AI for content and marketing, across 5 workflow patterns.

An end-to-end pipeline that takes a content brief — topic, audience, format, tone — and moves it through research, drafting, internal review, editorial polish, and publication. Different from a tool that just generates text in that it works from the firm's actual content principles, references the firm's own prior writing and research, routes drafts to the right humans at the right stages, and never publishes anything without explicit human approval. The pattern's value is compressing the time from brief to published from weeks to days while keeping the firm's voice and quality bar intact.

Continuously analyzes what people search for in the firm's space, what the firm has published, and what the competition publishes — and surfaces the highest-value gaps: topics with real search demand the firm doesn't cover, existing content losing rank, opportunities to consolidate underperforming pieces. Different from generic SEO tools because the pattern works against the firm's specific commercial priorities (which topics actually drive qualified pipeline) rather than just search volume. Output is a prioritized list of content actions: write this, update that, retire this old piece. Humans make decisions; the pattern does the analysis.

For firms running paid acquisition, generates ad copy variants for different audience segments, channels, and angles — then watches performance and continuously feeds back into what works. Different from generic ad-generators in that the pattern grounds variants on the firm's actual messaging principles and approved claims library, refuses to make claims it can't substantiate, and tracks performance back to inform future variants. Humans approve every variant before it goes live. The pattern's value is letting marketing teams test more angles more often without each test consuming hours of copywriting time.

Pulls product feedback from everywhere it gets mentioned — support tickets, sales call transcripts, customer success notes, public reviews, social channels — and synthesizes it into structured themes the product team can act on. Different from running a survey: this pattern works on unsolicited feedback in its natural form, identifying signals across thousands of mentions that no human would catch by reading individually. Output is themed feedback with weight (how many sources, how recent), severity (how badly does it block customers), and direct links to specific source mentions. Humans interpret and decide what to do with it; the pattern surfaces what's worth interpreting.

Continuously watches where the firm and its products get mentioned across public sources — news, social, review sites, podcasts, industry forums — classifies each mention by sentiment, topic, and influence, and surfaces what needs attention. Different from a generic mention-tracker because the pattern weights mentions by source authority and audience reach, distinguishes real reputational signals from noise, and routes the few mentions that genuinely need response to the right team. The pattern's value is ensuring that the firm sees what's being said about it without anyone needing to scroll through hundreds of low-signal mentions to find the meaningful ones.