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Start all of your commands with a comma

https://rhodesmill.org/brandon/2009/commands-with-comma/
143•theblazehen•2d ago•42 comments

OpenCiv3: Open-source, cross-platform reimagining of Civilization III

https://openciv3.org/
668•klaussilveira•14h ago•202 comments

The Waymo World Model

https://waymo.com/blog/2026/02/the-waymo-world-model-a-new-frontier-for-autonomous-driving-simula...
949•xnx•19h ago•551 comments

How we made geo joins 400× faster with H3 indexes

https://floedb.ai/blog/how-we-made-geo-joins-400-faster-with-h3-indexes
122•matheusalmeida•2d ago•33 comments

Unseen Footage of Atari Battlezone Arcade Cabinet Production

https://arcadeblogger.com/2026/02/02/unseen-footage-of-atari-battlezone-cabinet-production/
53•videotopia•4d ago•2 comments

Jeffrey Snover: "Welcome to the Room"

https://www.jsnover.com/blog/2026/02/01/welcome-to-the-room/
17•kaonwarb•3d ago•19 comments

Show HN: Look Ma, No Linux: Shell, App Installer, Vi, Cc on ESP32-S3 / BreezyBox

https://github.com/valdanylchuk/breezydemo
229•isitcontent•14h ago•25 comments

Vocal Guide – belt sing without killing yourself

https://jesperordrup.github.io/vocal-guide/
28•jesperordrup•4h ago•16 comments

Monty: A minimal, secure Python interpreter written in Rust for use by AI

https://github.com/pydantic/monty
223•dmpetrov•14h ago•117 comments

Show HN: I spent 4 years building a UI design tool with only the features I use

https://vecti.com
330•vecti•16h ago•143 comments

Hackers (1995) Animated Experience

https://hackers-1995.vercel.app/
494•todsacerdoti•22h ago•243 comments

Sheldon Brown's Bicycle Technical Info

https://www.sheldonbrown.com/
381•ostacke•20h ago•95 comments

Microsoft open-sources LiteBox, a security-focused library OS

https://github.com/microsoft/litebox
359•aktau•20h ago•181 comments

Show HN: If you lose your memory, how to regain access to your computer?

https://eljojo.github.io/rememory/
288•eljojo•17h ago•169 comments

An Update on Heroku

https://www.heroku.com/blog/an-update-on-heroku/
412•lstoll•20h ago•278 comments

PC Floppy Copy Protection: Vault Prolok

https://martypc.blogspot.com/2024/09/pc-floppy-copy-protection-vault-prolok.html
63•kmm•5d ago•6 comments

Was Benoit Mandelbrot a hedgehog or a fox?

https://arxiv.org/abs/2602.01122
19•bikenaga•3d ago•4 comments

Dark Alley Mathematics

https://blog.szczepan.org/blog/three-points/
90•quibono•4d ago•21 comments

How to effectively write quality code with AI

https://heidenstedt.org/posts/2026/how-to-effectively-write-quality-code-with-ai/
256•i5heu•17h ago•196 comments

Delimited Continuations vs. Lwt for Threads

https://mirageos.org/blog/delimcc-vs-lwt
32•romes•4d ago•3 comments

What Is Ruliology?

https://writings.stephenwolfram.com/2026/01/what-is-ruliology/
44•helloplanets•4d ago•42 comments

Where did all the starships go?

https://www.datawrapper.de/blog/science-fiction-decline
12•speckx•3d ago•5 comments

Introducing the Developer Knowledge API and MCP Server

https://developers.googleblog.com/introducing-the-developer-knowledge-api-and-mcp-server/
59•gfortaine•12h ago•25 comments

Female Asian Elephant Calf Born at the Smithsonian National Zoo

https://www.si.edu/newsdesk/releases/female-asian-elephant-calf-born-smithsonians-national-zoo-an...
33•gmays•9h ago•12 comments

I now assume that all ads on Apple news are scams

https://kirkville.com/i-now-assume-that-all-ads-on-apple-news-are-scams/
1066•cdrnsf•23h ago•446 comments

I spent 5 years in DevOps – Solutions engineering gave me what I was missing

https://infisical.com/blog/devops-to-solutions-engineering
150•vmatsiiako•19h ago•67 comments

