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Does My Net Work?

https://doesmynet.work/
1•Mr3zee•34s ago•0 comments

Take the 2026 Go Developer Survey

https://blink.qualtrics.com/jfe/form/SV_ba8fa1ZcSQQdTRs
1•vanyauhalin•2m ago•0 comments

A Git Forge Without a Center

https://entire.com/blog/a-git-forge-without-a-center
1•meetpateltech•3m ago•0 comments

Did the Hardest Problem in AI Just Get Much Easier?

https://www.nytimes.com/2026/10/27/science/ai-problem-interpretability.html
1•flowerlad•4m ago•0 comments

Learning Is Memory

https://www.justinmath.com/learning-is-memory/
1•gmays•4m ago•0 comments

Show HN: FOSS Habit Tracker for iOS

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1•zamai•4m ago•0 comments

Notational Velocity and nvALT, classic macOS note-taking apps, are back

https://manualdousuario.net/en/notationa-velocity-nvalt-updated/
1•rpgbr•5m ago•0 comments

The Download: Anthropic's IPO, smarter power grids, and exercise pills

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2•joozio•8m ago•0 comments

Running Local AI on Nvidia DGX Spark Without CUDA

https://github.com/aien-dev/CUDApp
1•drakestapleton•9m ago•2 comments

Blazle – Block prompt injection and secret leaks before AI agents act

https://www.blazle.io/
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Microsoft and Epic Games DCMA AI-Gen Clones

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Tom Hegen Documents the Indelible Effects of the Green Transition

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1•rdmuser•12m ago•0 comments

Police Are Pulling People over Because AI Deems Their Driving "Suspicious"

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3•JumpCrisscross•13m ago•0 comments

I Used AI to Fake a Scientific Paper. Here's What Happened

https://spectrum.ieee.org/ai-generated-scientific-papers
1•jruohonen•14m ago•0 comments

MAI Image 2.7 debuts above GPT Image 2.5 Flare on Artificial Analysis

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2•doomroot13•14m ago•0 comments

The Rise of Überengineers

https://ashu1461.com/posts/the-age-of-uberengineers/
2•ashu1461•15m ago•0 comments

Apache POI 6.0.0 Released

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1•ejboy•15m ago•0 comments

Omni Magazine Archive

https://archive.org/details/omni-archive
1•pavel_lishin•15m ago•0 comments

Glacex: GPU-Rendered UI library built from scratch in Rust

https://github.com/artemtsitronov/glacex
1•adamnemecek•15m ago•0 comments

The Web Can't Afford a JavaScript Runtime Monoculture

https://redmonk.com/kholterhoff/2026/10/27/js-runtime-monoculture/
3•eatonphil•16m ago•1 comments

How to Give Your AI Agent Memory You Can Audit

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1•Arshad-Talpur•17m ago•0 comments

The State of Greenhouse Gases in the Atmosphere

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1•layer8•21m ago•0 comments

Show HN: SkillScout, ranking AI tools by how you work instead of popularity

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2•pepe4chan•23m ago•0 comments

Experimenting with Databases

https://replicated.live/blog/db
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Seam Cutter

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A suspended user's agent run still wrote a file: an internal pilot

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1•YusefSyed•24m ago•0 comments

Protobuf in Python and TypeScript is good now

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1•eatonphil•24m ago•0 comments

Show HN: Web-based, super barebones markdown editor

https://github.com/ConorCallanan2003/browsermd
1•conor_callanan•25m ago•0 comments

Stop Vibing, Start Resonating: Pair Programming with LLM Agents

https://alphapixeldev.com/vibe-coding-vs-resonance-coding/
1•XenonofArcticus•26m ago•0 comments

Gilgamesh by Simon Armitage review – an ancient epic is brilliantly translated

https://www.theguardian.com/books/2026/oct/20/gilgamesh-by-simon-armitage-review-an-ancient-epic-...
1•benbreen•26m 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.