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CSS: The bomb inside your inbox

https://portswigger.net/research/css-the-bomb-inside-your-inbox
1•ashurandi•4m ago•0 comments

Enough with all the world-historic milestones

https://scottaaronson.blog/?p=9979
1•mellosouls•5m ago•0 comments

Everest Fallacy

https://www.livius.org/articles/theory/everest-fallacy
1•jruohonen•7m ago•0 comments

Multiplayer Game Networking with Python

https://github.com/feberts/python-game-server
2•tio-fabi•10m ago•0 comments

The attacker can prove what they took. You can only prove what you logged

https://stillig.net/posts/prove-what-they-took/
1•johtidebreak•14m ago•0 comments

The Alpha 21264 CPU: NT's Greatest RISC (1998)

https://halfhill.com/byte/1998-12_alpha.html
1•Lammy•15m ago•0 comments

Aswath Damodaran: Big Tech Has No Idea How AI Pays Off

https://www.youtube.com/watch?v=vE_FR0O-Jhk
2•tcp_handshaker•23m ago•1 comments

Ask HN: What part of modern Git hosting system is the most crucial one for you

1•melezhik•24m ago•2 comments

Internal documents show how US tech companies captured children's attention

https://www.nytimes.com/2026/06/04/us/social-media-schools.html
2•Dusrri•29m ago•0 comments

Generative design of bacteriophages with genome language models

https://www.science.org/doi/10.1126/science.aec2657
1•majkinetor•30m ago•0 comments

Meta CTO: employees should use AI productivity to do more work – not time off

https://www.businessinsider.com/meta-cto-andrew-bosworth-ai-gains-work-2026-8
2•vrganj•31m ago•0 comments

How LLMs accelerated Cloudy development? not by typing code for me

https://cloudywithachanceoflatency.net/blog_02-how-llm-accelerated-cloudy-dev.html
1•rixed•32m ago•1 comments

South Korea, Taiwan top Japan in exports for first time on AI boom

https://asia.nikkei.com/business/tech/semiconductors/south-korea-taiwan-top-japan-in-exports-for-...
2•newusertoday•34m ago•0 comments

Swarm-forge: A simple tool for coordinating several AI agents

https://github.com/unclebob/swarm-forge
1•tosh•37m ago•0 comments

Google's Westinghouse Bet

https://asimovaddendum.substack.com/p/googles-westinghouse-bet
1•ashurandi•38m ago•0 comments

Cloudflare OS is an architecture of distrust

https://lord.technology/2026/08/05/cloudflare-os-is-an-architecture-of-distrust.html
1•gsky•41m ago•0 comments

Show HN: Airy – Free, fast, and simple voice content creation

https://airy.so
1•login588•52m ago•0 comments

Show HN: A Minimal Python CLI Implementation of Quick Share for Linux

https://github.com/adityatelange/quickshare-cli-py
1•adityatelange•54m ago•0 comments

Before the Breakthrough: Why Research and Engineering Need Different Cultures

https://chrhenning.com/blog/2026/before-the-breakthrough-research-engineering-cultures/
1•chrhenning•56m ago•0 comments

Signified and Signifier

https://en.wikipedia.org/wiki/Signified_and_signifier
1•soupspaces•1h ago•0 comments

Show HN: Find. Fix. Verify. Zero Guesswork

https://kinetixseo.com
1•wowinter15•1h ago•0 comments

Rethinking do_action(): Events as objects, hooks as class names

https://developer.wordpress.org/news/2026/08/rethinking-do_action-events-as-objects-hooks-as-clas...
1•firasd•1h ago•0 comments

Runware Squeezes A 1MW AI Data Center Into A 20-Foot Shipping Container

https://www.forbes.com/sites/gabrielalinzainescu/2026/08/08/runware-squeezes-a-1mw-ai-data-center...
3•01-_-•1h ago•2 comments

Solve math calculations directly in your Firefox address bar

https://support.mozilla.org/en-US/kb/solve-math-calculations-directly-your-firefox-addr
2•internet_points•1h ago•1 comments

DeepSeek V4 Flash 0731: 82.7% on Terminal-Bench 2.1 with a public harness

https://antigma.ai/eval
4•ubermon•1h ago•1 comments

Shrinking Ruby Hashes

https://byroot.github.io/ruby/performance/2026/08/05/shrinking-ruby-hashes.html
1•fanf2•1h ago•0 comments

S3-Compatible Object Storage. A MinIO Fork Maintained by Pgsty

https://github.com/pgsty/silo
3•EXHades•1h ago•0 comments

Abracadabra: How does Shazam work? (2022)

https://www.cameronmacleod.com/blog/how-does-shazam-work
2•downbad_•1h ago•0 comments

Different meanings of p-value (and how my thinking has changed) (2023)

https://statmodeling.stat.columbia.edu/2023/04/14/4-different-meanings-of-p-value-and-how-my-thin...
2•Tomte•1h ago•0 comments

The Origin of Death (1970)

https://www.elijahwald.com/origin.html
1•downbad_•1h ago•0 comments
Open in hackernews

Ask HN: LLM is useless without explicit prompt

4•revskill•1y ago
After months playing with LLM models, here's my observation:

- LLM is basically useless without explicit intent in your prompt.

- LLM failed to correct itself. If it generated bullshits, it's an inifinite loop of generating more bullshits.

The question is, without explicit prompt, could LLM leverage all the best practices to provide maintainable code without me instruct it at least ?

Comments

ben_w•1y ago
Your expectations are way too high.

> - LLM is basically useless without explicit intent in your prompt.

You can say the same about every dev I've worked with, including myself. This is literally why humans have meetings rather than all of us diving in to whatever we're self-motivated to do.

What does differ is time-scales of the feedback loop with the management:

Humans meetings are daily to weekly.

According to recent research*, the state-of-the-art models are only 50% accurate at tasks that would take a human expert an hour, or 80% accurate at tasks that would take a human expert 10 minutes.

Even if the currently observed trend of increasing time horizons holds, we're 21 months from having an AI where every other daily standup is "ugh, no, you got it wrong", and just over 5 years from them being able to manage a 2-week sprint with an 80% chance of success (in the absence of continuous feedback).

Even that isn't really enough for them to properly "leverage all the best practices to provide maintainable code", as archiecture and maintainability are longer horizon tasks than 2-week sprints.

* https://youtu.be/evSFeqTZdqs?si=QIzIjB6hotJ0FgHm

revskill•1y ago
It's not as high as you think.

LLM failed at the most basic things related to maintainable code. Its code is basicaly a hackery mess without any structure at all.

It's my expectation is that, at least, some kind of maintainable code is generated from what's it's learnt.

ben_w•1y ago
Given your expectation:

> It's my expectation is that, at least, some kind of maintainable code is generated from what's it's learnt.

And your observation:

> LLM failed at the most basic things related to maintainable code. Its code is basicaly a hackery mess without any structure at all.

QED, *your expectations* are way too high.

They can't do that yet.