AI Content Resources

Curated AI Writing & Content Creation Resources

A curated reading list of the best resources on AI content creation, prompt engineering, and AI writing techniques. Each resource includes why it matters and a practical takeaway.

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Prompting

OpenAI — Prompting guide

Why: Practical guidance on structuring prompts, variables, and iteration.

Takeaway: Put global guidance in system messages; keep task-specific detail/examples in user messages; iterate + evaluate.

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Tools

OpenAI — Working with evals

Why: If you ship prompts, you need a way to measure quality consistently.

Takeaway: Treat prompts like code: define expected behavior, test, iterate, and track regressions.

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Prompting

Google Cloud — Introduction to prompting

Why: Clear breakdown of prompt components and few-shot usage.

Takeaway: Good prompts = task + optional system instructions + optional few-shot + optional context.

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Prompting

Prompt Engineering Guide (DAIR.AI)

Why: Big index of techniques, papers, and learning paths.

Takeaway: Prompting is a discipline: techniques + evaluation + safety patterns.

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Prompting

arXiv — A Prompt Pattern Catalog (White et al., 2023)

Why: A pattern-based way to think about reusable prompt techniques.

Takeaway: Combine multiple prompt “patterns” (like software patterns) to solve recurring problems.

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Writing/UX

Nielsen Norman Group — How users read on the web

Why: Ground truth: users scan; copy must be scannable.

Takeaway: Use meaningful headings, bullets, one idea per paragraph, inverted pyramid; avoid hype “marketese”.

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Writing/UX

Nielsen Norman Group — Inverted pyramids in cyberspace

Why: Shows why “start with the conclusion” works especially well online.

Takeaway: Lead with the conclusion, then support; readers can stop early and still get value.

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Writing/UX

Unbounce — Landing page best practices

Why: A practical checklist for conversion pages.

Takeaway: Keep CTA visible above the fold, remove distractions, keep copy clear, and test changes.

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