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Would you use an e-commerce platform that shares transaction fees with users?

https://moondala.one/
1•HamoodBahzar•1m ago•1 comments

Show HN: SafeClaw – a way to manage multiple Claude Code instances in containers

https://github.com/ykdojo/safeclaw
2•ykdojo•4m ago•0 comments

The Future of the Global Open-Source AI Ecosystem: From DeepSeek to AI+

https://huggingface.co/blog/huggingface/one-year-since-the-deepseek-moment-blog-3
2•gmays•4m ago•0 comments

The Evolution of the Interface

https://www.asktog.com/columns/038MacUITrends.html
2•dhruv3006•6m ago•0 comments

Azure: Virtual network routing appliance overview

https://learn.microsoft.com/en-us/azure/virtual-network/virtual-network-routing-appliance-overview
2•mariuz•6m ago•0 comments

Seedance2 – multi-shot AI video generation

https://www.genstory.app/story-template/seedance2-ai-story-generator
2•RyanMu•10m ago•1 comments

Πfs – The Data-Free Filesystem

https://github.com/philipl/pifs
2•ravenical•13m ago•0 comments

Go-busybox: A sandboxable port of busybox for AI agents

https://github.com/rcarmo/go-busybox
3•rcarmo•14m ago•0 comments

Quantization-Aware Distillation for NVFP4 Inference Accuracy Recovery [pdf]

https://research.nvidia.com/labs/nemotron/files/NVFP4-QAD-Report.pdf
2•gmays•15m ago•0 comments

xAI Merger Poses Bigger Threat to OpenAI, Anthropic

https://www.bloomberg.com/news/newsletters/2026-02-03/musk-s-xai-merger-poses-bigger-threat-to-op...
2•andsoitis•15m ago•0 comments

Atlas Airborne (Boston Dynamics and RAI Institute) [video]

https://www.youtube.com/watch?v=UNorxwlZlFk
2•lysace•16m ago•0 comments

Zen Tools

http://postmake.io/zen-list
2•Malfunction92•18m ago•0 comments

Is the Detachment in the Room? – Agents, Cruelty, and Empathy

https://hailey.at/posts/3mear2n7v3k2r
2•carnevalem•18m ago•0 comments

The purpose of Continuous Integration is to fail

https://blog.nix-ci.com/post/2026-02-05_the-purpose-of-ci-is-to-fail
1•zdw•21m ago•0 comments

Apfelstrudel: Live coding music environment with AI agent chat

https://github.com/rcarmo/apfelstrudel
2•rcarmo•21m ago•0 comments

What Is Stoicism?

https://stoacentral.com/guides/what-is-stoicism
3•0xmattf•22m ago•0 comments

What happens when a neighborhood is built around a farm

https://grist.org/cities/what-happens-when-a-neighborhood-is-built-around-a-farm/
1•Brajeshwar•22m ago•0 comments

Every major galaxy is speeding away from the Milky Way, except one

https://www.livescience.com/space/cosmology/every-major-galaxy-is-speeding-away-from-the-milky-wa...
2•Brajeshwar•22m ago•0 comments

Extreme Inequality Presages the Revolt Against It

https://www.noemamag.com/extreme-inequality-presages-the-revolt-against-it/
2•Brajeshwar•23m ago•0 comments

There's no such thing as "tech" (Ten years later)

1•dtjb•23m ago•0 comments

What Really Killed Flash Player: A Six-Year Campaign of Deliberate Platform Work

https://medium.com/@aglaforge/what-really-killed-flash-player-a-six-year-campaign-of-deliberate-p...
1•jbegley•24m ago•0 comments

Ask HN: Anyone orchestrating multiple AI coding agents in parallel?

