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i'm not sure you fully read my comment.

my example posted is an example of how business interests are relevant to how livable the planet is for humans.

and then my quote is almost word for word what they said in the article.

their quote: "It seems the regulation in New Mexico has had an impact without hurting business"

my paraphrase: "yeah it seems like New Mexico doin real good with more laws"

They need to provide much, much much more proof because as regulation can have net negative affect then the burden is on them.

> double the amount of the gas than in New Mexico, per unit of production, since 2019.

when we look at data at scale, we use p99 metrics to get more insight into the average. because this article, i'm assuming, is just using average, the metric here does not have enough information. There could be just one incident in texas over 4 year period that affects the average per unit of production.

> Despite increasing its own oil production in recent years, New Mexico has no site with repeated methane leaks, unlike in Texas,

Why not deep dive into root cause of a few of these abusers? Blameless post mortem to assess what must be changed with very specific examples of issues.

Are we wrong to request a higher bar for journalism / research from Kayrros?

My conclusion on hackernews being "pro-regulation" is based on observance that posts discussing the downside of regulation are often downvoted.

I agree with what you said. Knowing that repealing regulation is much less frequent than producing new regulation -- we should assume all new regulation is high risk, since its' impact is known to have tradeoffs, is to some degree created from perverse incentives and minority interests, and once in place is immutable. Regulation can be good and it can be bad.

So if we know that regulation carries high risk, we need to be very apprehensive to anyone calling for more regulation such as this article via "https://www.kayrros.com/". We don't know who they are, what they want, and what their suggested change in policy affects in net to humanity over time.

I guess what I want is for companies like "https://www.kayrros.com/" to be held to a higher bar and be more responsible for the outcome of their research and conclusions.

I know the hackernews crowd is very pro-regulation, so before downvoting please consider responding so we can have a discussion and share experience together.

"It seems the regulation in New Mexico has had an impact without hurting business"

Assuming that oil has some net affect on humanity -- pros and cons. Then we need to consider the net affect of oil produced by texas on humanity, and consider how that net affect is changed with more regulation.

Simply saying "yeah it seems like New Mexico doin real good with more laws" is extremely dangerous, because most regulation DOES harm and destroy market affects and competitive businesses. The authors on the study here should AT LEAST report with due diligence on this before requesting for increased regulation and attempting to sway public opinion -- potentially having a net NEGATIVE affect on humanity.

One possible example of not considering the net negative affect of regulation, is, for example, if there are many competing energy companies in texas, and there is a consumer demand for more responsible operations, then those competing energy companies are forcing each other to tighten their operations wrt environmental impact. However, if regulation destroys small producers and benefits big corporations, then we would see LESS competition and LESS Priority from companies to tighten their operations, negatively affecting the environment.

in addition there is a scaling factor. it's easy to control mistakes when you have 1 well. hard to control mistakes when you have 10,000,000 wells. thus the regulation has to be mapped appropriately.

also, I'd be interested in seeing p90, p99, etc. to see if outliers affect the average that is reported -- because as texas probably has larger 100x production, average is exposed to more large incidents.

i would be MOST interested to compare against other similar "sovereign entity" with comparable production scale and comparable challenges e.g. geography and infra.

the US has a huge environmental benefit in producing oil vs entity's like China, Saudi Arabia, because as a transparent democracy we are able to hold our producers accountable to regulation where offshore producers have no transparency and accountability.

by no means is go/java/rust/c++ a silver bullet. it is a way to raise the bar for debugging, reliability, support. it is more effective than bundling python with 5 other type bandaids. in the medium/long term, lets guess at 2 KLoC or >3 person team, these typed langs will result in faster feature development and lower issues in production.

its comfortable, easy, appealing in the short term. just like why people overeat their junk food.

there's this common idea in management that new grads, SREs, "less experienced devs", can jump in and contribute. it's a falacy because the code becomes unmaintainable without a large investment (more unittests, refactoring the "buggy" code blocks with mypy type annotations, some SME who continues fixing prod bugs). a Python developer will shove their head in the sand with repl'ing, testing after deploy, and settle with this dev/ex while being completely unaware of the benefits of compiler errors and warnings.

