Preference interpretation
Typed preferences and checkbox selections should map to structured fields: topics, excluded topics, locations, frequency, sources, tone, article length, and confidence thresholds.
AI standards
The FirstFold trust layer.
FirstFold can use AI to understand preferences, rank relevance, summarize sourced material, format the paper, and personalize the edition. But the product needs guardrails so personalization does not become misinformation, plagiarism, or a filter bubble.
Core principle
Preferences guide relevance. They do not rewrite reality.
The user can choose topics, markets, tone, and read length. The system should still preserve essential context, competing credible viewpoints, and visible source notes where needed.
Source qualification
Eligible sources should be classified by type: original reporting, public records, official releases, data sources, subject-matter publications, wires, local outlets, and contributor submissions.
Print-ready output
Articles should be written to fit physical space. Each story needs a source trail, time stamp, update status, and a label explaining whether it is news, analysis, explainer, opinion, or contributed material.
Source policy
FirstFold should not be built as a black box that “just knows.” A defensible media product needs rules for where facts come from, what counts as sufficient support, and when a story should be withheld.
For high-risk subjects — politics, health, legal, finance, safety, criminal allegations, and breaking news — the system should require stronger sourcing, recency checks, and human review before print publication.
Article minimums
- Visible source note or citation trail.
- Clear distinction between fact, analysis, and opinion.
- Publication/update time for time-sensitive items.
- No unsupported claim presented as fact.
- No article built by copying protected content without rights.
- Escalation path for uncertain or disputed facts.
Hallucination control
How the AI should be constrained.
AI should function like a research assistant, summarizer, layout editor, and personalization engine — not an unsupervised reporter inventing facts.
Retrieval-first drafting
The model should draft only from retrieved, approved, and logged source material. Unsupported claims should be blocked, flagged, or rewritten as uncertainty.
Confidence labeling
Stories should carry internal confidence scores based on source quality, source agreement, recency, directness, and subject risk.
Audit logs
Every edition should keep a back-end record of prompts, sources, model outputs, edits, review decisions, and final print version.
Human review tiers
Low-risk lifestyle stories can move faster. High-risk or disputed stories should require editorial review, legal review, or exclusion from automated print editions.
Corrections policy
Corrections should be public, dated, and tied to the affected edition. Future prints should include corrected language and a correction note when appropriate.
User controls
Users should be able to edit preferences, mute topics, request more or less depth, flag inaccuracies, see why a story appeared, and access the source trail for articles in their edition.
Business risk note: FirstFold should develop publisher licensing, contributor agreements, copyright policy, privacy policy, AI use disclosures, advertising labeling, and editorial standards before operating as a commercial media product.