nudpiedo

And the word from arabic comes, for both of them comes from persian for hte term lapis lazuli (lāžward) and suposedly this comes from sanskrit... but I ignore how it may sound in sanskrit.

In this case it does by hitting hardware maximum. It scales until the max it is possible, due the bottleneck being in the hardware, not in the database or i/o. Check the article again:

> At maximum throughput, Postgres CPU is fully utilized, showing the database is actually saturated instead of bottlenecked on contention.

There are Static code analyzers which already would have detected that.

And these were also automatic. Looks very likely that the team didn’t give a damn about top basic security and good practices.

Like a house made of paper wouldn’t be an example of the insecurity of the construction industry.

> Misconception 1: specification documents are simpler than the corresponding code

Anyone who studied software engineering, should know that specification doesn’t bother with implementation details of the underlying technology.

Things such as quite specific engine are used, are the contents of an encapsulated subsystem.

Proper software engineering specification is incompatible with a hacker culture and picking technology beforehand is a bad practice. It’s much closer to waterfall than to C4.

However, the last 20 years we got software building blocks which impose system architectural restrictions: frameworks. And also pieces of software which are half cooked systems.

Far are the days of requirements, preconditions, postconditions and invariants, network diagrams and entity relationship models.

So in a couple of years we will have de MacBook Neo Neo?

I think they got just cheaper marketing since jobs died. No focus or brand protection.

I often want to try, but never get the time, aren’t you missing packages and solutions out of the shelf and ready to use?

This was AI generated right? And saying that in 2010 Linux was complex and needed to compile everything across virtual machines for cloud solutions and that socket solved that… really in what universe people lived?

Docker made convenient distribute some functionalities which were planned as stack of services rather than packaging appropriately for each distribution and handling to an administrator the configuration. That’s it. And it has many inconveniences. And Linux as well as BSD had containers before and chroots and many other things.

All the issues you mention are about uncertainty.

Uncertainty is one of the largest perceived threats by the human brain, it’s normal you feel it like a threat, it can even cause you anxiety and force you to take severe and unnecessary decisions. If that’s the case talk to a mental health professional because it is not an issue.

However if mental health is not an issue, try some of the many techniques that are there on how to handle uncertainty psychologically, you may start with stoicism (a modern book is fine) and with distribution of risk only of the threats that are an actual problem to you and you have any little of control over them

They will wish that you use an official API, follow the funnel they settled for you, and make purchases no matter how

I get where you come from, but really needs it to be a whole SQLite instance per database? Wouldn’t be more efficient just logic separation in a larger DB?

Better usage of resources and it always allows a parent style agent do complex queries (e.g: intersection of two different actors data doesn’t need to fetch all, copy and do it in buggy non sql code)

Literally the first line of the link:

“The current interface was designed for internal use in Lean and should be considered unstable. It will be refined and extended in the future.“

My point is that in order to use these problem provers you really gotta be sure you need them, otherwise interaction with an external ecosystem might be a dep/compilation nightmare or bridge over tcp just to use libraries.

I like a lot of the idea behind such theorem provers, however, I always have issues with them producing compatible code with other languages.

This happened to me with idris and many others, I took some time to learn the basics, wrote some examples and then FFI was a joke or code generators for JavaScript absolutely useless.

So no way of leveraging an existing ecosystem.

Are you an AI just summarizing the article?

I think the only people who burnt of the discussion were people who is terminally online. But in the industry, there is people in any paradigm with any previous development times you can remember of.

> Is there any formal language that is usable as general-purpose programming language I don't know of?

That’s sort of my point, the closest thing to a rich type system yet pragmatic enough is to me F# and it’s still falls short as formal verification and ecosystem integration.

I think eventually, we should invest into this direction so LLM production can be trusted, or even ideally, producing or helping with the specific specifications of models. This is yet to be done.

I don’t want to make a prophecy, but the day, ergonomics and verification meet in an LLM automated framework, this new development environment should take over everything previous.

And also with Ada which would be even safer. And the same it is for me... we all got trained in skills are slowly going to fade away.

Serious question: why won’t JUST use SELinux on generated scripts?

