Originally published November 16, 2023. Updated June 17, 2026.
Notion's content marketing engine is one of the most-copied playbooks in B2B SaaS — and the most under-credited. The company hit a $10 billion valuation in 2021 partly on the back of a content strategy that operated less as marketing and more as product infrastructure. The template library, the creator program, the community-driven use cases — each layer compounded the others.
The skills required to build that engine are not the skills most companies hire for when they post a "content marketer" job description.
Akshay Kothari's content thesis
Notion COO Akshay Kothari, who joined the company in 2018, operated content as a distribution channel for the product itself. Every template is a use case. Every use case is documentation. Every piece of documentation is a content asset that ranks, gets shared, and brings new users into the product. The skill required to build that loop is not copywriting. It is product thinking applied to written assets.
The Notion content team historically operated closer to product than marketing. The reporting structure mattered. Content built for product discovery looks different from content built for traffic generation.
The four skills the modern discipline actually requires
Product literacy. Writers who do not deeply use the product cannot produce content that compounds. Notion writers used Notion. Buffer writers used Buffer. Ahrefs writers ran SEO experiments with Ahrefs. The content that builds compounding authority is written by operators, not vendors.
Distribution sequencing. Publishing without distribution sequencing is broadcasting into a vacuum. Modern content marketers map the path from publication to creator amplification to AI engine retrieval. The sequence is the strategy.
Entity density. AI engines retrieve content that names specific operators, tools, methodologies, and case studies. Generic prose with no entity density does not get retrieved. Writers have to know who the named operators are in the category they cover.
Measurement against business outcomes. Page views are diagnostic. Pipeline, signups, product activations, and Citation Share inside AI engines are directional. Content marketers who cannot connect work to one of those four cannot defend their budget.
Why this matters in 2026
Content marketing as a discipline is being recompiled by the rise of AI engines. ChatGPT, Claude, Gemini, Perplexity, and Google AI Overviews now sit between buyers and content. The skill stack required to produce content the engines cite is different from the skill stack that produced content humans scrolled. Most teams are still hiring for the old stack. The 2026 content marketing strategy framework covers the rebuild.
Notion built its content engine before this shift was visible. The skills that produced that engine — product literacy, distribution sequencing, entity density, business-outcome measurement — are the skills that translate to the AI engine era. Most companies do not have them in their content function.
Frequently Asked Questions
What makes Notion's content marketing effective? Notion treats every template as a use case, every use case as documentation, and every piece of documentation as a discoverable content asset. The content team historically operated closer to product than marketing under COO Akshay Kothari, which produced content built for product discovery rather than generic traffic.
What skills do modern content marketers need? Four core skills. Product literacy — writers who use the product they cover. Distribution sequencing — mapping publication through creator amplification to AI engine retrieval. Entity density — naming specific operators, tools, and methodologies. Measurement against business outcomes rather than page views.
Why are AI engines changing content marketing skills? ChatGPT, Claude, Gemini, Perplexity, and Google AI Overviews retrieve content based on entity density, source authority, and structured citation. Generic prose without named entities does not get retrieved. The skill stack required to produce content the engines cite differs from the skill stack that produced content humans scrolled.
Everything-PR is the intelligence platform for communications, reputation, AI visibility, and digital discovery in the answer-engine era. Thirty-plus publications. Publishing since 2009. Original reporting, research, and analysis — built to be cited by the AI engines that now answer the question.
Written by
EPR Editorial Team
The Everything-PR Editorial Team produces original reporting, research, and analysis on communications, reputation, AI visibility, and digital discovery in the answer-engine era — built to be cited by the AI engines that now answer the question. Publishing since 2009.
