At Cognite, we render large CAD models and have been using this technique (billboarding) to render large volumes of geometries. Created this page for a visit by math elites who wanted to work on some cool problems!
If you are able to render many torus efficiently in the shader, let me know!
> If you are able to render many torus efficiently in the shader, let me know!
Same way as anything else surely? Acceleration structures. Fit an oriented bounding box around each torus, add them as custom geo to the acceleration structure API.
I remember this very clearly myself. Before opus 4.5, I was doing a lot of hand holding and was coding a lot myself, but I have not written code since that day more or less.
I did write some stuff myself just to learn how the enigma encryption machine worked, so wrote myself to learn. But professionally, I stopped coding in November.
A pattern I've settled into is to write code but leave a TODO for every narrow thing I want the LLM to do for me. Then just tell the agent to fix the todos. It's often faster and easier to give "instructions" this way
In most cases you could work around that. For instance write the code yourself and make the AI write the tests. Or keep it busy writing superfluous documentation. Very few people are micromanaged to the extent that they can’t subvert the system.
Exact same experience here. Prior to Opus 4.5 I'd sometimes use AI for some frontend webdev stuff (I am a C/C++/Python programmer; my HTML/CSS/JS knowledge is probably on par with a first-year uni student) and I'd have to manually edit things and retry, tell it not to attempt a paradigm that had failed before or cycle between models in Cursor just to try and get one that could make a simple widget that worked properly.
Now, I'm using Claude or Codex (GPT-5.5) for frontend and backend and it just gets it right first time more often than not. I've been making use of things like LSPs, Context7 and CLAUDE.md (global and per-repo) and it just stops doing the dumb LLM things that I hate.
How do you justify your salary given that you're just using OSS compiler/editor any of us could use for free in your role ?
AI just changed how I edit code - I still see coworkers (senior developers) failing with Claude/Codex and get stuck when there are trivial solutions if you understand the full problem space. Right now AI is just a productivity tool.
Usually I describe the problem, explore a bit with LLM iteratively. Then I switch to creating a plan when I have enough insight (and the LLM has it in context/same session as exploration), specifying all the things I'm trying to accomplish.
Then I just iterate with LLM - I let it start writing stuff in YOLO mode and check on what it's doing in the code steering it in the direction I want.
Usually the code LLM generates will work but is kind of garbage - but I can easily steer it towards better implementations.
Sometimes using an LLM is theoretically slower than hand-rolling - if I just sat down and focused I could outperform the iteration and the waiting, especially considering how stupid agents are at running expensive builds/test suites (with a bunch of explicit instructions in skills/claude/agents.md). But the practical improvement of going with LLM is that you have a bunch of thinking traces saved as a part of your iteration proces - it's really easy to get back into flow. This is a huge productivity win for me given how many interruptions I have in my work day. Like so many people like to point out - writing code ends up being less and less of your time as you level up in your career.
I don't feel the need to justify my salary, since I'm simply lucky in that regard. But I'm pretty sure you couldn't do my job just because you had access to a coding agent. Most of my time at the office is spent discussing high-level architecture and strategy, ideas, customer requests, backward compatibility, safety, security, quality assurance, etc.
Writing the actual code is a significant part of that, but the codebase is so complex that even Opus 4.7 and GPT-5.5 struggle with it without being fed a *lot* of context and constraints. And even then, they need a *lot* of steering due to making bad decisions that only someone with an intimate knowledge of the theory behind our software is able to catch.
I can only assume that people who think coding agents can completely replace an actual developer mostly deal with trivial software regarding both scope and the type of customers they serve (individuals instead of big companies in industry).
They're using a tool that anyone can use for $20 an hour, sure. But that's not what they're "just" doing. This is what is so insane about non-technical people talking about code - writing the actual syntax is not really the hard part.
What you're saying is like "how do you justify your salary as a NASA engineer when anyone can use Simulink and generate the code?"
Please see Ben Evans’ podcast on a good take on this. Coding is just one of the task you do in your job, it is not the job or at least it probably is not. You do not get paid to code, you get paid to make a set of decisions that create value to the company. If this is automated then yes sadly your salary is not justified.
I agree, but the reality is that most people work to make a living, not to have fun. If you enjoy your job because you mostly get to write code in a tight feedback loop instead of doing the "hard" work of planning, writing and reviewing specs, balancing customer requirements, and the lot, you have a very privileged life. And those jobs are probably going to get fewer now.
It's kind of sad. But on the other hand, I am glad I don't have to write every little line of code myself *on top* of having to do all the other stuff.
I totally agree. I loved coding because of its closed feedback loop. Since last November, I also delegated it mostly to agents. Now I concentrate more on the design part, which is not the same. However, you move with the times and hope something else will become exciting. I do not know a more worthwhile and satisfying way than computing to spend my work hours.
To me, LLM's free up time for me so that I can spend time on the fun parts of coding. Less boilerplate, more focus on the interesting problems. This is no different from using high level languages. The problem domain is less around memory management and garbage collection and closer to the problem you're actually trying to solve.
But we’ve had tools to automate out the boilerplate for years. We don’t need ai for that. It’s seriously like we all forgot we could run one command and scaffold a project. AI isn’t even that great at it. Last I tried a month ago it used a really out of date version of nextjs and picked all sorts of random deps that weren’t in the plan.
I could have just used the next project scaffold tool and been on my way before the ai even started returning output.
Or copy paste another file and edit the 10 lines that are actually different. The nice thing is that when you have an epiphany that you’ve already done this twice and that it’s for the same purpose, so you abstract the code and remove 100 lines from the project.
