Standard file formats like .docx and .pptx are filled with complex code that LLMs struggle to parse. To build effective AI workflows, companies must create deliverables in formats that are both human-readable and AI-friendly. HTML is a prime example, as it is visually appealing for people and easily ingested by AI.
Related Insights
Technical interfaces like drag-and-drop workflow builders are immediately rejected and delegated by senior business leaders. To achieve executive buy-in and direct engagement with AI process tools, the interface must be presented in a familiar format: a plain English document that they can read and edit.
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.
Move beyond generating plain text by prompting AI to build complete, individual HTML artifacts for email campaigns. By specifying brand styles, you can get production-ready code that can be directly imported into an email service provider, significantly reducing manual design and coding work for marketing teams.
Tools like Genspark's AI Slides are most valuable for rapidly structuring ideas into a coherent presentation, acting like a 'wireframe' for content. The primary benefit is transforming raw information into a logical first draft, which can then be exported to traditional tools like Google Slides for final design polish.
When building AI workflows that process non-text files like PDFs or HTML, consider using Google's Gemini models. They are specifically strong at ingesting and analyzing various file types, often outperforming other major models for these specific use cases.
Move beyond basic AI prototyping by exporting your design system into a machine-readable format like JSON. By feeding this into an AI agent, you can generate high-fidelity, on-brand components and code that engineers can use directly, dramatically accelerating the path from idea to implementation.
New AI-powered browsers struggle to index content locked in PDFs. To ensure your information is discoverable and summarized correctly by these tools, you must replicate gated content in standard, scannable HTML on your website.
When building multi-agent systems, tailor the output format to the recipient. While Markdown is best for human readability, agents communicating with each other should use JSON. LLMs can parse structured JSON data more reliably and efficiently, reducing errors in complex, automated workflows.
Since Microsoft is a primary partner for OpenAI, its published guidelines for making content AI-friendly (e.g., using Q&A blocks, simple tables) are a direct feeder for what gets surfaced in ChatGPT. Marketers should follow Microsoft's rules to optimize for all major AI tools, not just Microsoft's.
Feed AI coding tools text-based Mermaid diagrams which compress complex application logic into a format AIs can parse much faster and more accurately than raw code. This improves the quality and speed of AI-generated work by providing compressed, robust context.
