Instead of asking an LLM to write for you, feed it high-performing content (tweets, landing pages). Prompt it to analyze the structure, psychological triggers, and core components. This reverse-engineers success into a detailed guide you can use to replicate it with your own ideas.

Websites now have a dual purpose. A significant portion of your content must be created specifically for AI agents—niche, granular, and structured for LLM consumption to improve AEO. The human-facing part must then evolve to offer deeper, more interactive experiences, as visitors will arrive with their basic research already completed by AI.

Instead of just using external AI chats, teams can build custom tools like a "notebook LM" on top of their own asset libraries (e.g., case studies). This centralizes knowledge, making it instantly queryable and useful for both marketing and sales, maximizing the ROI on past content creation.

The audience for marketing content is expanding to include AI agents. Websites, for example, will need to be optimized not just for human users but also for AI crawlers that surface information in answer engines. This requires a fundamental shift in how marketers think about content structure and metadata.

Instead of asking an AI to repurpose content ad-hoc, instruct it to build a persistent "content repurposing hub." This interactive artifact can take a single input (like a blog post URL) and automatically generate and organize assets for multiple channels (LinkedIn, Twitter, email) in one shareable location, creating a scalable content remixing system.

Instead of only planning future content, systematically tag every published piece with its topic, performance metrics, and the pain point it addresses. This creates a data-rich, reusable library that allows you to identify and remix your most successful content ideas.

Optimizing for AI is not a task for a single team. It requires a holistic, coordinated effort across brand, content, lead gen, and ABM teams to ensure all content is consumable by LLMs in a consistent and desirable way, preventing misinterpretation of the brand's narrative.

Instead of only planning future content, create a database (in Notion or a Google Sheet) of all published assets. Tag each piece by topic, pain point, and performance metrics (likes, shares, open rates) to systematically identify what resonates and should be repurposed.

Instead of writing a style guide from scratch, feed your most successful and on-brand articles, emails, and web pages into an AI model. This process allows the AI to capture the essence of your unique voice, creating a foundational asset for generating new, consistent content at scale.