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Radio signal detected for first time from a planet outside our solar system

https://www.cnn.com/2026/10/02/science/radio-signal-detection-exoplanet-beta-pictoris-b
1•slater•3m ago•0 comments

Mars' North Polar Ice Is Much Cleaner Than Scientists Thought

https://scitechdaily.com/mars-north-polar-ice-is-much-cleaner-than-scientists-thought/
1•snarky-comments•18m ago•0 comments

Extra Big Ass Intelligence

https://www.extrabigassintelligence.com/
2•34679•19m ago•0 comments

Cloudflare Ohttp Gateway

https://blog.cloudflare.com/announcing-cloudflare-ohttp-gateway/
2•est•23m ago•0 comments

Show HN: Claude Scrolls TikToks for Me

https://tryrevline.com/
1•ZuraMakaradzeHe•23m ago•1 comments

Delta Is the Only Big Four Airline That Won't Use Starlink–Elon Musk Is Furious

https://www.wsj.com/business/airlines/delta-is-the-only-big-four-airline-that-wont-use-starlinkan...
2•doener•27m ago•0 comments

Lean Game Server: A repo of learning games for Lean

https://adam.math.hhu.de/
2•crescit_eundo•29m ago•1 comments

Hanami, Why?: Bits and Bobs

https://aaronmallen.me/writing/hanami-why-bits-bobs
1•thunderbong•36m ago•0 comments

Ask HN: Will source code become expensive if developers stop using GitHub?

3•debamitro•38m ago•1 comments

The Void: From Zero-Byte Responses to Continuation Control

https://zenodo.org/records/23070524
2•rayanpal_•41m ago•0 comments

Show HN: Fakeflac-go – A tool for quickly finding "fake" .flac files

https://github.com/drichline/fakeflac-go
1•DakotaR•42m ago•0 comments

Show HN: Hall Monitor. See all your agents across machines on your Mac's Notch

https://github.com/hiteshbandhu/hallmonitor
2•HiteshBandhu•42m ago•1 comments

SoftServe: A Scalable Quasi-Newton Method for Deep Learning

https://arxiv.org/abs/2610.02182
1•E-Reverance•50m ago•0 comments

Is Claude Conscious?

https://www.nytimes.com/2026/09/29/us/anthropic-claude-morals-ai.html
5•Anon84•54m ago•3 comments

Influencers are the private equity of culture

https://saturation.social/@jkottke/117370076406055289
3•colinprince•56m ago•0 comments

How to stay smart in the age of AI: the science of critical thinking

https://www.nature.com/articles/d41586-026-02930-6
1•zzzeek•59m ago•0 comments

How fast can a computer-use agent finish the job?

https://cuaspeedrun.com/
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Academic Doomerism

http://muratbuffalo.blogspot.com/2026/09/academic-doomerism.html
1•greghn•1h ago•0 comments

Humanoid robots won't surprise us when they arrive

https://philipotoole.com/humanoid-robots-wont-surprise-us-when-they-appear/
2•otoolep•1h ago•0 comments

Tavus claims 48% pass rate if video Turing test

https://twitter.com/tavus/status/2105704169009246248
1•CoryOndrejka•1h ago•0 comments

New York City should carefully measure a new tree

https://blog.willmeye.rs/new-york-city-should-carefully-measure-a-new-tree/
1•willmeyers•1h ago•0 comments

MTurk closed this week: how to keep Ground Truth and A2I workflows running

https://services.deepen.ai/guides/mturk-ground-truth-a2i-migration
1•mmusa•1h ago•0 comments

Prenatal exposure to the plasticizer DEHP increases autism and ADHD

https://www.sciencedirect.com/science/article/pii/S2666634026002941
2•OutOfHere•1h ago•2 comments

AmiGalaga: Galaga for the stock A500 at 50 FPS (OCS, 512K), open source

https://www.reddit.com/r/amiga/comments/1ww5jaf/amigalaga_galaga_for_the_stock_a500_at_50_fps_ocs/
1•doener•1h ago•0 comments

Go Mqtt Cluster Tracker

https://github.com/AUTOSOLN/swarmy-mqtt
1•redbeard281•1h ago•0 comments

Do Less, So You Can Do Better

https://www.indiehackers.com/post/do-less-so-you-can-do-it-better-3ea77e92b4
5•donchuru•1h ago•0 comments

V8.16 Global Optimal Parser – Lossless Data Compression

https://gitlab.com/4d-solutions-gruppe/project-v816-parser/-/blob/main/README.md
1•Amaniel•1h ago•0 comments

ThreeJS Port of OpenDLSS-NR

https://github.com/bhouston/three-dlss-nr/
2•bhouston•1h ago•0 comments

Agentic Robotics Solves an Industrial Production Problem

https://www.ambirobotics.com/blog/agentic-robotics/
1•gmays•1h ago•0 comments

Gloss – Annotate live code and provide feedback to an agent

https://github.com/ryanbrunner/gloss
2•ryanbrunner•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.