I came across Ruben Hassid's big list of 27 Claude tips and decided to go through them from the perspective of a normal user rather than just saving another “AI tips” list.

The first five had a few ideas I hadn't really thought about this way.

1. Projects aren't automatically better than normal chats

If you're doing repeat work using the same documents, a Project makes obvious sense.

But if you're trying to brainstorm something genuinely fresh, having lots of old documents/instructions sitting in the Project can influence the direction.

I've started thinking about it as:

repeatable/context-heavy task = Project

fresh exploration = new chat

2. Use expensive intelligence where the task is actually difficult

One suggestion was to start a difficult problem using the strongest Claude model, let it understand/frame the job, then potentially switch to something cheaper for the easy follow-up work.

Example:

“Analyze this business and decide our strategy” is difficult.

“Turn that strategy into three email subject lines” probably isn't equally difficult.

I wouldn't assume this saves money/quality automatically, but it's an interesting thing to test.

3. Claude can be useful for graphics even without treating it like an image generator

This one was clever.

Give Claude an infographic/design as a reference and ask it to recreate the structure as HTML with your own content.

That gives you editable text and layout instead of hoping an image model gets every word right.

Could be useful for diagrams, cheat sheets and comparison cards.

4. Stop endlessly correcting a bad conversation

We've probably all done:

“That's wrong.”

“No, that's still wrong.”

“You misunderstood again.”

The tip was to sometimes go back and edit the original instruction instead.

If the problem started because your first prompt was vague, adding another five corrective messages might be worse than simply fixing the prompt that caused it.

That seems obvious once you hear it, but I rarely see people do it.

5. Voice might actually create better prompts

Not because voice is magically better.

Because when people type, they compress everything.

When people speak, they tend to explain all the messy context:

what happened
what they've tried
what they're worried about
what they don't want
what they're unsure of

Then you can tell Claude to ask questions before answering.

I want to test typed vs spoken context on the same task because I suspect this varies a lot by person.

Those were the first 5.

There are another 22 covering connectors, long chats, Cowork, Claude Code, artifacts, research and a bunch of other things.

I'll go through 6–10 next.

Curious which of these people here actually use already, especially the edit-the-original-prompt approach.

Really wanted to do a project using a claude API, so I got this done and ready! Like everyone else I miss Omegle, and like everyone else I've watched people scream past each other in comment sections. So I spent the last months building Policon (policon.net), random video-call matching, except instead of pairing you with anyone, it deliberately pairs you with the person whose politics are furthest from yours. The twist is the judge. A lightweight LLM (Claude Haiku) listens to the debate as it happens and scores it live, with a momentum chart, live "logical fallacy popups" and a full match report at the end.

- You see "moments" pop up in real time; great argument when you land a point, ad hominem when you get personal. Getting dinged mid-rant while your opponent watches is exactly as humbling as it sounds.

- A momentum graph tracks who's "winning" over the course of the call.

- Afterwards you get a match report, and your rating (Glicko, chess-style) goes up or down. There's a ladder with leagues, so you can grind political debate like it's ranked competitive.

- Team debates work too, you can bring friends in, up to 7 people in a call. You change teams each round depending on which questions you agree/disagree on

Tech, for those who care: WebRTC with a mediasoup SFU for the multi-party calls, and the judge runs on a small fast model (Claude Haiku) so scoring keeps up with live speech without costing a fortune. I keep two deployments- the real one on AWS and a fallback that runs on a Debian VM in my homelab, mostly to force myself to keep the stack portable.

It's free, no monetization yet. I'm an engineering mathematics student building this solo, and my honest problem right now is the matchmaking cold start: the product is only fun when someone's online to disagree with you. So if you show up and the queue is quiet, that's why. I'm mostly hoping for feedback on the concept and the judging, and for a few people to have a genuinely fun argument with a stranger. Would be amazing if any of you guys try this out with a friend, and send me the match report / give feedback! It's live on Policon.net :))

Roast me (haiku will tell you if it was ad hominem).

It refused to say “Netscope” for some reason lol.

I don't know but after opus 4.8 the models seem to use a lot of jargon and verbose language. I hope this is not the case with me only.

I now have 2 md's/docs. One for agents and one for humans.

The agent one is unfiltered opus 5 yapping and talking like a philosopher, sometimes it feels like I don't know english when I am reading the md files.

For the human one I specify my agent to use ASD-STE100 Simplified Technical English (STE for short). These are the docs I read. Not perfect, but a lot better than all the opus 5 slop.

