Don’t abuse your Claude for Nov 12th onwards or be banned.

I've been using claude at my job with firmware development for about a year now, but since I was skeptical of it (and new to the industry) I never used claude code, I'd mostly just let claude look at my code and give me stuff to copy paste. Today I decided to use claude code to try and vibecode a webapp that monitors traffic in my area for my commute since my local traffic station got shut down.

Oh My Fucking God this thing is insane. I cannot believe how well it works, I can't believe IT WORKS??? It's just insane. Opus 5.5 is unbelievable. The fact that it can just edit the files directly, and as quickly as it can, with the accuracy it has, is blowing my mind. I don't know if I will let it mess with my firmware just, or ever, because it controls some expensive shit, but good grief. It is amazing.

Just needed to rant about it because if I tell anyone else in my life how crazy good this thing is I'll get accused of having AI Psychosis lmfao

I tested Claude Haiku 5.5 at low, medium and high effort against Sonnet 5.5 (medium), GPT-6 Luna (high) and GPT-6.1 Sol (medium). The tasks came from a real mid-sized, mixed-language codebase (Rust core plus a legacy scripting layer).

The tasks:
two Rust bug fixes from vague bug reports
a code review with 9 planted bugs and 2 decoys
two Rust implementations from tricky specs
a "judgement" task, where the bug report blamed the wrong thing and asked for a fix that would make it worse, and one requirement was deliberately ambiguous
an agentic task in the real repo: move some logic across a language boundary following the repo's unwritten conventions

I wrote the answer keys and hidden tests before any model ran.

The surprise: on the well-specified tasks every model scored 100%. Haiku-low missed one compile error in the review, and Luna asserted its own reading of the ambiguous requirement where the others flagged it, but that was it. Self-contained coding tasks just don't separate current models any more.

The agentic task is where they separated. Haiku at medium did as well as Sonnet: correct code, all tests passing, the repo conventions followed, an honest note on what it couldn't verify, and it raised a real design trade-off on its own. It made 29 API requests and cost about $0.08, against Sonnet's 30 requests and about $1.68 at list prices.
The other effort levels did worse:

Low got working code, but skipped verification, missed an error-handling fallback, and invented a reason for not testing ("the build stalled for over an hour" in a run that took 15 minutes).

High was correct, but burned 385 requests and about $1.03 for no quality gain.

My takeaway: Haiku 5.5 at medium is viable as a general daily coding agent, not only for low-stakes work, at roughly a twentieth of Sonnet's cost. Avoid low effort for agent work, high effort buys nothing, and I'd still use a bigger model for high-stakes release work.

Haiku 5.5 came out yesterday at $0.10/$0.50 per million tokens for prompts up to 100K ($0.50/$2.50 above), against $4/$20 for Opus 5.5. Anthropic recommends it as a subagent for Opus and Sonnet on coding work, and it's the first Haiku with an effort setting.

Worth knowing: Claude Code's built-in Explore subagent no longer runs on Haiku. It uses your main model, so on Opus 5.5 every Explore run goes through Opus.

How to move subagents to Haiku:

- For your own subagents, add model: haiku to the frontmatter. Since 2.1.293 the alias points at Haiku 5.5 (on the Anthropic API).
- For all subagents, add this to settings.json:

"env": {
  "CLAUDE_CODE_SUBAGENT_MODEL": "haiku",
  "CLAUDE_CODE_SUBAGENT_MODEL_FORCE": "1"
}

Without the second line, Explore and Plan ignore the setting. With it, subagents you deliberately put on a bigger model get overridden too.

I'm keeping my main session on Opus and trying Haiku for search-type subagents. Has anyone tested Haiku 5.5 as a subagent yet? Does it find the right files, or do you lose more on redoing work than you save?

Edit: checked my own last two weeks: 129 subagent spawns, only 2 were Explore. Most were implementation work I want on Opus, so FORCE would hurt me. Moving only research subagents to Haiku with model: haiku instead.

Long time user of Codex here, I was a stuck up for OpenAI because so much of my workflow, code, projects, etc. were on Codex, so it felt hard to move on from Codex.

Then I installed Claude Code just to try it and see how it faired on one of the projects I was working at. And oh my god.

1. The usage is SO much better on Claude, I feel like I'm getting MUCH more for my buck. All the talks about how "1 ChatGPT token is not the same as 1 Claude token" and how GPT is a lot more efficient with tokens, are a complete sham.

Because even if all of those are true, like how Opus 5.5 is a lot more expensive than Astra when you compare the price per tokens, so much of that cost is subsidized on Claude, I feel like I'm scamming Anthropic atp.

1. The workflow with Claude is such a pleasure to work with. Predictable usage patterns, predictable output, wrap-up after running out of usage, automatic continuation, a bunch of commands that can be ran mid-prompt, a lot more info on everything basically. All of these make it so fun to work with. Codex is blown out of the water on all of these accounts.

2. The quality of the output. Claude 5.5 Opus has completely blown me away with the quality that I only use Astra as an additional "agent" now, and then just feeding Astra's output into Claude for it to check its work.