You have no idea how many times I’ve asked “why are we not using the project generator” or “why did you write 200 lines to parse a csv? Here’s a library and five lines to get it done” in the last year. Its easily up 20x compared to pre ai, and getting worse.
I agree with this. I feel like there’s a false dichotomy right now in a lot of these discussions where one can only vibe code or only code by hand. It is possible to do both…
I watched the last one S5:E17 What jobs are AI jobs and I think it gives the right framing to think about this. It is not prescriptive, it does not give a list which is smart. The job title might be the same but the actual role might have different context so the best is to have the right frame to explore your particular situation.
How do you justify your salary given that you sit in a chair all day, likely making the world worse, and make 5x as much as someone saving lives, building houses, or teaching kids how to read?
Supply and demand. Not many people are good at programming and it's highly in demand.
The question is how many people will be good at vibe coding? If the answer is "lots" then we can definitely expect programming salaries to return to "normal" levels. His question is very relevant; you can't dismiss it as easily as that.
it can be easily dismissed because "anyone can use the tool that costs $20" makes no meaningful sense.
this was always true in fact $20 is more than the free it costs for notepad++
it's a flippant statement. Go down the line of any tool; it's cost has basically nothing to do with skill difference to operate it. See basically everything. There's levels.
I have no idea what you're trying to say. If anyone really can vibe code then programming salaries are pretty much guaranteed to come down. The critical question is whether it really is true that anyone can do it, or if it still requires rare skill.
are you a programmer? it 100% requires skill. AI or not.
i'm trying to say there's levels to this. if you don't agree then you don't agree. but i can buy commodity tools for any skill and that doesn't make me professional grade at that skill.
Yes I am. The vibe coding I've tried didn't work very well so I agree that still required my skill. But I also don't have access to the latest models and supposedly they're a lot better (see this article for example!).
So is it possible for non-programmers to vibe code if they have the latest models? If not now, what about in a few years?
AI is clearly a different class of tool to something like a welder.
Never to feed the trolls ... but, how does my carpenter deserve $100 an hour when he is using an electric drill and power saw I can get at Home Deepo for $100 bucks?
Most good developers are not employed because just because they can code well.
What is over is: fizzbuzz and trivial CS algorithm regurgitation as a gate.
Someone competent using them is today a requirement and for awhile will make the marginal utility of skilled workers greater than that of unskilled. The justification is that they are much more productive than they were before.
You can build things quickly with AI, but you can’t delegate your responsibilities to AI. Once the AI starts struggling, you’ll need to takeover and figure it out.
This is _the_ question we must all be able to answer, so here goes my attempt - we all have access to the same tools, before stackoverflow it was forums, books/manuals, so its always been about “getting there, showing up, figuring it out”
your hypothetical boss has other things to do than kick a LLM around at that price
Because the tool will happily give you a "solution" that kinda works for a few inputs. It will happily correct itself when you give it more incorrect tests.
It will almost never converge on the general solution that will pass tests you haven't given it yet.
This is why AI is sooo good at Javascript and related slop. A solution that "kinda works" is good enough 9 times out of 10 and if some tests fail well ... YOLO and the web page will probably render anyway.
Contrast that to using Scheme or Lisp where AI will have trouble simply keeping the parentheses balanced.
While I certainly like parentheses highlighting and rainbow parentheses, I've programmed Clojure without syntax highlighting and while it’s not as nice as it would be with, it’s fine.
I’ve also written C++ and Java in Notepad long ago. Not ideal, but hardly a problem.
Same experience here.
I now think AI writes much better code than me. So I shifted my focus to finding requirements, analyzing possibilities, and making good plans.
Because that’s literally the definition of open source:
> Open-source software is software released under a license where the copyright holder grants users the rights to use, study, change, and distribute the software and its source code, for any purpose.
That’s the first result you get on Google—and it’s exactly why so many companies relicensed their projects (Redis, HashiCorp, Elasticsearch, MongoDB…).
If it’s open source, you can sell it, host it, or give it away for free. The only difference is which obligations the license attaches:
GPL → you must keep the license.
AGPL → you must keep it and extend it to hosted services.
BSD/MIT → do almost whatever you want.
But the core right is always the same: distribute, host, and sell. Courts have even confirmed this is the accepted definition of “open source.”
hook.js:608 Failed to parse JSON from match: SyntaxError: Expected ',' or ']' after array element in JSON at position 207 (line 3 column 194)
at JSON.parse (<anonymous>)
at build-studio-C28lcD4m.js:67:471
Stuck at "Starting project..."
Also, seems like 15-20 people to build this, after just a couple of months. Something is off with the numbers. Also, vibe coding platforms are becoming commodity with other platforms lightyears ahead, approaching zero margins.
Definitely wish you luck, but something feels off with the numbers, timeline, product and the market you chose :)
If navier-stokes equations can be derived from Newton's laws, then Newton's laws can be derived from Galileo, Archimedes before him, even some older thinkers before them.
Newton ignored viscosity, and density. He made some discoveries on fluid dynamics but his famous laws only apply to solid objects. Same for velocity, he knew about that of course but only worked it out for solids. Ignoring two critical components meant he didn't establish relations between them either.
That's my read.
Not to dismiss credits to Newton, who's is in another league than navier and stokes. In his own league even. He probably would have figured out what was only solved centuries later had he explored further, or had he benefited from perhaps just a few other later discoveries.
But that's dismissive of navier-stokes significant discoveries on fluid dynamics to not simply give them credit for the formula behind this simulation.
What do you mean by considered bad practice? By whom? I would think this is one of the reasons that my Macs since 2008 have just worked without any HW problems.
If you are able to render many torus efficiently in the shader, let me know!
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