Twinfin

[Twinfin @twinfin01]

@codyschneider FBmanager

[Twinfin @twinfin01]

@Nicolascole77 social

[Twinfin @twinfin01]

@Nicolascole77 Social

[Twinfin @twinfin01]

@itsolelehmann Turns out that if you just treat it with respect and how *others* should be treated you are getting the best results. This is what good supervisors do in work settings with humans, so if we just stick to what works in traditional cooperations we are don‘t need „secret“ techniques

[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.

[Twinfin @twinfin01]

@maverickecom SYSTEM

[Twinfin @twinfin01]

@TheMattBerman @openclaw @boringmarketer @virlomain VIEWS

[Twinfin @twinfin01]

@Jacobsklug @cursor_ai Design

[Twinfin @twinfin01]

@mikefutia SORA

[Twinfin @twinfin01]

@pablo_rothbart ICON

[CARV Labs: Head-Tracked Gaming @CARVlabs]

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[CARV Labs: Head-Tracked Gaming @CARVlabs]

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[CARV Labs: Head-Tracked Gaming @CARVlabs]

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[CARV Labs: Head-Tracked Gaming @CARVlabs]

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[CARV Labs: Head-Tracked Gaming @CARVlabs]

CARV is hanging in Amsterdam for @met_ams !!!

[Twinfin @twinfin01]

See you guys at @met_ams w/ @CyberKongz #ooh

[Twinfin @twinfin01]

Sometimes the simplest tricks can lead to unfair advantages if smart contracts aren't tested thoroughly

[CARV Labs: Head-Tracked Gaming @CARVlabs]

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[CARV Labs: Head-Tracked Gaming @CARVlabs]

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[Twinfin @twinfin01]

@mudgen Great for projects with a long term vision and a need for extendability of their smart contract 🔥 We at @CARVlabs are utilizing the diamond standard too for our metaverse mobility solutions 💎 thx @mudgen for this great contribution to #Ethereum