Everybody's building AI slop games ... what about coding though?

English
MMaximilian Schwarzmüller
Computing/SoftwareVideo & Computer GamesPhotography/Art

Transcript

00:00:00so last week i was on vacation so i only watched the launch of the gpt-6 astra model from afar
00:00:08with some delays since i spent my day robber at the beach then on x or in the internet in general
00:00:15but of course the launch followed the typical pattern we had posts by people hyping up the
00:00:21model people that had early access one could say influencers and then of course a couple of days
00:00:28later after the rest of the world was able to use the model we had more sober or maybe disappointed
00:00:37posts by people that shared that the model seemed overhyped and maybe isn't that amazing now this
00:00:46week i also got my hands on it or i started working with it and where do i start the model is really
00:00:52great at 3d stuff i mean i don't know about you but my timeline has been drowning in blender 3d art and
00:01:02games created by astra now it's hard to verify if everything is truly generated by astra but i got
00:01:08some hints because i also played around with it and at least for the games there are some recurring
00:01:18elements you can spot in these different wiped up games nonetheless clearly the 3d capabilities of astra
00:01:26are really amazing especially compared to what the models were able to do before so clearly it has been
00:01:32heavily fine-tuned and optimized to be better at that kind of work there has been a lot of 3d stuff in the
00:01:40post training data in the fine tuning process i would guess but what about coding that is the part i
00:01:48personally care most apart about and in this launch blog post we of course also have coding related
00:01:57benchmarks and here astra also does really really well now i will say that benchmarks are one thing
00:02:06you know that we had that in all these launches it is possible to optimize models to do well in benchmarks
00:02:13and of course you're heavily incentivized as a lab as an ai lab to make your model do well in benchmarks
00:02:21because imagine releasing a model that does not do well in benchmarks it wouldn't count if it does well
00:02:27in actual usage because nobody would start using it in the first place so i don't blame ai labs those for
00:02:34benchmarks you basically have to do it but benchmarks therefore also don't tell us that much it's it's a nice
00:02:41indicator but yeah you all know it benchmarks are not everything it's more the vibe of using it and
00:02:49and how it behaves when you actually start using it in your day-to-day work and here gpd6 astra for me
00:02:57at least feels a lot like gpd 5.6 sol it maybe has a different set of quirks and features but in the end
00:03:08it's still a good coding model it's a very good coding model it's not horrible at least for me but it's also
00:03:16not groundbreakingly better you still have to know what you're doing and what you're asking for and
00:03:23of course you still can also vibe code stuff that was possible before and that can get you quite far and
00:03:29for many tools or things you needed maybe all you need you don't need to have the perfect code base for
00:03:35every little project or internal tool you need but if you do care about your code base your architecture
00:03:42if you're building something you plan on maintaining and building up one it's the same as with the
00:03:48previous models you need to have proper constraints you need to know what you're doing what you're asking
00:03:54for you need to know how to work with such a model and then you can get good results out of astra that
00:04:01so that has been my experience it still can lead to ugly code it still can lead to unnecessarily complex
00:04:08code though at least in that respect for me it tended a bit less to add layer over layer of
00:04:15complexity and fallback code here and legacy compatible code here which gpt 5.6 sold it a lot
00:04:23it always treated every piece of software as if it were a big well-established enterprise software that
00:04:30needs to be maintained and that existed for 10 years but that's a different story astra is a bit better
00:04:36there for me but it still is a model you need to steer and control and i don't know if that will change
00:04:44when that will change clearly these models are getting better and clearly these models are
00:04:50good at following instructions i mean it's easy to forget this but a year ago we had models that
00:04:57stopped early that didn't do that well when it came to follow instructions that often went astray and
00:05:05whilst that still happens today they're of course much much better they can work on their own on a task
00:05:11for a very long time frame you just want to make sure that you defined the task such and have guidelines
00:05:18in place to ensure that it doesn't wander off but they are much better there and especially of course
00:05:24if you give the model something it can evaluate it can measure it can really dig into a task and keep on
00:05:33going and ultimately solve it maybe not in the most beautiful way but that again doesn't count for every
00:05:40task and depending on your setup it can also solve it of course in in good ways so gpt6 astra is a good
00:05:46model but it's also not the last model we'll ever need and i mean that shouldn't come as a surprise on
00:05:53the other hand i think it's just also the the current meta in which we are where all these labs or especially
00:06:02open ai anthropic in the end they hype up their models so much when they are released and they probably
00:06:09have to to please investors and to get the traction they want to get for these models to keep people in
00:06:16their subscriptions or have new people sign up for subscriptions they have to hype up everything so much
00:06:23that you just you have to be disappointed at some point because nothing can live up to that hype i'm a
00:06:30gamer and you know the same from video games some games are just hyped up that much gta 6 maybe well i
00:06:36think it will be a good game but we have games that are hyped up so much that when they're actually
00:06:41released it's underwhelming or it just doesn't live up to the hype and i think we're constantly seeing
00:06:47that with these models now of course combined with the fact that we get new models almost every week it's
00:06:54really exhausting especially also combined with the fact that we're talking about our our future year
00:07:00we all don't know what we're going to do in in a few years we don't know where our profession is
00:07:07heading and that's not just true for programming it's true for all white collar work we don't know where
00:07:13we're heading we feel like we constantly have to learn new stuff and that of course is exhausting
00:07:18and i feel that's like another big part of why it's so easy to feel really annoyed or disappointed by
00:07:27these model releases because you have that mixture of all these different parts of the exhaustion of
00:07:33the hype and then the the model not living up to it and yeah these are my two cents after being back
00:07:39from vacation it's a good model it's it's much much better at 3d work for coding it's just a good model
00:07:46use it learn how to work with ai properly and i will soon have more to share on that