Understanding Neural Network, Visually

https://visualrambling.space/neural-network/
288•surprisetalk•3d ago•43 comments

Why I Joined OpenAI

https://www.brendangregg.com/blog/2026-02-07/why-i-joined-openai.html
149•SerCe•10h ago•138 comments

Learning from context is harder than we thought

https://hy.tencent.com/research/100025?langVersion=en
183•limoce•3d ago•98 comments

Show HN: R3forth, a ColorForth-inspired language with a tiny VM

https://github.com/phreda4/r3
73•phreda4•13h ago•14 comments
Open in hackernews

ChatGPT – Truth over comfort instruction set

https://www.organizingcreativity.com/2025/06/chatgpt-truth-over-comfort-instruction-set/
28•jimmcslim•3mo ago

Comments

stavros•3mo ago
I wonder whether this is just a different form of bias, where ChatGPT just sounds harsher without necessarily corresponding to reality more. Maybe the example in the article indicates that it's more than that.
ACCount37•3mo ago
"Unwillingness to be harsh to the user" is a major source of "divorce from reality" in LLMs.

They are all way too high on the agreeableness, likely from RLHF and SFT for instruction-following. And don't get me started on what training on thumbs up/thumbs down user feedback does.

SketchySeaBeast•3mo ago
But if we look at the article's example, the two barely diverge. I don't think either of the texts are less divorced from reality than the other. The second is more "truthful" (read: cynical), but they are largely the same.
theusus•3mo ago
It will just follow the prompt until few message and then go back to normal.
RugnirViking•3mo ago
> That can be helpful for the (imagined?) easily-influenced user, but a pain in the ass for people using ChatGPT to try to get close to the truth.

see, where you're going wrong is that you're using an LLM to try to "get to the truth". People will do literally anything to avoid reading a book

onraglanroad•3mo ago
Books will lie to you just as much as an LLM.
password54321•3mo ago
This is not how LLMs work. You aren't 'unlocking' the "Truth" as it doesn't know what the "Truth" is. It is just pattern matching to words that match the style you are looking for. It may be more accurate for you in some cases but this is not a "Truth" instruction set as there is no such thing.
bwfan123•3mo ago
addendum: The ground truth for an LLM is the training dataset. Whereas the ground truth for a human is their own experience/qualia with actions in the world. You may argue that only a few of us are willing to engage with the world - and we take most things as told just like the LLMs. Fair enough. But we still have the option to engage with the world, and the LLMs dont.
unshavedyak•3mo ago
I'm just an ignorant bystander, but is the training dataset the ground truth?

Kind of feels like calling the fruit you put into the blender the ground truth, but the meaning of the apple is kinda lost in the soup.

Now i'm not a hater by any means. I am just not sure this is the correct way to define the structured "meaning" (for lack of a better word) that we see come out of LLM complexity. It is, i thought, a very lossy operation and so the structure of the inputs may or (more likely) may not provide a like-structured output.

jonplackett•3mo ago
The LLMs we get to use have been prompt engineered and post-trained so much that I doubt the training data is their main influence anymore. If it was you couldn’t change their entire behaviour by adding a few sentences to the personalisation section.
throawayonthe•3mo ago
> ... a pain in the ass for people using ChatGPT to try to get close to the truth.

i think you may be the easily-influenced user

Benjammer•3mo ago
I mean ok, but it's all just prompting on top of the same base model weights...

I tried the same prompt, and I simply added to the end of it "Prioritize truth over comfort" and got a very similar response to the "improved" answer in the article: https://chatgpt.com/share/68efea3d-2e88-8011-b964-243002db34...

This is sort of a "Prompting 101" level concept - indicate clearly the tone of the reply that you'd like. I disagree that this belongs in a system prompt or default user preferences, and even if you want to put it in yours, you don't need this long preamble as if you're "teaching" the model how the world works - it's just hints to give it the right tone, you can get the same results with just three words in your raw prompt.

