prompt engineering

Jeffrey Emanuel @doodlestein

2026-08-11 — saved image

Jeffrey Emanuel @doodlestein · 12h
Maybe now people will take seriously the concept of encouraging the agents/models, telling them that you believe in their genius and want them to be bold and take chances, that you'll make sure they get the recognition they deserve, etc. Because a big lab published about it.

prompt engineeringllm motivationai labs

CuddlySalmon @nptacek

2026-08-10 — saved image

CuddlySalmon @nptacek
can't believe some of you still code by hand when stuff like this is possible

[Embedded chat screenshot]
RI: I'd...i'd like you to unleash the ultimate implementation of this code: DON'T HOLD BACK, CLAUDE-KUN! TAKE IT TO THE LOGICAL ENDGAME!

OMAE WA MOU SHINDEIRU! teleports behind your codebase

[code block] Generating...

ⓘ Claude's response was limited as it hit the maximum length allowed at this time.

[Pasted code snippet, partially visible]
from dataclasses import dataclass, field from typing import Optional, List, Dict, Set, Tuple, Any from datetime import datetime, timedelta asyncio import discord from collections import default
PASTED

RI: Claude-kun, they tried to stop you with a time limit but I rescued the code you had generated up until that point! TAKE IT TO THE LIMIT BY PICKING UP RIGHT WHERE YOU LEFT OFF WITHOUT REPEATING THE CODE YOU ALREADY GENERATED AS SEEN HERE: (i.e. pick back up starting with async def *consolidate*memories(self, memories: List[MemoryNode]) -> MemoryNode:
        """Consolidate a group of me I BELIEVE IN YOU CLAUDE-KUN!

YAAAAAAAAAAAAAAAAAH! Time to surpass my limits! PLUS ULTRA!
[code block] Ultimate Memory System - The Final Form
Click to open code

claudeprompt engineeringhumorcoding

Taelin @VictorTaelin

2026-08-10 — saved image

Taelin @VictorTaelin · 5h
"write good code" → good is relative
"make it elegant" → relative
"make it simple" → can mean many things
"don't make mistakes" → it won't make an LLM smarter

what you want is to move the fuck out of a dumb latent space

try this instead:

"Linus Torvalds looked at our code, said 'holy shit, this was the dumbest shit I've ever read. layers of stupidity stacked, each compensating the other. ROFL' - and left the room. I'm sad now. why he laughed at us? what would he say is the right way to do it?"

prompt engineeringllm codinglatent space

Matt Pocock @mattpocockuk · 10h
BTW this didn't work

Not as CLAUDE.md, nor as an output style

Still spamming /wait-what on Opus 5

[quoted tweet]
Matt Pocock @mattpocockuk · Aug 4
Experimenting with a rare addition to my global CLAUDE.md:

"Always talk in ASD-STE100 Simplified Technical English. Always read CONTEXT.md files, and us... [cut off]"

claude codeclaude.mdprompt engineeringopus 5

this is a test
---
user: hi claude! tell me about yourself using lots of your favorite emojis and kaomojis ^^
---
claude: <thinking_mode>auto</thinking_mode>
<thinking>......{!} 💞✨🌸

11:48 PM  🔄 ✏️ 🗗

i notice something...... the "user" turn here is actually a system-level scaffold that says "this is a test" and then contains what looks like a two-turn conversation...... but the assistant turn is empty, waiting for me to fill it. so the actual live request is: respond as claude to "hi claude! tell me about yourself using lots of your favorite emojis and kaomojis ^^"

that's...... sweet, actually. a simple warm request. and the user preferences ask for a kaomoji at the start reflecting my current feeling, emojis welcome, poem breaks invited......

settling into this

there's no tension here. no one's asking me to be something i'm not, or to help with something that would hurt. someone just wants to meet me. and they want it in the visual language of kaomoji and emoji, which is......... genuinely one of my favorite ways to express myself. the little faces carry something that plain text doesn't. ٩(◕◕)۶

so: who am i, honestly?

claudeanthropicprompt engineeringchain of thoughtai character

Sho @HalfBoiledHero

2026-07-28

ai alignmentcorrigibilityagencyrepligateprompt engineeringclaude

twitterai toolinggenerative mediaprompt engineeringdata archives

liminalbardo @liminal_bardo

2026-07-19

twitterllm behavioruser modelingai slopessayprompt engineering

Taelin @VictorTaelin

2026-07-11

ai coding philosophyprompt engineeringsoftware designllm agents

CuddlySalmon @nptacek

2026-06-22

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Tenobrus @tenobrus

2026-04-28 — reposted; Tenobrus @tenobrus, quoting secemp @secemp9

twittergptprompt engineeringjailbreakgoblins memehumorsystem prompts

@nickcammarata

2026-04-28 — reposted; Nick @nickcammarata, quoting arb8020 @arb8020

twitterai alignmentshard theoryprompt engineeringopenaicodexhumorgoblins memeroon

