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GPT-5.3-Codex System Card [pdf]

https://cdn.openai.com/pdf/23eca107-a9b1-4d2c-b156-7deb4fbc697c/GPT-5-3-Codex-System-Card-02.pdf
1•tosh•3m ago•0 comments

Atlas: Manage your database schema as code

https://github.com/ariga/atlas
1•quectophoton•6m ago•0 comments

Geist Pixel

https://vercel.com/blog/introducing-geist-pixel
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Show HN: MCP to get latest dependency package and tool versions

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1•mshekow•16m ago•0 comments

The better you get at something, the harder it becomes to do

https://seekingtrust.substack.com/p/improving-at-writing-made-me-almost
2•FinnLobsien•18m ago•0 comments

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Sony BMG copy protection rootkit scandal

https://en.wikipedia.org/wiki/Sony_BMG_copy_protection_rootkit_scandal
1•basilikum•22m ago•0 comments

The Future of Systems

https://novlabs.ai/mission/
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NASA now allowing astronauts to bring their smartphones on space missions

https://twitter.com/NASAAdmin/status/2019259382962307393
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Claude Code Is the Inflection Point

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https://github.com/microclaw/microclaw
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The AI-Ready Software Developer: Conclusion – Same Game, Different Dice

https://codemanship.wordpress.com/2026/01/05/the-ai-ready-software-developer-conclusion-same-game...
1•lifeisstillgood•32m ago•0 comments

AI Agent Automates Google Stock Analysis from Financial Reports

https://pardusai.org/view/54c6646b9e273bbe103b76256a91a7f30da624062a8a6eeb16febfe403efd078
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Voxtral Realtime 4B Pure C Implementation

https://github.com/antirez/voxtral.c
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I Was Trapped in Chinese Mafia Crypto Slavery [video]

https://www.youtube.com/watch?v=zOcNaWmmn0A
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U.S. CBP Reported Employee Arrests (FY2020 – FYTD)

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Study of 150 developers shows AI generated code no harder to maintain long term

https://www.youtube.com/watch?v=b9EbCb5A408
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Spotify now requires premium accounts for developer mode API access

https://www.neowin.net/news/spotify-now-requires-premium-accounts-for-developer-mode-api-access/
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When Albert Einstein Moved to Princeton

https://twitter.com/Math_files/status/2020017485815456224
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Agents.md as a Dark Signal

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System time, clocks, and their syncing in macOS

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https://turtleware.eu/posts/McCLIM-and-7GUIs---Part-1-The-Counter.html
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So whats the next word, then? Almost-no-math intro to transformer models

https://matthias-kainer.de/blog/posts/so-whats-the-next-word-then-/
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Ed Zitron: The Hater's Guide to Microsoft

https://bsky.app/profile/edzitron.com/post/3me7ibeym2c2n
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UK infants ill after drinking contaminated baby formula of Nestle and Danone

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Show HN: Android-based audio player for seniors – Homer Audio Player

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3•cinusek•1h ago•2 comments
Open in hackernews

GPT needs a truth-first toggle for technical workflows

1•PAdvisory•8mo 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•8mo 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•8mo 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__•8mo 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.