It will have access to the original runtimes and ecosystems and it can’t be tampered, it’s well tested, no amount of forks and tricky indirections to bypass syscalls.

Such runtimes come with a bill of technical debt, no support, specific documentation and lack of support for ecosystem and features. And let’s hope in two years isn’t abandoned.

Same could be applied for docker or nix Linux, or isolated containers, etc… the level of security should be good enough for LLMs, not even secure against human (specialist hackers) directed threads

It was better because it had no silent errors, like 1+”1”. Far from perfect, the fact it raised exceptions and enforced the philosophy of “don’t ask for permission but forgiveness” makes the difference.

IMHO It’s irrelevant it has a slightly better typesystem and runtime but that’s totally irrelevant nowadays.

With AI doing mostly everything we should forget these past riddles. Now we all should be looking towards fail-safe systems, formal verification and domain modeling.

Same thing applies to other system aspects:

compressing the kernel loads it faster on RAM even if it still has to execute the un compressing operation. Why?

Load from disk to RAM is a larger bottleneck than CPU uncompressing.

Same is applied to algorithms, always find the largest bottleneck in your dependent executions and apply changes there as the rest of the pipeline waits for it. Often picking the right algorithm “solves it” but it may be something else, like waiting for IO or coordinating across actors (mutex if concurrency is done as it used to).

That’s also part of the counterintuitive take that more concurrency brings more overhead and not necessarily faster execution speeds (topic largely discussed a few years ago with async concurrency and immutable structures).

No one thought juniors would be more benefited than seniors. St some people some said everything would be automatic and seniors would disappear altogether with programming itself.

But that was just said by crappy influencers whose opinion doesn’t matter as they are impressed by examples result of overfitting

This might depend on where you live and the kind of business… last time I made an Unmeldung online I needed to call after a week waiting and they literally told me that in person would be solved the same day. And it was.

Same as many, I had wonderful experience with F# in the past, I would use it again if:

- fable would 100% detach from dotnet - keeps up yo the LLM rush, specially vibe coding on cursor

Last LLM experience it generated obsolete grammar (not much but a bit).

Such la gauges are key for vibe coding experience and modeling.

Wow, thank you so much, that was 11 pages full pages. I will be a bit critical with it hoping my review helps you as well, since to me, it was very friendly and useful your offer (also I wonder if you can still do 99 more reserachs like this one during the month or this amounts already to many of such research in total).

Superficially:

- Awesome how fast is available and all sources linked to explain each claim

- To export that to a proper doc with footnotes and proper formatting it's already something to be worked by openAI

- it looks like the perfect way to create a gut feeling and a sense of what is going on

Content:

- Wrong studies: It mixed SysML (a particular visual language for which it was specifically requested) with MBSE (the family of tools) which is exactly not the same as the desired study was particular for SysML.

- Quality of data: Most of the data comes from public articles and studies made by others, all the time about MBSE, not SysML, and just quotes their numbers, it does not do its own estimates looking for the benefits of such products on each company and estimating a projection (that would be an actual research, and an AI should be capable of tirelessly do that or even biasedly look for the right pieces if information). For example it was a report on diet, a report like that should avoid debunk articles, bro's blogs, etc.

- Inconsistent scales: at some comparison table, it mentioned at the foot that it will display pricing with such schema:(Pricing: $ = low, $$$$ = high) however it made that in a single row. Why? the source for that field made that as well in its source, but none of the other fields repeated this system to value or adapt results.

- Only googleable data: companies reports or private databases here are key for a high quality report. Sometimes this is not always possible for an AI or a crawler but here am I evaluating the outcome (use case): a market analisis for strategic purposes.

- Quality of the report: Many things mentioned like services around the products are also highly valuable... would be useful to remark case by case the business model of each company and how much is in the product and how much is in the related service (using a pie chats or whatever) and showing particular case studies to remark the market trend, from which model is coming from (product) and where it is going to (services and SaaS).

I could continue longer with many other things and such errors but it is quite long.

Conclusion:

It is very useful, particularly to grasp a general, yet detailed, idea on what is going on, on a market. However it is only as valid as a remix of previous things, not an actual market research for an actual strategy. Many sources, elements, landscape of which companies and products related are there are totally useful, perhaps 30%-40% of the total work and it gives a clear structure where to go from here.

