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Text AI watermarks will always be trivial to remove

https://www.seangoedecke.com/text-ai-watermarks/
1•ingve•38s ago•0 comments

Show HN: Scalable AI Management Platform

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1•metaralf•4m ago•0 comments

The gauge broke: devs felt 20% faster with AI, measured 19% slower

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BioShocking AI: "Gaming" the AI Browser and Escaping Its Guardrails

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1•croes•6m ago•0 comments

Horsewood (2 July 2026) We Tried It My Honest ReviewS

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Seattle Just Had an Earthquake

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Feds Might Flip the Script on Right to Repair Vehicle Emissions Systems

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2•josephcsible•20m ago•0 comments

Likelihood, and Maximum Likelihood, in Statistics

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Fable 5 is insanely good

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My Story of 3D Realms / Apogee Part I (2020)

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NoUI()

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2•ingve•31m ago•0 comments

OpenAgents makes Sonnet 5, Fable 5 and other agents collaborate in one thread

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The Socialist Wave Reaches the Heartland

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PyCanopy: A spatial query layer for Polars, competitive with DuckDB, SedonaDB

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The Complete Homemade Juggling Beanbag Guide

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Google's exponential path to climate-wrecking digital bloat

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1•jalev•45m ago•0 comments

LongCat 2.0: The first trillion-parameter model trained on Chinese-made GPUs

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Limine: Modern, secure, portable, multiprotocol bootloader and boot manager

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Cotal: Agentic Coordination Layer

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CSS Logical Properties Converter

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The Three Projections of Doctor Futamura

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1•tristenharr•55m 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.