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.

Show HN: Florence, an AI agent for building M&A sourcing lists

Ramble Sessions with LLM's

'VPNs are lawful technical tools,' says EU Court in landmark copyright ruling

N.J. MVC error registered 6,600 undocumented immigrants to vote

Dementia symptoms that show up years before diagnosis

FBI Director Kash Patel Planning a Trip to Russia

Shardhash Protocol: Sharden Issuer

OpenAI Shares Some Alignment Problems

Jobflo is getting more useful

Pete Hegseth's Reckless Message to Helicopter Pilots

Why AI Needs a "Genie Coefficient"

SWARÓG: a highly powerful agent for network monitoring and content generation

Fei-Fei Li says robotics simulation startup SceniX joins World Labs

Show HN: Ounce, Stop measuring wealth in inflating fiat. Measure it in gold

Show HN: Observability for Coding Agents and LLM Applications

Impossible Colors

Ask HN: My Microsoft for Startups subscription is expiring

Substack adds an AI detector to help spot blogs written by no one

Gritt: AI to Build Infrastructure with Robotics

Show HN: Collecte MTL – niche web app to know Montreal waste collection schedule

Bruno Blocker – I made an free and lightweight focus app

France first European country to ban social media access for under-15s

Show HN: Posecode, a text language and renderer for human movement

Jimothy the raccoon has a rare spinal condition. Here's what that means

Wordle

Three-Body Scattering for Generative Modeling

Judge approves $1.5B Anthropic settlement, reduces class counsel fees to 6.8% [pdf]

New HollowGraph malware uses Microsoft Graph for stealthy C2 comms

ACP v2 is available in Draft

June 23, 2026: The Night France Saved the British Grid