Python has the same level of complexity as another language but you'll only see all of that dirty baggage in production as runtime exceptions.

Yep! I think all of those repos will either proverbially die a hero or live long enough to see themselves as a villain.

And thats because of the fundamental tradeoff of dynamic typing vs static typing. That part no one can disagree on.

The only disagreeable part I believe I'm saying is where does the dynamic typing scale limit happen. As a polyglot developer, working a lot with junior developers, I can say that dynamic typing hits a scale limit of feature velocity / production support / cost much faster than the general folk are aware of.

yup! along the dimensions of feature velocity and developer experience with regard to cost.

of course python/ruby/javascript have succeed in bringing value to the world in general -- but in this thread we're focusing on production reliability, debugging, refactoring.

as we see, dropbox is proud to admit that they hired Mypy core developers and fund the project, but guess how much they spent on the mistake of using python?

twitter, famously an advocate for Ruby, spent an ungodly amount of engineering to work around ruby, hit a wall, and switched to JVM.

Just the fact that mypy and typescript exist and have exploded in adoption is proof that eng. teams very quickly hit a sand pit when using dynamic typed languages. Mypy being funded by dropbox, Typescript funded by microsoft, shows the level of investment needed to support these dynamic languages.

I'm rejecting all dynamically typed languages *for production*. Where production means anything that needs to exist for a long time and is supported by a team. A litmus test for whether an app is production is if you actually need mypy, pyright, jedi, to effectively work on the repo.

Python is great for single developer experience and going fast as a single developer. I use it every day, willingly, in jupyter notebooks. But at scale there are no success stories. You are zoomed in on the present success of "engineering miracles" and ignoring the big picture that the application would have moved faster if they had the foresight to choose a typed language.

Hence, why i'm saying be warned on following the path of mypy+black+pyright+ruff+etc., since you will be doomed to patching on top of a fundamental flaw of the language.

I highly recommend to avoid Python for production apps especially if it is your free will (and not a matter of refactoring or rewriting existing mistakes).

It doesn't take an expert to notice that enforced types make a language more reliable in production, easier to debug, and faster to refactor.

You should be horrified by Dropbox's blog post on python in production: https://dropbox.tech/application/our-journey-to-type-checkin.... because this problem only existed and required $Ms of dollars to fix (even hiring the core team behind Mypy) because Python is being used instead of a typed language.

I have 90 PRs to Mypy configured repos this year, across 10+ python repos which are a mix of services and background jobs. All of them have some mix of pyright/jedi+ruff+black. I have implemented these tools either via CI or in my ide like experience in NVim.

TLDR; BE WARNED. this basket of bandaids is NOT a replacement for a strongly typed language. I would NOT recommend Python to teams or for services. No amount of mypy, pydantic, pyright, ruff, black, can convert python into a production language. This collection of bandaids is complex to maintain, upgrade, standardize, and has infinite edge cases where type annotation errors are just wrong.

The worst part about this basket is that you get all of the above features for free and are REQUIRED with go via gopls and gofmt. Gopls "is the official Go language server developed by the Go team." good luck achieving parity of this in python.

If you implement a service/app/anything production, use anything but a dynamically typed language like python.

Speaking as a current engineer at LinkedIn,

Big Tech companies will often conflate micro service with large distributed system.

These services are by no means at all micro.

Link?

Career progress means that Principal Engineers don't have certs -- does that add any value to determine whether certs have value? I'd say Principal Engineers are typically the ones designing the courses and have no use for displaying their qualifications.

No I think Zuckerbergs words should be read at face value.

Managers with small amount of reports will be converted to ICs and strong managers will be given more reports. The org will be more lean and will have less overhead per manager of converting work between layers.

I’m summarizing above but in the article are specific goals to address this and I didn’t pick up on any signs that employees should overwork themselves.

Arguments ad hominem are inappropriate for hackernews. Let’s leave this type of argument to Reddit or blind.

I understand your perspective though. layoff announcements trigger an emotional response esp. in an uncertain economic condition.

To answer the question, I think it’s worth explaining my perspective first. My company did “hidden layoffs” where an entire org was cut without any leadership announcement. Everyone freaked out, and we got no response from company. We found out about increased PIP quotas from blind. We have a mountain of technical debt hindering developer experience with no priority to address it.

