HN user
I agree with the point about dogmatism, but I have so many other issues with this piece.
I mean... how do you even make the comparison between "A Handbook of Agile Software Craftsmanship" and "History of Hispanic Colonialism”!?
I got downvoted for asking a related question recently, but I also don't think people really understood what I was asking - I'm not trying to anthropomorphise LLMs to that extent.
Basically, if you tell a model "You're an absolute moron, of course that's wrong!", will it give better or worse results? How much of that response will it absorb into its persona (like some humans tend to do)? Will it try to give "safer" responses to avoid negative feedback? How much of the associated behavior can be attributed to RLHF (e.g. like the sycophantic nature of LLMs)? How much can be attributed to training data?
Obviously this will vary by model and training, but I'm trying to get a general understanding.
I recall seeing related outcomes in some of Anthropic's studies, but I'm not sure how much of this particular aspect was studied.
I've often wondered if LLMs can suffer from psychological abuse in symptomatic ways. Not literally of course, but for example, if you berate the LLM by calling it stupid, or useless, does that modify its behaviour negatively? Part of me think it does, but I don't really have any evidence for this. Maybe a fun weekend research topic.
It's also one of my major issues I have with how this is being introduced into many enterprises, including the company I work for:
"Here's AI. Figure out how we can make money from it. We're adding it to your performance reviews"
Basically, here's a solution. Find problems for it.
"Conceptual integrity" is something I always try to adhere to when I design and build systems. I also use it also a bit of an indicator when gauging someone's experience. For example, mid-level devs will often try to introduce some form of "optimisation" somewhere in the codebase that results in the codeflow deviating from existing patterns. More often than not I will reject the PR, or the idea. For me, it's better than all flows follow similar paths. It makes it easier to reason and communicate ideas about, modularise and/or form logical groupings etc etc.
This is also why one of my instructions to coding agents is that they adhere to established coding and testing patterns, even where they appear to be sub-optimal.
What was the "pattern" before this in these fields?
What is the current pattern in other industries?
Does the pattern exist elsewhere in the world?
Venting is important.
Of course. But you shouldn't run retros that are focused on it.
I personally have never worked in a team where Agile (the concept) has failed. But I've also seen it fail all around me. Especially when it's mandated without buy-in. Or when people just don't "get it".
e.g.
- 45 minute "standups" (!?)
- PI "planning" that consisting of deadlines and glorified multiplayer MS Paint
- Rigid adherence to ceremonies or processes that add zero value
- Retros that focus on complaints and venting with no actionable outcomes
- etc etc
Every time I've introduced Agile to a team or project that was new to it I was always met with skepticism. But 6 months down the line noone on the team/project wanted to go back to the "old" way of working. I don't even really care about any text book definitions. These are the only things we try to stick to:
- Short, daily standups
- Planning based on risk reduction
- Estimates based on complexity (ties in with risk reduction)
- Actionable retro items
- User demos every sprint (makes it easier to pivot - users rarely know what they want)
The only person who seems to claim that Dyson Spheres were a "joke" is Angela Collier and people quoting her. I've seen no other source for this claim.
The concept of "Dyson spheres" was a joke by Freeman Dyson. It was never meant to be taken seriously. There's a clip about this floating around somewhere in which he finds it funny that the thing he's most well-known for was not even a serious paper. Dr. Angela Collier did a video about it.
Probably at least slightly misleading, just reading the names of some of the countries in the list (I am from South Africa).
Just because a country generates 100% of its energy from renewables, it doesn't mean that its enough to power the entire or even majority of the country. Case in point: DRC. I believe only half of the population has access to electricity. It's been a while since I've looked into continental stats, but a quick Google search suggests the situation hasn't changed that much in the last few years.
It wasn’t even good to users
I may be out of the loop, but how was Bitwarden not "good" to users? Does this relate to the recent price increase?
Too little, too late. In fact, in this post they seem to be committing to keeping it as bad (or even making it even worse) for my use case.
I've used Windows since 3.1. Win 11 was the straw that broke the camel's back. I moved to CachyOS a few months ago and I honestly can't find a reason to switch back.
Can someone explain why LLM's write like this when most humans don't?
Was he entirely wrong?
