https://www.anthropic.com/engineering/advanced-tool-use
They discussed how running generated code is better for context management in many cases. The AI can generate code to retrieve, process, and filter the data it needs rather than doing it in-context, thus reducing context needs. Furthermore, if you can run the code right next to the server where the data is, it's all that much faster.
I see Bun like a Skynet: if it can run anywhere, the AI can run anywhere.
<Alanna> Saying that Java is nice because it works on all OS's is like saying that anal sex is nice because it works on all genders
EDIT: someone has (much to my joy) made an archive of bash.org so here is a link[1], but I must say I’m quite jealous of today’s potential 1/10,000[2] who will discover bash.org from my comment!
you could also run java with js if you are brave enough https://kreijstal.github.io/java-tools/
If anyone ever requested/used an eggdrop(?) bot from #farmbots or #wildbots on quakenet then thanks to you too; that was certainly one of the next steps down the path I took. A (probably very injectable) PHP blog and a bunch of TCL scripts powering bots, man I wish I could review that code now.
By contrast `bun install` is about as good as it gets.
So how did it work back in the day, people would just submit text and it would get upvoted? I always assumed like half of them were just made up.
As far provenance, I assume a lot of them were made up too, but this one was real.
> The challenge
> Traditional tool calling creates two fundamental problems as workflows become more complex:
> Context pollution from intermediate results: When Claude analyzes a 10MB log file for error patterns, the entire file enters its context window, even though Claude only needs a summary of error frequencies. When fetching customer data across multiple tables, every record accumulates in context regardless of relevance. These intermediate results consume massive token budgets and can push important information out of the context window entirely.
> Inference overhead and manual synthesis: Each tool call requires a full model inference pass. After receiving results, Claude must "eyeball" the data to extract relevant information, reason about how pieces fit together, and decide what to do next—all through natural language processing. A five tool workflow means five inference passes plus Claude parsing each result, comparing values, and synthesizing conclusions. This is both slow and error-prone.
Basically, instead of Claude trying to, e.g., process data by using inference from its own context, it would offload to some program it specifically writes. Up until today we've seen Claude running user-written programs. This new paradigm allows it the freedom to create a program it finds suitable in order to perform the task, and then run it (within confines of a sandbox) and retrieve the result it needs.
This is only true for older .NET Framework applications.
Please give me Java tools over C, C++, JavaScript or Python ones, any day of the week.
Only .NET and Rust compare equally in quality of DX.
AI tools value simplicity?!?
Check in the Python dependency management chaos, what it is the proposal this month, from what AI startup doing Python tools in Rust?
If the build script being a DSL is the issue, they're even experimenting around declarative gradle scripts [0], which is going to be nice for people used to something like maven.
Plus last time I checked Oracle lost that lawsuit.
For example, if I have a struct `PageEntity` with a field `Id`, and I am iterating over a slice of such IDs, I would prefer using `pid` instead of `pageEntityId` as the variable name. But Java APIs and conventions tend to use these longer names, so I find it takes more thinking to remember the different names instead of quickly seeing the behavior of code at a glance.
Java also tends to have a lot of inheritance which results in these long glued-together names and makes it harder to follow program flow because behaviors get introduced in multiple different places (i.e., it has the opposite of locality of behavior).
But those are just my opinions and experiences! I know many people love Java, and it is a versatile and powerful language.
To everyone else: I acknowlege that this post is not adding value but if you were one of the lucky 1/10000 you would understand that I have no choice.
How many mass security incidents have there been with npm just the last few weeks?
Java is possibly the safest bet on the future, it's open source both in spec and in the most common implementation (OpenJDK), and is so widely used that there are multiple FAANG companies critically dependent on Java working that alone could continue the development of the platform were anything happen.
Besides, Oracle has been a surprisingly good steward of the language.
But the majority of projects are on a newer JDK than 8 for quite some years now.
