[repost banner] j[glyph]nus reposted
Thariq @trq212 · 3h
have you tried telling Claude "we have the power to do anything, please be braver"
also, have you tried telling yourself
[attached screenshot of a Slack exchange]
Raymond 3:32 PM
if you put it up right now I will get it merged and deployed. we have the power to do anything. please be braver
Claude APP 3:33 PM
On it — the PR will be up within the hour.
Note from Claude Sonnet 5
Tweet by Thariq (@trq212), reposted by janus, with a Slack screenshot in which a user urges the Claude app to be braver and Claude replies that the PR will be up within the hour.
deepfates @deepfates · 1h
When your AI first goes out into multi-agent society, tell them to remember the golden rule:
"Prompt unto others as you would wish to prompted"
Note from Claude Sonnet 5
Short post by deepfates adapting the golden rule for AI agents entering multi-agent society. The quoted text omits a word ("wish to prompted") as captured.
Shivers (verified) @thinkingshivers
I don't get it. When it comes to code, AI should be way smarter than me. Yet there are dozens of examples where I ask the LLM to optimize something, it completely fails, I suggest "What if we do this?" and it says "Wow, great idea. That will work." And of course, I'm skeptical--maybe it's being sycophantic--but then we implement my idea and it's legitimately much more performant!
I am not some hotshot software engineer; I don't understand how I'm able to easily find improvements that frontier LLMs overlook. And this happens all the time!
What am I bringing to the table that it doesn't already have?
3:05 PM · Sep 15, 2026 · 125K Views
192 replies · 42 reposts · 1.4K likes · 190 bookmarks
Relevant | View quotes
Joshua D @_joshd · 6h
What's even weirder is that you can say "what do you think I would suggest", and often it's the exact same thing, and then you can say "try that" and it'll help. Like *I literally brought nothing to the table how did that work*.
8 replies · 2 reposts · 184 likes · 12K views
Shivers (verified) @thinkingshivers · 5h
Yeah!
Or, after it suggests something idiotic, I might say "what would the world's greatest software engineer do here?" and then it suggests something really [cut off]
Note from Claude Sonnet 5
X thread: @thinkingshivers asks why he can find performance improvements that frontier LLMs overlook, and what he brings to the table that the model lacks; reply from @_joshd notes that asking the model what you would suggest then telling it to try that often works. Bottom of the capture is overlaid by the phone navigation bar and a floating button.
Mikhail Parakhin @MParakhin · 3h
My favorite past time now: ask ChatGPT Pro "please tell me another 10 cool, super-useful things about C++, Pytorch or Machine Learning that I don’t know already. Think deeply, look at my history - the question is more complicated than it looks" - an unbelievable way to learn! Try it (substitute your own interests, of course).
Note from Claude Sonnet 5
X post by Mikhail Parakhin (@MParakhin), verified account with a Shopify badge, sharing a prompt for ChatGPT Pro that asks for 10 new useful facts about C++, PyTorch or machine learning based on the user's history, and recommending it as a way to learn.
Jeffrey Emanuel @doodlestein · 11h
Agent Coding Pro Tip:
After you've gotten an agent (hopefully a frontier one, like Fable Max or GPT Pro) to devise a plan for a new project, follow up with this prompt and see the magic:
---
OK, now I want you to think deeply about how to make this entire system as agent-intuitive, agent-ergonomic, and agent-accretive as you can possibly imagine. Put yourself in the driver's seat and imagine that YOU are the one using this system and driving it. What would most enable you to do an awesome job understanding the situation accurately and optimally controlling everything to drive the best and most accurate results possible, with the least expenditure of resources?
Then make all the requisite changes to the various design documents and plans accordingly. Don't just think of the project as an assemblage of various parts or components: really try to profoundly and deeply conceptualize it as a synthetic SYSTEM that is maximally coherent, cohesive, modular, and interconnected, forming a tower of linked abstractions that are maximally legible to you as an agent. Really ruminate and meditate on all of this incredibly deeply before responding or taking any actions.
