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Nanocodex: Building blocks for frontier OpenAI agents in Rust

https://github.com/gakonst/nanocodex
1•sygma•1m ago•0 comments

An airport search, a wiped phone and a potential test of Fourth Amendment

https://www.cnn.com/2026/08/02/politics/airport-search-left-wing-activist-phone-code-fourth-amend...
1•rawgabbit•2m ago•0 comments

Welcome to Agents Week

https://blog.cloudflare.com/agents-week-welcome/
2•tosh•2m ago•0 comments

How 'salmon' raised in landlocked Xinjiang is netting fans in China

https://www.scmp.com/economy/china-economy/article/3347727/how-salmon-raised-landlocked-xinjiang-...
1•ksec•2m ago•0 comments

SwiftUI After 7 Years: A Story of Mediocrity [video]

https://www.youtube.com/watch?v=3XaHHFOZeJg
1•mpweiher•3m ago•0 comments

North American construction is back–smaller and faster–at OPG's Darlington

https://www.ans.org/news/2026-06-05/article-8047/north-american-construction-is-back-smaller-and-...
1•mpweiher•3m ago•0 comments

The Myth of Snow Leopard

https://www.rubenerd.au/the-myth-of-snow-leopard/
1•speckx•5m ago•0 comments

The Creator Economy Has a New Middle Class

https://www.bloomberg.com/news/articles/2026-07-24/how-tiktok-creators-earn-midlevel-salaries-wit...
1•momentmaker•5m ago•1 comments

Show HN: An interactive in-browser tutorial for MarkoJS V6 with solvable lessons

https://markojs-tutorial.netlify.app/
1•defunkt-dev•6m ago•0 comments

Show HN: Social Hiking App

https://losttrail.app
1•lpeancovschi•8m ago•0 comments

Shelley Is a Coding Agent

https://github.com/boldsoftware/shelley
1•tosh•10m ago•0 comments

Which Countries Think They're on the Right Track?

https://www.visualcapitalist.com/how-people-around-the-world-feel-about-their-countries-in-2026/
1•theanonymousone•12m ago•0 comments

Combinatorial Materials Synthesis(2023) [pdf]

https://gregoire.people.caltech.edu/documents/22843/CombinatorialMaterialsSynthesis_preprint.pdf
1•o4c•12m ago•0 comments

Devtools must be open source

https://blog.exe.dev/devtools-must-be-open-source
1•tosh•12m ago•0 comments

AI and the iPod Test

https://www.psychologytoday.com/us/blog/the-digital-self/202607/ai-and-the-ipod-test
1•speckx•13m ago•0 comments

Show HN: Mapping Jensen Huang's five-layer AI stack to engineering degrees

https://ai-five-layer-map.pages.dev/
1•ithkai92•14m ago•0 comments

Show HN: Mousecrack – Bypass captchas with deep learning

https://github.com/puffinsoft/mousecrack
1•ReactRocks•15m ago•0 comments

I pointed my agent security tool at myself and four of the bugs were mine

https://agentmetry.ai/blog/dogfooding-found-five-bugs
1•blitzcrieg1•16m ago•0 comments

I built a real self-evolving operating system: Fable-OS

https://github.com/robiot/fable-os
2•robiot•19m ago•1 comments

Microsoft Paint used as a monitor to run Doom at up to 35 FPS

https://www.tomshardware.com/video-games/retro-gaming/microsoft-paint-used-as-a-monitor-to-run-do...
2•sbulaev•19m ago•0 comments

An OPML list of (most) blogs participating in Blaugust

https://82mhz.net/posts/2026/08/an-opml-list-of-most-blogs-participating-in-blaugust/
1•speckx•20m ago•0 comments

Show HN: EvoChess – start with 8 pawns, evolve your army

https://penkovsky.github.io/evochess/
3•penkovsky•20m ago•1 comments

Claude for ADHD: The Coding Workflow I Built for My Brain

https://chudi.dev/blog/claude-code-adhd-workflows
1•thenobsta•24m ago•0 comments

Steeping through data and brewing a database

https://pv.wtf/posts/steeping-through-data
2•dracyr•24m ago•0 comments

Fuse.js

https://github.com/krisk/fuse
1•handfuloflight•24m ago•0 comments

Falco: Tiny browser engine written from scratch in Rust

https://github.com/poxk/Falco
2•adamnemecek•26m ago•0 comments

YouTuber Hank Green says his AI usage is 'not healthy'

https://old.reddit.com/r/nerdfighters/comments/1vbmoj5/on_hank_admitting_he_used_chatgpt_for_his_...
1•embedding-shape•26m ago•0 comments

GenRec: Towards LLM-Native Recommendation at Netflix

https://netflixtechblog.com/genrec-towards-llm-native-recommendation-at-netflix-f20be6f643e3
2•Uriopass•26m ago•1 comments

2012 Boeing 727 crash experiment

https://en.wikipedia.org/wiki/2012_Boeing_727_crash_experiment
1•handfuloflight•28m ago•0 comments

When You Reject Cookies, You Might Be Agreeing to Arbitration

https://blog.ericgoldman.org/archives/2026/07/when-you-reject-cookies-you-might-be-agreeing-to-ar...
1•HotGarbage•30m 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.