Yes. I mean... of course he was?. Firstly, I had already gone through this process with multiple LLMs, from various perspectives, including using Deep Research models to find out if any other businesses faced similar issues, and/or if products existed that could help with this. That lead me down a rabbit hole of data science products related to regulatory reporting of a completely different nature which was effectively useless. tl;dr: Virtually all LLMs - after understanding the context - recommended us doing thing we had already been urging the business to do - hire a Technical BA with experience in this field. And yes, that's what we ended up doing.
Now, give you some ideas about why his idea was obviously absurd:
- He had never seen the SP
- He didn't understand anything about regulatory reporting
- He didn't understand anything about financial derivatives
- He didn't understand the difference between Transact SQL and ANSI SQL
- No consideration given to IP
- etc etc
Those are the basics. Let's jump a little bit into the detail. Here's a rough snippet of what the SP looks like:
SELECT
CASE
WHEN t.FLD4_TXT IN ('CCS', 'CAC', 'DEBT', ..... 'ZBBR') THEN '37772BCA2221'
WHEN t.FLD4_TXT IN ('STCB') AND ISNULL(s.FLD5_TXT, s.FLD1_TXT) = 'X' THEN 'EUMKRT090011'
END as [Id When CounterParty Has No Valid LEI in Region]
-- remember, this is around 5000 lines long ....
So... you're not just dealing with incredibly unwieldy and non-standard SQL (omitted), noone really understands the business rules either.
So again... yes he was entirely wrong. There is nothing "trivial" about refactoring things that noone understands.
I'm roughly the same (started at 9, currently 48), but programming hasn't really changed for me. What's changed is me having to have pointless arguments with people who obviously have no clue what they're talking about but feel qualified either because:
a) They asked an LLM
b) "This is what all our competitors are doing"
c) They saw a video on Youtube by some big influencer
d) [...insert any other absurd reason...]
True story:
In one of our recent Enterprise Architecture meetings, I was lamenting the lack of a plan to deal with our massive tech debt, and used an example of a 5000 line regulatory reporting stored procedure written 10 years ago that noone understood. I was told my complaint was irrelevant because I could just dump it into ChatGPT and it would explain it to me. These are words uttered by a so-called Senior Developer, in an Enterprise Architecture meeting.
I understand what this does. I don't get the hype, but there are obviously 1000s of people who do.
Who are these people? What is the analog for this corner of the market? Context: I'm a 47y/o developer who has seen and done most of the common and not-so-common things in software development.
This segment reminds me of the hoards of npm evangelists back in the day who lauded the idea that you could download packages to add two numbers, or to capitalise the letter `m` (the disdain is intentional).
Am I being too harsh though? What opportunity am I missing out on? Besides the potential for engagement farming...
EDIT: I got about a minute into Fireship's video* about this and after seeing that Whatsapp sidebar popup it struck me... this thing can be a boon for scammers. Remote control, automated responses based on sentiment, targeted and personalised messaging. Not that none of this isn't possible already, but having it packaged like this makes it even easier to customise and redistribute on various blackmarkets etc.
EDIT 2: Seems like many other use-cases are available for viewing in https://www.moltbook.com/m/introductions. Many of these are probably LARPs, but if not, I wonder how many people are comfortable with AI agents posting personal details about "their humans" on the net. This post is comedy gold though: https://www.moltbook.com/post/cbd6474f-8478-4894-95f1-7b104a...
I had a lengthy argument about this in our architecture forum. I argued that "re-use" shouldn't be included as an Enterprise (keyword here) Architecture principle because they are clear use-cases where duplication is preferable to alternatives. e.g. deployment and testing decoupling etc etc. I had a lot of resistance, and eventually we just ended up with an EA principle with a ton of needless caveats.
It's unfortunate that so many people end up parroting fanciful ideas without fully appreciating the different contexts around software development.
People need to stop making Meme distributions.
Heh. I've been saying that since I was on Mandrake in the early 2000s. This is just what the Linux landscape is like.
That said, I'm generally not easily impressed, especially by random *nix distro 347, but CachyOS is surprisingly good. I've finally switched full time from Windows. I don't even need VS anymore because Rider is x-platform.
