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Science Is Drowning in AI Slop

https://www.theatlantic.com/science/2026/01/ai-slop-science-publishing/685704/
2•sizzle•29s ago•0 comments

Show HN: I'm writing an alternative to Lutris

https://github.com/navid-m/styx
1•death_eternal•3m ago•0 comments

The engineering behind an AI app builder

https://getmocha.com/blog/no-escape-hatch-engineering-behind-mocha/
4•nichochar•4m ago•0 comments

SSH has no Host header

https://blog.exe.dev/ssh-host-header
1•todsacerdoti•4m ago•0 comments

How Anthropic's Cowork Actually Works

https://deadneurons.substack.com/p/how-anthropics-cowork-actually-works
1•nr378•5m ago•0 comments

Goldman Sachs Global Macro Research: Gen AI: too much spend, too little benefit [pdf]

https://www.goldmansachs.com/static-libs/pdf-redirect/prod/index.html?path=/images/migrated/insig...
1•u1hcw9nx•6m ago•0 comments

Deleting Code for Performance

https://dbushell.com/2025/12/04/deleting-code-for-performance/
1•speckx•7m ago•0 comments

AI usage policy for Ghostty contributions

https://github.com/ghostty-org/ghostty/pull/10412
1•bpierre•7m ago•1 comments

OpenAI will do "outcome-based pricing will share in the value created"

https://openai.com/index/a-business-that-scales-with-the-value-of-intelligence/
3•moomoo11•9m ago•2 comments

Show HN: ProblemHunt – A place to collect real problems before building startups

https://problemhunt.pro
2•gostroverhov•10m ago•0 comments

Half of NIH's institutes due to freeze billions in funding by 2027

https://www.nature.com/articles/d41586-026-00183-x
1•kozlov8•12m ago•0 comments

Show HN: Elden Ring–style "Git Pushed" screen when you Git push in VS Code

https://github.com/iiviie/CODE_PUSHED_darkSouls
2•iiviie•13m ago•0 comments

How Tim Cook Is Battle-Hardened to Win AI's Biggest Prize: The Trust Layer

https://pitchfreaks.substack.com/p/napster-zuck-and-studio-ghibli-how
1•ThePitchfreak•13m ago•1 comments

Ask HN: Modern test automation software (Python/Go/TS)?

3•rajkumar14•16m ago•0 comments

A Claimed Quantum Computing Breakthrough Was Just Debunked

https://scitechdaily.com/scientists-say-a-major-quantum-computing-breakthrough-was-not-what-it-se...
2•xthe•17m ago•1 comments

Why it's still hard to track Y Combinator Companies

https://www.researchly.at/post/y-combinator-companies-finden-tracken
3•leo_researchly•17m ago•1 comments

Cursor 2.4

https://cursor.com/changelog/2-4
2•leerob•18m ago•0 comments

Us-vs-Them Bias in Large Language Models

https://arxiv.org/abs/2512.13699
1•geox•19m ago•0 comments

Dependency Churn and You

https://dan.turnerhallow.co.uk/dependency-churn-and-you.html
2•speckx•19m ago•0 comments

Sprites – Stateful Sandboxes

https://sprites.dev/
1•varun_chopra•20m ago•0 comments

Theory X and Theory Y

https://en.wikipedia.org/wiki/Theory_X_and_Theory_Y
1•baxtr•20m ago•0 comments

Show HN: Figr – AI that thinks through product problems before designing

https://figr.design/
2•Mokshgarg003•21m ago•0 comments

Show HN: CLI for working with Apple Core ML models

https://github.com/schappim/coreml-cli
2•schappim•21m ago•0 comments

YouTube Keeps Blocking This Space Video. We're Showing It Anyway [video]

https://www.youtube.com/watch?v=WoNQ257OUNc
3•consumer451•21m ago•0 comments

Show HN: AI Gakuen – Specialist agents for Claude Code via compiled knowledge

https://github.com/ntombisol/aigakuen
1•ntombisol•22m ago•0 comments

Microsoft 365 Outage

https://twitter.com/MSFT365Status/status/2014422298506285161
4•6uJYSrt8M•23m ago•0 comments

Taming P99s in OpenFGA: How we built a self-tuning strategy planner

https://auth0.com/blog/self-tuning-strategy-planner-openfga/
4•elbuo•23m ago•0 comments

The 80% Problem: Why the Energy Transition Isn't What You Think

https://twitter.com/IamPranavJ/status/2014429406077583665
1•pranavj•23m ago•0 comments

Fastverse: A Suite of High-Performance and Low-Dependency R Packages

https://fastverse.org/fastverse/
1•PaulHoule•25m ago•0 comments

A clear visual explanation of what HTTPS protects

https://howhttps.works/why-do-we-need-https/
2•birdculture•26m 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.