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The OP implicitly raises the question of why does "productivity" exist. I've been giving that some thought lately, and the hypothesis I arrived at was that of diminishing suffering.

Many types of performance optimization work, including "programmer productivity" are really the engineer's getaway from having to contend with the ambiguity of the problem domain, the politics, the vagueness, the risk of failure and other kinds of suffering.

Alas, solving a problem coming from the world requires confronting the world - a couple of examples are the tedium of mentally working through a user workflow, getting somebody else to cooperate by articulating and proposing a joint strategy and more.

I do not believe in pain for pain's sake, but good delivery has an inherent quality of athleticism, and one cannot be an athlete without accepting that training for the track means proficiency at managing pain - and at the track rather than elsewhere.

I wonder what is the contextualization of the OP's preference of the "Palantir as a data/power broker" narrative to that of "Palantir as a highly profitable staffing agency".

Re the "Manhattan project in 1944" argument - I am very cautious about the "modulo engineering scaling" carve-out -- unlike the uranium manufacturing pipeline of World War 2, that involved massively scaling up a known process, on the face of it there's no uncontroversial process/architecture to scale up in this case.

On the face of it, even relatively "point-target" goals of this kind could take many decades if at all; GaN for blue diodes come in mind as an example of a field that was stuck for a generation -- until it wasn't.

Touché! That's a good one.

Is the question at hand about balancing local building authorization with the government's intent to encourage a specific kind of national infrastructure businesses?

This seems to be supported by this quote:

> Putting arbitrary deadlines on state, local, and Tribal governments to start and finish complicated permit reviews...

I'm not an American but I am alarmed at the recent tendency for bad-faith rule making. However - the above sounds in reasonably good faith - is that indeed the case or am I missing some angle?

There's correlation all right, but is there causation?

A lot of folks I know regard mechanical watches as a type of jewelry, a high value item that's not intended for the everyday.

I concur that that popularity of mechanical watches is on the rise, but having a cool mechanical piece on in the evening does not preclude having a digital watch at all other times.

I find merit with the core point as well the delivery.

I wish it was more commonly accepted that choosing not to act is effectively a stand against one's own value system in favor of the value systems of those who do act.

I think Python's centrality is a consequence of its original purpose as a language intended for instruction.

Yeah, some of its design decisions required immense cost and time to overcome to make for viable production solutions. However as it turns out, however suboptimal it is a language, this is quite made up by the presence of a huge workforce that's decently qualified to wield it.

I came to regard YAML as a kind of a syntactic HFC syrup, a bearable idea that was taken too far.

Alas, YAML is just about everywhere, so the chances for a replacement that'll be both better behaved and as ubiquitous are unfortunately slim.

To the extent a random person's evidence on the Internet amounts to proof:

From people at Facebook circa 2018, I know that end user privacy was addressed at multiple checkpoints -- onboarding, the UI of all systems that could theoretically access PII, war stories about senior people being fired due to them marginally misunderstanding the policy, etc.

Note that these friends did not belong to WhatsApp, which was at that time a rather separate suborg.

TL;DR: is the described business viable?

I can see how a tech-centric person would see the described business as viable, but putting on my founder hat, I realize that it faces enormous risks:

- Any competitor could build the same product with less janky UX; users tend to hate even unavoidable usability issues.

- There's no compliance strategy even remotely possible in the described scenario.

- If a capital investment becomes necessary for business scaling, I cannot imagine this organization passing even a perfunctory level of due diligence.

Would be happy to hear out if that makes sense.

I'd like to encourage you consider the following two perspectives --

1. A senior Google leader telling the shareholders "we've asked 1% of our engineers, that's 270 people, costing $80M/year, to work on services that produce no revenue whatsoever." I don't think it would pass that well.

2. A Google middle manager trying to figure out if an engineer working exclusively on non-revenue projects is actually being useful or otherwise; this is made more complex by about 30% of the workforce trying to go for the rest and vest option provided by these projects.

Proper disclosure: I'm not a US resident, and I'm deeply alarmed by the de facto defunding going on right now.

Furthermore, I concur with the piece that a proper investment in the said fields would further the common good.

However, take objection with equating investment with investment in the way specifically done up until now.

The article opens with longevity; the Alzheimer amyloid hypothesis, which served as a bandwagon for low impact, perhaps even bad faith research, whole syphoning out billions of public spending and blocking out alternate research pathways.

Many of the other domains mentioned exhibit similar dynamics. To my ears, it makes little sense to champion further spending without exploring the reform that needs to be carried out to align that spending with the various notions of public good.

To reiterate, I abhor the populist choice of dismantling everything and putting cronies to feed off the rest. I'd be looking forward for a way forward to make change, because some change is due.

Hey, I've been developing professionally with Python for 20 years, so wanted to weigh in:

Decent threading is awesome news, but it only affects a small minority of use cases. Threads are only strictly necessary when it's prohibitive to message pass. The Python ecosystem these days includes a playbook solution for literally any such case. Considering the multiple major pitfalls of threads (i.e., locking), they are likely to become a thing useful only in specific libraries/domains and not as a general.

Additionally, with all my love to vanilla Python, anyone who needs to squeeze the juice out of their CPU (which is actually memory bandwidth) has a plenty of other tools -- off the shelf libraries written in native code. (Honorable mention to Pypy, numba and such).

Finally, the one dramatic performance innovation in Python has been async programming - I warmly encourage everyone not familiar with it to consider taking a look.

Thank you, that's a well stated and thorough critique.

A lot of your reaction is towards the notion of dramatic impact. Note that I tend to distinguish between an "intellectually capable" researcher and a "right stuff" researcher, which involves the ability to manage risks in self-led multi-year high-risk high-impact programs.

My icons are Katalin Karikó and James P. Allison, who are not necessarily the brightest people of their fields, and subpar at politics, but are actually very good at making impact (duh).

Circling back to the original thesis, setting up a Bell Labs necessitates spotting out the Karikós and Allisons out of a very large flock of (at best) diligent followers of current academic fashions or (worse) popularity contest winners, and I reckon that's not practically possible today.