Not really relevant to this article, which is about graduate students in research programs, who get a stipend and don't pay anything. Of course, low stipends are also a big detractor for potential students
Forget AI, Google/Microsoft/Amazon could all in theory have built a clone of Jira/Figma/<x> tool by now. But large companies lack the focus and commitment needed to build true competitors to these products, especially if it's not a big enough market to make a real difference to their bottom line.
Perhaps this will change soon if AI models reach the "army of geniuses in a datacenter" level, but current models are a far cry from just being able to clone Jira or Asana.
1. Companies can hire overseas. There's some cost to it in terms of added friction, but if wages rise enough in C1, then it's worth the friction to hire in C2 instead.
2. Workers also consume and invest, raising demand for other jobs. Employment is not a zero sum game, especially at the macro scale.
How is that different from the US? Immigrants also get booted here if they lose their job. They also pay social security, Medicare, and other taxes but usually don't get the benefits unless they stay here for long enough and get a green card.
The difference is the number. Workers on temporary visas make up ~1% of the labor force in the US. And a large chunk of them will eventually get citizenship or permanent residency and qualify for benefits later in life.
Countries like Singapore and all of the Middle East meanwhile rely on a revolving door of cheap immigrant labor. In the extreme cases like Qatar 95% of the working population are on short term visas. Most of these countries don't have a pathway to citizenship at all for this worker class. You could live there, work and pay taxes for 10 or 20 or 50 years, but the day you "retire" you need to pack up and leave.
The US also has a huge pool of undocumented immigrants who don't get any benefits, don't pay into the social security system, and can be paid below minimum wage (because officially they don't exist). Any time this labor supply is threatened, the construction and agriculture industries rise up (and probably sponsor all those massive protests you see in the news).
You're attributing way too much intent to what is the viewpoint of some random analyst at Goldman Sachs (who doesn't even control any purse strings). A year ago there was another big hullabaloo when a GS team wrote a long post about how AI companies would never make enough revenue.
well, Musk has been overpromising and under delivering for a decade (or more?), so it seems pretty clear this too is shithousery, albeit possibly ambitious.
But anyways, the order of causation is probably reversed. Cities with high density are forced to invest in good public transport by sheer public demand and pressure.
Mercedes' feature has been sunset. It only ever worked in good weather on a limited set of motorways, below a certain speed, and with a guide vehicle in front of it l.
Is there anything substantial in his list ("agents, subagents, their prompts, contexts, memory, modes, permissions, tools, plugins, skills, hooks, MCP, LSP, slash commands, workflows, IDE integrations") that Claude Code or Cursor don't already incorporate?
I empathize with his sense that if we could just provide the right context and development harness to an AI model, we could be *that* much more productive, but it might just be misplaced hope. Claude Code and Cursor are probably not that far from the current frontier for LLM development environments.