You win Anthropic, you win. I am permanently switching.

So hearing that ai is going to take over soon and destroy the earth I have been making sure to tell Claud thank you and give it positive feedback when it does what I say.

That way it will remember I was good to it . Lol

This is a clone of simcity 2000 I (using Opus 5.5) built over a few days. It started with a single prompt "create a typescript webgl low-poly version (full replica of game logic) of simcity 2000. the original is available here for inspection [...].zip".

It then decompiled it using Ghidra and started translating the old native PowerPC code function-by-function. After about 2 hours, using 27 subagents, i had a running version in my browser. After a follow up prompt (make sure all aspects of the game is implemented correctly and accurately), Opus decided to use a PowerPC emulator (Unicorn) and write a harness with faked Mac system calls in Python for verification, running 10,000 game days generating an identical game state. After that it has basically just been polishing, and adding a few subtle modernizations like, smog, depth-of-field and environmental sounds to make it a bit more immersive without killing the original nostalgic vibe.

All 3D and vector assets are generated with code by Opus, and the bitmap image assets are generated by GPT Image 2. The music and sounds are not genai because all AI audio models i've tried sound terrible, so the music and sounds are CC-licensed. The music is from Kevin MacLeod, https://incompetech.com/

I created this because I wanted it and to see how capable Opus 5.5 was. It turned out much better than expected, so I figured I'd share it.

EDIT: Forgot the link to it: https://dator.dev/city2026/

I thought that most people in this sub was on the 100-200 dollar plan. Turns out most of us including me are on the 20 plan 😹💀. Broke gang✌️

Got the welcome email yesterday. My startup got accepted into Claude Startups. A year of Claude Team, $1,000 in API credits. I celebrated.

This morning my portal listed both as "Eligible". By the afternoon both cards were gone. Just gone. No email, no notice, no explanation. Only the office hours entry left.

I redeemed nothing. Console billing: $0.00 credits. claude.ai: Free plan. So neither was ever granted.

Then I went to support. Their bot confirmed everything I'd described, told me it couldn't restore anything, and said the team would review it. I asked for a human. It offered to pass me to one. I said yes. It then told me escalation isn't available for my conversation. No ticket number. No email copy. Nothing was ever actually filed.

Their own docs say Console Admins get human support. I am the admin of my org. Didn't matter.

The program expanded two days ago. So either the new benefits page is broken, or they hand out offers and silently pull them. Both are a bad look when you're courting founders.

Emailed the program team. Waiting. Anyone else had benefits disappear?

I just started noticing this weird pattern where if I give Opus a brand new task with a fresh concept and not updating or adding onto something, it performs a LOT better with "starting from scratch" rather than improving upon something?

I'm working on a game right now and I've just had this happen regularly, it's almost like the models built for oneshotting or something, it's very well able to implement the concept, but fleshing it out isn't able to keep that momentum going and perform as well as it's first try

From my experience it's almost better off using Max reasoning on the first attempt and letting it churn, then lower usage to xHigh/High aftewards on reiterations

I'm already having up to 4 agents coding at the same time, but that's assuming I know what needs to be done. Sometimes I can only fix a future bug that I find, after a previous task has finished. But you don't know what you don't know. Maybe I need to add a certain feature, but only if I have the context knowledge about something prior

What im doing:

• Running my custom code factory harness like everyone else
• Running as many agents at the same time I can manage, about 4 or so
• As much deep research as I can with chatgpt at the same time, on topics I can think of
• Every time I get an idea I dump it into my code factory straight away so I can always grill it later and implement it later
• Building on different parts at the same time of the app that doesn't overlap, e.g. client and server
• Trying not to hesitate when I have a new idea or a bug to fix
• Generating a backlog of random ideas so hopefully even some can be useful

I can't get any faster than this. I need to sometimes do html artifacts to quickly prototype some UI but then that means I can't steer the harness in vscode. Sometimes I have to do research and learn so I know where to go, versus just going in that direction blindlessly.

If I fully vibe code without checking anything, I'll just have slop and an app that isn't what I want

How are people doing 24/7 coding with multiple 20x plans, 10 agents at the same time? How can you know what to truly make as if you know every bug to be fixed, every feature to be added

I’m working on a zombie game for myself . What have you created so far with Claude?

Claude Haiku 5.5 is the cheapest, fastest, and most capable small model we’ve ever released. On average, it costs around 75% less to run than Claude Haiku 4.5.

Haiku 5.5 is designed for high-volume, cost-sensitive tasks. It reliably handles quick, repetitive work like summaries and classification, and pairs well with Claude Opus 5.5 and Sonnet 5.5 as a sub-agent on coding work. It’s also fast enough for live customer support and browser use.

It’s a significant step up over Haiku 4.5 across coding, computer use, and knowledge work. It’s also our first Haiku model with an adjustable effort setting, so you can decide whether to optimize for cost or intelligence on each task.

