Karrot_Kream

Better. I've implemented a system to block commenters that I don't like since I wrote that. You're about to go on that list, thanks.

> If you're willing to buy that will be possible, then my guess is that it will occur in the form of small scale startups and actual mavericks rather than someone trying to run an existing business who will simply be too risk adverse to go all in when the time comes. Some guy in his basement is more likely to leverage AI "properly" to build an actual "AI-native" engineering org because that person won't have much to lose.

FWIW I think the company writing this post is one of those small scale startups. But that being said, you're not the only one who thinks this. A decent amount of VCs and funds think that only smaller, newer companies have the potential to be truly AI native because there's too much organizational inertia in an existing business in keeping its existing human processes and so only a newer company can achieve the true "scaling potential" or using AI to scale without human labor.

This is a 25 eng startup. Anything can go wrong here. A hike in interest rates can lead to a down round causing the company to go into cost cutting mode, leading to a decrease in product velocity and prod incidents as infra is cut to the bone, in order to cope. Your top engineer can get sick and quit and your next in line isn't strong enough to keep the ship going.

I'm curious if you've ever worked at a startup, tried to invest in a startup, or considered purchasing a startup's product to know what it's like? The whole point is you're taking a risk trying something new and different. If you're just doing what a much bigger, established company is doing, you're fighting against an incumbent who already has much lower COGS than you.

Taking a bet on being AI-native as a startup is taking a bet that use of AI will result in lower COGS than the incumbent. As the old saying goes, "Nobody got fired for buying IBM", and yet Amazon was able to crack into that space by doing something novel. If Amazon was just IBM, why not buy IBM? The ultimate test of AI-native business models will be if these companies become the Amazon of today, or whether we'll write about them the way we wrote about "fifth generation computing" in Japan.

> It was the article that used metrics related to engineering velocity as evidence of success

Success for what? The article opened with: "Last week Will Larson (@Lethain ) asked how leaders are evaluating engineering managers for AI skills. My reply , a list of questions to think about, got a lot of bookmarks. More broadly, I've been thinking about how to build an AI-native engineering org for a while. Sharing some lessons from the last nine months of building at FurtherAI."

The opener is "how to build an AI-native engineering org" and the context is a company of roughly 22 engineers (from a reply.) Nothing here says "evidence of success"

> I don’t see how asking how this ties back to core business results is thinking about it at the wrong level.

In an company of 22 engineers, how would you make these measurements? Would you split your company into a velocity focused group and a quality focused group and make them compete? How? What would a customer motion look like? What would these groups share? This makes no sense. This is like asking a small company to A/B test teams that used a computer vs didn't use a computer.

A larger, more mature organization has the luxury of splitting business units into AI-native vs not-AI-native workflows and comparing COGS/business objectives against each other. I know of very large tech consulting services who did exactly this around the beginning of the cloud era to figure out which aspects of their business they wanted to place on clouds and which aspects they kept on-prem, and even then that was messy because part of the value of on-prem is the scale benefit you get by owning and operating your own DC. But no 22 person engineering team I saw A/B tested this out. Companies were founded either with a cloud-first philosophy or an on-prem philosophy.

You're thinking about this at the wrong level. This org has made the decision to be AI-native. They aren't A/B testing being AI-native vs not being AI-native. That's the kind of thing "the market" does; if a company's markup is higher than another's it can attract more investment or its equity can trade for higher pricing on public markets.

I don't think it makes sense to A/B test "AI-native" vs other regimes of development unless you are a large, decentralized company like an F5 company or a Big Tech. How will a team of 25 (the size of the company if you read the thread) have enough output to even A/B test the difference?

Back when I managed teams that dealt with API traffic at a unicorn, this wasn't the case. We'd ban a /32 and several times customers would start reaching out to our support portal (which ran behind different ingress rules) asking why they couldn't use the site a couple weeks later.

I've never worked on the ISP side so there's no doubt that there is a process at the competent ones, but my guess is most users do not have a competent one.

Until a service's WAF catches your /32 because your ISP had previously handed it out to a spammer.

There's more that's been written about configuring/protecting IPv4 networks and if you learn about network security from a mentor or from coworkers at a job, rather than reading books/the internet/LLMs, you're more likely to learn about IPv4 security.

