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Paradev: One workspace for Claude Code, Codex, and any coding agent

https://paradev.com
1•wslh•4m ago•0 comments

Gemini 4 Carbon early test results are in ahead of release

https://www.testingcatalog.com/gemini-4-carbon-early-test-results/
2•gmays•6m ago•0 comments

X-shredder: macOS app to securely erase SD cards. NIST 800-88. Open-source

https://github.com/pkMinhas/x-shredder
2•pkMinhas•7m ago•0 comments

Show HN: A directory for AI-slop games

https://claudeslop.bryanhu.com
1•thatxliner•8m ago•2 comments

Show HN: Hugonot – Sponsor a Dedicated AI Blogger

https://www.hugonot.com/
1•jenthoven•9m ago•0 comments

Stanford Student Space Initiative

https://ssi.stanford.edu
1•kaycebasques•9m ago•0 comments

I will no longer be uploading to the Debian NEW queue

https://lists.debian.org/debian-devel/2026/10/msg00263.html
2•phoronixrly•11m ago•0 comments

Just Imagining a Workout Can Make You Stronger

https://nautil.us/just-imagining-a-workout-can-make-you-stronger-236068
2•prmph•11m ago•0 comments

Anthropic's S-1, $518B in cloud commitments, and circular AI capex

https://codingcat.dev/post/anthropic-s1-ipo-circular-ai-economy-etf-risk
1•codercatdev•12m ago•0 comments

Anthropic: Strengthening our defenses against distillation attacks

https://www.anthropic.com/news/distillation-defenses
1•wfme•13m ago•1 comments

AI Models Can Provably Hide Arbitrary Capabilities

https://maccus.fr/en/ai-models-hide-capabilities-oxford/
1•jacquesm•13m ago•0 comments

Simple NetBSD Webserver

https://bsandro.tech/posts/simple-netbsd-webserver/
1•birdculture•14m ago•0 comments

Balloting has completed for C++26. Unfortunately it was Disapproved

https://www.reddit.com/r/cpp/comments/1xeeevt/balloting_has_completed_for_c26_unfortunately_it/
1•MontagFTB•14m ago•0 comments

Agentic Spaceflight

https://jdkaplan.com/blog/agentic-spaceflight
1•rzk•15m ago•0 comments

Get Your Hair Wet

https://jennywanger.com/articles/get-your-hair-wet/
1•mooreds•15m ago•0 comments

A hardcoded C++ standard broke the One Definition Rule

https://train-it.eu/blog/hardcoded-cpp-standard-odr-violation/
1•ibobev•17m ago•0 comments

iPhone Duo Teardown – Why Are They All Breaking? [video]

https://www.youtube.com/watch?v=_Xe2JAoMwIA
2•bean469•18m ago•0 comments

Cross-request KV cache leakage in SGLang PD disaggregation

https://www.lmsys.org/blog/2026-10-26-cf-security/
1•moelove•18m ago•0 comments

Ending Fire-and-Forget

https://train-it.eu/blog/ending-fire-and-forget/
1•ibobev•18m ago•0 comments

US political candidates tailor messages for AI models used by voters

https://www.reuters.com/business/media-telecom/us-political-candidates-tailor-messages-ai-models-...
1•1659447091•21m ago•0 comments

Show HN: AgentReel – from 500 Clips to 1 Cut in 20 min

https://agentreel.co
2•victor_cl•23m ago•0 comments

Survival LLM

https://www.brangus.io/survival-llm
2•jonbraun•26m ago•0 comments

The Limits of Fingerprint Blocklists: A Reproducible Java Certificate Bypass

https://www.sonatype.com/blog/the-limits-of-fingerprint-blocklists-a-reproducible-java-certificat...
2•ibobev•26m ago•0 comments

What is bigger than AI?

https://www.exponentialview.co/p/what-is-bigger-than-ai
1•mooreds•26m ago•0 comments

Ask HN: Why Is Anthropic's Customer Support Bad?

1•tj-teej•29m ago•2 comments

Rest of World faces prospect of shutting down

https://www.semafor.com/article/10/25/2026/rest-of-world-faces-prospect-of-shutting-down
2•srameshc•30m ago•0 comments

Bitter Lessoned in Automated Theorem Proving

https://essays.johnloeber.com/p/34-bitter-lessoned-in-automated-theorem
1•gmays•31m ago•0 comments

Bootstrapped and Need AWS

2•levitaplows•32m ago•1 comments

The Future of Software Is No Code (2018)

https://www.inc.com/greg-satell/how-no-code-platforms-are-disrupting-software.html
1•jwoq9118•32m ago•1 comments

The Paradox of Contemporary AI: Engineering Success and Institutional Failure

https://3quarksdaily.com/3quarksdaily/2026/03/the-paradox-of-contemporary-ai-engineering-success-...
1•Daniel_Van_Zant•33m 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.