But when I broke it down into function units, some parts were bad and some parts were good.
So I can't tell the difference
51–60 of 334 posts
But when I broke it down into function units, some parts were bad and some parts were good.
So I can't tell the difference
gpt-6-astra is a bitch, it constantly scope creeps itself with "yet another thing" to give it that darn polished lick. the results are eventually a little bit better but at what cost? let's do the math. gpt-5.6-sol: 1x base gpt-6-astra 2.5x base in subscription then gpt-6-astra tends to spawn subagents a lot, often with all kinds of models such as gpt-5.6, 5.3-codex etc., which is neat. it's a good coordinator but ev…
I've got a custom agent loop that will reuse unit testing results if no apply patch operations occurred since the last invoke.
Wall clock time isn't something I would put on the AI provider. That's entirely a consequence of the system that you've brought to the party.
> And potentially as a byproduct of enabling all of this, you can now slop your way to a one-shot 3D game over the weekend which looks impressive. I think we've finally reached a weird point where AI has effectively reduced the amount of competition that real game developers have to endure. Nothing unravels faster than a game project being built with AI. You can achieve impressive results in a day, but you can't get…
> And potentially as a byproduct of enabling all of this, you can now slop your way to a one-shot 3D game over the weekend which looks impressive. I think we've finally reached a weird point where AI has effectively reduced the amount of competition that real game developers have to endure. Nothing unravels faster than a game project being built with AI. You can achieve impressive results in a day, but you can't get…
That is a very bold claim, unless you meant "current LLMs".
You can groom the epic with the help of AI, but final review must be done by someone who can take ownership of the specs and hence is responsible if something has fallen through the cracks. AI's response will be limited by the output tokens of that specific agent, and there will no repercussions for AI even if it accepts its mistakes.
These machines are doing some crazy things to get to the result. That said, I can't help but feel like this is the compilers argument all over again. Are the methods used to get to the result good? No. Is the code that it generates good? No. Does it achieve the goal. Yes. Is it likely to get better with time. Also yes. In my use cases, jobs that would have taken weeks to months are being done in minutes to hours. Inv…
What is the "compilers argument"?
Earlier quoted context omitted.
What is the "compilers argument"?
Back in the day, the argument was that compilers produce unreadable assembly, so people used to writing assembly were arguing against the use of compilers. Compilers also had bugs, so we still had to debug the assembly to understand how to fix the problem. Nowadays, almost nobody has to resort to those steps, except of course compiler developers. But that is just a testament to the quality of compilers. Comparing LLM…
But is it relevant? does it matter from a product perspective if LLMs are non-deterministic. You don't need to one shot the correct result, english is ambiguous and LLMs non-deterministic, but you can iterate.
If it's possible to iterate fast and cheap enough, even ambiguous language can produce the results you want, given enough iterations.
There are a lot of ifs and buts here, just a thought on the compiler argument.
> And potentially as a byproduct of enabling all of this, you can now slop your way to a one-shot 3D game over the weekend which looks impressive. I think we've finally reached a weird point where AI has effectively reduced the amount of competition that real game developers have to endure. Nothing unravels faster than a game project being built with AI. You can achieve impressive results in a day, but you can't get…
Do these games really look impressive? Everything I've seen has looked like someone completely new to Unity/Unreal has slapped together a bunch of premade scripts and very poor 3d assets.
In SWE I've found gpt-6-astra (high) inconsistent and oddly focused on overtly taking responsibility for mistakes it made rather than prioritizing concrete steps to rectify problems. Such steps once elicited are often either incomplete or beyond the scope.
Opus also does this and then writes comments in code or PR descriptions describing how it went wrong earlier in the session.
The biggest issue with LLMs is that they still suck at general contextual awareness and ability to judge what is appropriate.
I've observed the same thing where the new models want to run obscene bash commands or python scripts which are completely unreadable and utilise every option flag that exists. It's impossible to review. These commands are less readable than regex.
I only dabble in the use of LLMs to generate code for hobby programming (I'm retired from software development) so I don't use any specialised tools.
I almost always have to tell ChatGPT (via Duck AI usually) to rewrite several times even when it has produced a workable script just because it has often used some unnecessarily roundabout way of achieving something. Usually with extra prompting I can get something that is both more efficient and more readable.