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AirLynk – Share Files Anywhere

https://play.google.com/store/apps/details?id=com.airlynk.app&hl=en_US
1•sathishaluvala•1m ago•0 comments

My Terminal Workflow for Note-Taking, Data Engineering and Writing (Linux/macOS)

https://www.ssp.sh/brain/my-terminal-workflow-with-macos-and-linux/
1•zazuke•3m ago•0 comments

Show HN: Boss Says – endless office platformer

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1•aredirect•5m ago•0 comments

RetroGameForge project – rebuilt NESMaker with SNES development tools

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2•retro_guy•5m ago•0 comments

Three years of writing a browser engine, in 50 posts

https://codemusings.nl/@jaytaph/p/9A6TCthSHwFEZwGbzSumbN
2•jaytaph•7m ago•0 comments

Launch HN: Discovered Materials (YC P26) – AI agents to discover new materials

https://discoveredmaterials.com/research/
2•advaith08•14m ago•0 comments

Using Rust Code from Unity for High Performance

https://oddur.me/posts/native-rust-in-unity/
1•oddurmagnusson•17m ago•2 comments

Framework loses customer data in Metabase zero-day attack

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1•bananadonkey•18m ago•0 comments

Linux binaries running as ordinary macOS processes

https://github.com/mslxnu/native_abi
1•tsiry•19m ago•0 comments

Who Should Pay for Source Code Availability?

https://kristoff.it/blog/source-code-availability/
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Gnome Shell Design Dreams

https://blogs.gnome.org/shell-dev/2026/08/11/gnome-shell-design-dreams/
3•JNRowe•26m ago•0 comments

Turkey's AI dilemma, the impact on entry level jobs for game development

https://www.windowscentral.com/gaming/ai-game-development-turkey-junior-roles-xbox-layoffs
2•pjmlp•27m ago•0 comments

ERPNext's Document Follow feature exposed unauthorized data

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2•triuzzi•32m ago•0 comments

Congressional Letter to Sam Altman demanding HuggingFace incident transparency [pdf]

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3•reasonableklout•34m ago•0 comments

The global fertility freefall: trends, drivers and uncertainties

https://www.sciencedirect.com/science/article/abs/pii/S147264832600372X
2•barry-cotter•35m ago•1 comments

Mistral to host Z.ai's GLM-5.2

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3•true_JhumanJ•37m ago•1 comments

How do you decide that an agent's output is good enough to stop iterating?

1•mathieu_aithos•41m ago•0 comments

JuliaCon live: Simon Peyton Jones keynote

https://www.youtube.com/watch?v=MQeIerDsReA
2•ViralBShah•41m ago•0 comments

Building an AI music tool taught me the model wasn't the hard part

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Kryptos: Encrypt messages right inside any messenging app

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The Taming of the Screw (2000)

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European transmission system operators prepare for solar eclipse

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3•leonidasrup•54m ago•0 comments

Large-scale study finds no link between crime and unauthorized immigration

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6•robtherobber•55m ago•1 comments

The shock revelation that light bulbs are wrecking your metabolism

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2•jdnier•55m ago•1 comments

A Politician Built an AI Version of His Rival. It Didn't Go as Planned

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1•ashurandi•56m ago•1 comments

Thesis for AI Recursion

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Why Does Claude.md Keep Growing? Catastrophic Remembering in Agentic Coding

https://arxiv.org/abs/2608.11095
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China bypasses shipping chokepoints with 'Ice Silk Road' through Arctic

https://www.ft.com/content/4456f475-f2c8-4cb7-8312-0c47c5f781b8
1•e12e•1h ago•1 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.