sysmax

8 ms·

1.
by sysmax 5mo ago
They can, but this reduces the quality. The LLM has a harder time picking the first edit, and then all subsequent work is influenced by that one edit. Like first creating an unnecessary auxiliary type, and then being stuck modifying the res
2.
by sysmax 5mo ago
Well, LLMs are priced per token, and most of the tokens are just echoing back the old code with minimal changes. So, a lot of the cost is actually paying for the LLM to echo back the same code. Except, it's not that trivial to solve. I
3.
Cerebras Is Back(openrouter.ai)
4 points by sysmax 5mo ago|1 comments
4.
by sysmax 5mo ago
For those not following: they are running inference on their own chips way faster than any competition, which I find really useful for refactoring some old code. It's like 3 seconds vs 40 seconds with Claude and the likes. Their system
5.
by sysmax 11mo ago
Bah. It's a really cool idea, but a rather crude way to measure the outputs. If you just ask the model in plain text, the actual "decision" whether it detected anything or not is made by by the time it outputs the second word
6.
by sysmax 1y ago
Want a good use case? I am playing around with interactive workflow where the model suggests what can be wrong with a particular chunk of code, then the user selects one of the options, and the model immediately implements the fix. Biggest
7.
by sysmax 1y ago
Ironically, that's how I got the whole idea of symbol-level edits. I was working on project like that, and realized that a lot of work is actually fairly small edits. But to do one right, you need to you need to look through a bunch of
8.
by sysmax 1y ago
It greatly depends on the type of work you are trying to delegate to the AI. If you ask it to add one entire feature at a time, file level could work better. But the time and costs go up very fast, and it's harder to review. What works
9.
by sysmax 1y ago
Adding entire files into the context window and letting the AI sift through it is a very wasteful approach. It was adopted because trying to generate diffs with AI opens a whole new can of worms, but there's a very efficient approach i
10.
by sysmax 1y ago
Cool. The part that is released already is described here [0]. You can point at some code and give brief instructions, and it will ask the model to expand them, giving several options. E.g. if you point at a vector class and just "Dist
11.
by sysmax 1y ago
Most of the AI hiccups come from the sequential nature of generating responses. It gets to a spot where adhering to code structure means token X, and fulfilling some common sense requirement means token Y, so it picks X and the rest of the
12.
by sysmax 1y ago
I use hierarchical trees of guidelines (just markdown sections) that are attached to every prompt. It's somewhat wasteful in terms of token, but works well. If AI is not creating a new wrapper, it will just ignore the "instruction
13.
by sysmax 1y ago
There's a pretty good sweet spot in between vibe coding and manual coding. You still think out all the classes, algorithms, complexities in your head, but then instead of writing code by hand, use short prompts like "encapsulate X
14.
Show HN: CodeVROOM – an AI editor for large projects
1 points by sysmax 1y ago|0 comments
15.
by sysmax 1y ago
It works with low-level C/C++ just fine as long as you rigorously include all relevant definitions in the context window, provide non-obvious context (like the lifecycle of some various objects) and keep your prompts focused. Things li
16.
by sysmax 1y ago
I don't see it as anything bad. LLMs are a interesting, alright. They can very quickly do a lot of mind-numbing work that used to be done by hand, and then they can stumble and produce total nonsense that no human being would even cons
17.
by sysmax 1y ago
Looked into it a lot. There are deterministic refactoring tools for things like convert for into foreach, or create constructor based on list of fields, but they still don't cover a lot of use cases. I tried using a refactoring tool fo
18.
by sysmax 1y ago
It's just faster and less distracting. What is a total game-changer for me, is small refactoring. Let's say, you have a method that takes a boolean argument. At some point you realize you need a third value. You could replace it w
19.
by sysmax 1y ago
It's not really that specific. There's a actually a hidden command there for comparing the current source file against an older version (otherwise, good luck testing the diff GUI without pre-recorded test cases). If anyone's
20.
by sysmax 1y ago
You can't trust LLMs to copy-paste code, but you can explicitly pick what should be editable, and also review the edits in a more streamlined way. I am actually working on a GUI for just that [0]. The first problem is solved by having
21.
by sysmax 1y ago
It's not the IP, it's sadly how people react. Some folks will be appreciative of help, credit to them. Others will immediately get back how they tried it, it didn't work and now they need you to rewrite everything, or do thei
22.
by sysmax 1y ago
Sadly, that stuff backfires. The researcher will publish your response along with some snarky remarks how you are refusing to fix a "critical issue", and next time you are looking for a job and the HR googles up your name, it pops
23.
by sysmax 1y ago
I wish people would make distinction regarding the size/scope of the AI-generated parts. Like with video copyright laws, where a 5-second clip from a copyrighted movie is usually considered fair use and not frowned upon. Because for pr
24.
by sysmax 1y ago
I think, there are different niches. AI works extremely well for Web prototyping because a lot of that work is superficial. Back in the 90s we had Delphi where you could make GUI applications with a few clicks as opposed to writing tons of
25.
by sysmax 1y ago
If you are launching one product per day, you are using LLMs to convert unrefined ideas into proof-of-concept prototypes. That works really well, that's the kind of work that nobody should be doing by hand anymore. Except, not all work
26.
by sysmax 1y ago
I am working on a GUI for delegating coding tasks to LLMs, so I routinely experiment with a bunch of models doing all kinds of things. In this case, Claude Sonnet 3.7 handled it just fine, while Llama-3.3-70B just couldn't get it. But
27.
by sysmax 1y ago
AI can very efficiently apply common patterns to vast amounts of code, but it has no inherent "idea" of what it's doing. Here's a fresh example that I stumbled upon just a few hours ago. I needed to refactor some code th
28.
by sysmax 1y ago
Not exactly. Let's say, you-the-human are trying to fix a crash in the program knowing just the source location. You would look at the code and start hypothesizing: * Maybe, it's because this pointer is garbage. * Maybe, it's
29.
by sysmax 1y ago
>The same kind of bias keeps resurfacing in every major system: Claude, Gemini, Llama, clearly this isn’t just an OpenAI problem, it’s an LLM problem. It's not an LLM problem, it's a problem of how people use it. It feels natur
30.
by sysmax 1y ago
I think, there's nuance. If a human can solve a problem without second thoughts and hesitations (Hey, stop, this doesn't look right. Are there other options?), an LLM will tear through it at breakneck speed. But if there are thing

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