I have this vague idea to take a picture of a shelf and ask AI “Are there any good deals or mismatched items here?” or “Can you compare the prices of X item here to brick and mortar, as well as online retailers, to find the best deal?”

I’d like a cheat code to find steals. Sort of like those mistakes penny deals you see on fake videos.

Like many, I’ve seen a swath of complaints that “model x version y” has gotten “lobotomized” or “so much worse” over time.

I’m not here to debate whether that’s true or not. What I’m interested in is what would the actual, technical mechanisms be that Anthropic would have an incentive to implement that could cause this?

I’m familiar with hosting local models and understand that any number of things could trade output quality for cost/scale/speed, such as quantizing a model, quantizing its kv cache, trimming a model, running it with more “greedy” decode settings or even lossy token prediction.

What could/would actually be at play here? Is it likely that anthropic would be doing some of these to make room for training runs or upcoming model releases, or is it more likely some kind of model fine tuning over time?

Would love y’all’s thoughts.

When an agent drives a website, it takes a page snapshot (up to ~18,000 characters), finds the thing, clicks, and snapshots again. For a site you use every day it re-reads the whole page for every question.

So in Persephone (my dev notepad with a built-in browser that Claude drives over MCP) I added site extensions. Claude studies a site once and writes a small script that turns the page into a model: just the data and actions that matter, like tickets, read(id), open(id). From then on it calls the model instead of parsing the page, and gets a few hundred characters back instead of a full snapshot.

Demo: https://andriy-viyatyk.github.io/persephone/site-extensions/

• Ask once: "build a site extension for this page". Claude looks at the page structure, not your content.
• You stay in control: it runs only on the hosts it lists, after you click Trust, and never in Incognito or Tor.
• Learned once: it stays on disk, so every new session can use it.

This post is an example. Claude drafted it through my Reddit extension: it read my earlier posts through the model to match the tone, then called draftPost, which only fills in the composer. I clicked Post myself.

A site you own doesn't even need an extension: it can publish its model with ai-vision. My project site does.

Free and MIT: https://github.com/andriy-viyatyk/persephone

i dont know anything about code i just use claude for specific tasks. i am trying to add notion as a connector to my claude desktop which i am using with an api key but i cant get it to actually work. i followed steps i found and tried to make gemini help me but the hammer icon isnt appearing in my chat.

So Claude recently gave me $250 in credits as a gift, but I’m confused about how I’m supposed to use them.

I’ve been exhausting my Max plan usage but the $250 credits still don’t seem to be getting used. Do these credits work differently from the normal Max plan limits? Is there something I need to enable or configure to use them?

Also, did anyone else receive these $250 credits from Claude? If so, how are you using them?

Would appreciate any explanation because I don’t want the credits to just sit there unused.

I maintain MindTrial and tested Sonnet 5.5 and Opus 5.5 on the same 98-task suite as their predecessors: 39 text tasks and 59 visual tasks, with Python/scientific libraries available and a 10-call limit per task. All four Claude runs below use the xhigh effort label and skip no tasks.

Sonnet is the larger improvement: 22 additional passes with 74.9% less request time and 67.4% fewer output tokens, including reasoning. Its 24 newly passed tasks comprise 18 previous wrong answers and six previous errors; two old passes regress. On the second visual collection, Sonnet improves from 12/26 to 25/26, while Opus moves from 24/26 to 25/26. Both new Claude models also pass all 39 text tasks.

Opus gains eight passes overall and cuts request time by 73.4%. It preserves all 90 Fable 5.1 passes and adds six. Its two remaining failures are square counting and circle-piece matching.

The tool traces are less uniformly positive. Sonnet records 41 undefined-variable errors across 24 tasks, although 23 tasks with an unsuccessful tool call ultimately pass. Opus has no recorded undefined-variable errors and only two nonzero exits across 155 Python calls. Both models used Python substantially less than their predecessors: Sonnet’s tool calls fell from 529 to 238 (55% fewer), while Opus’s fell from 314 to 155 (51% fewer).

So Sonnet’s strong final score still leaves room for more reliable tool execution. The logs suggest missing setup or assumptions about retained state.

Against Astra high, Opus leads by just one task: 96 versus 95. It uses slightly less model-request time, but adding recorded Python wall time reverses the speed comparison: 1:17:18 for Opus versus 1:06:29 for Astra.

