Editorial Prompt Engineer, ITP Luxury Group ITP Media Group

1) Prompt Systems & Libraries

• Build and maintain prompt libraries (headline packs, SEO/meta, outlines, interview preps, listicles, explainers, social captions, scripts, show notes) per brand voice.
• Create multi-step prompt chains for drafting refinement fact-check style pass; version prompts, run A/B tests, document what works.

2) Editorial Workflow Design

• Map end-to-end editorial workflows and insert AI at the right steps (research assistance, angle generation, text polishing, packaging), always with human-in-the-loop sign-off.
• Stand up repeatable automations (e.g., CMS draft package SEO social variants) using off-the-shelf tools (no-code/low-code) and enterprise LLMs.

3) Research, Verification & Fact-Checking Aids

• Design verify mode prompts that force sourcing, quote extraction, claim lists, and line-by-line evidence checks; require links and provenance for all assertions.
• Create hallucination-reduction patterns (structured checklists, constrained schemas, refusal triggers).

4) SEO & Audience Packaging

• Build prompts for entity/keyword clustering, meta descriptions, URL slugs, image alt text, and headline/subhead variants tailored to each title.
• Provide platform-native social packs (IG/TikTok/YouTube/Threads) with hooks, lengths, and CTAs matched to channel behaviours.

5) Multimedia Support (Post-friendly)

• Prompt frameworks for video/podcast packaging: titles, descriptions, chapters, thumbnails copy, shownotes, and transcript clean-up.
• Generate multi-ratio copy variants and localised (EN/AR) versions with style checks.

6) Training, Playbooks & Change Management

• Run editors rooms/office hours, lunch-and-learns, and build concise playbooks and style-infused system prompts per brand; track adoption and outcomes.
• Coach teams on prompt hygiene, disclosure, and when not to use AI (sensitive topics, high-risk reporting).

7) Governance, Safety & Rights

• Embed newsroom AI principles: transparency, human oversight, labelling of AI-assisted outputs, and data/PII protection; align with AP/Reuters/BBC-style guidance.
• Set guardrails for branded work (church & state), copyright/citations, and content labelling for any automated assistance.

8) Evaluation & Analytics

• Define quality rubrics (accuracy, originality, tone, fairness) and productivity metrics (turnaround time, accepted-as-final rate, edits per draft).
• Report lift in pageviews/engagement for AI-assisted packaging and measure subscriber/loyalty impact on premium brands.

9) Model & Tool Selection

• Compare models/tools (ChatGPT Enterprise, Claude, others) for task fit, safety and cost-performance; maintain a menu of approved use cases.
• Pilot retrieval-augmented workflows using brand archives (licensed content, past issues) to keep outputs on-brand and verifiable (e.g., Ask FT -style constrained assistants).

10) External Signals & Stakeholder Confidence

• Monitor public trust signals around AI in news; propose disclosure language and FAQ for audiences and clients.
• Liaise with legal/compliance on rights, data retention, and crawler policy posture.