1•buildingwdavid•25m ago•0 comments

Show HN: Knowledge-Bank

https://github.com/gabrywu-public/knowledge-bank
1•gabrywu•31m ago•0 comments

Show HN: The Codeverse Hub Linux

https://github.com/TheCodeVerseHub/CodeVerseLinuxDistro
3•sinisterMage•32m ago•2 comments

Take a trip to Japan's Dododo Land, the most irritating place on Earth

https://soranews24.com/2026/02/07/take-a-trip-to-japans-dododo-land-the-most-irritating-place-on-...
2•zdw•32m ago•0 comments

British drivers over 70 to face eye tests every three years

https://www.bbc.com/news/articles/c205nxy0p31o
47•bookofjoe•32m ago•18 comments

BookTalk: A Reading Companion That Captures Your Voice

https://github.com/bramses/BookTalk
1•_bramses•33m ago•0 comments

Is AI "good" yet? – tracking HN's sentiment on AI coding

https://www.is-ai-good-yet.com/#home
3•ilyaizen•34m ago•1 comments

Show HN: Amdb – Tree-sitter based memory for AI agents (Rust)

https://github.com/BETAER-08/amdb
1•try_betaer•35m ago•0 comments

OpenClaw Partners with VirusTotal for Skill Security

https://openclaw.ai/blog/virustotal-partnership
2•anhxuan•35m ago•0 comments
Open in hackernews

Daoism, Prompting, and Why Trying Too Hard Makes Everything Worse

1•yanjiechg•2mo ago
I’ve been spending a lot of time with AI image models lately, trying to get good ad creatives out of them.

One thing keeps coming up:

Writing prompts feels weirdly similar to practicing Daoism.

Most people (including past me) assume: if you want a “perfect” image, you must control everything:

lens, lighting, angle, composition

every style tag under the sun

10 adjectives for mood + 5 for color + 3 for vibe

Basically: design the whole image in your head, then force the model to follow.

What usually happens?

The prompt is heavy, the intention is blurry, and the image looks stiff and over-produced. Exactly the opposite of what we wanted.

This is where Daoism quietly laughs at us.

1. Over-controlling the model = going against the “Way”

Daoism has this idea:

“The Dao does nothing, yet nothing is left undone.”

It’s not about being lazy. It’s about not fighting the natural flow of things just because we’re anxious.

Translate that into prompting:

We try to control every tiny variable

The model receives a wall of instructions, many of them conflicting

It squeezes out something that technically “checks all the boxes” but feels… dead

Too many rules = no real direction. You’re basically telling the model: “Do everything, in every style, all at once.”

2. Good prompts are more “go with the flow” than “command the universe”

Now when I look at a prompt, I ask myself:

Is this a clear intention, or is this a control freak moment?

The “control freak” prompts usually:

are very long

try to lock down every parameter “just in case”

come from fear: “if I don’t specify this, the model will ruin it”

The “go with the flow” prompts are different:

One clear idea: what is this image really about?

A few key constraints: scene type, mood, rough composition

Then space for the model to do its job

And the funny thing is:

Short, sharp prompts often give me images that feel more natural, human, and alive.

3. Daoism for prompt engineers: very practical version

If I compress all this into something usable, it’s probably:

① One center

Pick one core priority:

Is this about the product look?

The real-life scene?

The emotion on the person’s face?

Choose one. A single image can’t carry five main messages without breaking.

② Know when to stop

Every time you add a line to the prompt, ask:

If I remove this, will the model still understand what I want?

If the answer is “yes”, you probably don’t need it.

Most good prompts can be explained in 5–7 key pieces of information, not 25.

③ Leave room

Your job is to set direction, not micro-manage:

“Morning light, casual kitchen scene, young person using X for their daily ritual” is usually enough.

You don’t have to decide every highlight and shadow. Some of the “happy accidents” from the model are exactly what make the image feel alive.

4. Follow the “nature” of the model instead of fighting it

The model has its own “Dao”:

It’s very good at expanding from a clear, slightly open-ended idea

It’s very bad at satisfying 10 pages of strict, sometimes conflicting rules

When we prompt from a place of panic (“I must specify everything or it will mess up”) we are basically fighting the system.

When we prompt with more Daoist energy:

clear

restrained

directional

with space

we usually get results that are more:

natural

believable

and actually closer to how humans see the world

Closing

Prompting looks like a purely technical skill from the outside. But the more I do it, the more it feels like a mirror:

How much do you need to control?

How much can you let go, once the direction is right?

Personally, I’m trying to move from “control-everything prompts” → “Daoist prompts”.

Curious where you are on that spectrum. If you’ve noticed similar things in your own prompting, I’d love to hear it.