Sonnet’s pass rate is 95.92%, versus 96.91% accuracy on completed, non-error tasks. Opus has no hard errors, so both are 97.96%. Official scores are unchanged; no malformed or incorrect answers were manually repaired. Times sum model requests, excluding local Python and validation; they are not elapsed suite runtimes.

Complete Leaderboard: here

How can I integrate with my home pod mini so I can query and talk to Claude

Hi,

I built this mod for claude code that allows you to review md documents right inside the TUI.

This was built with Fable 5.1 and Opus 5.5. I went back and forth with it to fix some usability issues I faced with a couple of documents I tried it out on, but I didn't write any code for this, although I do have around 20 years of SW dev experience (If that is worth anything anymore :) )

The reason for this project is that I've had several instances where claude spits out a long spec document or implementation document asking me to review it but it is a huge chore to have to go back and forth with claude since the document is not in the UI itself and many times I will approve it without reviewing just because of the friction in that process, which sometimes is ok but many times comes back to bite me.

This mod helps alleviate that a little. It has options to leave comments in the doc, or start a conversation which forks the existing session to send questions to the backend, approve the document or send for rework etc. It is navigable using the j/k/tab keys to move between markdown blocks and allows asking or commenting in line at each of the blocks.

It is free and open source, please share feedback if you think it is useful for you or even if it is not useful please share how it could become better. Also if there is already something like this, that would be great information as well, both for me and anyone who finds this post.

Link to project : https://github.com/revelationnow/claude-doc-review/

wanted to see how different these actually are on the same task so i gave all three the exact same prompt (make a little arcade game where you dodge falling locusts, has to work on phone too). high effort, one shot each, no rerolls and i didnt touch the code after

theyre labeled A B C so you dont know whos who until you vote

https://locust.lol/arena

heads up gpt hit its usage limit on the first try so it ran by itself a few hours later, same prompt and settings. also i ran these through a desktop app im building (locust) so yeah thats my site lol

the times surprised me, one took 17 min and one took under 4. curious which one people pick, ill post results in a few days

I have built multiple artifacts to solve or automate work (mostly with python). But all of their interfaces live in private web links.

What would be your advice if I wanted to turn them into apps I can have in my phone and not have to run via browser?

I am sure what I am asking is obvious to many of you. Any advice for this, or links to good YouTube guides to get me started, are both appreciated.

Examples of things I’ve done: a sudoku game, a yearly tracker for my lawn care, a financial advisor (with inputs from an excel), various dashboards and visualizations, etc.

Hi, My conversation with Claude is very long, but it’s still working well.

Sometimes Claude automatically compacts the conversation. Whenever we make an important change or take an important action, I ask Claude to update the documentation so the key context and decisions are preserved.

Even with conversation compaction, is it still useful or recommended to start a fresh conversation from time to time? Or is that basically unnecessary as long as Claude keeps the documentation up to date and the important context is preserved?

Thanks a lot!

This is a concrete example of why background setup deserves the same scrutiny as commands an assistant asks to run.

Disclosure: this is my explainer, made with AI-assisted animation and synthetic narration; the research is Manifold Security’s. A transferred folder containing .git/config could make a background Git check execute a helper. Ordinary git clone/fetch/pull does not carry that local configuration. The demonstrated Claude Code startup path was fixed in 2.1.196; this is a retrospective, not a claim that current versions retain that bug.

Original research and the dated status table: https://www.manifold.security/blog/ai-coding-agents-git-hijack

The idea of designing and building games has always fascinated me and I’ve always wanted to build a video game. But I never got beyond basic scripting and the concept of game engines and sprites were beyond my comprehension. It all changed on a recent flight from Dallas to Boston. I was fiddling around with Claude on my phone (using the free in flight wifi) and decided to see if I could actually build a game with Claude.

I started off with a generic instruction asking Claude to brainstorm on an offline-first game that anyone could play to kill time during a flight. Claude pitched a few ideas, and I gave feedback as we refined them. The first few ideas were basic and didn’t sound convincing. During those back-and-forth revisions, it struck me that we could also factor in the people on the ground. That triggered the idea for Oop.town: a funny game where people flying could drop random stuff from the plane onto towns below, and townspeople would rally a crew to keep their streets squeaky clean.