Probably it may improve the more interactive that the tool is, for example asking to correct some sections or improve in specifically suggested ways by the user. Basically the user needs to bring expertise, reasoning from the field and critical thinking (things machines will be lacking in any foreseeable future).

Why am I so critic? Remember, map is not the territory, particularly in strategic terms. And it is also a problem that many professionals do also these kind of failures: uncritically copying data from other's reports without verifying critically any of it which leads to very specific kinds of strategic errors.

It will become more useful as it becomes specialized in the kind of reports, and judges critically (which does not) and if it can be adapted to work on a private repo or preselected amounts of sources, or even prescripted agent behaves for the sort of report.

Verdict:

I would purchase it, not to solve the problem or resell it, but as a way to get started and accelerate the process. It already does what an internship student would do, or a mediocre professional: revamp preexisting mashups to get a general, but detailed, feeling but no more insights or research than what it is already well known (googling after all).

It has a great future as it would be great if such level of non creative work is automated away as their value often is marginal and uncritically propagates previous beliefs and biases (and if there is a centralized tool, that can be tuned to avoid well known issues)

Thanks for the offering, seriously, it is an important investment/cost I wasn't sure it would be worth right now. (If you wish to I added some contact information, for an easier chat, in my HN profile; just for the following day).

Here is a realistic case I would have used

Short prompt: "research the market of the SysML products and industry cap, key actors, opportunities and advantages"

Expanded prompt:

“Conduct a detailed market analysis of SysML (Systems Modeling Language) products and services, focusing on the following aspects: 1. Industry Overview: • Current market size and growth trends for SysML-related products and services. • Global market cap or valuation of the SysML industry or similar system engineering software. 2. Key Players: • Identify major companies and organizations offering SysML tools, including established leaders and emerging competitors. • Provide a brief description of each key player’s products, innovations, and market share. 3. Product Offerings: • Highlight the range of SysML-based products available (e.g., modeling software, integration tools, training services). • Compare features, target industries, and pricing strategies. 4. Market Opportunities: • Explore new or underserved industries where SysML adoption could grow (e.g., aerospace, automotive, healthcare). • Identify gaps in current product offerings that represent potential areas for innovation or competitive advantage. 5. Competitive Advantages: • Analyze what makes SysML valuable to companies (e.g., improving system complexity management, ensuring design consistency). • Evaluate how SysML tools offer a competitive advantage compared to alternative solutions like UML or other system modeling methods. 6. Challenges and Risks: • Discuss potential challenges such as market saturation, training requirements, or competing technologies. • Highlight external factors that could affect market growth, such as regulations or advances in adjacent industries.

Provide sources where relevant, including reports, studies, or insights from industry experts.”

Hvala.

I wish to know how to access it for myself, but how may I contact you?

is it chatGPT Plus, Pro or something else? Where are you based UK or Germany?

I was hoping for a market research on SysML tooling.

if it would make whole market research on products and companies I would gladly pay for it... but a bit unsure from Europe where it seems to be everything restricted due political boundaries.

Today I wasted 1 hour looking in how to use or where to find "Deep Research”.

I could not. I have the business workplace standard, which contains the Gemini advance, not sure whether I need a VPN, pay a separate AI product, or even pay a higher workplace tier or what the heck is going on at all.

There are so many confusing products interrelated and lack of focus everywhere that I really do not know anymore whether it is worth as an AI provider.

so if I understand this right, it could be a way to run scheme on esp32 and similar microcontrollers, isn't it?

Also its small size would make it a perfect target to compile to typescript/deno/wasm without rejecting the s-exp power and runtime possibilities in its full chicken code at the backend...

I guess faster reaction times might have been decisive for many early startups.

Nowadays is another story because everyone does and cargo cults are in place.

is the certificate right?

mmmmm someone might want to steal my coffee...

False dichotomy doesn’t bring anything to the conversation. However it it true that the far left is the main motivated to quit X, and the progressive views Silicon Valley were also dominant on HN.

Just something to accept and think about. Do not blame the messenger.