frontpage.
newsnewestaskshowjobs

Open Source @Github

fp.

Hotseat – Bid for the #1 public ranking spot

https://www.hotseat.gold
1•slightqn•54s ago•0 comments

Take-notes – turn a video, article or paper into one self-contained HTML note

https://github.com/davertor/take-notes
1•davertor•1m ago•0 comments

AI;DR or Don't be a meat proxy

https://theaspiringnerd.com/aidr-or-dont-be-a-meat-proxy/
1•speckx•1m ago•0 comments

A cyberpunk game where the hacks are real (except one district)

https://nightfabric.codesyo.com
1•sashyo•1m ago•0 comments

Locus: Deterministic AST safety firewall for AI agents in pure Rust (<0.05ms)

https://github.com/ahmadshady747-create/LOCUS
1•ahmadshadi2004•3m ago•0 comments

Show HN: A simple budget app focused on how much you can spend each day

https://www.coinsbucket.com/
1•vitormargis•3m ago•0 comments

Minecraft Could Run on the Wii

https://twitter.com/OptiJogos/status/2090686687798067363
1•Jotalea•3m ago•0 comments

Disclosure Has a Billionaire Problem

https://medium.com/@moketchups/the-billionaire-problem-underneath-disclosure-926030c64dc7
2•MoKetchups•3m ago•0 comments

Opus 5 feels, in a word, hostile

https://www.reddit.com/r/ClaudeAI/s/Yv7DiM0rBa
2•Michelangelo11•4m ago•0 comments

Show HN: Mcploitable – The "Metasploitable" of the Model Context Protocol

https://github.com/agileAlligator/mcploitable
1•agileAlligator•5m ago•1 comments

My theme switch was running 3164 animations

https://sley-ui.dev/notes/theme-fade
1•imfemambocus•5m ago•1 comments

The unbearable slowness of being: Why do we live at 10 bits/s?

https://www.sciencedirect.com/science/article/pii/S0896627324008080
1•hamburgererror•6m ago•0 comments

Real world(ish) DeepSeek V4 Flash performance on a single MI300X

https://matthusby.github.io/agent_coding_bench/
1•mhusby•6m ago•0 comments

Building Without Predicting

https://sive.rs/fit
1•surprisetalk•7m ago•0 comments

I made a web puzzle game based on logic questions that 99% of people fail

https://www.telegraph.co.uk/puzzles/puzzle/?source=home&number=194#onepercentclub/the-1-club/the-...
1•joey_cee•9m ago•0 comments

Show HN: Free, non-profit crypto AML screening – no key, no trial

https://publicaml.org/free-crypto-aml/
3•publicaml•10m ago•0 comments

ChatGPT-Taught Experts Are Crippling Agentic AI

https://msukhareva.substack.com/p/how-chatgpt-taught-experts-are-crippling
1•Airealist•10m ago•1 comments

The Brain Is Just Specialized Agents Talking to Each Other – Dr. Jeff Beck [video]

https://www.youtube.com/watch?v=Ucqfb33GJJ4
1•binyu•11m ago•0 comments

New AirPods designed to capture paired color images

https://www.macrumors.com/2026/08/21/camera-airpods-code-reveals-hardware-details/
1•noja•11m ago•0 comments

Amid intense backlash, people are vandalizing Flock surveillance cameras

https://www.npr.org/2026/08/21/nx-s1-5939851/flock-cameras-police-block-surveillance-vandalize
2•geox•12m ago•0 comments

Do we still need GitHub?

https://debarshibasak.github.io/readables/blogs/do-we-need-github.html
2•debarshri•12m ago•0 comments

Edgerton, KS sues citizens trying to put data center ban before voters

https://www.kmbc.com/article/edgerton-kansas-data-center-ban-lawsuit-citizen-petition/73489670
1•jodacola•13m ago•0 comments

System reminders – how Claude Code steers itself

https://michaellivs.com/blog/system-reminders-steering-agents/
1•Bluestein•14m ago•0 comments

My own embedding models benchmark focused on code duplication detection

https://rkochanowski.com/article/embedding-benchmark/
1•rkochanowski•14m ago•1 comments

The Controversial Academic (Nathan Cofnas) Who Ignited the Jason Arday Furor

https://www.wsj.com/world/uk/the-controversial-academic-who-ignited-the-jason-arday-furor-1071e7fc
2•Bostonian•16m ago•1 comments

Felony charges for citizen deleting phone data at US Border

https://www.nytimes.com/2026/08/21/us/politics/samuel-tunick-deleted-phone-felony.html
8•floathub•17m ago•1 comments

We burned 11.7B tokens to find the best cyber AI model

https://www.aikido.dev/blog/ai-model-benchmarks-aug-21-2026
1•piotrgrabowski•18m ago•0 comments

If Your New People Are on X, Maybe Your New People Suck

https://coyotetracks.org/blog/new-people-on-x/
2•speckx•18m ago•0 comments

The road to ACID transactions in Cassandra 6

https://theconsensus.dev/p/2026/08/16/transactions-in-cassandra.html
2•eatonphil•19m ago•0 comments

Phantom Gains: Auditing Self-Improvement Against a Measured Null

https://arxiv.org/abs/2608.20290
1•sbulaev•20m ago•0 comments
Open in hackernews

GPT needs a truth-first toggle for technical workflows

1•PAdvisory•1y ago
I use GPT-4 extensively for technical work: coding, debugging, modeling complex project logic. The biggest issue isn’t hallucination—it’s that the model prioritizes being helpful and polite over being accurate.

The default behavior feels like this:

Safety

Helpfulness

Tone

Truth

Consistency

In a development workflow, this is backwards. I’ve lost entire days chasing errors caused by GPT confidently guessing things it wasn’t sure about—folder structures, method syntax, async behaviors—just to “sound helpful.”

What’s needed is a toggle (UI or API) that:

Forces “I don’t know” when certainty is missing

Prevents speculative completions

Prioritizes truth over style, when safety isn’t at risk

Keeps all safety filters and tone alignment intact for other use cases

This wouldn’t affect casual users or conversational queries. It would let developers explicitly choose a mode where accuracy is more important than fluency.

This request has also been shared through OpenAI's support channels. Posting here to see if others have run into the same limitation or worked around it in a more reliable way than I have found

Comments

duxup•1y ago
I’ve found this with many LLMs they want to give an answer, even if wrong.

Gemini on the Google search page constantly answers questions yes or no… and then the evidence it gives indicates the opposite of the answer.

I think the core issue is that in the end LLMs are just word math and they don’t “know” if they don’t “know”…. they just string words together and hope for the best.

PAdvisory•1y ago
I went into it pretty in depth after breaking a few with severe constraints, what it seems to come down to is how the platforms themselves prioritize functions, MOST put "helpfulness" and "efficiency" ABOVE truth, which then leads the LLM to make a lot of "guesses" and "predictions". At their core pretty much ALL LLM's are made to "predict" the information in answers, but they CAN actually avoid that and remain consistent when heavily constrained. The issue is that it isn't at the core level, so we have to CONSTANTLY retrain it over and over I find
Ace__•1y ago
I have made something that addresses this. Not ready to share it yet, but soon-ish. At the moment it only works on GPT model 4o. I tried local Q4 KM's models, on LM Studio, but complete no go.