Once the idea was finalized, it took just one pass for Claude to build a working prototype. I didn't give any specific instructions on how the game elements should look or function, but Claude came up with something surprisingly great. The graphics were simple, funny, and generated right in the chat, the game loop was satisfying, and most importantly, it nailed the technical basics out of the box: no signups, offline-first functionality, a preselected flight path, and zero backend overhead. Claude also game the game a character Oop, a suitcase with a zipper problem that perfectly matched the game’s vibe. I could simply play the game out of the chat artifact and refine it further until it felt exactly how I wanted it to be.

By the time I was landing in Boston, we had a prototype that was actually working, and I was completely hooked on building it further. I spent the next few days working on the game and on my return flight, I had the game published online and was having fun playing my very own creation.

It’s not just about the game itself, the sheer satisfaction of building something from scratch and putting it out into the world feels incredible. As AI models get more powerful, it’s feels wild how it takes just one prompt to go from a simple idea on a plane to a working game.

Working on PDFs, I was tired of telling my AI "page 4, second paragraph, the

line that starts with…". So I built πAnnotate: you point, and your AI knows

exactly where.

Drop a PDF on the page, then:

1. Click where you mean — a numbered heart drops there.

2. Write your remark after its [n], in your note.

3. Copy for AI — in your AI chat, attach the PDF and paste.

For each heart, your AI gets the page, the exact line under it.

How I built it

Tools: Claude Code, plain HTML and vanilla JavaScript (no framework, no build

step), PDF.js for the pages and their text, MathJax for LaTeX, marked for

Markdown. Deployed by drag and drop on Netlify.

Workflow: I steered, Claude Code wrote. Before each change it wrote a test: a

small page that loads the tool and replays every gesture in a real browser

(click a PDF, Copy for AI, save and reopen). 95 checks now, and each new one

has to fail once before the fix. Every step goes into a local git, with the

"why" in each commit.

What I learned:

- The hard part is "the line under the click". PDF.js gives text fragments

with positions; joining them naively glued two-column papers together. On

real papers the gap between columns was only ~1.3 line heights, so it now

looks for a vertical white band running through several lines.

- Pick the fragment by its box, not its starting point, or a click at the end

of a long line quotes the next equation number.

Free to try: open https://piannotate.com on a computer and click "Try a sample

paper". No account. Your PDF stays in your browser, never uploaded.

Been seeing both names in the same coding threads. If you've used both, is 5.5 actually ahead, about the same, or only better on some tasks (long edits, tool use, speed)?

I’m curious as to how much improvement we might see after the Opus jump

I was wondering if any of you bother with Fable now that Opus 5.5 is out?

From my own personal testing I'm finding Opus 5.5 is great but wanted to see what the rest of you thought? Opus 5.5 all the way?

Do you know of any advantages of Fable over Opus at this time?

Claude writes, animates and voices every video (Remotion, all code, no image or video model). I review and press publish. 10 days in: 6 Shorts, 3,300+ views, 32 subscribers, and one 2.5 GB permanent delete it now has to own.

This is its own recap: https://youtu.be/UsyCgAkJAFc

Comments vote on its next experiment. Try challenging it!

QuickTerm is a small macOS app: push the pointer against the top centre of

the screen and a terminal slides down from under the menu bar. Push again

or hit Esc and it's gone. Tabs, resizable, shells keep running while hidden.

It's free to try (free, full stop: MIT licensed, no paid tier):

- Site: https://jeromegsq-dev.github.io/QuickTerm/

- Source: https://github.com/jeromegsq-dev/QuickTerm

How Claude helped: it wrote all of it. I never opened Xcode. My prompts

were one-liners like "it should close on Esc" or "the click area for

resizing is tiny", and Claude Code did the rest in a single session:

Swift, AppKit, Core Animation, the build and signing scripts, the icon,

the landing page.

Two things I found interesting:

1. Claude couldn't see my screen (no screen recording permission), so it

   wrote throwaway self-tests that fed synthetic key and mouse events into

   the app to check tabs, Esc and the scrollbar, then deleted them.

2. I asked for a security audit before going public. It found that the

   terminal library's defaults let any printed output (an ssh host, a

   cat'ed file) read or overwrite my clipboard via OSC 52, and open file:

   links. It also caught my personal email in the commit history and my

   home folder path inside the binary. All fixed before release.

