This comment by gopalv from Hacker News:

If you manage 500+ people organization, most of the headaches with agents already exists with you – you set directions, ask people to go run fast in those directions, check in frequently and course correct on results without actually understanding those people do.

Those aren’t the deal breakers.

They entirely rely on the competence of the folks they hired and cross-match enforcers with the drivers they have – they deal with fallible people on both sides of that.

The fundamental difference is that the humans are good consequence predictors, have built up reputations they are not willing to trash, can say no to things and in general don’t want to go jail.

AI tools look like that, but don’t have any of the useful conflict which came for free with employing humans.

It also doesn’t have any useless conflict, but not all conflict between what I say and what someone is willing to do is bad conflict.

Brian Potter explaining how Helium is produced and where it is used.

Helium is the second lightest element in the periodic table (after hydrogen), and the second most common element in the universe (also after hydrogen). But while helium is very common on a cosmic scale, here on earth it’s not so easy to get. Because helium is so light, it rises to the very top of the atmosphere, where it eventually escapes into space. So essentially all helium used by modern civilization comes from underground.

Helium is produced via the radioactive decay of elements like uranium and thorium, and it collects in underground pockets of natural gas. This source of helium was first discovered in the US in 1903, when a natural gas well in Kansas produced a geyser of gas that refused to burn. Scientists at the University of Kansas eventually determined that this was due to the presence of helium. Like petroleum, helium has collected in these pockets over the course of millions of years, and thus (like petroleum) there’s a limited supply of underground helium that can be extracted. As with petroleum, people are often worried that we’re running out of it.

Because helium is a byproduct of natural gas extraction, and because only some natural gas fields have helium in appreciable quantities, a small number of countries are responsible for the world’s supply of helium. The US and Qatar together produce around 2/3rds of the world’s helium supply. Russia, Algeria, Canada, China, and Poland produce most of the remaining balance.

Much like the movie Surrogates starring Bruce Willis, Om Malik reflects on the idea of creating a digital version/twin of yourself to interact with your readers (or fans).

The more I think about it, the more I realize this is the ultimate expression of what began in the social media era, when media manipulation became the primary currency instead of authenticity. We all created curated, and often false, lifestyles on Instagram.

Social media gave us tools to edit our lives into a highlight reel. Photos of coffee, food, selfies from places you couldn’t afford last year, some pithy comment. It was all one directional. A movie about me, by me, for me to broadcast and you to watch. This is what led to the rise of influencer culture, where anything and everything was for sale. The self first became a gallery, then a reel. It was all passive, beautiful, controlled and fake.

We shared bumper sticker wisdom on Twitter. LinkedIn became a public square to hawk faux expertise. This popsci compression of complex thinking into shareable nuggets, designed for distribution and optimized for engagement, was the next step in the self becoming a product.

The pseudo-conversation twin is the crescendo. The self’s full immersion into illusion is now interactive. It answers questions. It gives the impression of encounter, of dialogue, of relationship. But it is still the same curated self with a conversational interface bolted on. It is as authentic as a Potemkin village. And with every step we have moved further from the actual person. The twin is not a rehearsal. It is the first act of abstraction of ourselves. Reid AI can do the job from a bunker in New Zealand.

[…]

The twin doesn’t just represent you. It restructures how others relate to you. The copy becomes the relationship. Send out the twin, and you have not freed yourself for deeper thinking. You have replaced the possibility of being surprised by another person with the certainty of your own archive.

While reading this post, I also learned about:

Bumper sticker wisdom

are short, punchy, and witty maxims, slogans, or philosophical snippets that are designed to fit on a car’s bumper sticker, but are oversimplified and miss the nuances of the argument.

Potemkin village

is a construction, literal or figurative, that provides a façade to a situation, to make people believe that the situation is better than it actually is.

Bryan Cantrill talking about how using LLMs for writing breaks a social contract.

[…] LLM-generated prose undermines a social contract of sorts: absent LLMs, it is presumed that of the reader and the writer, it is the writer that has undertaken the greater intellectual exertion. (That is, it is more work to write than to read!) For the reader, this is important: should they struggle with an idea, they can reasonably assume that the writer themselves understands it — and it is the least a reader can do to labor to make sense of it.