Key Takeaway

GPT-6 Astra excels in 3d asset generation and instruction-following reliability, but functions as an incremental upgrade for coding tasks rather than a revolutionary architectural shift.

Highlights

  • The GPT-6 Astra model delivers advanced 3d generation capabilities that outperform previous iterations.

  • Astra exhibits a reduced tendency to introduce unnecessary layers of complexity compared to GPT-5.6 Sol.

  • Coding capabilities in Astra match a strong overall standard without representing a massive leap forward.

  • Instruction-following reliability has improved significantly over the past year across AI development models.

  • Constant industry hype cycles create unrealistic expectations and subsequent user disappointment during model releases.

Timeline

Astra model launch patterns and 3d generation capabilities

  • Launch patterns follow predictable cycles of influencer hype followed by sober user feedback.
  • Astra demonstrates advanced proficiency in generating 3D assets and browser-based games.
  • Heavy fine-tuning on 3d training data accounts for the noticeable improvement in graphical tasks.

Model releases trigger an initial wave of exaggerated promotion from early access users, which shifts to realistic assessments after general availability. Astra dominates social media timelines with blender art and generated mini-games. This specific performance jump stems from targeted optimization within the post-training data pipeline.

Coding performance, constraints, and architecture management

  • Coding benchmarks indicate strong performance metrics that reflect lab-level optimization priorities.
  • Astra performs similarly to GPT-5.6 Sol while occasionally producing less overly complex legacy code.
  • Maintained code bases still require strict constraints, proper direction, and clear user oversight.

AI labs prioritize benchmark success to secure initial user adoption, despite those metrics offering limited insight into everyday utility. Astra functions as a competent coding assistant that requires deliberate guidance to prevent poor architectural decisions. Unlike older iterations, Astra avoids treating every minor script as a legacy enterprise application.

Instruction-following reliability and industry exhaustion

  • Modern models maintain focus on extended tasks far better than earlier versions from the previous year.
  • Continuous weekly releases and intense marketing hype contribute to widespread professional exhaustion.
  • Unrealistic expectations set by labs guarantee user disappointment upon model release.

Instruction-following improvements allow models to execute multi-step workflows independently without stopping prematurely. White-collar professionals face mounting fatigue due to the relentless pace of technological shifts and uncertain career trajectories. Excessive corporate marketing inevitably creates a gap between advertised capabilities and practical daily experiences.

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