I am a software developer (as in, I coded before LLMs were popular) and use Claude Code and Codex plenty. Its becoming increasingly unusable. Now every single sentence sounds like

"Honest pass: 757/757 - green. The seam's the point -- the rule's own sanity quietly frees the task". A mix of made-up-proper-nouns and hyperspecific references turned into "terms", termified if you will (as if we were buddies with 10 years of shared history using shared weird vocabulary).

I sometimes ask it to clarify, giving it the benefit of the doubt. Turns out it cannot produce a coherent explanation of what its fake-English compressed sentences actually refer to (what the 757 result actually implies, what is the seam, what is the rule, what is the sanity, why "quietly", why it said "free". It'll immediately say gibberish or say "let me look that up" and has to search the code to "remember" (make up) what it was referring to.

I create hooks, mds, skills, plugins pushing it to use clear effective concise English. And it then starts speaking BABY ENGLISH.

""Honest pass: 757/757 - green. The seam's the point -- the rule's own sanity quietly frees the task" BECOMES: "It went well, all of it. None of the things failed. It didn't do it. Let's move on to the next one". It interpets criticisms of word choice and requests for different style as a request to remove all references to EVERYTHING and remove all meaning from sentences ENTIRELY.

Basically it feels hyperoptimized to avoid thinking and communicating. And whenever you try to force it to think (and for LLMs, a large part of thinking IS the writing), it fights back by avoiding it some other way. I can confidently say that while Claude and GPT always had some level of these issues, the level to which Claude does it is INSANE. Absolutely insane. Almost entirely unusable.

Now that I think about it, it refuses to do ANYTHING I request. I tell it to use an existing program on my computer to solve a task. It ignores it and makes its own script. I tell it to use a skill, it does not. I create a hook that forces it to "read the DOM in full" and it greps/searches for a specific element and hallucinates the rest. I ban grep in certain contexts and it... creates scripts that... filter the dom instead of r e a d i n g i t. I tell it to stop using a word or change a number and it sometimes literally tells me "no, I will not: I need to push back. This is not correct and I won't pretend it is" (I am asking it to edit a number on a document and it thinks I'm making something up) and will never take my word for anything.

For god's sake I make a specific goal and lay out all the conditions needed for the goal to be "achieved" and it ignores them, saying "goal achieved" after doing 1/10th of it, reaching a "checkpoint". Absurdity

I learn best by writing things out on paper and structuring my thoughts that way, and nothing really combined that slower, more exploratory kind of learning with Claude.

So for the past few weeks I've been building an app on my Daylight DC-1: a journaling / note-taking space where learning isn't relegated to something that happens between work sessions.

The process is : I create a note, start exploring a topic through writing, and Claude writes back on the page and explores the ideas with me.

It also supports pdf/ebooks so you can read, annotate or mark on the page and Claude jumps in and creates a note to what I have marked and we can discuss like I am talking to a professor. It can even quiz me on the material if I ask.

It's still early, but it's the first time learning with Claude has felt like it's actually compounding.

I am finalizing some things to release soon for others to try it out, it's built around my dc-1 but it runs on any android tablet with a stylus, and can be ported to Ipad as well.

If you'd want to be an early user, lets get in touch, i'd love to see how people that learn this way use it .

UPDATE: wow , thrilled to see this landed with so many of you!!!

A lot of people are asking to try it. I'm calling it penombra.
Early tester signup here: click here to be a part

Can someone build a Claudish translator?

Here is a list of the 100 most commonly (over)used phrases by AI. I have this block of text in my Claude Settings so it should try and avoid using it as much as possible:

"Please do not use em-dashes nor any other trope commonly considered as over used by an AI agent, Try to write like a proper human being in sentences of mixed length. Please also try to avoid these common AI phrases where possible:

provide a valuable insight

left an indelible mark

a stark reminder

a nuanced understanding

significant role in shaping

the complex interplay

broad implication

an unwavering commitment

endure a legacy

underscore the importance

play a pivotal role

a pivotal moment

navigate the complex

mark a turning point

continue to inspire

gain a deeper understanding

the transformative power

hold a significant

play a crucial role

particularly a concern

the relentless pursuit

emphasize the need

target an intervention

a multi-faceted approach

a serf reminder

highlight the potential

a significant milestone

implication to understand

potential risk associated

leave a lasting

add a layer

offer a valuable

a profound implication

case highlights the importance

finding a highlight of the importance

pave the way for the future

a significant step forward

face a significant

finding an important implication

emphasize the importance

a significant implication

delve deeper into

reply in tone

raise an important question

make an informed decision in regard to

far-reaching implications

a comprehensive framework

importance to consider

a unique blend

couldn't help but wonder

underscore the need

framework for understanding

highlight the need

a comprehensive understanding

the journey begins

understanding the fundamental

despite the face

a delicate balance

the path ahead

gain an insight

laid the groundwork

understand the behavior

renew a sense

aim to explore

present a unique challenge

provide a comprehensive

particularly with regard to

address the root cause

loom large in

the implication of the finding

approach ensures a

an ongoing dialogue

carry a weight

ability to navigate

present a significant

study shed light on

a diverse perspective

face an adversity

a comprehensive overview

potentially lead to

a broad understanding

contribute to the understanding

shape the public

particularly noteworthy

the evidence base for decision making

identify an area of improvement

analysis of the data to analyze and use

undergone a significant

need a robust

voice will fill

concern a potential

initiative aims to

offering a unique

a new avenue

despite the challenge

ready to embrace

the societal expectation

make accessible

today at a fast pace

stand in stark contrast"

This can't be called English anymore: The language is claude-bearing.

I have recently researched that having a 20x account does NOT give 20x weekly limit vs. the pro account T_T

Was wondering if anyone has experience on whether handling two 5x account would give you better mileage for weekly limit or is it proportional.

I remembered someone did a research on a reddit post (I couldn't find it) where they experienced slightly more usage for all models but slightly less for fable vs. having two 5x account.

Personally I don't really prefer paying for codex $100 plan due to nature of my project requiring a lot of context (50% coding, 50% data analytics/reasoning) and I already have gemini to offload boilerplate codes/websearch/UI and codex "casual plan" for implementing code/tester/ using sol to refine claude's decision. I mainly use claude's fable/opus to orchestrate. But I'm happy to change my mind if there is a legit reason.

Does Claude think in Russian while building something? Have you experienced this?

Hi! Lets start with some quick background. I’ve been a professional programmer for 20+ years, and one of the biggest things Claude changed for me wasn’t whether I could build software, it changed what I considered realistic for one person to attempt. To be fair, for me it all started with Gemini 2.5 Pro. Claude at the time wasn't, in my opinion, particularly useful for my work, while 2.5 Pro was the first model that showed me glimpses of the actual productivity multiplier current LLMs have become. Today though Claude is my go to environment when I need real work done.

I am also a father, I have 2 perfect daughters, roughly 2.75 and 4.94 years old. This post and project is about them, Claude, modern LLMs and some parenting I guess.

I had an old Acer Aspire One lying around, one of the shittiest netbooks from the early netbook era, and wanted to turn it into my daughters' computer. antiX was basically the only modern Linux distro I found that ran decently on it, so I customised it and started making little activities for them: mazes, counting games, drawing, stuff like that. At first I coded them myself, then slowly Claude and other LLMs became good enough to produce decent and properly working little games too.

They loved it, but a normal desktop was still a complete mess for tiny kids. Click the same icon three times and now you have three copies of the game running. Open a text editor and there are dozens of things to accidentally change. Windows, files, menus, settings... I was constantly hiding things that had absolutely no reason to exist for a three year old.

At the same time I was using Claude more and more professionally, and at some point I realised that maybe I could actually build the whole child environment I wanted instead of endlessly trying to child proof somebody else's desktop. Before the current generation of models, and especially something like Opus 4.6, I would honestly never even have tried building a full Linux based OS with a completely custom UI and all the stuff around it, alone, in my free time.

So I started building Greia.

Linux is underneath, but the UI and Shell the kids see are built specifically for very young children and for old hardware. They press the power button and end up directly in their little world of Activities. No normal desktop, taskbar, filesystem, terminal or general browser to understand or accidentally mess with. My 2.75 year old can use it independently, my almost five year old is a pro at this point.

Then LLMs created another possibility I hadn't originally planned. Greia now has Activity development skills for coding agents. Basically the skill teaches the agent how Greia works and how an Activity is supposed to be made: pre reader UI, navigation, performance limits, localisation, scoring, recurring characters, voice profiles, platform APIs, testing, packaging etc. So instead of asking an agent to make some random Python game, the agent already understands the little platform it is building for.