If, however, prose is LLM-generated, this social contract becomes ripped up: a reader cannot assume that the writer understands their ideas because they might not so much have read the product of the LLM that they tasked to write it. If one is lucky, these are LLM hallucinations: obviously wrong and quickly discarded. If one is unlucky, however, it will be a kind of LLM-induced cognitive dissonance: a puzzle in which pieces don’t fit because there is in fact no puzzle at all. This can leave a reader frustrated: why should they spend more time reading prose than the writer spent writing it?

Derek Sivers:

Forty years ago, a family moved from India to Canada, and raised their children with “Indian values”. When those children visited India last year, the locals laughed at their outdated beliefs. What their family had said were factswere just a perspective from 1980.

[…]

When someone speaks of a place, you have to ask, “When?” Geography is four-dimensional. You can’t know a place – only a place as it was at a time. Where is bound to when. Unless you are in a place right now, you can only speak of it in past-tense.

From the movie The Gods Must Be Crazy:

And here you find civilized man. Civilized man refused to adapt himself to his environment. Instead he adapted his environment to suit him. So he built cities, roads, vehicles, machinery. And he put up power lines to run his labour-saving devices. But he some how didn’t know when to stop. The more he improved his surroundings to make life easier the more complicated he made it. So now his children are sentenced to 10 to 15 years of school, just to learn how to survive in this complex and hazardous habitat they were born into. And civilized man, who refused to adapt to his surroundings now finds he has to adapt and re-adapt every hour of the day to his self-created environment.

This insightful post by David Oks on how Japanese companies do so many things. He cites example of Toto, which manufactures variety of bathroom fixtures, and how it has become a key supplier in the AI supply chain ecosystem.

Since 1988, in a once-obscure corner of the company called the “advanced ceramics division,” Toto has been producing a very particular component called the electrostatic chuck, or the “e-chuck.” The e-chuck is a sort of high-precision ceramic plate, about the size of a steering wheel, that uses electrostatic force to hold a silicon wafer perfectly flat and thermally stable while memory chips are etched into it with bombardments of plasma. Making these components is extraordinarily difficult, since the ceramic body needs to have near-zero particle generation and be polished to submicron flatness: and this means that there are only a few companies in the world that are capable of manufacturing e-chucks reliably. Almost all of them—Shinko Electric, NGK, Toto, Kyocera, Sumitomo Osaka Cement, Niterra—are based in Japan.

For most of its history, the advanced ceramics division was a rounding error on Toto’s balance sheet: the money maker, as it had been since the 1910s, was the toilet and bidet business. But we’re in a new era. Demand for AI is exploding, meaning that demand for the high-bandwidth memory that AI data centers require is exploding, meaning that demand for memory chips is exploding, meaning that demand for e-chucks is exploding. And so Toto’s advanced ceramics division is suddenly the company’s largest business, generating the majority of its operating profit. Toto’s leadership, suddenly awash in AI-driven revenue, announced that they would double down by investing hundreds of millions in expanded electrostatic chuck production: the toilet company had become, quite unexpectedly, a supplier to the semiconductor supply chain. 

The Toto story is a fun and interesting illustration of corporate diversification and how strange bets can pay off. But that type of diversification—a toilet company that also produces photocatalytic coating and high-precision components for semiconductors—isn’t really unique to Toto. Practically every company in Japan seems to do a thousand very different things.

Mitchell Hashimoto talking about how in the world of AI programming languages are fungible. He gives example of recent Bun rewrite in Rust.

On the interesting side is how fungible programming languages are nowadays. Programming languages used to be LOCK IN, and they’re increasingly not so. You think the Bun rewrite in Rust is good for Rust? Bun has shown they can be in probably any language they want in roughly a week or two. Rust is expendable. It’s useful until its not then it can be thrown out. That’s interesting!

This reminds me of how AI can empower developers to rewrite code without regret.