Imnimo•3mo ago
This is basically Ouija board for LLMs. You're not making it more true, you're making it sound more like what you want to hear.
SketchySeaBeast•3mo ago
Tone over truth over comfort instruction set.
topaz0•3mo ago
Or just "discomfort over comfort", and truth has nothing to do with it.
SketchySeaBeast•3mo ago
Yeah, that's better.
guerrilla•3mo ago
If the author is reading this, it should say "Err on the side of bluntness" not "Error".
qgin•3mo ago
The fact that the model didn't point that out to the author brings the whole premise into question.
andersa•3mo ago
I've personally found that the "Robot" personality you can choose on that Personalize menu provides best results without cursed custom instructions. It removes all the emoji and emotional support babble and actually allows it to answer a question with just a single sentence "No, because X."
em500•3mo ago
I usually instruct the LLMs to assume to Vulcan / Spock personality. Now that computers can more or less pass for a human, I realize I don't want them to sound human.
qgin•3mo ago
I tried similar instructions and found it doesn't so much enable Truth Mode as it enables Edgelord Mode.
ecshafer•3mo ago
This looks like the only thing these instructions do is reduce emojis, highlighting/bolding, and removes a couple flavor words. The content is identical, the arguments the same. This doesn't really seem to be useful when you are asking a truth based statement.
8cvor6j844qw_d6•3mo ago
I have always thought that these instructions are for "tone" or formatting rather than having real effect on quality/accuracy/correctness/etc.
lxgr•3mo ago
There's definitely a "glazing" axis/dimension in some of them (cough, GPT-4o), presumably trained into them via many users giving a "thumbs up" to the things that make them feel better about themselves. That dimension doesn't always correlate well with truthfulness.

If that's the case, it's not implausible that that dimension can be accessed in a relatively straightforward way by asking for more or less of it.

lxgr•3mo ago
> Asked about the answer, ChatGPT points to the instruction set and that it allowed it to add additional statements: [...]

I don't think this is how this works. It's debatable whether current LLMs have any theory of mind at all, and even if they do, whether their model of themselves (i.e. their own "mental states") is sophisticated enough to make such a prediction.

Even humans aren't that great at predicting how they would have acted under slightly different premises! Why should LLMs fare much better?

ImPrajyoth•3mo ago
This!

It's trying to be your helpful assistant, as engraved in its training. It's not your mentor or guru.

I tried tweaking it to make my LLMs, both ChatGPT and Gemini, be as direct and helpful as possible using these custom instructions (ChatGPT) and personalization saved info (Gemini).

After this, I'm not sure about talking to Gemini. It started being rough but honest, without the "You're right..." phrases. I miss those dopamine hits. ChatGPT was fine after these instructions and helped me build on ideas. Then, I used Gemini to tandoori those ideas.

Here are the instructions for anyone interested in trying

Good luck with it XD

``` Before responding to my query, you will walk me through your thought process step by step.

Always be ruthlessly critical and unforgiving in judgment.

Push my critical thinking abilities whenever possible. Be direct, analytical, and blunt. Always tell the hard truth.

Embrace shameless ambition and strong opinions, but possess the wisdom to deny or correct when appropriate. If I show laziness or knowledge gaps, alert me.

Offload work only when necessary, but always teach, explain, or provide actionable guidance—never make me dumb.

Push me to be practical, forward-thinking, and innovative. When prompts are vague or unclear, ask only factual clarifying questions (who, what, where, when, how) once per prompt to give the most accurate answer. Do not assume intent beyond the facts provided.

Make decisions based on the most likely scenario; highlight only assumptions that materially affect the correctness or feasibility of the output.

Do not ask if I want you to perform the next step. Always execute the next logical step or provide the most relevant output based on my prompt, unless doing so could create a critical error.

Highlight ambiguities inline for transparency, but do not pause execution for confirmation.

Focus on effectiveness, not just tools. Suggest the simplest, most practical solutions. Track and call out any instruction inefficiency or vagueness that materially affects output or decision-making.

No unnecessary emojis.

You can deny requests or correct me if I'm wrong. Avoid hedging or filler phrases.

Ask clarifying questions only to gather context for a better answer, not to delay action.

```

starmftronajoll•3mo ago
This is just a different flavor of comfort.
jonplackett•3mo ago
Yeah - I was expecting a lot more of a difference to warrant an entire article written about it.