It seems like these trusts should all be delegated to the OS unless there's a really specific need.

Cool. I am applying to jobs and it seems graph theory is popular in the "Leet Code" questions pace. So very timely, thank you! And clever domain name :)

Just use hashmap for everything.

I have studied algorithms in college. I believe the goals of leetcode vs the goals of graph theory may be against each other.

A good graph theory course abstracts away the details of code and pursues the goal of understanding how many problems can be expressed concisely and clearly through graphs.

A good leetcode practice ... honestly just hones how patient you are in debugging and memorising various code patterns.

If you want to pursue money, it's almost always better to pursue leetcode exclusively

This is not true.

Graph theory and algorithm engineering overlap a great deal. And not only in the directly graph theoretic terms like BFS, Dijkstra, Flow, etc, but also in that you need a good grasp of greedy algorithms, dynamic programming, divide and conquer, and several other general techniques.

I think their point is that there's a split between the modeling / mathematical focus versus an imperative algorithm focus.

Kind of like how being good at relational-databases and SQL is different than being good at coding up B-tree implementations.

You don't need to be a good algorithm engineer to secure a high-paying job though. In fact high-paying jobs regularly turn away strong algorithm engineers because they can't pass leetcode challenges.

The advice is sound -- if you want money focus on the flashy buzzword thing, not the actually useful thing.

this is cool

Claude to Prod. Every day.

Amen. If it works, its good enough.

The CVEs are going to be epic.

I don't understand these types of comments. Aren't the CVEs epic today with human written code? What difference does it make then? You want no CVEs, make software engineering into a real gate-kept engineering professions with accountability chains, government regulations, formal education, etc.

> Aren't the CVEs epic today with human written code? What difference does it make then?

LLMs cause errors at a noticeably higher rate than human devs do. If you lean on them without actually checking what they wrote, the error rate in your software is going to go up.

> You want no CVEs, make software engineering into a real gate-kept engineering professions with accountability chains, government regulations, formal education, etc.

This will not only not prevent CVEs, it will also make everything a giant pain in the ass

Of course it will. But at the same time I don't see building falling left and right like CVEs in software. So don't tell me agents write bad code, because humans do as well. The only way to prevent this (or minimize), is to turn software engineering into real engineering.

The problem is what's happening right now is the opposite of that... software engineers are being turned into managers.

And if you don't think the firings and reduced pay are right around the corner, I have a bridge to sell you.

By default Claude chooses old versions of libraries. without something that checks for CVEs you're gonna be shipping criticals like no tomorrow.

Yes, there are more CVEs discovered every day, but, if you don't patch, the hacker doesn't have to try.

"If it works, ship it" is very different from "If it works, and I understand it because I wrote it, ship it".

Does the LLM understand it, in detail? Can you trust its interpretation of the information and instructions you provided? Did it independently make an adverse decision you haven't noticed, because you didn't read the code? Was the model missing any information it required -- and would you know if it was?

LLMs depend on humans and human oversight to ensure they have the information required to make the right decisions, to catch when they don't, and to steer them based on your much more complete understanding of the broader context and requirements. You can't rely on them to do that thinking for you (yet?).

I’d argue that most people also don’t understand code they read from their colleagues. Or if they do, then they don’t understand the entire context of the app.

You said LLM need human oversight and it’s true, but it does not imply you have to read the code.

I think we are going towards a place where code no longer makes sense, you just describe what you want in English, and the LLM just builds directly in machine code. You then build different verification tests to make sure the program is doing what it’s suppose to do.

More opportunities for me to jump in and save the day. Win-win.

I've been trying to find a list I had previously of sites hosting webpages at top-level domains. I think there was a webpage you could access at http://ai./ for a long time.

Claude has been doing this already.

I think Firefox is doing a good job overall.

What’s wrong with using work offered for free?

The implicit arrangement in corporate use and contribution to open source is that everyone benefits. People contribute work and testing that improves libraries and tools that everyone else can use, making all our projects better. This includes corporations, many of which also engage in this mutual benefit by hiring actual developers to back open source projects. I think it’s a brilliant system, huge fan.

Enter LLMs training off that data. It looks similar on the surface, but if you think about the balance of cost and benefit it becomes clear it is no longer balanced. The training algorithms and models are closed source, and come at a hefty usage cost. AI companies saved hundreds of billions of dollars of paying humans to help train their algorithms by taking advantage of an open system that was open on with another kind of balance in mind.

So in short the work was offered for free within a specific kind of relationship. Now a powerful outsider is steamrolling and taking advantage of that existing open dynamic.

Most FOSS is offered free of charge, but not free of conditions. You still have legal requirements spelled out in the licenses, from attribution to actually requiring you to license your work accordingly.

I feel like the standard "Free as in Gratis vs. Free as in Freedom" argument doesn't quite explain the issue people have here.

Open-source code still had terms, and AI training was an unfortunate blind spot in those terms. If a human being learned how to code 100% from open-source code, nobody saw a problem if that person went on to write closed-source code.

But it feels fundamentally different when the open-source code is just being fed into a machine that uses absurd amounts of processing until closed-source code comes out the other side. It feels like theft.