AI Content Factory with Human Quality Control

AI Prompts to Build This

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1. 1. Project Setup

   Build the weekend MVP of "ContentFactory": draft a batch of articles with Claude, score every section with a critic pass, and send only the flagged sections to a human editor.
   
   Stack: Next.js (App Router), TypeScript, Tailwind, Supabase (Postgres, Row Level Security, Auth with email magic link), Claude (Anthropic API) for the drafts and a separate prompt for the critic. Drafting and the critic run inline in route handlers. Deploy on Vercel.
   
   Tables (Row Level Security on, each user reads only their own rows):
   - brand_kits(id, user_id, voice_samples, banned_claims, icp_notes, policy_version)
   - briefs(id, user_id, brand_kit_id, brief, status)
   - documents(id, brief_id, title)
   - sections(id, document_id, ordinal, markdown, critic_json jsonb, status)  where status is one of drafted, needs_review, approved, rejected
   - reviews(id, section_id, reviewer_id, action, reason, created_at)
   
   Screens: /login, /kit (brand kit), /queue (flagged sections).
   Env vars (names only): NEXT_PUBLIC_SUPABASE_URL, NEXT_PUBLIC_SUPABASE_ANON_KEY, SUPABASE_SERVICE_ROLE_KEY (server only), ANTHROPIC_API_KEY.
   
   Do not build: billing, plans or pay-per-review, a job queue, CMS publishing, multiple organizations, an admin area.
   Done when: npm run dev starts, you can sign in, and the five tables exist with Row Level Security on.

2. 2. Core Feature

   Build the one feature that proves ContentFactory: a critic pass that shows an editor only the sections that failed.
   1. For each brief, ask Claude to draft a document using the brand kit and split it into sections.
   2. Send the sections to a second Claude prompt with a strict JSON schema: an array of { section_id, voice_score 0-1, claims_score 0-1, duplication_score 0-1, policy_hits: string[], needs_review: boolean, rationale }.
   3. Mark needs_review true if any score is under 0.7 or policy_hits is not empty. Save critic_json on the section and set its status to needs_review. Every other section is approved.
   4. /queue lists only needs_review sections, with the section before and after for context. Accept (with an optional rewrite) or reject with a reason.
   5. Log the model, the prompt version and the reviewer on every status change.
   Rules: never send the whole article to a human by default. A reviewer may expand an approved section to read it.
   Empty state: with no brand kit, show the kit form first.
   Done when: a 10-brief batch drafts and scores, the queue holds only the flagged sections, and accepting or rejecting one updates its status and writes a reviews row.

3. 3. Landing Page

   Build a one-page landing site for ContentFactory, an AI content line with human quality control.
   Hero: "AI drafts at scale. Humans only see what failed the critic." Sub: "Route flagged sections to editors. Collapse the rest." One button: Send a 10-URL batch, get a critic report, which joins the waitlist.
   Sections: the Thursday-batch problem, how it works in four steps (load constraints, draft in bulk, critic pass, human QC), a mock editor portal with three flagged spans, and an FAQ (will it replace a writing tool, who is liable: a human still signs).
   Waitlist: store the email in a waitlist table in Supabase. No other service.
   Style: Geist, off-white, one ink accent.
   Done when: the page renders on a phone and a submitted email appears in the waitlist table.

4. 4. Branding Package

   Use a design or image tool for this one. A coding agent cannot draw a logo.
   Brand ContentFactory as industrial quality control, not a playful AI writer: a wordmark and a stamp mark.
   Colors: near-black, paper white and one lime or steel-blue accent. Type: Geist for headings and a serif for sample article text.
   Voice rules: talk about editor hours saved and sections flagged, never "AI-powered content", and never claim a review-time cut unless that client's own evaluation shows it.
   Deliverables: wordmark, stamp mark, a one-page brand sheet, three critic rationale examples (voice drift, unsupported claim, banned phrase), and two empty states: "0 flags, still reviewable" and "12 flags across 4 articles".
   Done when: each deliverable is saved in one folder and the stamp reads at 48 px.