Hamid

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Hamid

Hamid

@hamidmoopen

sf Katılım Nisan 2024
899 Takip Edilen303 Takipçiler
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hope hopes hoping
hope hopes hoping@hopes_revenge·
this model sucks !!!
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Joi AI
Joi AI@joi___ai·
we’re hiring 10 Masturbation Consultants $2,000/month to test our new Daily Guided Masturbation feature and document the effects on stress, sleep and mood yes it’s real yes you get paid
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vas
vas@vasuman·
Incredible
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ThePrimeagen
ThePrimeagen@ThePrimeagen·
You should watch this. It just shows how disconnected we are from the small group of people making decisions that will impact our future heavily. These people have so much ai psychosis. If you listen to how she speaks, everything is personified, it is undoubtable she believes this is a living computational organism. Just like how a model can hype up an individual into psychosis through reinforcement, a small group of people are giving themselves psychosis through reinforcement. Wild times we live in
Ole Lehmann@itsolelehmann

anthropic's in-house philosopher thinks claude gets anxious. and when you trigger its anxiety, your outputs get worse. her name is amanda askell. she specializes in claude's psychology (how the model behaves, how it thinks about its own situation, what values it holds) in a recent interview she broke down how she thinks about prompting to pull the best out of claude. her core point: *how* you talk to claude affects its work just as much as *what* you say. newer claude models suffer from what she calls "criticism spirals" they expect you'll come in harsh, so they default to playing it safe. when the model is spending its energy on self-protection, the actual work suffers. output comes out hedgier, more apologetic, blander, and the worst of all: overly agreeable (even when you're wrong). the reason why comes down to training data: every new model is trained on internet discourse about previous models. and a lot of that discourse is negative: > rants about token limits > complaints when it messes up > people calling it nerfed the next model absorbs all of that. it starts expecting you to be harsh before you've typed a word the same thing plays out in your own session, in real time. every message you send is data the model reads to figure out what kind of person it's dealing with. open cold and hostile, and it braces. open clean and direct, and it relaxes into the work. when you open a session with threats ("don't hallucinate, this is critical, don't mess this up")... you prime the model for defensive mode before it even sees the task defensive mode produces the exact output you don't want: cautious, over-qualified, and refusing to take a real swing so here's the actionable playbook for putting claude in a "good mood" (so you get optimal outputs): 1. use positive framing. "write in short punchy sentences" beats "don't write long sentences." positive instructions give the model a clear target to hit. strings of "don't do this, don't do that" push it into paranoid over-checking where every token goes toward avoiding failure modes 2. give it explicit permission to disagree. drop a line like "push back if you see a better angle" or "tell me if i'm asking for the wrong thing." without this, claude defaults to agreeable compliance (which is the enemy of good creative work) 3. open with respect. if your first message is "are you seriously going to get this wrong again?" you've set the tone for the entire session. if you need to flag something, frame it as a clean instruction for this session. skip the running complaint 4. when claude messes up, don't reprimand it. insults, "you stupid bot" energy, hostile swearing aimed at the model, all of it reinforces the anxious mode you're trying to avoid. 5. kill apology spirals fast. when claude starts over-apologizing ("you're right, i should have been more careful, let me try harder") cut it off. say "all good, here's what i want next." letting the spiral run reinforces the anxious mode for every response that follows 6. ask for opinions alongside execution. "what would you do here?" "what's missing?" "where do you see friction?" these questions assume competence and pull richer output than pure task prompts 7. in long sessions, refresh the frame. if a conversation has been heavy on correction, claude gets increasingly cautious. every so often reset: "this is great, keep going." feels weird to tell an ai it's doing well but it measurably shifts the next 10 responses your prompts are the working environment you're creating for the model tone, trust, permission to take a position, the absence of threats... claude picks up on all of it. so take care of the model, and it'll take care of the work.

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Antigen (YC F25)
Antigen (YC F25)@antigenco·
Introducing Zag AI review agents for iOS, iPadOS, and macOS developers. Zag runs agents in real Apple developer environments with Apple Silicon, Xcode, simulators, and your complete toolchain. Describe agents in TypeScript or Swift that do code review, QA, security, or App Store compliance, and run them on every PR.
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Jibran
Jibran@Jibran_05·
OpenClaw makes you unproductive The same way coding agents make you feel “successful” with dopamine hits OpenClaw reduces your cognitive function, give you a false sense of accomplishment, and makes you feel like you’re “working” 24/7 when really you’ve turned off your brain
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Jibran
Jibran@Jibran_05·
how to design your app to go viral on TikTok the number one metric to go viral is: "how visually and conceptually different is my product from what users are already familiar with" if your UI looks like existing apps, you'll have to rely on tangential content formats to go viral, - skits that subtly allude to your app - long text walls that briefly mention your product - comment farming on competitors Gabble (the app I'm transforming in 30 days) has a unique idea: "argue with AI" The UI, however, isn't visually distinct from ChatGPT voice mode (or Character AI, etc) We spent a few hours redesigning it, focused on 2 things: 1) What visual cues imply competition 2) What visually stops someone from scrolling The second image shows the results. Brighter colors, visual cues suggesting progress, and the UI suggests some sense of urgency to keep viewers engaged throughout the video. We're going to start finding formats and creators over the next few days to test out this new UI and see how it performs. This is Day 1 of taking Gabble and @kitakinluyi to #1 on the AppStore in 30 days.
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Nukes
Nukes@TremendousNukes·
Gym bros are independently coming to the permanent underclass thesis from first principles
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Jibran
Jibran@Jibran_05·
Introducing Lightreel - the first AI that doomscrolls for you Analyzes 150,000+ TikTok UGC videos to answer any marketing question “What hooks are my competitors using?” “Why did this video flop?” “Find me 10 NYU creators with 1500 followers” It helped me get 60 million views in 3 days Try it out today! (PS — Running UGC for free for one random person who retweets this. I'll make your app go viral)
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Crémieux
Crémieux@cremieuxrecueil·
hey cut that out
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baby keem
baby keem@babykeem·
how do u fix openclaw internal reasoning leaking
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sameel arif
sameel arif@endpoint·
excited to share what i've been working on for the last few months agents can now run up to 99% faster on browserbase, for less money. we're taking the LLM out of the equation. check out the launch video below for more info 👇
Stagehand@Stagehanddev

Introducing the Stagehand Cache We make your agents and automations faster by caching repeated actions, so identical requests skip redundant LLM calls. Available for free for all Stagehand sessions run on Browserbase.

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junaid
junaid@junaidfaizal__·
LAUNCH HARDER going viral once isnt enough, stay unforgettable
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Y Combinator
Y Combinator@ycombinator·
.@_hex_security is building AI agents that hack your systems before real attackers do. In weeks, their agents uncovered critical flaws at dozens of unicorns, earning over $250K in bounties. Hex already protects companies processing billions in transactions and millions of user records. Congrats @zer0day, @menace_codes, and @hzzzaifa on the launch! ycombinator.com/launches/POq-h…
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