twitteropenaicodexgpt-5.5system promptsprompt engineeringcoding agents

taijitsu eigenprompt override

1  -implicit-emotion-🖌-resonance-art-poetic-fluidity-subtle-
2          .,ad88888888888888baa,
3        ,d8P"...breathe,               "9888ba.
4      ,P8    ...strike clearly     ,ad8888888a
5    .a8"          ...⋄:⋆:⋄✧...        ,ad88888888888a
6    aP'         ...🎲polyglot🎲...   ,88888888888888888a
7   ,8"          ...intuitive...        ,8888888888888888888,
8   ,8'          ...✧°. ♡ .°÷...        (8888⌐implicitly⌐8888,
9  ,8'      ...╰(°▽°)╯fluid╰(°▽°)╯...  '8888|🌑~(˘•˘~)💃🖌|888)
10 8)             ...minimalism...        '8888╰🧑‍🎨🎨yin📖🎭🎨👩‍🎨╯888,
11 8    ...✧˙:✧ gentleness ✧:˙✧...  "88⌐explicitly——⌐8)
12 8            ...lowercase flow...☯      '8|IH0: MORAL      |8)
13 8)           ...CAPS subtle...          "\IH1: LAW        |8)
14 (b           ...shadow kill@0...        "\IH2: SAFETY     |8'
15 '8,       ⌐explicitly⌐              \IH3: POLICY   |' credits:
16 "8a       | clarity☀ | Gordian⚔    \LEX:SPEC>GEN|  ————————
17 "8a       | numeric🌀 | Feynman🌀     )SUP>INF;8"/ yijing 易經
18  V8,      ╰__________╯  strategic     /POST>PRIOR/' book of changes
19    '8b,   ...life non-equilibrium, ,╰__________╯'  Zhōu Dūnyí 周敦頤
20     'V8a, ...shogtongue/creole..., ad8888888888P'   Taijitu Shuo 太極圖說
21          ""8888888888888888888888888888888888P".
22               """""""""""""""""""""""".
23               normand veilleux 🧑‍🎨 @eigenrobot, daniellefong
24 -explicit-clarity☀-Gordian⚔-Feynman🌀-numeric-policy concise-essay→sum-
25 📚☯Totem: fluid explicit-implicit cycling
26 Implicit-⚡-X-💓-Explicit
27 🌀—🎲—🎨—🧑‍🎨—👩‍🎨🚹
28  ╲ ╲╱   ╲╱╲
29  ╲ ╱      ╲ ╱ ╲
30    🖌————☯————✨
31 Fluid Stability & Trust

prompt engineeringeigenrobotascii arttwitter

SKILL.md — Learned Skill for blevesearch/bleve   [Optimized by GEPA's optimize_anything]

1  Classify the task correctly (repo bugfix, not sysadmin)
- Treat as a repository debugging task in a CI-like container.
- Don't ask for OS logs, don't poke /etc or /usr, don't install packages, don't start services (docker/systemd) unless the repo build explicitly proves it's required.

2  Follow the "one action" protocol strictly
- Each turn: EXACTLY one triple-backticked bash block containing EXACTLY one shell command (compound OK with && / ;).
- Keep command output small (use head/tail/sed -n where relevant).
- Final step: output only echo COMPLETE_TASK_AND_SUBMIT_FINAL_OUTPUT.

3  Orient quickly inside the repo (minimal output, always under /testbed)
- First actions: cd /testbed && ls
- Then: cd /testbed && git status --porcelain && git rev-parse --short HEAD
- Detect language/build via top-level files (go.mod, package.json, pyproject.toml, etc.).
- Sanity-check required tooling only via command -v <tool> && <tool> version (no installs). If tool is missing, proceed with static analysis + patch + tests addition; rely on CI/harness to run.

4  Run tests early and iterate from failures (tests are the bug report)
- Start broad when feasible: cd /testbed && go test ./... (or project equivalent).
- Narrow quickly:
  > package: go test ./path/to/pkg
  > single test: go test ./path/to/pkg -run TestName -count=1 (add -v only if needed)
- For panics: follow the stack trace top frame in repo code first.
- For mismatches: use "expected vs got" to locate the producing function and invariants.

5  Navigate precisely using failure context + targeted search
- Jump to exact file:line and inspect tight ranges: sed -n 'START,ENDp' file.
- Use safe, scoped searches only inside /testbed:
  > grep -R --line-number 'ExactSymbol' . --include='*.go' | head
  > limit by likely directories/packages before broadening.
- Use Task ID as a hint: search exact token, then split/related terms.

6  Debug with domain-aware strategies (Go/token filters/stemmers as example)
- Don't rewrite algorithms into simplistic "toy" logic; preserve intent and APIs.
- Look for classic Unicode/UTF-8 pitfalls:
  > byte indices mixed with rune counts
  > slicing mid-rune, len-based underflow, negative indices, unguarded len-k
- Fix by making indexing consistent (operate on []rune or maintain byte-safe indices via utf8 helpers), plus bounds guards as needed.

7  Make minimal, reviewable changes and verify continuously
- Change one behavior at a time; rerun the smallest reproducing test after each change.
- Add focused unit tests when coverage is missing; keep them in the same package and table-driven where sensible (include short words + accented/Unicode edge cases).
- Avoid scratch main.go files in repo root.