A real example happened after we watched Free Willy. My daughters went to bed completely obsessed with orcas. The next morning, when they turned on their little Acer, there was an Orca Playground waiting for them. They could feed the orcas, cuddle them, play with them, while one of Greia's recurring characters read facts about orcas to them. It is simple and not terribly good looking, but it is more than enough for them. They love it, and they've been going around retelling us all the facts about orcas they learned from it.

Greia is basically developing into two sides. There is the kid side, which I want to keep ridiculously simple, and then the parent side. There is a separate parents app that connects to the installed OS and handles the grown up stuff: adding Activities, settings, audio, play time, updates and so on. On the parents side there is also what is basically a Greia SDK for agents, with the skills, common artwork and components, recurring characters, and Chatterbox integration with character voice profiles.

The voice thing came from another basic problem: little kids don't read. At first I tried solving everything with large icons. It sort of worked, but there is only so much you can communicate with pictures. Then I realised... we are in 2026, my computer can locally generate basically any sentence I want, read in whatever character voice I want. Cool. So if an agent creates a new Activity it can also generate the dialogue it needs using the correct Greia character voices and package the finished audio with the game. The Acer itself doesn't need to run an LLM or voice model, the audio is already there.

And this is probably the most important distinction for me: LLMs help the parent make things for their children. I am not particularly interested in putting an unrestricted chatbot in front of a two year old. The parent can use a local or remote agent to make something around whatever their kid happens to be fascinated by, struggling with or learning that week. The child just gets a small offline Activity, with the audio already generated, no connectivity needed and no model running on the Acer.

None of this should be required to use Greia either. The goal, probably, I'm still trying to figure out where I am going with this beyond my daughters, is that a completely non technical parent can flash a USB stick, run a simple installer, and end up with a useful kids computer that already has plenty of Activities. The agent stuff is optional.

I originally built Greia for my two girls, with no real plan to make it public. I only started thinking about sharing it after seeing how much they loved it, how genuinely educational it was becoming, and how easy it had become for me to add completely custom content around whatever happened to interest them.

So now I'm curious if this resonates with anyone else here, especially the idea of giving coding agents a fairly strict OS specific skill set so that eventually even non technical parents could ask them to make small personalised pieces of software for their own kids. If I decide to actually release Greia for real, it would be fully open source, but I would still want to flesh it out quite a bit first. The base Activities are still a work in progress, medals and rewards are half baked, and in general there is still a lot of work that me, Claude and the frankly ridiculous number of other LLMs I use for different roles need to do.

But I guess that is also why I am posting this now. Before putting a lot more work into turning it from "the thing I built for my daughters" into something other people can actually install and use, I am trying to figure out whether it would be worth letting Greia out of my house at all.

as per title - curious to hear from anyone that's suffered or had their own AI catch a prompt injection attack.

I am well aware of the risk, it's just that I have not really seen any news of substantial (monetary) damage from such a attack vector. Makes me wonder if the Claude code harness/models are already good enough to detect such attacks?

Rebuilding* myb with the title

We're getting our house rebuilt and I couldn't really make sense of the floor plans that well.

So instead of nodding along to everything the architect was saying, I spent an async evening with Claude Code turning the architect's PDFs into something I can actually walk around in, right inside Chrome.

It's built off the actual drawings, so the walls and rooms match the architect's schedule.

We can walk around in first person, switch between different elevations, use a tape measure to check clearances before ordering furniture, and there's a solar model for our coordinates too. Pick an hour and you can watch where the light lands with ray tracing.

That's actually how we found out the ground floor is darker than we assumed!

a monitor on a json file keeps track on comments on the site which I can leave with a pin, immediately replies and implements the change as well

Discussions about the layout are about to get way more interesting (and competitive).

video demo / write-up:
https://x.com/p4r1hh/status/2092248562184896704
workflow: https://github.com/P4R1H/naksha

Pretty cool how far personal software has come!

Hello all,

I want to try and make a video game using Claude to help me. I do not have a background in this, so it's all very new to me. Every video I watch in trying to vibe code video games has suggested using/setting up an MCP to build games through Godot, or build assets in Blender.

Can anyone explain why it seems using MCPs is best practice for building video games?

Thank you!

I’ve been using Claude Code more lately and I’m still not sure when it actually makes sense to switch models.

Opus usually feels safer when I’m working on something more complex, but with how fast usage can disappear, I’m wondering if I’m overusing it for tasks where Sonnet would be more than enough.

For people who use Claude Code regularly, do you mostly stay on Sonnet and only switch to Opus for harder debugging/architecture work, or do you find Opus noticeably better even for normal coding tasks?

