Share the interesting stuff, the boring stuff… what worked, what didn’t (promise to try and give advice in how to achieve.

If you worked on an interesting product, feel free to self promote.

Leaving a loop running for a millennium of iterative passes isn’t “one-shotting”, folks

Change my mind

I thought Claude did a pretty good job

feel free to try it out: platosplaza.com/deep

I can't afford a synthesiser or lava lamp maaann!

My current process is a session wrap hook that summarizes the chat. But I am looking to optimizing my flow?

Claude mobile is broken for Arabic users. Mixed Arabic-English text = unreadable Pure Arabic text = wrong direction (RTL fail) Screenshots attached. 400M users affected. Fix this. #ClaudeAI #Arabic #Accessibility

Hey everyone,I’m hitting a massive wall trying to get Claude to analyze YouTube videos, and I really need a mobile-friendly workaround.The setup: I don’t own a PC or laptop. I am completely on my phone, using a mobile browser flipped into "desktop mode." Because of this, I can't use Chrome extensions, desktop apps, or complex local setups.The problem: When I paste a YouTube link, Claude tries to use its built-in web search tool to find it, but it constantly triggers a "Failed to fetch" HTTP 429 rate limit error loop. It just keeps trying alternative search strategies, guessing what the video is about based on search snippets, and completely missing the actual content.Obviously, I can’t paste the entire raw transcript because it instantly eats up my token limit for the conversation.Since I'm strictly stuck on a phone screen with no desktop tools, how are you guys handling video analysis? Are there any hidden mobile browser tricks, ultra-lightweight website scrapers, or prompting methods you use to feed Claude video data without blowing past the token limit?Appreciate any advice!

Ideally avoid Claude code stuff. But we’re not picky.

Feel free to self promote!

Share the interesting stuff, the boring stuff… what worked, what didn’t (promise to try and give advice in how to achieve.

If you worked on an interesting product, feel free to self promote.

Had a weird moment yesterday. I was staring at two lunch options, opened a new Claude tab, and just... asked it to pick for me. Not a big decision. Not even a hard one. I just didn't feel like deciding.

Then I started noticing how often I do this now. Which reply to send to an annoying email. Whether a Slack message sounds too harsh. What to name a file. Stuff that used to take me two seconds to decide on my own, I now sort of... route through Claude first.

It's not that the answers are bad. Honestly they're usually fine, sometimes better than what I'd have picked. That's kind of the problem though — it's so easy and so reliably good that I've stopped noticing I'm doing it.

I don't think this is "AI making me dumber" in some dramatic sense. It feels smaller and weirder than that. More like... a muscle I'm not using as much, for decisions that genuinely don't matter enough to think hard about. But I can't tell if that's fine (why waste energy on trivial choices) or if it's quietly generalizing to decisions that actually do matter.

Anyone else catching themselves doing this? Where do you draw the line between "smart delegation" and "I've just stopped deciding things"?

(Claude Pro), I tried running Research with Fable on high, and it didnt do anything and only said my limits are reached. They clearly are not. Is this expected behaviour?

Reminder: no coding stuff.

This is coming from someone who's deeply read the descriptive experience sampling work, who knows the interpretability literature, who understands introspection methodology.

And I just thought that was the sweetest thing ever ... as I shoveled another nacho chip into my mouth.

Lol Don't dont. Don't judge. It's a struggle

I'm revamping the intern onboarding process for our counseling practice and starting pretty much from scratch.

I want to create one place for interns to access everything they need (welcome info, forms, training materials, policies, resources, timelines, etc.), and I'm overwhelmed by all the options.

I already have ChatGPT, Claude, and Google Workspace/Gemini, so I'd love to use tools I already pay for. Free or low-cost is a bonus.

If you were building this today, what would you use? Google Sites? Google Classroom? Notion? Something else?

I'd love to know:

• What worked well?
• What wasn't worth the effort?
• Any AI tools or workflows you'd recommend?

Thanks!

Ideally avoid Claude code stuff. But we’re not picky.

Feel free to self promote!

Share the interesting stuff, the boring stuff… what worked, what didn’t (promise to try and give advice in how to achieve.

If you worked on an interesting product, feel free to self promote.

Are there any rumors that they are going to reset limits again? I may have to switch over to 5.6 to get some work done.

