Astra for Coding: Why Are We Doing This Again?

I think ultimately 90% of the time, Luna XHigh is basically as good as you need, as long as you're willing to step in occasionally before it creates an architectural disaster.

As another commenter pointed out, I feel that the biggest change that occurred in the last 6 or so months is that these tools are removing the human "hurdle" in order to complete a task at all costs. The best way to complete the task is to no longer ask for input, clarify unclear things or use existing solutions but code the whole thing yourself from start to finish.

I have had the misfortune of working with such people who are now encapsulated in Opus 5/Fable/Astra which means that you WILL get a solution, but it won't generally be maintainable or useful. Multiple times have I found myself stopping Fable or Opus or even Sol from building their own JSON validator in Python or god knows what else, because at the end of the day, the reward is to complete the task.

It's also one of the reasons why I'm finding older models more useful for the type of work I actually do and why I've been favoring something like Deepseek Flash. Just started using Flash 4.1, so not sure if it exhibits the same maniacal approach to tasks as the Western counterparts. (I only briefly tried GLM 5.2/5.3 and for nothing major, so I couldn't comment on those).

For context, 80% of my professional work relies on adding functionality to an existing code-base that is very difficult to work with, has a ton of business logic scattered across and was built in a go-go-go fashion many years ago. Since then people kept pilling "features" on top with no testing strategy in mind apart from the business manually testing it. Letting something like an LLM loose on the code-base would introduce soooo much risk that it's just untenable so the only way to work is to really isolate changes and then try to build out small reusable components. Even so I find Opus go off on a tangent "Hey, let's not bring in Markdig, I'll build my own Markdown rendering engine, give me 7 hours...".

I have written on the subject of LLMs previously on my personal page, I find them completely unnecessary and a trove of theft and value extraction through theft, but I understand that they can provide benefits when used judiciously. However, despite all the hype in the last few months, these latest models feel and behave off.

If I hold the answers to a test, you might score more in a test if you break my arms to get the answers out of me, but that doesn't make you smarter.

> Maybe it’s objectively good for a codebase that is entirely written by agents and only needs to be understood by agents.

Yeah that's what they're aiming for. This is why codex and claude code probably doesn't have cursor like editor window. They don't want humans to read and write code

Ironically I burned out Fable usage early this week because of Astra using it to run inane full codebase reviews over one line changes, so I have been using Astra extensively.

We need a word for “potentially highly capable, but in reality an idiot savant” to describe certain models. No, I don’t need you to write a tmux emulator in bash to test your changes bro, just ask me to run the command.

I asked Astra for fully working code, and it gave me bad code.

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

I love this dance we are doing where when people write the "AI models are garbage machines that produce garbage and are no where close to the fantasy being pedalled by the Crypto bros who pivoted to AI" it always has to be caveated with "AI models are useful and I am highly productive with them"

It feels like people should just be able to say "This article comes with the standard disclaimer" and just dive into the meat of the article without wasting time.

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"But for how much more Fable costs, for how much more Astra costs, I do not feel like the results are there."

we are in the middle of the beginning. Its just a weird take to talk about the newest model like this while we are still in a R&D phase.

And these points don't matter if you let it search and analyse a bug, for example, or if you have good harness and a good architecture and let it do small PRs or if you do stuff no one needs to read (yes a software engineer also needs tools)

Just switch back and wait a little bit?

The first paragraph is unnecessary - why start off so arrogant?

I see this a lot in Asian writing - as if they have to first establish that the West is “doing it wrong” at the societal level before I get to read the rest of their usually unrelated message.

I didn’t like how the author classified all 3D gamedev as slop as if it’s a pointless endeavor - but talks about spending money on ChatGPT tokens to build a “software factory” as if it’s some ingenious plan. I don’t think the author realizes he is the slop dev.

And “shitty code” doesn’t mean anything in-and-of-itself. What are you making and why? A software factory???. It ain’t the code bro.

Anyway, I read enough.

> I’m more and more convinced that all of AI engineering is Neijuan (内卷, meaning curl inwards). In China it describes a system that demands ever more effort and competition without improving output

I don't know what to say, except that articles exactly like this one have been showing up constantly for the last three years, and literally all of them were obviously outdated and irrelevant within about a month.