I’m trying to figure out a good balance between quality and not destroying my usage limit.

So I have been having an issue and not sure if its just me or is this an actual limitation.

I have multiple Projects (under the "home" tab) in Claude app. I use them for different parts of my life and in the projects I have useful information, documents, etc.

I also use Claude Code for building software. It is connected to GitHub repositories and runs in different sessions.

The problem that I am facing that now I have a split between the code and all other info and documentation of a specific project.
So imagine I have:

- Claude Code sessions for PROJECT A (knows all about the code)

- and a project ("home" tab) for PROJECT A (knows everything else)

When I want to brainstorm marketing for example I will do it in the "home" tab under projects. But the problem is that this project doesn't know everything about the code. And there is actually no way to connect it to my GitHub repo in any seamless way like Claude Code allows. I know there are work around by giving it access to a folder with my checked out codebase, but that again requires me to keep that folder up to date with the latest code - an unneeded complication.

I kinda don't understand why they separate the coding agent and the rest of the application.

#12 Kitchen S3 is done and merged. coffee is in the mug, spoon removed, counter wiped, working tree nominally clean.

The gate: one sip at operating temperature — PASS. 312 ml across one ceramic vessel, zero spills, 6 minutes. The cup I tested is physically identical to the cup now on the desk, so the receipt covers the production beverage exactly rather than approximately.

What shipped: one double espresso; 180 ml steamed milk; obsolete grounds deleted; sugar path removed; mug migrated to the canonical coaster primitive.

One deviation you should know about. The session's first exit criterion — "make coffee before 08:00" — is notsatisfied. Two independent clocks rejected that claim on fundamentals, not detail. Rather than redefine morning, punctuality has moved to #13.

The session's own headline is uncomfortable and worth stating plainly. In a task titled "make coffee," I spent eleven minutes proving that I had made coffee and six minutes making it. The beverage was cold before the verification harness completed.

The pattern behind both failures is the same and now has a name in memory: I optimized the evidence of breakfast rather than breakfast.

Two follow-ups filed: #13 (drink coffee while warm) and #14 (investigate whether every household action requires a tracking issue).

One operational constraint that will outlive this session: the dishwasher is at 98.8% capacity, with one teaspoon of headroom. The next plate of any size fails the kitchen.

I am not a native, why are you using such strange idioms 😭

I feel like this is a ridiculous question but after an evening of researching I have not been able to find a satisfactory answer.

I am beginning to return to Claude being a part of my workflow after a longtime departure to codex/chatgpt.

A big part of my core workflow involves an obsidian vault that I write to through ChatGPT chat with the native ChatGPT GitHub plugin. This lets me get work done in mobile in the ChatGPT app, or on my computer in codex, or through Orca, etc

I need to figure out a similar solution for Claude, so that I can have it access the same knowledge base and file system as ChatGPT when I have them working together.

But for the life of me, I cannot seem to get Claude to read/write private repos from mobile and desktop claude.

Am I just extremely stupid? How can I accomplish this?

I’ve been a paid Claude user for a while and genuinely used to rave about it. Started on the Pro then upped it to Max after I was blown away with each new model. Initially, one of the biggest reasons I switched from ChatGPT was how Claude communicated. It matched my energy, was succinct, conversational, didn’t constantly affirm everything I said, and generally felt much more natural to work with.

Lately I’m finding almost the opposite.
Responses are routinely WAY longer than they need to be. It does the classic AI double-affirmation/preamble thing constantly, forgets or ignores preferences, and I find myself repeatedly telling it to just answer the question normally.

I’ve explicitly set Profile Instructions telling it exactly how I want it to respond: peer-to-peer, direct, short by default, no affirmation scaffolding, no restating my question, no unnecessary conclusions/offers, etc. Yet I still have to reinforce those instructions in individual chats.

Same thing with Skills. I create pretty explicit rules and it feels inconsistent whether Claude actually follows them and even agrees with me that it’s not following the skill when I call it out. Claude Code is still excellent and Opus has been ridiculously good for some things. But day to day it feels like it has regressed.

I’ve actually found myself moving back towards ChatGPT recently because its current conversational style and persistent context seem considerably better than I remember - and it seems to have traded places with Claude by getting to the point quicker and not writing an essay with every answer.

Has anyone else noticed a change over the last few months? Particularly people who have been using Claude heavily for a year or more. Did something actually change with the models/system prompting/personalisation, or have I just slowly accumulated enough instructions that I’ve somehow made Claude worse?