mo_42

Did the invention of the steam engine and all other heavy machines make us physically weaker? I guess so. People working on (literal) heavy stuff don't need the strength they used to.

But now they move around even more heavy stuff with machines.

I think something similar might happen to our brains. Maybe we won't be able to work ourselfs through every detail of a mathematical proof, of a software program, or a treatsie on philosophy. But we'll abe able to accomplish intellectual work that only really smart poeple could accomplish. I think this is what counts: outcome.

I spent 15 minutes looking at the diagram in the article and tried to figure out how I can conclude whether it's a bubble.

I couldn't conclude it.

It's just a diagram that shows the economic relationship between companies. If they'd all merge into MegaAI, these flows would just be departments supporting each other on different AI projects.

It's not suitable to prove a bubble.

I think a bubble is nothing else than a sudden change in expected value. Currently, the market expects that AI is very valuable because of actual practical value. In this expectation there's also future improvements which might or might not come.

We might see a crash if we realize that this technology reached its limits. Then, we'll all look poorer on paper in the reverse way that we look richer on paper now than 12 months ago. However, I don't think anything serious will happen if such a crash would occur. It's not that people take loans to bet on these stocks.

(Even the 2008 housing bubble could be seen as a temporary market correction when looking at the long-term real estate prices. Housing is much more expensive today than on the peak of that bubble.)

> Back to the dashboard experiment: after you applied the Bonferroni correction you got... nothing.

I guess you got something: Users are not sensitive to these changes, or that any effect is too small to detect with your current sample size/test setup.

In a startup scenario, I'd quickly move on and possibly ship all developed options if good enough.

Also, running A/B tests might not be the most appropriate method in such a scenario. What about user-centric UX research methods?

I agree. Hamburger menus aren't any better than menu bars. It seems like an example where design has more importance than function.

My alternative to the menu bar would be a search bar that allowed me to search in a Google style everything related to that program: functions, features, shortcuts, and documentation.

File | Edit | View | etc. is not the right choice for every program.

Yes, this was also a concern when I started this approach. However, restricted time can also be a yard stick for accomplishing something in a short amount of time. But there are, of course, other factors that influence the success of such a method.

For some reason I tend to forget about task management apps. So whenever I got back to them, it was depressing to see all the unfinished tasks that I haven't touched.

My solution is extreme time boxing. Every Sunday, I sit down and time box the next week. Work and personal stuff goes into the same calendar. I've learned to keep enough slack to not get stressed out. I also know how much unplanned time I need to coordinate with co-workers.

It's kind of absurd that less freedom when to do things, gives me more happiness.

In the beginning I thought that this cannot work because sometimes you just need uninterrupted time to finish something. However, such uninterrupted long spans don't exist anyways for many people. There are stand-ups at work, you have appointments with some of your team members and at 5pm you need to pick up your kids.

I don't think one would put only the specification in Git. LLMs are not a reliable compiler.

Actual code is still the important part of a business. However, how this code is developed will drastically change (some people actually work already with Cursor etc.). Imagine: If you want a new feature, you update the spec., ask an LLM for the code and some tests, test the code personally and ship it.

I guess no one would hand over the control of committing and deployment to an AI. But for coding yes.

You implicitly assume that a good's price should be based on the amount of effort that was put in.

My impression is rather that the price of goods is based on how much people appreciate it. To me it better explains reality with the absurd prices for some stuff.

Lately, I've been thinking that LLMs will lift programming anyways to another level: the level of specification in natural language and some formal descriptions mixed in. LLMs will take care of transforming this into actual code. So not only users don't care about programming but also the developers. Switching the tech stack might become a matter of minutes.

I guess the standard answer would be a foundation. In some countries, there are minimum capital requirements for foundations but I don't think it's the case for the US. So some thousands of dollars should be enough to keep a website running forever and also hire web developers and accountants every now and then to maintain it.

The Programmer's Brain by Felienne Hermans

Humanity has bootstrapped itself out of a lot of BS over the centuries. There's a mechanism for discarding bad ideas. For example:

Badly-designed boats just don't return.

Ill-designed protection of cities means they'll be conquered.

Scientific ideas that do not corroborate, will be discarded.

etc.

Our current approach to AI doesn't have this mechanism. In the past, humanity just implemented ideas: a city was built according to some weird idea and lasted centuries. So the original idea would spread and be refined by further generations. I guess we need to bring such a mechanism into the loop.