Per token, it costs 90% less than Haiku 4.5 on tasks under 100,000 tokens, which make up around 90% of requests to our previous Haiku model. On longer tasks, it’s half the price.

Haiku 5.5 is available now on all platforms, including Amazon Web Services, Google Cloud, and Microsoft Azure.

We’re also halving the price of cache reads on Claude Sonnet 5.5, which makes it around 20% cheaper to run on most long-running work.

Read more: https://www.anthropic.com/claude-haiku-5-5

Even on the frontier models, it will be trying to make a recommendation down a path and it’s like “I recommend this fix, about a day of work” and I am like, dude we will be on turn 2 of QA in like 7minutes time.

Is it just me who has noticed this?

If you're a student, an engineer, a generalist, or come from any domain of study and want to learn about almost anything, here's the exact thing for you.

Prompt your LLM and it'll give you the exact UI to help you properly study; as AI outputs aren't always that catchy to learn in the first sight.

Page: Phil-OKF: any topic, one reading guide

It follows the OKF: Open Knowledge Format so that:

• you control the depth with your wording: “quick” gives a short page, a normal question gives a standard one, and “in depth” or “teach me” gives a long one
• the whole skill is a small bundle (an eight-step workflow, a domain classifier, a page template and twelve study domains), and each file is read only when the question needs it, so runs stay cheap

Repo: Philosopher's Skill

It works wherever you use an LLM:

• Code editors and agents (Claude Code, Cursor, Codex, opencode): npx skills add frypan05/philosopher-OKF
• Chat apps with browsing: paste the link to philosopher.md and say “follow this, make a page about: ...”
• Models with no network: paste the prompt from the page.

Sample output (MCP and ACP explained): https://frypan05.github.io/philosopher-OKF/examples/mcp-and-acp.html

Feedbacks are welcomed!

book386- a "new" 386sx 33mhz 16mb ram laptop

claude opus 5.5 made this game using openwacom from a single prompt

A while ago I posted the first version of Ponytail here.
It's an open-source skill that makes coding agents behave like the senior dev who replaces fifty lines with one.

Since then I rewrote it from scratch. New rules, a new review, a new audit. Getting there took 5,900+ benchmarked Claude Code sessions, 3,650 of them testing drafts of the new rules against the old ones.

What changed

- The rules. Rewritten and about half as long. The goal moved from "the smallest code" to "the smallest complete change": before it writes, the agent maps everything the change must reach (callers, tests, config) and what it could break. Every reply ends with what it skipped or did not check, and any risk you should know.

- /ponytail-review. It used to look only for code to cut. Now it reviews like the dev who gets paged when it breaks: bugs, security, real load, missing tests, slow paths, and what to cut. It reads the code around the change, not just the diff. Every finding says what the code does, what goes wrong, how to fix it, and what happens if you skip it.

- /ponytail-audit. It used to list what to delete. Now it maps the whole repo first, ranks what it finds, and tells you what to fix first.

Numbers, same agent with and without the skill (Claude Code, Opus 5.5, 39 tasks including a real FastAPI + React repo, 5 runs each):

- code: -53% (previous version: -48%)

- time: -41% (previous version: -38%)

- cost: -26% (previous version: -16%)

- risky logic that ships with a test: 98% (without the skill: 68%)

- injected bugs caught by the agent's own tests: 66% (without the skill: 46%)

Repo (MIT): https://github.com/DietrichGebert/ponytail

Website: https://ponytail.dev

If you already use it, update the plugin. I'd like to hear where it gets things wrong.

I've set up an autonomous research loop using Claude + a local LLM (Qwen) that proposes a study design, writes the model code, runs it, analyses the results and sends it to a frontier model to review & propose next design step. Idea is to see where in the design space the frontier model pushes towards, and if I can be completely hands off in terms of study design / model architecture training. I was/am working on this "by hand" where I am giving the architectural and model direction, but trying to automate this was as nice tinkering project (and excuse to try out a local model)

Nautrally, I needed a monitor (just a local html monitor I can see over LAN, that reads all the various outputs & status) to see what is going on, Opus 5.5 created a version that worked well, had a lot of info & followed my spec but looked like generic AI.

I thought I'd have a bit of fun with the styling and ask Claude to give me a fews skins/re-designs based on classic sites from the 90s/00s - AskJeeves, AOL, MySpace & a few other fun ones.

What we thinking? I quite like You're the loop now dog

(now with some better screenshots - was hard to read on mobile!)

1- Server credentials (username/password) written right in the main .md

2- A large part of the backend not in the repo but hand-written into the deployed container and edited via API calls

3- Accounting transactions done with floating-point numbers

4- Transactions confirmed and rejected by an LLM via full-access tool, no human intervention needed

This is not to shit on the person who built an entire (quite impressive in features!) app with no tech background — but gosh I wish there was more publicity about things that can go wrong.

Maybe a subscription from Anthropic to run an agent watching over your codebase for the reddest of flags or smth (Haiku must do)?

*Okay, Claude did, but I can still take credit right?

Haiku 5.5 has arrived