But if you've ever had to deal with endpoint security, if you're just doing static rule based blocking/throttling, /32 or /24 blocking is often your best option. Thanks to CGNAT this often means having a pretty large impact since an ISP's residential customer might end up getting randomly assigned a "bad" address and the cooldown for these rules is often months long or more.

In IPv6 land, you can just block a /128 or even a /64 and rarely hit anyone else in the crossfire.

Almost all of my tech worker friends use Instagram. It's almost universally used. I never talk about it because anything positive about any Meta property on this site gets downvoted. It's been like this for years and only gotten worse over time.

The "average worker" ends up getting more wealthy because younger, newer employees who grow up native to the new technology often capture its upsides at the expense of older workers who were unable to. The Rust Belt is a great example of this because most kids ended up migrating out to cities for work while their parents or the less successful ones ended up stuck.

There's a lot of questions right now.

1. Will there be a net-new creation of jobs? Is positive-sum knowledge work a real thing, or have we run out of new jobs to create?

2. How quickly will workers transition to an AI version of their jobs?

3. Will AI even succeed in a broad way across knowledge work or will the frontier of AI remain jagged and only impact some jobs (coding) while leaving others alone?

4. For workers left behind in this transition, what will their lives be like? We know from looking at previous technology transitions (industrial revolution, factory automation, computer revolution, now maybe AI revolution) that many workers really do end up in bad places. It's perfectly reasonable to demand that in today's world in our advanced societies that even if those workers are unable to adapt that they are able to lead lives with dignity.

There's a lot of interesting conversations and investigations to be had but my biggest fear is just that nobody is really willing to listen to the other side with empathy. This entire conversation thread is just people snipping at each other, hitting the vote buttons based on where they want to steer their favorite opinion. If you want to do social and economic science in this space but people are so polarized, the work will be thwarted. In general offline spaces are less polarized (not to be mistaken for pro or anti AI disruption) than online spaces, but my fear is that we continue to polarize, making understanding the fabric of our social change challenging and letting down everyone in the process.

FWIW it's quite easy to farm karma to get to the downvote threshold. If you go to any of the energetic political HN threads, you just need to submit an enthusiastic comment that is pro the dominant position and you'll get tens of upvotes quite quickly. Do that for a week and you'll be ready to downvote. Before HN had LLM detection I had an experiment with an LLM doing that (though I approved everything it wrote by hand) and farmed karma very quickly. I stopped because I felt quite gross about it, but realize it's probably trivial to do now.

The problem isn't really the site, it's the people. People like smashing the up and down buttons on things they agree with and unfortunately a comment's score affects where it shows up on the page.

Elisp is homoiconic and has a strong culture of REPL development, but really the thing that makes elisp so nice is that it has decades of use to iterate on an editor. There's an attempt to do this with Common Lisp that's quite cool, called Lem, but the sheer amount of person-years that have gone into making emacs and elisp a conjoined system makes it a pleasure to use and iterate on. Lem, in comparison, is building up all the UX associated with a "live programming environment" that just comes out of the box with elisp (though I, personally, prefer Common Lisp as a language/environment.)

Pre-LLM I used to spend the occasional afternoon at work when I was a bit demotivated just adding new features to my emacs or fixing small papercuts in the environment. Now I largely have the LLM work on it for me, though I separate out LLM code from my own by loading them separately in my config.

I don't think this is true for most people on the big issues but do think it's true for a lot of small issues. Reddit (and HN) lead to a lot of pageant show dynamics where the people with the time to hit the buttons decide what content to boost. Small Discord communities are free from that.

I don't know how much they can do. I don't want to speak for the mods, but most of the problems on this site come from upvotes and downvotes. I guess some cheap things you can do are increase the karma threshold required to downvote and apply a smoothing function to upvotes (like quadratic voting for vote scores, aka n votes on a comment bumps the score up by sqrt(n).)

But ultimately a site moderated by up and downvotes that wants to keep a relatively light hand on moderation is going to end up like what HN is today. Changing the voting structure on the site or the moderation POV on the site would be a radical change and could change the entire site's culture drastically.