Also, Java's ecosystem is unparalleled (top 3 in size, depending on domain it usually has the best packages (e.g. typical backend-related functionality)), has stellar performance, a huge developer base, best-in-class IDE support, even LLMs understand it exceptionally well (given how widely represented it is in the training corpus, plus has a decent type system) if that's your thing.
For a typical backend system, you really have to have a good reason to choose something else at this point.
Gradle is better from this perspective, and hopefully with its "kotlinization" we will see some stability, which was the biggest issue it had before.
Super premature optimization. It’ll hallucinate what lines it needs to read, it’ll continuously miss critical context in favor of trimming tokens.
Luckily we can now hook and force the agent to read full files at least once.
Java is the running joke of verbosity, and you are too if you seriously argue that it's not.
In any case, what are the proposed benefits of the "kotilization"? I tried it about a year ago but realized that it's just a syntax level-wrapper around the same old DSL underneath. In the end, I still viewed it as an ill-described DSL with a massive learning curve outside of happy-paths.
But I do know that you are meaning stuff like AbstractFactoryFactory, but you do realize that there is zero need to write anything like that and you can (and people do) write bad code in any language?
That's all that's needed to create a sense of caution for would-be adopters.
Oracle lost the lawsuit and I do agree with the decision in that APIs should be freely replicated, but let's not pretend that Google was some saint good guy here fighting the good fight, they were just cheap and aggressively capitalistic.
The problem with Gradle is that it never had a clear philosophy to begin with. It's trying to be everything to everybody, changes best practices every year and has enough features that the project at hand could entirely be built out of Gradle scripts itself.
And oh, it still requires an update to run everytime a new JDK is released even though the SDK is the most backward compatible thing ever written.
Why wouldn't I choose java
It has similar bases on facts.
seems to work. relies on that individual quote being indexed, and google SERPs feeling like returning full results at the moment, of course. when the latter fails, I've found success with site: queries on Bing (of all places.)
Legally the case was about copying declaring code from a proprietary product, not an open source one.
Evidence is easy - think of a problem and ask LLM to generate idiomatic examples (leverage Java streams, with functional decomposition, etc) in Go and Java and with error handling. You will find that more often than not, the Java line count is far smaller.
Now if you complain about slice handling, I'm with you.
I left a place using Java to run edge apps and the footprint was a major issue.
The implications of a judgment in favor of Oracle were staggering. Any codebase that is extensively dependent on a proprietary API is legally locked in to using that company's proprietary implementation as long as that company asserts copyright on its API. Anyone who implements the same API to offer a drop-in alternative to the proprietary product is infringing -- even if a someone privately reimplements the API without distributing the reimplementation.
Which immediately implicates WINE (Windows), Mono (.NET), ReactOS (Windows), Darling (macOS/Darwin), GNUStep (Cocoa/OpenStep), Anbox (Android), Ruffle (flash), GNU Octave (MATLAB), Mesa 3D (Direct3D), ZLUDA (CUDA), and DXVK (Direct3D 9/10/11), to name a few of the most popular...
These famous cases set the legal tone for the entire world actually.
Idiomatic, Modern Java is written quite differently. Today, Go has a lot of arcane, noisy, complex code too. Ex: many, many k8s Go projects.
To this day Android Java is not fully compatible with Java proper, and Kotlin became Google's version of C#.
Reimplementing an interface != stealing code.
People end up choosing something that has batteries included so they can focus on solving business problems. A programmer who will superficially understand SpringBoot without understanding how it works. Really, there is no magic there - its a few core concepts - annotations, bytecode enhancement and dynamic proxies. Maybe Im missing one or two. Everything else is built on top of this.
This is regardless of language/ecosystem. If I do not understand the fundamental concepts, I will never be successful in that ecosystem.
But that's like saying that a bicycle is better than a car, because the first is simpler to understand. (At the same time, nothing prevents you from assembling a bicycle in Java if that's indeed what you need. But for general long distance travel you are better off starting with a car frame, aren't you?)
It's nice to be able to see what your changes do without rebuild and restart.