Four episodes on what AI actually changes for a content marketer in 2026 — and what it doesn't. The honest read on volume (you can produce more, the ceiling on quality moves slower), the workflow changes that produce real time savings (versus the ones that look productive but don't), and the specific moves that compound (using AI for research, ideation, and structural drafting; not for finished prose). Built for the content marketer or content lead who's been pitched 'AI content tools' for two years and wants the operator-tier read on what's worth building into the workflow.

The book on integrating AI into a content marketing workflow without producing the slop the audience can spot at twenty paces. Covers the structural moves: which parts of the workflow benefit from AI (research, structural drafting, distribution variants) and which don't (the original argument, the lived examples, the editorial taste), the prompt patterns that produce useful output, and the QA layer that prevents the output from drifting into generic-marketing-Claude. Built for the content marketer who wants to take AI seriously without producing content that signals 'this was written by AI'.

The structured checklist for writing prompts that produce useful content output, not just volume. Covers the audience definition step (the prompt's first move), the brief structure that gives AI enough context (and not too much), the output format specification, the example provision (when few-shot beats zero-shot), and the iteration protocol that distinguishes 'good first try' from 'good final draft'. Run it on each new prompt before adding it to the standard library. Most content marketers reach for AI without this structure and produce output that needs more editing than writing from scratch.

The detailed framework for prompt construction that produces output that's useful without being over-specified. Covers the right-sizing question (most content prompts are too short, some are too long), the constraint hierarchy that controls output without killing the model's contribution, the example placement that works (and the placement that doesn't), and the iteration protocol that gets the prompt to a working state in three rounds rather than ten. Worked through with five example content prompts at different scales. Built for the marketer using AI weekly and ready to take the prompt-as-tool seriously.

Twenty-one workflow patterns that consistently slow content production — most invisible to the team running them. The brief that doesn't actually brief (so the writer asks three rounds of questions). The approval chain that loops the same person twice. The editorial calendar that's a calendar but not editorial. The measurement step that gets skipped because the dashboard is in another tool. Each gets a specific structural fix. Read time fifteen minutes. Most content teams recognise at least six. The bundle's other resources turn the recognition into action.

Seven specific applications of AI in content production that consistently save real time without the quality drop. The research compression (turn three hours of source-gathering into thirty minutes of structured input). The outline generation that takes editorial direction and produces a usable brief. The variant generation for headlines and subject lines (where AI is genuinely good). The repurposing brief from one cornerstone piece to five derivatives. Each gets the implementation note. Read in ten minutes. Most marketers can deploy three this week without changing their tooling.

Eight daily emails that walk a content marketer through integrating AI into the actual workflow they're already running. Day 1: workflow audit (where time goes, where AI could fit). Day 2: research-phase AI integration. Day 3: drafting-phase integration (the parts AI handles versus what stays human). Day 4: editing and QA layer. Day 5: distribution and repurposing. Day 6: measurement. Day 7: prompt library setup. Day 8: integration and ongoing iteration. Built for the marketer ready to do the work, not just read about it.

Content marketing eats time in the structured drafting jobs: the strategy memo, the audience research synthesis, the next blog post, the editorial calendar, the SEO meta tags, the repurposing brief, the performance review. The pack moves those jobs to AI-assisted starting points: content-strategy prompts that align tactics with business goals, audience-research prompts that turn raw data into action-ready insights, content-idea prompts across blogs, videos, emails, and social, drafting prompts that hit the structural beats while preserving voice, on-page SEO prompts that handle meta tags and internal links, repurposing prompts that turn one piece into multiple formats, and performance-analysis prompts that read raw data and surface what to repeat. Drop them into Claude or ChatGPT alongside the actual brief. Pair with the content-marketing book for the strategic frame; the prompts are the working session.

The platforms that compose into a working content operation in 2026: the writing layer (Claude, ChatGPT, dedicated content platforms), the distribution and scheduling layer, the measurement and attribution stack, the SEO research tooling that's still worth paying for. Names specific platforms at specific team sizes with the integration patterns that hold up. Includes the honest take on which 'AI content platforms' produce useful output and which are wrappers around the same models you can use directly for less.