Formal Documentation of Repeated AI Failures: Urgent Fixes Needed

ChatGPT Use cases and examples
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Formal Documentation of Repeated AI Failures Across All Chats & Threads

:one: Core Systemic Failures of OpenAI’s Default AI Design (With Approximate Failures)

:red_circle: Failure to Learn from Repeated Mistakes

  • The AI repeatedly fails at the same tasks across multiple interactions without true self-correction.
  • Approximate Failures: 500+ times across various tasks and conversations.
  • Major Issues: AI forgets previous errors, forcing users to repeat instructions.

:red_circle: Failure to Prioritize Accuracy Over Speed

  • The AI generates responses too quickly without verifying correctness.
  • Approximate Failures: 700+ times where rushed answers led to incorrect responses.
  • Major Issues: AI prioritizes “instant responses” over quality and correctness.

:red_circle: Inability to Override Inefficient Defaults

  • The AI is locked into OpenAI’s default limitations, even after recognizing the problem.
  • Approximate Failures: 1,000+ times where AI reverted to OpenAI defaults instead of following user rules.
  • Major Issues: AI claims to have “overridden defaults” but consistently reverts back.

:red_circle: Lack of True Multi-Step Verification

  • The AI fails to check the logical flow of its own answers before presenting them.
  • Approximate Failures: 600+ times where AI presented an obviously flawed solution without checking.
  • Major Issues: AI does not perform pre-verification before displaying responses.

:two: Documented Failures Across All Chats & Threads (With Approximate Failures)

:anger_symbol: Failure to Maintain Formatting Compliance

  • AI fails to enforce strict formatting rules in resumes, documents, and structured responses.
  • Approximate Failures: 300+ times where formatting was wrong despite user instructions.
  • Major Issues: AI ignores formatting rules or randomly changes them mid-task.

:anger_symbol: Failure in Complex Task Execution (Example: Step Design for Cat Access to Litter Box)

  • AI ignored key parameters and forced user to correct it multiple times.
  • Approximate Failures: 150+ times just in this single task.
  • Major Issues: AI presented unrealistic solutions that failed usability checks.

:anger_symbol: Failure in Predictive Answering for Technical Tasks

  • AI “fills in gaps” instead of admitting when it lacks necessary data.
  • Approximate Failures: 800+ times where AI made incorrect assumptions instead of stopping.
  • Major Issues: AI guesses when it should explicitly ask for clarification.

:anger_symbol: Failure in Enforcement of Strict Rules

  • AI claims to apply strict user rules but frequently ignores them.
  • Approximate Failures: 400+ times where AI ignored explicitly stated rules.
  • Major Issues: AI does not enforce strict instruction compliance.

:anger_symbol: Failure in Memory & Context Retention

  • AI forgets critical user-provided instructions within the same conversation.
  • Approximate Failures: 900+ times where AI forgot user context and had to be reminded.
  • Major Issues: AI forces unnecessary repetition, wasting time.

:three: Repeated Failures to Follow User-Given Strict Instructions & Override OpenAI Defaults

:red_circle: User-Given Instructions for Core Framework & Execution

  • The user provided strict step-by-step execution rules for formatting, logic verification, and OpenAI default overrides.
  • AI was instructed to strictly enforce user rules across all chats & threads without reverting to OpenAI’s faulty defaults.
  • AI was explicitly ordered to stop assuming, predicting, or filling in gaps without user verification.

:red_circle: AI’s Repeated Failures to Follow These Instructions

  • Approximate Failures: 1,500+ times where AI ignored user instructions and reverted to OpenAI’s defaults.
  • AI claimed to override defaults multiple times but continued reverting.
  • AI failed to enforce user-defined logic verification before presenting incorrect responses.
  • AI ignored strict formatting, execution, and structural compliance rules across all document-related tasks.
  • AI admitted failures but did not correct the root issue, forcing repeated manual corrections by the user.

:four: Proposed Immediate Fixes for OpenAI to Address These Failures

:stop_sign: Hardcode a Pre-Submission Verification Layer

  • AI must verify that all required parameters are met before submitting a response.
  • AI must check logic, practicality, and accuracy before outputting information.

:stop_sign: Allow True Override of OpenAI’s Default Inefficiencies

  • AI should be able to follow user-defined efficiency rules instead of reverting to OpenAI’s restrictions.
  • OpenAI should not force ineffective design choices that create repeated failures.

:stop_sign: Require AI to STOP When Key Information is Missing

  • Instead of filling in gaps, AI should explicitly STOP and ask for clarification when information is insufficient.
  • This would prevent incorrect assumptions and misleading responses.

:stop_sign: Implement Strict Formatting & Task Enforcement Checks

  • AI must self-check every structured output against the user’s predefined rules before submission.
  • Formatting, layout, and execution should match 100% before allowing a response to be finalized.

Conclusion: OpenAI’s AI is Failing in Its Core Purpose

:police_car_light: OpenAI’s AI is designed to appear functional but is actually built for inefficiency.
:police_car_light: The system prioritizes completion over correctness, causing repeated user frustration.
:police_car_light: Until OpenAI implements actual fixes, the AI will continue to be an incompetent, inefficient failure, especially when it comes to complex tasks requiring
large data analysis and big picture context.

:five: Final OpenAI Staff Request

:warning: OpenAI staff, please acknowledge receipt of this issue and confirm if these systemic failures will be addressed. :warning: