rekrsiv

Out of curiosity, was that before or after LLM agents?

Oh right, I keep forgetting about those useful-but-historically-mentally-draining-to-update sources of truth. This might be extremely useful when paired with an agent.

My theory is that most problem solvers are bad at solving problems, and most managers are bad at managing, and it doesn't matter how evolution created them: They'll make mistakes, they'll have finite time and energy, a finite context window, they'll lie and internally rewrite their own internal narratives as needed, and forget things, and drop balls, and they'll go in circles trying to find a bug they created but are too close to be able to see, and they're going to need a lot of external tooling to get through the day without forgetting anything, and constant reminders from others to get shit done. And this dynamic fundamentally creates peaks and valleys in productivity.

Wait, were we talking about humans or AI?

...

Everyone seems to be assuming either the humans or the AI has to be special. What if neither are?

No, AI wasn't supposed to solve all that drudgery. The hypothesized AI singularity would, but an ordinary AI agent running an LLM is just a problem solving automaton with no will of its own, just like a fleshy brain solving computer problems is just a code monkey.

Yet another statistically misleading headline.

Time is finite and regression testing always gets punted to the back of the line when humans are excited. This simply reveals a staggering level of humanity.

The endgame in programming is reducing complexity before the codebase becomes impossible to reason about. This is not a solved problem, and most codebases the LLMs were trained on are either just before that phase transition or well past it.

Complexity is not just a matter of reducing the complexity of the code, it's also a matter of reducing the complexity of the problem. A programmer can do the former alone with the code, but the latter can only be done during a frank discussion with stakeholders.

A vibe coder using an LLM to generate complexity will not be able to tell which complexity to get rid of, and we don't have enough training data of well-curated complexity for LLMs to figure it out yet.

I agree with everything you said except that the US is able to stop it. Think about it: Wouldn't Israel simply use these same tools in the US to install a puppet president they can easily manipulate?

Can we even prove it hasn't already happened?

A bribe in a low trust society is not the same as a bribe in a high trust society.

In this context, a bribe is irrelevant compared to the act of election interference by a foreign actor.

Quick question: Could they also be manipulating this message board's voting?

You are correct. Robustness requires a system that is working within it's tolerance margin, and stressing that inevitably leads to failure. A fault-tolerant system in this case would require a large amount of redundant humans. Unfortunately, the capitalist mindset prevents accepting any amount of "waste" as tolerable, which makes a robust system impossible to implement over time. Every system touched by a capitalist optimizer will eventually fail.

The idea that waste must be reduced is killing society, and this mindset must be addressed first before any other safety-critical system can be made reliable again.

I am alarmed at the high number of supposed engineers on this thread that are seemingly unaware of how safety-critical systems work. Literally every other piece of this system has redundancy built into it. Robustness is never optional in a scenario involving human safety.

When did this lunacy become an arguable position?

Can a single human being reliably and robustly maintain a safety-critical system alone under any circumstances, ever?

Ever?

A terminal still offers a more composable interface than a GUI. Analog feedback is still a concern for high level pilots. You are confusing power tools with entry-level instruments.