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Instant payment rails meet batch bank cores

https://tuladb.com/blog/instant-rails-meet-batch-cores/
1•shubham3582•2m ago•0 comments

New Research Tests Whether AI Models Know Their Own Thoughts

https://www.quantamagazine.org/new-research-tests-whether-ai-models-know-their-own-thoughts-20261...
1•ibobev•2m ago•0 comments

Why worry about hot-patch atomicity if we can suspend all threads?

https://devblogs.microsoft.com/oldnewthing/20261106-00/?p=112838/
1•ibobev•2m ago•0 comments

Ace: GitHub Next's open-source tool for multiplayer agentic development

https://ace.githubnext.com/
1•zdgeier•4m ago•1 comments

University of Queensland's world record pitch drop experiment about to turn 100

https://www.abc.net.au/news/2026-11-08/queensland-pitch-drop-experiment/107337784
1•BuzzVII•5m ago•0 comments

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https://playgod.earth/every-country-vs-the-world
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Stack Overflow for Agents

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The scramble for your brain data

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https://twitter.com/backnotprop/status/2119211018966757669
2•ramoz•16m ago•0 comments

Hour "Do Nothing" Challenge

https://mattlakeman.org/2020/12/08/the-24-hour-do-nothing-challenge/
1•andsoitis•18m ago•1 comments

Peter Watts: Conscious Ants and Human Hives (2018) [video]

https://www.youtube.com/watch?v=v4uwaw_5Q3I
1•gregsadetsky•18m ago•0 comments

Massive expansion of immigration detention under new EU deportation rules

https://statewatch.org/news/2026/november/massive-expansion-immigration-detention-under-new-eu-re...
1•paimapi•23m ago•0 comments

The Computational Beauty of Nature

https://flake.org/site/index.html
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Ugh Fields

https://www.lesswrong.com/posts/EFQ3F6kmt4WHXRqik/ugh-fields
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California governor to grant clemency to all 548 death row inmates

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Remote Parents

https://www.jaymehoffman.com/writing/remote-parents/
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How to Read Hex Colors and Build Better CSS Palettes

https://palettevault.github.io/blog/understanding-css-colors/
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Commodore PET – The Worlds First Personal Computer

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1•andsoitis•39m ago•0 comments

Tesla's quiet EV software update is unplugging Australian homes

https://thedriven.io/2026/11/07/teslas-quiet-ev-software-update-is-unplugging-australian-homes/
1•motionlessveloc•41m ago•1 comments

GitHub New pull request overview page in public preview

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11•xiaoyu2006•45m ago•0 comments

Flowers for Algernon: Daniel Keyes [pdf]

https://www.sdfo.org/gj/stories/flowersforalgernon.pdf
1•omegacombinator•49m ago•1 comments

The Hardest Tarball

https://stoppels.ch/2026/11/07/the-hardest-tarball.html
1•stabbles•49m ago•0 comments

Starter homes cost $1M in a record 242 U.S. cities–proof of unaffordability

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1•rawgabbit•50m ago•0 comments

Responsible Use of Artificial Intelligence

https://www.nature.com/articles/s41561-026-02149-0
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Editing at the Speed of Thought in Emacs

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1•oumua_don17•53m 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.