After I read that emotive response I couldn't help but wondering if this wasn't part of a scheme to help someone cover up a crime. This is how I would have responded:
"Hi,
These do appear to be quite serious crimes. I've sent all the URLs, your email address, emails and responses to the relevant law agencies.
Regards, AdGuard"
These guys are quite well-known in China and have recently started uploading tto Youtube as well. Their videos are quite entertaining and have extremely high production value compared to many other creators.
https://www.youtube.com/@HTXStudio/videos
I love the one about the automated trash cans.
I'm referring specifically to the technique mentioned in that video. Yeah it's cool that it's there, but that doesn't seem intuitive at all.
I switched to iPhone from Android for a few months earlier this year. I don't think I qualify as an elderly person yet (I'm 47) but even I had trouble figuring things out. I don't think it was super-hard to use, but I often found myself asking "Why would they do it like this? Who uses a smart-phone like this?". I just found some things very unintuitive. Take for example re-arranging icons. I don't know if I would ever have figured out this technique without looking it up:
I would recommend watching Curt Jaimungal's series of talks with Jacob Barandes. He gives a nice background history of various aspects of QM, including the formulation of Matrix and Wave mechanics (and loads of other ideas). Barandes is excellent at clearly articulating complex ideas in very simple, concise terms. He also has his own formulation of QM based on "Indivisible non-Markovian Stochastic Processes". Even if you disagree with his ideas, the interviews are quite fascinating.
In this interview he goes over pretty much exactly what you mentioned (and a lot more):
I don't really have that much of an issue with vibe coding as an appropriate tool in experienced hands. I think the worst ideas in 2025 are probably related to IT execs pushing AI in the wrong ways, or people espousing vibe coding as some sort of software development panacea.
Pre-print of a paper which studied 1950 "transients" which - in tl;dr terms - might be evidence of artificial objects in orbit before the satellite era.
Recent comment from one of the main authors:
https://x.com/DrBeaVillarroel/status/1949780669141332205
Previous work: https://www.nature.com/articles/s41598-021-92162-7
In that snippet are links to Postgres docs and two blog posts
Yes, that's what a snippet generally is. The generated document from my very basic research prompt is over 300k in length. There are also sources from the official mailing lists, graphile, and various community discussions.
I'm not going to post the entire outout because it is completely beside the point. In my original post, I expliclity asked "What is the qualitative and quantitative nature of relevant workloads?" exactly because it's not clear from the blog post. If, for example, they only started hitting these issues with 10k simultaneous reads/writes, then it's reasonable to assume that many people who don't have such high work loads won't really care.
The ChatGPT snippet was included to show that that's what ChatGPT research told me. Nothing more. I basically typed a 2-line prompt and asked it to include the original article. Anyone who thinks that what I posted is authoritative in any way shouldn't be considering doing this type of work.
What is wrong with you? Why would you even bother posting a comment like this?
Maybe you also don't know what ChatGPT Research is (the Enterprise version, if you really need to know), or what Executive Summary implies, but here's a snippet of the 28 sources used:
The structured data gets written to our Postgres database by tens of thousands of simultaneous writers. Each of these writers is a “meeting bot”, which joins a video call and captures the data in real-time.
Maybe I missed it in some folded up embedded content, or some graph (or maybe I'm probably just blind...), but is it mentioned at which point they started running into issues? The quoted bit about "10s of thousands of simultaneous writers" is all I can find.
What is the qualitative and quantitative nature of relevant workloads? Depending on the answers, some people may not care.
I asked ChatGPT to research it and this is the executive summary:
For PostgreSQL’s LISTEN/NOTIFY, a realistic safe throughput is:
Up to ~100–500 notifications/sec: Handles well on most systems with minimal tuning. Low risk of contention.
~500–2,000 notifications/sec: Reasonable with good tuning (short transactions, fast listeners, few concurrent writers). May start to see lock contention.
~2,000–5,000 notifications/sec: Pushing the upper bounds. Requires careful batching, dedicated listeners, possibly separate Postgres instances for pub/sub.
>5,000 notifications/sec: Not recommended for sustained load. You’ll likely hit serialization bottlenecks due to the global commit lock held during NOTIFY.I'd like to see stats on how many people are getting arrested for petty crimes e.g. marijuana (which isn't even a crime in some contexts any more) back then vs now.