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StudentRisk AI – Predicting student dropout and wellbeing using AI and analytics

https://studentrisk.admnwizard.com/dashboard
1•sureshwin•2m ago•1 comments

Show HN: DeepFace now supports DB-backed vector search for face recognition

https://sefiks.com/2026/01/01/introducing-brand-new-face-recognition-in-deepface/
1•serengil•4m ago•0 comments

Give the Internet an Infinite Word Search and the Internet Will Draw Dicks on It

https://gizmodo.com/give-the-internet-an-infinite-word-search-and-the-internet-will-draw-a-dick-o...
1•yathern•6m ago•0 comments

Mailchimp Free Plan Now Supports Only 250 Contacts

https://blog.groupmail.io/mailchimp-free-plan-changes-2026/
2•apparent•10m ago•1 comments

Ask HN: Fastest Security Event Info Channels?

1•timnetworks•11m ago•0 comments

Why doesn't Google Maps show events?

https://tommaso-girotto.co/blog/a-universal-events-app
1•tgirotto•14m ago•2 comments

The Cathedral, the Megachurch, and the Bazaar

https://opensourcesecurity.io/2026/01-cathedral-megachurch-bazaar/
1•todsacerdoti•15m ago•0 comments

Inline-Replies, and Why Outlook 2013 Has Gone Blue (2013)

https://blog.extrobe.co.uk/blog/2013/07/09/inline-replies-and-why-outlook-2013-has-gone-blue/
1•WaluigiBSOD•15m ago•0 comments

Show HN: Run and Compile LLMs in PyTorch on WebGPU

https://github.com/jmaczan/torch-webgpu
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Nuclear bunker nears collapse due to erosion

https://www.bbc.co.uk/news/articles/c4g0dp65v77o
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NFR Breaking Shannon Entropy with Instance-Specific LSTM,Arithmetic Coding

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2•philippeantoine•17m ago•1 comments

Linux Mint 22.3

https://blog.linuxmint.com/?p=4981
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Systems feel slow to build and fast to use

https://www.alexscamp.com/p/the-best-systems-feel-slow-to-build
1•dovhyi•21m ago•0 comments

ConvertX – Self-hosted online file converter

https://github.com/C4illin/ConvertX
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Show HN: AI background remover that runs 100% in the browser

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Dict –- Dictionary Library in C

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Anatomy of a Narrative Virus

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David Cope's Experiments in Musical Intelligence

https://en.wikipedia.org/wiki/David_Cope
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Pentagon embraces Musk's Grok AI chatbot as it draws global outcry

https://www.pbs.org/newshour/world/pentagon-embraces-musks-grok-ai-chatbot-as-it-draws-global-outcry
4•amarcheschi•27m ago•2 comments

Apple's new Creative Cloud competitor lets you edit photos, music and video

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1•reaperducer•28m ago•1 comments

AI Adoption vs AI Transformation

https://dentro.de/ai/blog/2026/01/08/ai-adoption-vs-ai-transformation/
1•Zaloog•29m ago•0 comments

DAG of DAGs crushes math benchmark

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https://github.com/Schniz/fnm
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A Support End-Effector for Banana Bunches Based on Contact Mechanics Constraints

https://www.mdpi.com/2073-4395/15/12/2907
1•PaulHoule•33m ago•0 comments

Deepgram raises $130M at $1.3B valuation and buys a YC AI startup

https://techcrunch.com/2026/01/13/deepgram-raises-130m-at-1-3b-valuation-and-buys-a-yc-ai-startup/
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Show HN: ThreadPatrol ends messy Slack workspaces by gently enforcing threads

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Why I Failed to Build a Lego-Style Coding Agent

https://blog.moelove.info/why-i-failed-to-build-a-lego-style-coding-agent
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ELI5: Physical AI Must Sense, Think, Act and Optimize

https://www.aptiv.com/en/insights/article/physical-ai-must-sense-think-act-and-optimize
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Two Concepts of Intelligence

https://cacm.acm.org/blogcacm/two-concepts-of-intelligence/
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yolo-cage: AI coding agents that can't exfiltrate secrets or merge their own PRs

https://github.com/borenstein/yolo-cage
1•dbborens•39m ago•0 comments
Open in hackernews

Ask HN: LLM is useless without explicit prompt

4•revskill•8mo 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•8mo 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•8mo 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•8mo 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.