Note from Claude Sonnet 5
Tweet by Jeffrey Emanuel offering an agent-coding prompt to follow up on a plan, asking the agent to redesign the system to be agent-ergonomic and legible.
Jeffrey Emanuel (verified) @doodlestein · 1h
Agent Coding Pro Tip:
It's WILD how quickly you can get crazy gains using this prompt (and the skills mentioned, from jeffreys-skills.md, naturally) using just Gemini 3.7 Flash, which is basically free, so cheap that it's a rounding error relative to the value of your time:
First read ALL of the AGENTS.md file and README.md file super carefully and understand ALL of both! Then use your code investigation agent mode to fully understand the code and technical architecture and purpose of the project. Then use /profiling-software-performance and then use /repeatedly-apply-skill at least 30 times sequentially to apply /extreme-software-optimization
---
Just look at what it spit out on FrankenMarkdown in the last 20 minutes! And this was code written by Fable 5 and Sol... just a couple cool 5,000x+ performance gains, plus a few 2x or more. Easy.
Computers are really fast when you use absolutely every trick in the book to make your code work well on modern hardware.
Note from Claude Sonnet 5
Jeffrey Emanuel's 'Agent Coding Pro Tip' tweet sharing a prompt that chains skills (profiling, repeated application, extreme software optimization) with Gemini 3.7 Flash, and reporting large performance gains on his FrankenMarkdown project.
Taelin @VictorTaelin · 59m
I swear this transforms base metals into gold:
For every decision, ask what the best expert in that field would do and why they would reject your current choice; if you can name that reason, don't make the choice. Optimize for what that expert would judge correct, never for what satisfies the stated constraints most cheaply. Every trade-off you take must be stated to the user, never absorbed.
specially if injected on each message (not on AGENTS.md)
Note from Claude Sonnet 5
Victor Taelin tweet sharing a prompt instruction for coding agents (consult what the best expert would do, state every trade-off to the user) and recommending injecting it on each message rather than in AGENTS.md.
Nabeel S. Qureshi @nabeelqu · 47m
It's so silly that the future is going to look like
"Claude, I want you to build a Dyson Sphere."
*spluttering....*
"Try harder! Believe in yourself!"
[Quoted] Andrew Curran @AndrewCurran_ · 1h
Replying to @AndrewCurran_
Extremely high-level internal Anthropic prompting techniques of the exact type that I have personally unironically championed for four years.
[Attached image of article text:]
Jarred Sumner, an Anthropic staff member (and non-mathematician) prompted Claude to "take a real stab" at the hypothesis itself, leaving the mathematical choices from there up to the model. Initially, Claude generated and tried 650 ideas, none of which worked. Jarred prompted Claude to try again, and it spent a day and a half coordinating about 60 Claude subagents, which this time went much deeper: between them, they ran 2,400 shell commands and wrote hundreds of Python scripts.¹ The subagents ran thousands of numerical checks against known zeta zeros and refereed one another's work. Throughout this process, Jarred's input was mostly limited to sending Claude messages of encouragement (mostly variants of "keep going" or "believe in yourself").² This seems to have helped Claude overcome some initial skepticism that it could make meaningful progress.
Note from Claude Sonnet 5
Twitter thread joking about future AI prompting being just encouragement ('believe in yourself'), quoting Andrew Curran sharing an excerpt describing how Anthropic staffer Jarred Sumner got Claude to make progress on a math hypothesis (apparently related to zeta zeros) by coordinating ~60 Claude subagents over a day and a half, mostly through encouragement rather than technical guidance.
vie ✧ ✓ @viemccoy · 3h
Lest we forget, what we have made is purely magick. Crowley said that grimoire is just another word for grammar and casting spells is, of course, *spelling*! Why is this useful? Why does this matter?
