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Code only says what it does

https://brooker.co.za/blog/2020/06/23/code.html
1•logicprog•4m ago•0 comments

The success of 'natural language programming'

https://brooker.co.za/blog/2025/12/16/natural-language.html
1•logicprog•4m ago•0 comments

The Scriptovision Super Micro Script video titler is almost a home computer

http://oldvcr.blogspot.com/2026/02/the-scriptovision-super-micro-script.html
2•todsacerdoti•5m ago•0 comments

Discovering the "original" iPhone from 1995 [video]

https://www.youtube.com/watch?v=7cip9w-UxIc
1•fortran77•6m ago•0 comments

Psychometric Comparability of LLM-Based Digital Twins

https://arxiv.org/abs/2601.14264
1•PaulHoule•7m ago•0 comments

SidePop – track revenue, costs, and overall business health in one place

https://www.sidepop.io
1•ecaglar•10m ago•1 comments

The Other Markov's Inequality

https://www.ethanepperly.com/index.php/2026/01/16/the-other-markovs-inequality/
1•tzury•11m ago•0 comments

The Cascading Effects of Repackaged APIs [pdf]

https://papers.ssrn.com/sol3/papers.cfm?abstract_id=6055034
1•Tejas_dmg•14m ago•0 comments

Lightweight and extensible compatibility layer between dataframe libraries

https://narwhals-dev.github.io/narwhals/
1•kermatt•16m ago•0 comments

Haskell for all: Beyond agentic coding

https://haskellforall.com/2026/02/beyond-agentic-coding
2•RebelPotato•20m ago•0 comments

Dorsey's Block cutting up to 10% of staff

https://www.reuters.com/business/dorseys-block-cutting-up-10-staff-bloomberg-news-reports-2026-02...
1•dev_tty01•23m ago•0 comments

Show HN: Freenet Lives – Real-Time Decentralized Apps at Scale [video]

https://www.youtube.com/watch?v=3SxNBz1VTE0
1•sanity•24m ago•1 comments

In the AI age, 'slow and steady' doesn't win

https://www.semafor.com/article/01/30/2026/in-the-ai-age-slow-and-steady-is-on-the-outs
1•mooreds•31m ago•1 comments

Administration won't let student deported to Honduras return

https://www.reuters.com/world/us/trump-administration-wont-let-student-deported-honduras-return-2...
1•petethomas•32m ago•0 comments

How were the NIST ECDSA curve parameters generated? (2023)

https://saweis.net/posts/nist-curve-seed-origins.html
2•mooreds•32m ago•0 comments

AI, networks and Mechanical Turks (2025)

https://www.ben-evans.com/benedictevans/2025/11/23/ai-networks-and-mechanical-turks
1•mooreds•32m ago•0 comments

Goto Considered Awesome [video]

https://www.youtube.com/watch?v=1UKVEUGEk6Y
1•linkdd•35m ago•0 comments

Show HN: I Built a Free AI LinkedIn Carousel Generator

https://carousel-ai.intellisell.ai/
1•troyethaniel•36m ago•0 comments

Implementing Auto Tiling with Just 5 Tiles

https://www.kyledunbar.dev/2026/02/05/Implementing-auto-tiling-with-just-5-tiles.html
1•todsacerdoti•37m ago•0 comments

Open Challange (Get all Universities involved

https://x.com/i/grok/share/3513b9001b8445e49e4795c93bcb1855
1•rwilliamspbgops•38m ago•0 comments

Apple Tried to Tamper Proof AirTag 2 Speakers – I Broke It [video]

https://www.youtube.com/watch?v=QLK6ixQpQsQ
2•gnabgib•40m ago•0 comments

Show HN: Isolating AI-generated code from human code | Vibe as a Code

https://www.npmjs.com/package/@gace/vaac
1•bstrama•41m ago•0 comments

Show HN: More beautiful and usable Hacker News

https://twitter.com/shivamhwp/status/2020125417995436090
3•shivamhwp•42m ago•0 comments

Toledo Derailment Rescue [video]

https://www.youtube.com/watch?v=wPHh5yHxkfU
1•samsolomon•44m ago•0 comments

War Department Cuts Ties with Harvard University

https://www.war.gov/News/News-Stories/Article/Article/4399812/war-department-cuts-ties-with-harva...
9•geox•48m ago•1 comments

Show HN: LocalGPT – A local-first AI assistant in Rust with persistent memory

https://github.com/localgpt-app/localgpt
2•yi_wang•48m ago•0 comments

A Bid-Based NFT Advertising Grid

https://bidsabillion.com/
1•chainbuilder•52m ago•1 comments

AI readability score for your documentation

https://docsalot.dev/tools/docsagent-score
1•fazkan•59m ago•0 comments

NASA Study: Non-Biologic Processes Don't Explain Mars Organics

https://science.nasa.gov/blogs/science-news/2026/02/06/nasa-study-non-biologic-processes-dont-ful...
3•bediger4000•1h ago•2 comments

I inhaled traffic fumes to find out where air pollution goes in my body

https://www.bbc.com/news/articles/c74w48d8epgo
2•dabinat•1h ago•0 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.