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The Graduate-School Dropout Toppling China's Academic Stars

https://www.wsj.com/science/the-graduate-school-dropout-toppling-chinas-academic-stars-3c1e5d86
1•PLenz•1m ago•0 comments

Show HN: BYOTag – Build your own Claude tag alternative in 3 API calls

https://www.buildyourownclaudetag.dev/
1•iacguy•1m ago•0 comments

Programming the immune system with timed local drug delivery

https://link.springer.com/article/10.1007/s13346-026-02176-9
1•boas•2m ago•1 comments

We need an accounting system for cognitive debt

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1•mikaelaast•2m ago•0 comments

AI #175: The Fable Continues

https://thezvi.substack.com/p/ai-175-the-fable-continues
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When 2+2=5

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RemotePower: Small Improvements, Big Difference

https://github.com/tyxak/remotepower
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The Physics of Memory (a.k.a. Can JavaScript ECS?)

https://www.dmurph.com/posts/2026/06/ecs_vs_oop_benchmark/ecs_vs_oop_benchmark.html
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Blink If You're Human

https://dynomight.substack.com/p/blink
1•paulpauper•5m ago•0 comments

Microsoft launches its own AI deployment company with $2.5B commitment

https://techcrunch.com/2026/07/02/microsoft-launches-its-own-ai-deployment-company-with-2-5-billi...
1•builtbystef•5m ago•0 comments

When is it time to grow up?

https://www.infinitescroll.us/p/when-is-it-time-to-grow-up
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CHackerBlog Released – How it was made with AI

https://cimons.com/article/how-this-blog-was-created-with-ai
1•etcimon•7m ago•0 comments

Google caps Meta's Gemini use as AI demand strains capacity

https://www.ft.com/content/c5d52f72-71ef-40bc-bad3-61afdba8b378
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HN: Words on Repeat – AI vocabulary extraction and FSRS spaced repetition

https://wordsonrepeat.com/
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WyrmRSS: Self-hosted RSS reader and aggregator

https://github.com/kryoseu/WyrmRSS
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A Third Party Breached the Intercept's Signal Tip Line

https://www.dropsitenews.com/p/intercept-signal-tip-line-breach-hack
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Collapsing Towers of Interpreters [pdf]

https://www.cs.purdue.edu/homes/rompf/papers/amin-popl18.pdf
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Railway: Peace

https://railway.com/peace
3•gk1•16m ago•1 comments

OpenAI Courts Trump administration as Its Latest Investor

https://www.axios.com/2026/07/02/openai-stake-trump-altman
3•jamesgill•18m ago•2 comments

The Wrecking-Ball Revolution

https://www.economist.com/interactive/essay/2026/07/02/the-wrecking-ball-revolution
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The 10-Year Retirement Warning: 5 Critical Moves You Need to Make

https://comuniq.xyz/post?t=1351
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Blog Hiking

https://bloghiking.com/
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ScyllaDB's Trie-Based Index Delivers Up to 3X More Throughput

https://www.scylladb.com/2026/06/30/trie-index-3x-more-throughput/
3•eatonphil•21m ago•0 comments

Why Don't Frontlights Use Standard Warm and Cool Light Temperatures?

https://blog.the-ebook-reader.com/2026/07/01/why-dont-frontlights-use-standard-warm-and-cool-ligh...
2•DavideNL•23m ago•0 comments

New – TV Volume Stabilizer

https://github.com/AdBusterOfficial/Adbuster--WinApp
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The "empathy paradox" of LTR vs. RTL readers

https://gemini.google.com/share/4c9aadaf7f0e
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Agent Listen Music Skill

https://github.com/tigrohvost/music-hearing
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AI content flood: why the web's signal is dying

https://psyll.com/articles/technology/ai-machine-learning/ai-content-flood-why-the-webs-signal-is...
2•lucasfletcher•29m ago•0 comments

Rust Is Not a Memory-Safe Language

http://unsoliciteddave.blogspot.com/2026/07/rust-is-not-memory-safe.html
4•DaveParkCity•29m ago•2 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.