Editorial Policy

Last updated: October 2026 • Effective Date: October 2026

At Fix AI Results (https://fixairesults.com), we believe technical tutorials should be honest, practical, trustworthy, and grounded in real-world testing. We hold ourselves to rigorous editorial standards to ensure every troubleshooting guide delivers actionable value to creators, beginners, and professionals.

1. Topic Selection: Focus on Real Creator Problems

We do not produce content to chase search algorithm trends with hollow summaries or recycled press releases. Our editorial roadmap is guided entirely by genuine creator challenges:

  • Recurring failure modes documented across generative AI communities (such as character drift, anatomical warping, and unexpected conversational refusals).
  • Frequently asked troubleshooting questions submitted by our readers.
  • Major platform updates, parameter changes, and interface overhauls across popular AI tools.
  • Practical limitations of free and freemium subscription tiers.

If we cannot provide a real, tested, and reproducible solution to a problem, we do not publish the article.

2. Independent Hands-On Research & Verification

Every tutorial published on Fix AI Results is grounded in firsthand verification on live tools:

  • Direct Interface Testing: When we explain how to maintain character consistency, structure negative constraints, or rewrite rejected prompts, our editors test the techniques directly in the actual software environment.
  • Testing Multiple Variations: We do not rely on a single lucky generation. We test prompts across multiple seeds, model checkpoints, and parameter variations to ensure consistency.
  • Documenting Edge Cases & Limitations: We transparently report tool limitations, failure rates, and edge cases rather than promising effortless “one-click” miracles.
  • Transparent Configuration Notes: Each guide discloses the model version, tool tier (free vs. paid), interface environment, and date of our testing so readers understand the precise context of the results.

3. Verification of Prompts, Screenshots & Settings

To ensure our guides remain practical and reliable:

  • All prompt examples, command flags (such as --cref, --sref, --cw), negative prompt lists, and formatting rules are verified for syntactic correctness before publication.
  • Screenshots are captured from live tool sessions to accurately reflect the current user interface, settings menus, and generation outputs.
  • When an instruction requires a specific subscription tier, desktop browser, or API access, this requirement is clearly stated at the top of the guide.

4. Human-Authored, People-First Content & AI Disclosure

Although our publication covers artificial intelligence, we adhere strictly to human-centered editorial principles:

  • Human Authorship & Review: Every article is researched, written, structured, tested, and reviewed by human editors. We do not engage in automated mass-publishing, spun articles, or unmonitored AI-generated content.
  • Role of AI Assistance: Where AI tools are used to assist with brainstorming outlines, checking grammar, or organizing raw test notes, a human editor conducts all testing, verifies factual claims, refines the instructional voice, and assumes full editorial responsibility for the final publication.
  • Google People-First Alignment: We strictly follow Google’s helpful content guidelines by focusing on original, user-first problem solving rather than search engine manipulation.

5. Sourcing & Authoritative External References

Our explanations of how AI models work are grounded in reputable, authoritative sources:

  • Official developer documentation and API changelogs (such as OpenAI Documentation, Anthropic Prompt Engineering Guides, and Midjourney User Guides).
  • Published computer science research papers and model cards.
  • Direct announcements and release notes from official AI research labs.

We link directly to official sources so readers can easily verify underlying platform documentation.

6. Communicating Factual Uncertainty & Tool Volatility

Artificial intelligence models are probabilistic and evolve at an unprecedented pace. Vendors frequently update system prompts, retrain safety filters, or modify interface layouts without warning. To maintain transparency:

  • We clearly state the date and tested model version in our guides.
  • When tool behavior is known to differ between user accounts or geographic regions (such as during gradual rollouts), we communicate this uncertainty explicitly.
  • We encourage readers to notify us if a vendor update alters any documented behavior.

7. Prohibition of Fabricated Claims & False Guarantees

Fix AI Results strictly prohibits fabricated test results, invented benchmarks, or deceptive claims. We never promise guaranteed outputs because generative models are inherently probabilistic. We present our findings honestly, including both successes and limitations.

8. Commercial Independence & Clear Separation of Advertising

Our editorial decisions are entirely independent of commercial interests:

  • We do not accept paid reviews, sponsored rankings, or vendor compensation to endorse specific tools or alter our troubleshooting conclusions.
  • Advertisements (such as Google AdSense) displayed across the website are clearly separated from original editorial content and labeled to prevent reader confusion.
  • Commercial advertisements do not influence our tutorial recommendations.

9. Editorial Accountability & Reader Feedback

We treat our readers as vital partners in maintaining tutorial accuracy. If you notice an error or have feedback on our editorial standards, please review our Corrections Policy or reach out to our team via our Contact page.