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LLM

https://www.seangoedecke.com/what-requirements-dont-you-have/
1•saikatsg•32s ago•0 comments

Keyword search ties a purpose-built memory layer on 200 LongMemEval questions

https://www.memstrata.dev/
2•yadu989•1m ago•0 comments

How electric school buses power 1,000 homes in California

https://electrek.co/2026/10/20/how-electric-school-buses-power-1000-homes-in-california-and-make-...
2•zzzeek•2m ago•0 comments

Claude designed protein binders against scorpion neurotoxins

https://www.anthropic.com/research/claude-scorpion-toxin-binder-design
1•artninja1988•2m ago•0 comments

Offihito on the XERJ Corpus Hub

https://hub.xerj.org/contributors/Offihito
1•herculez•5m ago•0 comments

UK wages grew by annual 3.7% in three months to August, ONS says

https://www.reuters.com/world/uk/uk-wages-grew-by-annual-37-three-months-august-ons-says-2026-10-20/
1•frank_clover•5m ago•0 comments

Show HN: iOS location based traveler's currency conversion with tax estimations

https://www.smartercurrency.app
1•rock_artist•5m ago•0 comments

CRA Stewardship Guidelines for Red Hat Supported Open Source

https://access.redhat.com/security/eu-cyber-resilience-act-stewardship-guidelines
1•Tomte•6m ago•0 comments

Show HN: Ankita – an open-source personal AI companion for the desktop

https://github.com/akyourowngames/A.N.K.I.T.A
1•krishverma_2010•6m ago•0 comments

Tenstorrent Announces a $1.5B Series E at a $6.2B valuation

https://tenstorrent.com/en/newsroom/tenstorrent-announces-series-e
1•pella•7m ago•0 comments

Advanced coding in low-resource programming languages

https://openai.com/index/low-resource-programming-languages/
1•sumnole•8m ago•0 comments

Safari: Blocking Identity Resolution Infrastructure

https://webkit.org/blog/18438/blocking-identity-resolution-infrastructure/
2•robflaherty•8m ago•0 comments

XPS 16 Creator Edition Laptop

https://www.dell.com/en-us/shop/laptop-computers/spd/xps16dx16263
1•mudil•8m ago•0 comments

AI that was supposed to save us time is doing just the opposite

https://www.theguardian.com/commentisfree/2026/oct/20/ai-supposed-to-save-time-opposite-governmen...
2•cybermango•9m ago•0 comments

Legendary Revives Lionsgate Takeover Talks, Submits Offer

https://www.bloomberg.com/news/articles/2026-10-20/legendary-revives-lionsgate-takeover-talks-sub...
1•jaredwiener•9m ago•0 comments

Qualcomm to cut jobs worldwide in performance-focused layoffs

https://www.cnbc.com/2026/10/20/qualcomm-performance-focused-layoffs-reuters.html
3•jimt1234•10m ago•0 comments

TriggerAPI – A native API client written in Go with full support for MCP servers

https://github.com/nomad-software/triggerapi
1•kalekold•10m ago•0 comments

Damage Control

https://fireborn.mataroa.blog/blog/damage-control/
1•devinprater•13m ago•0 comments

Reducing Reward Hacking by Localizing Bad Behavior Instead of Penalizing It

https://alignment.anthropic.com/2026/graft/
2•medbar•14m ago•0 comments

Do Markets Dream of Artificial Intelligence? (DNB Working Paper)

https://www.dnb.nl/en/publications/research-publications/working-paper-2026/871-do-markets-dream-...
2•latentframe•14m ago•0 comments

Hooked on YouTube

https://www.nbcnews.com/specials/hooked-youtube-videos-schools-junk-infiltrating-classrooms-google/
2•hollerith•15m ago•0 comments

Show HN: Frink – Desktop-first app for multi-step workflows and parallel agents

https://github.com/benord-labs/frink
1•norvalbv•16m ago•0 comments

Google support pages start defaulting to AI chatbots

https://9to5google.com/2026/10/19/google-support-ai-summary-chatbot-update/
1•tech234a•18m ago•0 comments

Michael Rabin's fingerprints across the theory of computation

https://eccc.weizmann.ac.il/report/2026/259/
1•matt_d•19m ago•0 comments

Can a Million AI Agents Create Superintelligence?

https://www.noahpinion.blog/p/can-a-million-ai-agents-create-superintelligence
3•speckx•22m ago•0 comments

Summonos: An omarchy-inspired macOS environment

https://github.com/RohiRIK/SummonOS
1•RohiRik•24m ago•0 comments

Deriving Efficient Hardware in the Bluespec Style

https://stng.substack.com/p/deriving-efficient-hardware-in-the
1•matt_d•25m ago•0 comments

What Shall I Teach My Son?

https://stevekrouse.com/ends
13•Curiositry•26m ago•4 comments

Redux, docs, and career advice with Mark Erikson

https://www.youtube.com/watch?v=oKFAFAU50sA
1•jdauriemma•26m ago•0 comments

My coding agent deleted a project without asking. The audit log says I did it

https://zabta.ai/blog/my-coding-agent-deleted-a-project
3•Regzaar•27m ago•2 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.