> The Codex sprint was probably the hardest I've worked in nearly a decade. Most nights were up until 11 or midnight. Waking up to a newborn at 5:30 every morning. Heading to the office again at 7a. Working most weekends.

There's so much compression / time-dilation in the industry: large projects are pushed out and released in weeks; careers are made in months.

Worried about how sustainable this is for its people, given the risk of burnout.

I was active in the Python community in the 200x timeframe, and I daresay the common consensus is that language didn't matter and a sufficiently smart compiler/JIT/whatever would eventually make dynamic scripting languages as fast as C, so there was no reason to learn static languages rather than just waiting for this to happen.

It was not universal. But it was very common and at least plausibly a majority view, so this idea wasn't just some tiny minority view either.

I consider this idea falsified now, pending someone actually coming up with a JIT/compiler/whatever that achieves this goal. We've poured millions upon millions of dollars into the task and the scripting languages still are not as fast as C or static languages in general. These millions were not wasted; there were real speedups worth having, even if they are somewhat hard on RAM. But they have clearly plateaued well below "C speed" and there is currently no realistic chance of that happening anytime soon.

Some people still have not noticed that the idea has been falsified and I even occasionally run into someone who thinks Javascript actually is as fast as C in general usage. But it's not and it's not going to be.

Source?

Awesome, this literally could not be better for American tech workers.

It says something that he still believes he has "missionaries" after betraying all the core principles that OpenAI was founded on. What exactly is their mission now other than generating big $?

I actually take some minor issue with OP's definition of an agent. IMO an agent isn't just a LLM on a loop.

IMO the defining feature of an agent is that the LLM's behavior is being constrained or steered by some other logical component. Some of these things are deterministic while others are also ML-powered (including LLMs).

Which is to say, the LLM is being programmed in some way.

For example, prompting the LLM to build and run tests after code edits is a great way to get better performance out of it. But the idea is that you're designing a system where a deterministic layer (your tests) is nudging the LLM to do more useful things.

Likewise many "agentic reasoning" systems deliberately force the LLM to write out a plan before execution. Sometimes these plans can even be validated deterministically, and the LLM forced to re-gen if plan is no good.

The idea that the LLM is feeding itself isn't inaccurate, but misses IMO the defining way these systems are useful: they're being intentionally guided along the way by various other components that oversee the LLM's behavior.

Old Hindu philosphies have a similar split.

https://en.m.wikipedia.org/wiki/%C4%80%C5%9Brama_(stage)

0-25y grow and study

25-50y develop your household, your family, your community and gain wealth (non-extractive, provide value).

50y-75y hand over all worldly things to the next generation, advise, teach and help those around you. Focus on your spiritual enlightenment.

75y- renounce the world and disappear into the forest as a monk / hermit.