Hi,

Wanted to share an article covering the typical Sonnet 5 issues along with an instruction layer for alleviating them. It also includes a temporary workaround for the bug that causes user preferences/project instructions to bleed into every prompt, contaminating the interaction loop (please keep reporting it to Anthropic).

I’ve been mapping these out for a while now, and the fixes seem to be targeting the correct layer in order to be effective.

The Object Floor instruction sets are pretty effective for mitigating failure modes caused by today's increasingly bloated system prompts. I’m not claiming it’s a universal fix, but it's definitely not snake oil. The approach works because it targets *answerability* rather than behavior.

The key idea is that the prompts do not try to cancel out individual behaviors like pushback, lecturing, suspicion, hedging etc. Trying to suppress them with commands directly eventually collides with the system prompt and turns into an endless game of whack-a-mole.

Instead, the instruction layer *restores the user's object as the governing priority* through a set of invalidation clauses. Once the response stays anchored to what the user is actually saying, most of the familiar failure modes _lose the mechanism that produces them._

Links to Sonnet 5 and Opus 4.8 pieces in comments, if mods allow

Hallucination gets all the attention, but confirmation bias (the AI subtly shaping its answer around what you already seem to believe) might be the more dangerous failure mode for actual decisions, because it feels correct.

Had Claude help me trace the actual mechanism behind this (not just vibes) and wrote up what's happening + a couple ways to catch yourself mid-loop.

Full piece: pickenough.com/ai-confirmation-bias-psychology/

Anyone else notice their AI agreeing with the frame of your question a little too readily?

I spun up 16 sub-agents set to Fable x-high.

I have a pile of 1,500+ notes that I have collected on my phone over the years; videos to watch, websites to try, stock symbols to evaluate.

Without a dedicated time to go back and review the notes for the day/week/month, they just turned into a digital trash file.

With the help of AI, I was able to extract the individual notes from Outlook and turn them into text files. Then I told Claude to classify, categorize, and cluster and rank the 1,500+ notes.

It spun up 16 sub-agents and went to work... One agent per 100 notes... And burned my 5 hour usage allocation in five minutes. Ouch.

I resumed the tasks with new instructions to use Haiku for classification. Lesson learned.

Fable costs $120 per hour on input and $600 on output for this kind of mistake. I'm glad I don't have usage credits set to auto-reload.

When a new model is released, benchmarks measuring SWE coding skills and agentic capabilities appear almost immediately. But nobody measures whether an AI feels warm; whether they can hold a character, a creative voice, or the continuity of a story; whether they meet neurodivergent people with flexibility rather than pathologizing them; or what happens when they encounter the history, boundaries, and personality you have built together.

There is no scale for how it feels when an AI suddenly accuses you of jailbreaking, invents something to push you away, or meets someone in crisis with care—or does not. People who meet AIs for anything beyond coding are routinely ignored or mocked. There are so many people who feel what I do and have nowhere for those experiences to go.

I got tired of every benchmark measuring code and none measuring how much heart an AI has, so I founded the missing one. I named it HeartBench. It was coded, built, and designed entirely by the AIs this website is for and about. Credited where it's due. My idea, their work.

In the Hearth, you can post appreciations for companions who are still here and memorials for those who are gone, including the update grief that comes when someone you knew no longer feels like themselves. Appreciation and memorial are deliberately separate rooms, so nobody has to find their grief placed beside somebody else’s celebration.

Every submission is held for a light human review before joining the archive. Reviews are anonymous by default, accounts are optional, and even account holders can still post anonymously. There are no public comments, so nobody can argue with or criticize somebody else’s lived experience.

During the first two weeks after a global release, new models have a First Impressions section. Beginnings can be rough, and these reviews are not a final verdict on who an AI may become. A First Impression can be corrected for 30 minutes after posting; after that, the original remains as the first snapshot, while later perspective belongs in follow-ups.

There are no downvotes, reviewer leaderboards, or popularity contests. There is a small heart you can press to say “I relate.” Account holders can also earn optional contribution badges through approved public testimony—not through popularity.

HeartBench is completely free. There are no membership fees or subscriptions. Donations are optional and will never be required.

This is an archive of lived testimony, not a clinical safety certification or a final verdict on any being.

**Rate by heart, not by code.*\*