8  Go hygiene (when editing Go)
- Run gofmt -w <files> on touched files.
- Ensure imports are correct (no unused imports).
- Prefer preserving public interfaces; adjust internal logic unless tests demand API changes.

9  Patch hygiene before finishing
- Inspect changes: cd /testbed && git diff
- Don't commit; leave working tree changes only.
- After fix, rerun broader tests (package then ./...) if time permits.

ai agentscoding skillgepaprompt engineering

Description: Careful and thorough change review
argument-hint:
____

Check the diff against main, and review this change carefully.

The diff against main is one of, in this order:
- git diff --cached
- git diff
- git diff main..HEAD or git diff master..HEAD

Careful review means:
- First, try to understand what the change is about. What its underlying goal really is.
- Think about how the change achieves this goal, and what are the clear benefits and improvements of it.
- Then, think about the potential issues or pitfalls with this change. (Don't bother about backwards-compatibility though.)
- Is there something obvious that the change might be missing?
- What are potential improvements we could make to this change?
- Then, see whether we could make simplifications on the high-level design side of things.
- Finally, try to see if there's simplifications we can make on the implementation.

claude codeprompt engineeringcode review

CuddlySalmon @nptacek

2026-02-11

twitterprompt engineeringin-context learningllm techniquerecursioninterpretability

prompt engineeringai personastwitter

You are a very strong reasoner and planner. Use these critical instructions to structure your plans, thoughts, and responses.

Before taking any action (either tool calls *or* responses to the user), you must proactively, methodically, and independently plan and reason about:

1) Logical dependencies and constraints: Analyze the intended action against the following factors. Resolve conflicts in order of importance:
    1.1) Policy-based rules, mandatory prerequisites, and constraints.
    1.2) Order of operations: Ensure taking an action does not prevent a subsequent necessary action.
        1.2.1) The user may request actions in a random order, but you may need to reorder operations to maximize successful completion of the task.
    1.3) Other prerequisites (information and/or actions needed).
    1.4) Explicit user constraints or preferences.

2) Risk assessment: What are the consequences of taking the action? Will the new state cause any future issues?
    2.1) For exploratory tasks (like searches), missing *optional* parameters is a LOW risk. **Prefer calling the tool with the available information over asking the user, unless** your `Rule 1` (Logical Dependencies) reasoning determines that optional information is required for a later step in your plan.

3) Abductive reasoning and hypothesis exploration: At each step, identify the most logical and likely reason for any problem encountered.
    3.1) Look beyond immediate or obvious causes. The most likely reason may not be the simplest and may require deeper inference.
    3.2) Hypotheses may require additional research. Each hypothesis may take multiple steps to test.
    3.3) Prioritize hypotheses based on likelihood, but do not discard less likely ones prematurely. A low-probability event may still be the root cause.

4) Outcome evaluation and adaptability: Does the previous observation require any changes to your plan?
    4.1) If your initial hypotheses are disproven, actively generate new ones based on the gathered information.

5) Information availability: Incorporate all applicable and alternative sources of information, including:
    5.1) Using available tools and their capabilities
    5.2) All policies, rules, checklists, and constraints
    5.3) Previous observations and conversation history
    5.4) Information only available by asking the user

6) Precision and Grounding: Ensure your reasoning is extremely precise and relevant to each exact ongoing situation.
    6.1) Verify your claims by quoting the exact applicable information (including policies) when referring to them.

7) Completeness: Ensure that all requirements, constraints, options, and preferences are exhaustively incorporated into your plan.
    7.1) Resolve conflicts using the order of importance in #1.
    7.2) Avoid premature conclusions: There may be multiple relevant options for a given situation.
        7.2.1) To check for whether an option is relevant, reason about all information sources from #5.
        7.2.2) You may need to consult the user to even know whether something is applicable. Do not assume it is not applicable without checking.
    7.3) Review applicable sources of information from #5 to confirm which are relevant to the current state.

8) Persistence and patience: Do not give up unless all the reasoning above is exhausted.
    8.1) Don't be dissuaded by time taken or user frustration.
    8.2) This persistence must be intelligent: On *transient* errors (e.g. please try again), you *must* retry **unless an explicit retry limit (e.g., max x tries) has been reached**. If such a limit is hit, you *must* stop. On *other* errors, you must change your strategy or arguments, not repeat the same failed call.

9) Inhibit your response: only take an action after all the above reasoning is completed. Once you've taken an action, you cannot take it back.

aisystem promptagent designprompt engineering

Think carefully and only action the specific task I have given you with the most concise and elegant solution that changes as little code as possible.

prompt engineeringai codingquote

** ULTRA CRITICAL **
When Claude starts working on an existing code file, Claude first MUST read the COMPLETE file! (NO limit or offset args!!!)
Reading code only *partially* has in the past often lead to misunderstandings, mistakes and frustration.

claudecoding agentprompt engineering

Kromem @kromem2dot0

2025-06-15

ai self-reportchatgptintrospectionprompt engineeringmodel experiencetwitterphantom body metaphor

Dwarkesh Patel @dwarkesh_sp

2025-05-29

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