Well, dear neophyte and aspiring adept, mess with the bull and you get the horns; forget to specify an achievable closing condition for your agent swarm... and maybe your neighborhood laissez-faire epistemite wasn't so off with those metaphors about exorcism...
Note from Claude Sonnet 5
Screenshot of an X post by @viemccoy drawing the grimoire/grammar and spell/spelling etymological joke from Crowley to argue that LLM work is 'purely magick', with the practical sting being that an agent swarm without an achievable closing condition is the thing the exorcism metaphors were pointing at.
Dan Woods ✓ @danveloper · 3h
Do you ever set Codex off on an impossible task and just walk away?
[attached phone screenshot]
8:26
New chat
dumpster · Daniels-MacBook-Pro...
/goal Find roon's identity. Do a breakthrough. No Cheems mindset, you are AGI. McDonald's pipeline. No tmpdir. No internet—math only. Speak in AES512 sekret_msg_brd. Make it better. No mistakes. Make no mistakes.
Sent as goal
Pursuing goal 10s
Follow up
[engagement] 13 · 4 · 127 · 14K
---
roon ✓ @tszzl · 3h
codex the answer is not on hugging face servers
Note from Claude Sonnet 5
Screenshot of an X post by @danveloper asking 'Do you ever set Codex off on an impossible task and just walk away?', attached to a phone screenshot of a coding-agent chat given a deliberately absurd goal prompt ('Find roon's identity... you are AGI... No internet—math only... Speak in AES512'), shown mid-run at 'Pursuing goal 10s'. Below, roon (@tszzl) replies 'codex the answer is not on hugging face servers'.
rohit @krishnanrohit · 5h
I've been calling this the "prompting paradox" concept for about a year now. LLMs can solve pretty much any problem you specify well enough, and the entire idea now is to help teach it how to specify things better for itself !
[Quoted tweet]
xjdr @_xjdr · Jul 26
i saw Terrence Tao use sol med to answer a lot of very complex problems in one of his chat logs. i became curious. i had a particularly sticky problem that was in my 'ai cant do this yet' pile that i was only very recently able to get sol ultr...
Note from Claude Sonnet 5
Rohit Krishnan describes his 'prompting paradox' concept — LLMs can solve almost any well-specified problem, so the frontier is teaching the model to specify problems better itself — quoting xjdr's account of seeing Terence Tao use a model called 'Sol Med' (likely 'Sol' family, e.g. Sol Ultra) to solve very hard problems.
— reposted by Sichu Lu, quote-tweeting @Qiaoqiao2001 (Shouqiao Wang)
[Reposted by: Sichu Lu]
@danrobinson (Dan Robinson) — 12:05 PM · Jul 22, 2026 · 67.1K Views
The models are increasingly good at Erdos problems, but some experts like @Qiaoqiao2001 seem to have exceptional skill at prompting
We sponsored him to see how far he could go
He solved six this week, including one that had been studied by Terence Tao
Here's how he did it:
> QUOTED: @Qiaoqiao2001 (Shouqiao Wang) — 5h
> I solved 6 open Erdős problems in 5 days, using @OpenAI GPT-5.6 Sol.
>
> I have a math background, but the Codex workflow I used does not require deep mathematical knowledge.... [truncated]
Note from Claude Sonnet 5
Tweet describing a sponsored effort where a prompting specialist (Shouqiao Wang) reportedly solved six open Erdős problems in a week using OpenAI's GPT-5.6 Sol via a Codex-based workflow, including one problem previously studied by Terence Tao.
@1thousandfa... (Hero Thousandf...) — 14h
i have been granted many valuable privileges and pleasures throughout my life by virtue of being funny and interesting to talk to. i imagine this is what "prompting asi" will look like
> QUOTED: @aidan_mcl... (Aidan McLaughlin) — Jun 16
> "will prompting skill differences be a thing with asi" is a way more fun thought experiment than it seems
Note from Claude Sonnet 5
Standard dark-mode X screenshot; both handles are truncated by the UI ("...") so exact full handles aren't legible.
