cost of showing the company “yes we can” is so cheap. I worry for companies who have promotable replacements.

Idk how that works with journals today, but anything like this which helps me organize my thoughts should be off limits to discovery.

Some people seem to be better at it than others. I see a huge gulf in what people can do. Oddly there is a correlation between was a good engineer pre AI and can vibe code well.

But I see one odd thing. A subset of those who people would consider good or even amazing pre AI struggle. The best I can tell at this stage is because they lacked get int good results with unskilled workers in the past and just relied on their own skills to carry the project.

AI coders can do some amazing things. But at this stage you have to be careful about how you guide it down a path in the same way you did with junior engineers. I am not making a comparison to AI being junior, they by far can code better than most senior engineers, and have access to knowledge at lighting speed.

It does not happen overnight. But what happens is after they take control of the clinic or company they change the sales model to boost reoccurring revenue, this then allows the clinic or target company to take loans out. Because they look good on paper. The company then pays VC back when then pays bank back.

This can be done in about 6mo to 1 year process with some companies. The initial out of pocket expense is small and paid back very quickly.

I also forgot. Sometimes they will take the newly owned company and merge it. During that process they extract more money and load more debt onto the remaining entities, again making the VC money.

In some cases they can even get huge tax benefits by loading the company with debt which offsets the tax bill of the final entity.

When these transactions are done, within the span of a day multiple companies are created and merged and absolved.

There is little to no risk for the VC

This makes no sense. AI sex bots don’t need humans texting and role playing.

I don’t think whoever wrote this article understands what AI is.

Note the fist job of describing what was in the video seems like somebody building a AI dataset.

The VC lends (the money from the bank) which the vc borrowed, to the clinic.

They are a sort of middle man. It the clinic is on the hook to the bank and the Vc takes fist cut before playing the bank.

Eg. The vc only risked the company they were buying, and gets paid first.

I think this statement is misguided, and potentially comes from a lack of experience in getting AI coders to produce quality.

Proper engineering does not come about from the tools you use or how you use them. Proper engineering has always come from thought, and reasoning, it never was about the act of coding. It always was about the systems thinking and expressing the goals and desires that matched the requirements.

IDEs were never needed to properly engineer and in the days of AI will become increasingly less important.

Tools for planning, reviewing, and commenting on code are the future. The necessity to edit actual code is coming to an end.

The senate rejected the bill. They did not fail to do anything. The bill failed to get the approval of the senate.

But one thing we know. In the senate did not fail.

The wording here makes it seem like the senate wanted this but failed to get it.

So again the senate failing to do something the senate said they did not want to do is weird.

It comes down to some people in the senate wanted this, but they are not the senate.

Politicians have been treating a minority position as the institution’s will for some time. It’s our job to look past that and not be fooled even if you share the same minority position.

So true. To the point I have to maintain my own fork to make the command key my meta

I didn’t say right-wing policies are inherently anti-science. I said your contrast makes no sense. You’re blaming Western decline on xenophobia and far-right politics, but China has strong nationalism, social conservatism, demographic engineering, speech controls, and limited immigration. All things typically associated with the political tendencies you are criticizing.

So which is it?

If nationalism and social conservatism are corrosive to long-term success, then China shouldn’t be your example of strategic competence. If those traits aren’t inherently corrosive, then maybe "far-right politics" isn’t the explanatory variable you think it is.

You can’t simultaneously argue that right-wing xenophobia is sinking the West while praising a country that institutionalizes many of those same tendencies.

If your actual claim is about state capacity and science investment, then say that. But don’t smuggle in partisan framing as the cause of decline and then retreat to "pro-science funding" when the comparison falls apart.

Chinas political stance more closely resembles right-wing policies than left leaning ones.

All the xenophobic notions you are talking about china has in spades.

I am not saying China is not doing things right here will lead to your described outcome, what I am saying you conflation with western politics is completely out of this world, and is a excellent example of why the outcome you describe may be a reality for China.

Because companies want to make MORE money.

Your hypothetical company is now competing with another company who didn’t opposite, and now they get to market faster, fix bugs faster, add feature faster, and responding to changes in the industry faster. Which results in them making more, while your employ less company is just status quo.

Also. With regards to oil, the consumption of oil increases as it became cheaper. With AI we now have a chance to do projects that simply would have cost way too much to do 10 years ago.

I have found the following, but I suspect as AI gets better this will change.

1) those who where incompetent before still are, but AI hides it.

2) those who were competent before AI do vastly more with AI. They seem to apply it in away that simply overshadows what the incompetent are doing.

3) the incompetent seem to be fascinated with things like skills, pre prompts and, setting policies and guidelines, and workshops. The competent seem to need none of this, are not going to workshops, already have their own and simply are more productive.