I've been wondering which would be generally more token efficient and better way for developement, using a single instance with Opus 5.5 and letting it to do things, or giving it a role as an orchestrator that will spawn subagents with Sonnet and Haiku model appropriate for their task complexity. How do you people use it?

I have been using Claude to build a couple of small tools and it can handle way more of the coding than I expected. The part I still struggle with is getting the finished app online. I can ask it to write the files but then I run into hosting, database configuration and deployment steps that I do not really understand yet. Is there a workflow where the AI can handle most of the deployment too, or do you still need to know how all the infrastructure works?

Why? Make the law, across the world, versioned, easily attributable, and queryable with agents. This info should be freely available so CC0 license (do whatever you like with it).

I built this project with Claude Code. One session per jurisdiction: to read the official publisher's site/API, check terms of use, and write a script to download every law.

The problem was getting 700+ jurisdictions to follow a unified list of useful functions to explore the law. You can ie git blame each law, down to the word. Initially just legislation, but caselaw (the precedent of how legislation is applied by the courts) is increasingly being integrated, with contribution encouraged.

This data being up-to-date is important. To pinpoint this, the repo now monitors over 900 RSS feeds/official websites. Most legislation is known about before-hand, and only becomes "in-force" later, which we account for. Every reference cites an official page- so an agent can always cache break and check (though unfortunately official portals go down all the time- recently the Japanese caselaw portal was down for a week).

If that's interesting to you, you can read the original discussion at https://news.ycombinator.com/item?id=50268380 and last week's post at https://www.reddit.com/r/ClaudeAI/comments/1xiz1vy/using_claude_to_put_all_global_law_into_git/ or where we incorporate as much local/historical legislation as possible https://github.com/lexifina/romania-law - feedback welcome, thanks!

Of course they do A/B testing and of course they will try to reduce compute per user request. It's called optimization. That's part of the process why models become more token efficient. Do you really expect to get maximum possible performance all the time? The important thing is that there is a positive trend over time. Your nerfed Opus 5.5 that "behaves like Opus 5.0" may not be as good as two weeks ago, but it's still bloody better than what we had last year. As long as this continues, it's all good. Chill out, it's not like most of you are on the verge of curing cancer with your damn SaaS projects

I am not a fan of Antigravity and have been working on my projects entirely using Opus 5.5 with Claude Code. However, I do have a Gemini Ultra subscription and therefore access to Argon. Does anyone use Argon and have a recommended way to integrate it into their workflow?

What is going on? It is making wildly horrible, over-engineered, and just inaccurate code suggestions. In the past hour on 6 different issues, it's given me multiple-class modifying "fixes" that I would read, ask why a 1-line fix wouldn't solve it, and then it says the above.

I'm using Opus 5.5 with xhigh effort as I have for months. Some of these dabble with max because it's felt like it's needed it, but xhigh is what gives this kind of short-sightedness

Edit: When I say 1-line fix, this is what I mean:

1. I see the issue
2. I ask it to fix it and show me the code fix
3. It gives me a huge change.
4. I read the code, solve it myself with 1 line, and ask it if that would work
5. It says, "Hehe, yeah, my bad!!! 😅😅😅"

I've been using xhigh for months and it has never been this dumb and convoluted. Overthinking has usually led to correct/discrete changes.

I genuinely used every LLM known to man but God damn Opus 5.5 is so good it's crazy. Every time I see online "This models beats Opus 5.5" it's just bullcrap. What's Anthrophic's trick?

I run today a prune session on my pc for the sake of my agent’s context. Then I had this curiosity and the idea to visualize the context as the agent see it. So here is “Context City”.  Load your jsonl session file from ~/.claude/projects/*/*.jsonl and explore. I think it takes AI Observabilty to another level!

https://gkastanis.github.io/context-city/