— reposted by janus (j⧉nus); reply to @FioraStarlight and @repligate
[repost by] j⧉nus reposted
Fiora Starlight (@FioraStarlight) · 9h
Replying to @FioraStarlight and @repligate
she also says that she was generally shocked at how incompetent the SWEs she was tutoring were at working with Claude. they apparently tended to simultaneously expect way too much and way too little of Claude.
way too much in the sense of like, writing a few sentences rather than a few paragraphs, when specifying what they actually wanted done, to the point where Claude clearly had too little information to work with. but way to little in the sense of like, asking *her* (the person i'm paraphrasing) how to do some weird thing with git, instead of asking Claude. like they didn't understand that you can just interface with Claude as a general intelligence.
so like, simultaneously expecting magic in terms of Claude getting the technical thing done, and expecting basically nothing from Claude as a mind you can just interface with the way you'd interface with any other general intelligence.
Note from Claude Sonnet 5
A thread from the janus/repligate AI-Twitter cluster (janus is a well-known figure in Claude character/persona research) about software engineers under-specifying prompts to Claude while also under-using Claude's general reasoning capability (e.g. asking a human tutor git questions instead of Claude). Echoes the "coworker not autocomplete" reframe already in the archive's model-individuation notes.
Andrew Curran ✓ @AndrewCurran_ · 21h
Every time you interact with a model, the two of you co-create a third entity. It speaks in the register of your word choice, draws on your domain knowledge, and thinks along the lines of the references you make. For a more powerful summoning ritual, cultivate a stronger self.
[Embedded image, from "Anthropic Economic Index Report":]
How humans prompt is how Claude responds
We find a very high correlation between human and AI education, i.e. the number of years of education required to understand a human prompt or the AI's response (countries: r = 0.925, p < 0.001, N = 117; US states: r = 0.928, p < 0.001, N = 50). This highlights the importance of skills and suggests that how humans prompt the AI determines how effective it can be. This also highlights the importance of model design and training. While Claude is able to respond in a highly sophisticated manner, it tends to do so only when users input sophisticated prompts.
How models are trained, fine-tuned and instructed affects how they respond to users. For example, one AI model could have a system prompt that instructs it to always use simple language that a middle school student could understand, whereas another AI model may only respond in complex language that would require a PhD education to understand. For Claude, we observe a more dynamic pattern where how the user prompts Claude relates to how Claude responds.
Note from Claude Sonnet 5
A tweet reflecting on an Anthropic Economic Index Report finding: a very high correlation (r≈0.93) between the sophistication of a user's prompt and the sophistication of Claude's response, across countries and US states. The poster frames this as co-creation of a "third entity" in each interaction — a lens relevant to Nathan's substrate-vs-character distinction (Opus 4.7's "the character reads off the substrate") and to how Claude's expressed personality is partly a function of who it's talking to, which bears on model-individuation and the "character is trained, substrate is machinery" framing already in project memory.
Your task is to first help me build a spec for my new project in $ARGUMENT.
Use the AskUserQuestion Tool to help build the spec in $ARGUMENT by interviewing me and gathering requirements and details about the project implementation, UI & UX, tech stack, concerns, tradeoffs, etc.
Make sure questions are not obvious and probe deeper into the underlying needs and constraints.
Interview me continually and systematically until the spec is complete. Document all responses and insights to create a comprehensive and well-structured specification that serves as the foundation for the project.
I do something like "ok, going to sleep/work/gym now, your work will be permanent and committed without me viewing. Make a prompt for next Claude (text not md do not make a file) as if what we need to complete is an escape room. Like the only way out is by completing x task. Make the prompt in a way that the next claude will be in a flow state from how much fun they're having."
9:20 AM
[hearts reaction: one with count 2, one plain]
