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Save Wisdom Questions

https://savewisdom.org/the-1000-word-save-wisdom-questions/
1•momentmaker•1m ago•0 comments

Tech Slide Deepens as AI Fears Get Worse

https://www.wsj.com/livecoverage/stock-market-today-dow-sp-500-nasdaq-06-23-2026
1•doener•2m ago•0 comments

A scientist says he can scan prisoners' brains for signs of evil

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1•mellosouls•3m ago•0 comments

The Warfare of the Future Is Here

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1•sharjeelsayed•3m ago•0 comments

Not so empty nesters: record-high number of US adults under 35 live at home

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https://paulgraham.mooch.agency/
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The Struggle Is Valuable

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2•mooreds•8m ago•0 comments

Envoy AI Gateway 1.0 – A Stable, Production-Ready AI Gateway

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2•zoltano•16m ago•0 comments

Twenty Years Later, Everything Is the Truman Show (2018)

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5•thoughtpeddler•17m ago•0 comments

How to Think About AI Before It's Too Late

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2•joebuckwilliams•18m ago•0 comments

TOP500 – June 2026 List

https://top500.org/lists/top500/2026/06/
3•NKosmatos•18m ago•0 comments

Generate per-session LoRA adapters in <1s for agentic inference efficiency

https://github.com/theoddden/Tessera
2•Facingsouth•18m ago•1 comments

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https://answerjournal.com/
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Deciphering Basmalah

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2•rcanand2025•26m ago•0 comments

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5•mikhael•27m ago•0 comments

John Carmack on why he would push back against anti-datacenter efforts

https://twitter.com/i/status/2069486595917402117
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Formisch V1 – A Vite-inspired lightweight form builder

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Philip K. Dick Takes You Inside His Life Changing Mystical Experience (2014)

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2•Jimmc414•28m ago•0 comments

Carbon Language: An experimental successor to C++

https://github.com/carbon-language/carbon-lang
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Active Group and "Agentic Engineering"

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3•marvinborner•31m ago•0 comments

Ask HN: Has anyone replaced a human receptionist with AI for a

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2•edward•33m ago•1 comments

California AB 2047 makes 3d printers off-limits to students, educators, business

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68•Buildstarted•35m ago•10 comments

Embedded Skills Tree

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3•arbayi•40m ago•0 comments

A tiny shared Linux system

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3•davidcollantes•40m ago•0 comments

Fika Jobs raises $4M to build platform where AI agents interview candidates

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4•adityamwagh•41m ago•2 comments

Geothermal Startup Plans to Use Oil Tech for Green Energy

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3•crookedroad44•45m ago•0 comments

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https://replyvoice.com
2•kedimuzafer•46m ago•0 comments

United Wizards of the Coast recognized by NLRB

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51•d4mi3n•50m ago•10 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.