Editorial standards
How we publish and review.
Our guides and proof systems are designed to be useful, transparent, attributable, and maintainable as AI tools change.
Content responsibility
AI Craft Academy publishes organization-led resources and founder-attributed material. Omer Faruk Sahin is responsible for final review of founder-attributed methods, Studio positioning, public proof framing, and material claim or disclosure changes. Alihan Ergin contributes to selected course-production and module-development work.
Practical evidence
We prioritize tested workflows, observable output behavior, and production experience. We separate direct observations, fictional planning examples, internal demonstrations, and recommendations.
Review sequence
- Confirm the page has a defined user job and original answer.
- Check source assets, tool behavior, and factual statements available at review time.
- Review rights, claims, likeness, disclosure, and unsupported-result risks.
- Verify internal links, visible FAQs, metadata, and structured data match the page.
- Record a material update when the method or conclusion changes.
Benchmark transparency
When we publish an original benchmark, the protocol is defined before the final run. We record input assets, prompts, tool and model versions shown at the time, settings, run status, raw outputs, exclusions, and reviewer scores. Failed or unattractive outputs remain part of the evidence record.
Pilots are not rankings
Small pilots test a workflow and calibrate a rubric. We label them clearly, report raw counts where relevant, retain reviewer disagreement, and do not turn them into superiority or tool-ranking claims.
Proof and disclosure
Internal demonstrations, fictional brands, spec concepts, synthetic people, and unofficial references are labeled. They are not presented as client work, testimonials, partnerships, or performance evidence.
Tool volatility
AI products, interfaces, pricing, terms, and model behavior change quickly. Updated dates identify the current editorial state, but users should verify active tool capabilities and commercial terms before production.
No guaranteed outcomes
We do not promise income, virality, client acquisition, ranking, identical generations, or advertising performance. Examples demonstrate methods and production possibilities.
Original work
We may study public tools, formats, and campaigns, but public explanations, frameworks, prompts, examples, and recommendations must be written for AI Craft Academy rather than copied from another source.
Corrections
Material errors are corrected after confirmation. Send the URL, disputed statement, and supporting detail to support@aicraft.academy.