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How can a sticky note app make you ten times more productive?

https://www.taskloco.com/
1•tasklocozon•33s ago•0 comments

AI tutor that turns any document into interactive voice lessons

https://www.tutorlify.com/en
1•mcourrech•5m ago•0 comments

A hallmarks-of-aging profile from data you have

https://agelessatlas.com/
1•luciabazanw•6m ago•0 comments

Coding Used to Be Amazing

https://dinosaurseateverybody.com/blog/coding-used-to-be-amazing
1•dorkrawk•7m ago•0 comments

CDC travel notice for outbreak deadly incurable mosquito virus reaches Americas

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2•Bender•7m ago•0 comments

Apple Maps and cartographic erasure of Jews

https://www.jns.org/opinion/daniel-winston/apple-maps-and-cartographic-erasure
1•bryanrasmussen•8m ago•1 comments

More testosterone won't make a better soldier or a tougher man

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Mochi 0.8.0

https://mochi.fast/blog/mochi-0-8-0/
1•khromov•8m ago•0 comments

Gnome Changes Security Disclosure Policies Due to AI-Generated Reports

https://www.phoronix.com/news/GNOME-Security-Changes-2026
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Show HN: Memsprout – share your AI context with teammates

https://memsprout.com
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Intel Expanding Memory Options for Current Xeon 6 / Xeon 6 Servers

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Brazil and US clash over future of payments as Pix system stirs global interest

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4•petethomas•12m ago•0 comments

Show HN: Redential – open-source CLI that proves what you can build, NDA safe

https://github.com/redential/redential-cli
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Show HN: Surfacing gaps in neuroscience and narrative insights in Final Fantasy

https://dmerullo.github.io/crystal-pipeline/
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Show HN: Jaybase: Append-only fact store for AI doing business workflows

https://github.com/kyle-visner/jaybase
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Show HN: Hoop – A sandboxed P2P live collaboration harness for Claude Code

https://github.com/bruno-de-queiroz/hoop
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Was there a real Tower of Babel? This temple is the leading contender

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3•bryanrasmussen•19m ago•0 comments

Liquid: Back to the Future

https://twitter.com/i/status/2079633466581258469
2•graemebenzie•28m ago•1 comments

Headroom - compress AI agent input for reduced token usage w/out harming output

https://github.com/headroomlabs-ai/headroom
1•andsoitis•29m ago•0 comments

It's a shame what's happened to radio

https://blog.jimgrey.net/2026/07/21/its-a-shame-whats-happened-to-radio-3/
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Lanyard SSH Agent Switchboard

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Ask HN: GitHub CVE Delays?

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Circuit board quilts by Wally Dion

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1•banrafflemoth•35m ago•0 comments

EC: 'Guidance to Google for AI Interoperability on Android'

https://daringfireball.net/2026/07/ec_google_guidance_android_ai_and_search_sharing
2•heironimus•37m ago•0 comments

The truth nobody wants to admit: Chinese or not, open models are competitive now

https://www.theregister.com/ai-and-ml/2026/07/22/the-truth-nobody-wants-to-admit-chinese-or-not-o...
4•joebuckwilliams•37m ago•1 comments

Semantic Search, in the Browser, in a Day

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JetBrains Context: Repository Intelligence for Coding Agents

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1•monkey_monkey•46m ago•0 comments

Scaleway: [fr-par-1] – Issue with Compute Instances

https://status.scaleway.com/incidents/bsp2y5fysy9w
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Jimothy? He has an 8-bit Retro Video Game (in a single HTML file)

https://arcade.pirillo.com/jimothy.html
2•ChrisPirillo•57m ago•0 comments

OpenAI Says Its A.I. Models Went Rogue and Attacked a Digital Library

https://www.nytimes.com/2026/07/21/technology/openai-attack-hugging-face.html
7•sbulaev•58m 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.