Zuckerberg in this article, is the exact opposite of the horrible leadership that I have dealt with on my job. This is why I feel inspired to see specific reasons for restructuring, with multi month transparent plans, and pre-determined goals. When execs preach of transparency, point them to this article from Zuck which is entirely public. This content shows a proactive culture, and is so so refreshing when my experience has been as an employee of reactive leadership.

Definitely agree. I’be never read a post from CEO level explaining very specific reasons and goals for their actions.

I’m betting on Zuck here, and wish I could get this same level of specificity at my company.

Wow, so much negativity towards this announcement. This reaction is genuinely surprising because I found this post both inspirational and insightful. I hope there are others who feel the same way!

Maybe we can start a discussion on the content rather than our emotions from the headline?

Some of the best parts here:

> Today many of our managers have only a few direct reports. That made sense to optimize for ramping up new managers and maintaining buffer capacity when we were growing our organization faster, but now that we don’t expect to grow headcount as quickly, it makes more sense to fully utilize each manager’s capacity and defragment layers as much as possible.

> A leaner org will execute its highest priorities faster.

> we’re focusing on returning to a more optimal ratio of engineers to other roles.

> I think we should prepare ourselves for the possibility that this new economic reality will continue for many years. Higher interest rates lead to the economy running leaner, more geopolitical instability leads to more volatility, and increased regulation leads to slower growth and increased costs of innovation.

Thank god, a single source of good news is better than none. Does anyone have an aggregate view of the LCR / NSFR metrics across U.S. banks? I'd love to see the risk trend here at a wider scale than single bank disclosures like this one.

Why? Because I'm really nervous that SVB was in no unique situation -- after all VCs / Startups share a lot of low confidence and low cash traits in common with other investors.

How can I convince someone to try this, if they are comparing this solution with dbt? Can only pick one :)

Giving up is a great strategy, then we can let the market self regulate -- keep in mind that Tik Tok has to compete viciously with Facebook on who can design a more trusted platform :) In the end, we all win if we just let things play out.

UK minimum wage takes into account the current supply of labor and many layers of politics / economic theory. This is not comparable to the cost of labor wrt supply in ancient Maori culture.

And disregarding the fundamental error in comparison, the currency needs to be converted to the present Easter Island conversion rate -- does that even exist?

Additionally, total cost is probably not the bottleneck. These were allegedly hunter gatherer's, so TIME was more precious than cost because current theory is hunter/gatherer's didn't have spare time to spend on statues until agriculture.

Inorganic materials can't be dated using radiocarbon analysis and genetics don't account for civilization collapses.

After all, I'm in America with 0 percent of my genes attributed to Native American.

How was this converted from WARN public records into airtable? I'm curious if I can start using it for this purpose.

Government intervention is heavy handed and will cause unintended side affects with 100% certainty.

What should happen is for: 1) employees to choose to not join companies with contracts that they don't agree with 2) employers offer better incentive to not leave for roles at risk to poaching e.g. RSUs.

A natural market response to bad company policy is always preferred to government mandates.

The importance is that every free and democratic nation in the world has its’ policies influenced by the loudest voices on Twitter. So if Twitter amplifies an idea it becomes reality.

This opinion is ironic because this is exactly what the author intended to describe -- the typo IS hard to find.

The "Hello, World" example is nothing more than JSON, showing a string repeated 3 times. On the third time, "bill" is misspelled with "blil". The next tab shows how Dhall uses a variable definition to prevent this type of error.

I absolutely loved using this tool to generate many instances of Datadog resources in terraform json. Not only did it simplify a nasty mess of dynamic typed and schema-less bash/python/mako, it taught me a lot of functional programming paradigms along the way.

Whether it’s bank balances or pitchforks, the result is a conflict. Whether both parties are able to delegate judgement to a higher power determines the type of resolution. In the case where parties recognize a higher power it can be resolved without true violence (bloodshed)

This can be summarized as appealing to a higher power — your example is the courts, an alternative is the public reputation / free market. Without a 3rd party institution to appeal to, the parties must reconcile between themselves in a conflict e.g. violence. Same principle applies often in macro/micro contexts.