Deepak Shenoy’s thought provoking post on climbing the walls of worry:

The news is tiresome because it engulfs us in a sense of doom, while in reality we don’t see an impact. And the markets – they are now going up, both in India and the west. This sounds a little scary but often, when markets climb a wall of worry, you should sit up and give the market a little more credit for its moves.

[…]

In the long run, things do work out, but what does change is how you plan ahead. For example, one change for now is: the Rupee’s at 95. If you were planning your child’s college fees at an assumption of 40 lakh per year (Rs. 80 to a USD, and $50,000 USD per year), you might need to revise that to 50 lakh per year. If you have 15 years left, your monthly SIP would have to rise from Rs. 61,000 to Rs. 77,000 per month with this new information. (Assumptions: effective rise of 6% per year from now, blended return at 11% on investing)

At least this one is actionable. To make up for this higher SIP – if you needed to – you will have to perhaps need to rework your goals, and perhaps delay retirement, or change your spending patterns. These are useful reactions to this crisis, better than endless doomscrolling of meme videos involving lego characters.

[…]

The internet is designed to make you worry. Markets climb those walls often and surprise us on the upside. In life, one way to deal with worry is to climb those walls, not to let them be built around us. Enjoy the narrative, and stick with your game.

These two comments on Hacker News which talk about how difficult it is to impart your expertise by codifying it. It can only be taught by working along side your apprentice.

By hamstergene:

Because the most important parts of the expertise are coming from their internal “world model” and are inseparable from it.

An average unaware person believes that anything can be put in words and once the words are said, they mean to reader what the sayer meant, and the only difficulty could come from not knowing the words or mistaking ambiguities. The request to take a dev and “communicate” their expertise to another is based on this belief. And because this belief is wrong, the attempt to communicate expertise never fully succeeds.

Factual knowledge can be transferred via words well, that’s why there is always at least partial success at communicating expertise. But solidified interconnected world model of what all your knowledge adds up to, cannot. AI can blow you out of the water at knowing more facts, but it doesn’t yet utilize it in a way that allows surprisingly often having surprisingly correct insights into what more knowledge probably is. That mysterious ability to be right more often is coming out of “world model”, that is what “expertise” is. That part cannot be communicated, one can only help others acquire the same expertise.

Communicating expertise is a hint where to go and what to learn, the reader still needs to put effort to internalize it and they need to have the right project that provides the opportunity to learn what needs to be learnt. It is not an act of transfer.

By gooseyard:

By complete coincidence, yesterday I came across this link to an article Peter Naur wrote in 1985 (https://pages.cs.wisc.edu/~remzi/Naur.pdf) which I haven’t been able to stop thinking about.

I’ve been doing this for coming up on thirty years now, mostly at one large company, and I spent a significant number of hours every week fielding questions from people who are newer at it who are having trouble with one thing or another. Often I can tell immediately from the question that the root of the problem is that their world model (Naur would call it their Theory) is incomplete or distorted in some way that makes it difficult for them to reason about fixing the problem. Often they will complain that documentation is inadequate or missing, or that we don’t do it the way everyone else does, or whatever, and there’s almost always some truth to that.

The challenge then is to find a way to represent your own theory of whatever the thing is into some kind of symbolic representation, usually some combination of text and diagrams which, shown to a person of reasonable experience and intelligence, would conjure up a mental model in the reader which is similar to your own. In other words you want to install your theory into the mind of another person.

A theory of the type Naur describes can’t be transplanted directly, but I think my job as a senior developer is to draw upon my experience, whether it was in the lecture hall or on the job, to figure out a way of reproducing those theories. That’s one of the reasons why communication skills are so critical, but its not just that; a person also needs to experience this process of receiving a theory of operation from another person many times over to develop instincts about how to do it effectively. Then we have to refine those intuitions into repeatable processes, whether its writing documents, holding classes, etc.

This has become the most rewarding part of my work, and a large part of why I’m not eager to retire yet as long as I feel I’m performing this function in a meaningful way. I still have a great deal to learn about it, but I think that Naur’s conception of what is actually going on here makes it a lot more clear the role that senior engineers can play in the long term function of software companies if its something they enjoy doing.