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Show HN: Factlabel: catches AI agents lying about the data they're reporting on

https://github.com/generallymatthew/factlabel
1•generallymatt9•53s ago•0 comments

Bugs that broke driving: Machine Learning edition

https://blog.comma.ai/ml-bugs/
1•LorenDB•1m ago•0 comments

We Are Simulating Humanity

https://www.null0.ai
1•amaarc•2m ago•0 comments

In Search of a Compositional Theory of Self-Stabilization

http://muratbuffalo.blogspot.com/2026/09/in-search-of-compositional-theory-of.html
2•matt_d•4m ago•0 comments

You can use any LLM just like JEV

https://www.reddit.com/r/LocalLLaMA/comments/1wlxpaw/you_can_use_any_llm_just_like_jev/
2•theanonymousone•5m ago•0 comments

Evergarden

https://evergarden.moe/
1•birdculture•7m ago•0 comments

Adaptive Business Engine (ABE): Evidence, Authority and Governance

https://zenodo.org/records/22881485
1•ileuza_maya•7m ago•0 comments

Temporary Flight Restriction over SpaceX's McGregor, Texas, Test Facility

https://notams.aim.faa.gov/notamSearch/createNotamPdf?transactionid=82465898
2•uticus•8m ago•0 comments

RoboHarm: Do Frontier Robot Policies Refuse Unsafe Instructions?

https://robocurve.org/roboharm/
1•msadowski•10m ago•0 comments

An Age of Experimentation [pdf]

https://thomasdullien.github.io/about/slides/An-age-of-experimentation-BlueHat-Asia-2026.pdf
1•porridgeraisin•10m ago•0 comments

Jevmade.com

https://jevmade.com/#jev
1•zenoware•10m ago•0 comments

Can JEV Play Chess

1•dev_marcospimi•11m ago•0 comments

I'm so bad at billiards that I ended up in the hyperbolic plane [video]

https://www.youtube.com/watch?v=kL9BTbIGxLg
2•accrual•15m ago•0 comments

Frontier AI on Your Own Hardware

https://timdettmers.com/2026/09/21/dlab-open-source-week/
1•pretext•15m ago•0 comments

Behind the Rise of Censorship and Distrust in Europe [video]

https://www.youtube.com/watch?v=vL4VvmFYpW0
1•PorciiVorbesc•18m ago•0 comments

JavaScript is enough to build native firmware for microcontrollers

https://geastack.com/one-pager
1•arbayi•18m ago•0 comments

US preparing 'massive' potash deal with Belarus

https://kyivindependent.com/us-preparing-massive-potash-deal-with-belarus-trump-says/
2•consumer451•18m ago•0 comments

Project Terminal – A macOS workspace for terminals and coding agents

https://www.projectterminal.app/
1•soybelli•18m ago•0 comments

Planning with Agents: Divided Worlds, Boundary Objects, and Thicker Interfaces

https://maggieappleton.com/planning-agents
1•azhenley•20m ago•0 comments

Parsing Bolo Replays

https://rooklift.github.io/parsing_bolo_replays/
2•danielvf•21m ago•0 comments

When semantic judgment becomes cheap enough to put everywhere

https://sameernanda.com/system-one-models-jev/
1•sameernanda•22m ago•0 comments

Solving for faster SHA-1 collision detection

https://sam.dev/blog/faster-sha1-collision-detection
3•srijs•22m ago•0 comments

AI-Assisted Starling Desktop Introduces 3D View

https://www.phoronix.com/news/Starling-0.5-3D-Desktop
1•starlingos•25m ago•0 comments

US halts flights at busy East Coast airports, says fiber line cut

https://www.reuters.com/world/us/faa-halts-some-us-east-coast-flights-due-communication-issues-20...
18•allanbreyes•26m ago•8 comments

Developmental xenocortication using human-derived organoids in mice

https://www.nature.com/articles/s41586-026-11032-2
1•bookofjoe•26m ago•0 comments

We gave every managed cloud agent a durable SQL database

https://docs.opencomputer.dev/agents/database
1•iacguy•27m ago•0 comments

One Hundred Days of Fatherhood

https://suriya.cc/essays/100days/
2•suriyaG•27m ago•0 comments

GLM 5.3 Hosted by Mistral

https://twitter.com/mistralvibe/status/2102056993531871446
1•abc42•27m ago•0 comments

Gravity Linux Alpha Release: Linux on the M4 Mac Mini with GPU and DCP Support

https://gravitylinux.org/blog/early-alpha-m4-mac-mini/
4•ADevWithAnIdea•30m ago•0 comments

Robot Relations Departments: The New Corporate Reality

https://www.techbuzz.ai/articles/robot-relations-departments-the-new-corporate-reality
1•Vaslo•32m 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.