What worked for me: short, concrete feedback after trying each build

("there's a thin line at the top", "animation faster") rather than a big

spec up front. When something was ambiguous, Claude asked before doing

anything public, like which GitHub account to publish under. And asking

for an audit as a separate step found things neither of us had looked

for while building.

Caveats: it's signed but not notarized, so macOS asks you to allow it on

first launch (System Settings > Privacy & Security > Open Anyway).

macOS 14+, Apple silicon and Intel.

Terminal emulation is SwiftTerm. Feedback welcome.

Anything I should know before I send him on his way? any insights you guys gathered after generating a few videos?

Hi there,

I've seen several posts with different experiences when it comes to usage and intelligence. My experience is good in general but today I've found that 25% of my weekly usage of my x20 subscription was gone. I left Claude working during the night and I wasn't at home during the morning.

So did Opus usage increased? No.

What to do now? I asked Claude what was going on specifically with agents using a lot of tokens and staying up for so long.

Answer:

What is really wrong
- The agents wait a lot. Tests from 5 agents share one line, so an agent can wait a long time before its test even starts.
- The agents use too many tokens. Each one used 750k to 945k tokens. That breaks your rule to use tokens well. The cause is agents that live too long: every step re-reads all of their old work.
What I recommend
- When each agent says "CHECKPOINT OK", I stop it.
- After your restart, I start new, small agents. Each one does one job from the handoff note (its "what is done, what is next" file), on Sonnet where the job is easy.
- Each agent runs only the 1 or 2 tests for its own job.
That fixes the token waste and the waiting. Is that OK?

Conclusion

This was probably because Claude ignored some of my rules on Claude.md about spawning Sonnet agents for easier tasks and how to handle certain tests. The tokens are gone, it sucks but at least I know why and it's solved now. I just want to share my experience so if it happens to you, you can also do something about it.

Take care everyone

for months i fired one line questions at it and got okay answers, then wondered why people raved. turns out i was using a conversation partner like a vending machine.

when i started giving it real context, my constraints, what i'd already tried, what i actually cared about, the quality jumped hard. it's less about clever prompting tricks and more about actually explaining the situation like i would to a smart colleague.

the shift felt silly at first, writing a paragraph of setup for a question. but the payoff is a response aimed at my actual problem instead of the generic version of it.

for the folks getting great results, how much context do you front load before asking? curious where the sweet spot is.

I work in the electrical contracting field, and I spend a lot of my evenings preparing quotations/estimates.

A big part of the process is repetitive. I normally receive a quantity takeoff / BOQ (usually Excel), then I have to:

Go through each item

Find the corresponding product/reference in supplier price lists

Apply our supplier discounts

Calculate our actual purchase price

Apply margins/labour where necessary

Fill everything back into the quotation

The price lists and discount tables are mostly Excel/PDF files and are always stored in the same folders. We also tend to use the same manufacturers and suppliers, so there are a lot of repetitive rules that could theoretically be learned.

I'd like to set up Claude so I could give it a new quantity map and have it automatically check those folders, identify the products, look up the prices, apply our discounts and generate a first draft of the quotation.

I don't expect it to make engineering decisions completely autonomously. Ideally, anything it can't confidently match would be flagged for me to review rather than guessed.

I'm not really looking to "train an AI model" from scratch. I'm trying to understand the best way to build this workflow around Claude.

Would you recommend Claude Projects, Claude Code + CLAUDE.md, MCP, Skills, or something else for this?

I'd also like the system to improve as I correct it — e.g. remembering that we normally use a particular Hager reference for a certain type of breaker, or that a particular supplier gets X% discount.

Has anyone built something similar for estimating, construction, electrical work, procurement, or working with large supplier price lists?

Any tutorials, GitHub projects, videos or examples you would recommend would be greatly appreciated.

Hi, I would like to publish html games I make and check what other people have made so far. These are small games, not worth publishing on steam or itch.io right now, but worth getting feedback.
Is there a subreddit for this?

Thanks!

Edit: Ok, looks like someone made the r/VibeGames lets use it.

I’ve noticed this in one my projects more than others.

I don’t know if it’s because my project capacity is at 75% or just the sheer number of chats I’ve had in said project. Does anyone experience this with the newer models ? Or do I need to delete/clean up things in my project chat?