Picture this, Mihai: you manage forty WordPress client sites. One runs Elementor. Another runs Divi. A third uses Bricks. Your AI coding agent opens a file, tries to make a simple layout change, and silently corrupts the entire page. No error. No warning. Just broken content that took your client three weeks to build. That scenario is not hypothetical. It is the daily reality for WordPress agencies right now. Here is the number that frames the scale of the problem. WordPress powers approximately 43% of all websites on the internet. That is nearly half the web running on a single platform, yet that platform hosts a wildly fragmented collection of builders, each speaking its own private language. The fragmentation runs deeper than most developers realize. Elementor alone has over five million active installations, according to the WordPress plugin repository. Yet its internal data structure is fundamentally incompatible with Divi, with Beaver Builder, with Bricks, with Brizy. Each builder invented its own way to store layout data. Some use shortcodes stacked inside other shortcodes, what developers at WP Tavern have called "shortcode soup." Others use dense JSON blobs, serialized arrays, or proprietary binary-style formats. A standard large language model sees that raw data and has no reliable way to know what is structural and what is content. It cannot distinguish a column wrapper from a headline. So it guesses. And when it guesses wrong, it breaks the page. Now, the key idea here is the abstraction layer. Think of it like a translator standing between two diplomats who share no common language. The raw builder data is one diplomat. The AI agent is the other. Without a translator, every exchange risks a catastrophic misunderstanding. That translator is what Respira.press provides. It sits between your local AI coding agent and the live WordPress database, reading the proprietary format and converting it into structured, semantic information the agent can actually reason with. Anthropic introduced the Model Context Protocol in late 2024 specifically to standardize how AI models interact with diverse third-party data sources and tools. Respira.press is built on that protocol. That means your agent connects through a defined, stable interface rather than scraping raw database rows and hoping for the best. The process Respira.press uses is often described as flattening. That word matters. When a hero section gets flattened, the agent does not see a cascade of nested divs with cryptic class names. It sees a component. It sees a headline field, a subheadline field, a background image property, a call-to-action button with its label and its URL. That is a high-level representation a language model can reason about confidently. This is where it gets interesting for you, Mihai, because the same flattening logic applies across different builders in a single agent session. The agent does not need to know that Brizy stores its data differently than Bricks. Respira.press handles that translation internally. You stay in one terminal window. You issue one instruction. The right builder-specific write operation happens on the correct site without you opening a single browser tab. The takeaway from all of this is precise and worth holding onto. AI agents are not blocked by WordPress complexity because they lack intelligence. They are blocked because raw builder data is a wall of proprietary formats with no shared grammar. Respira.press tears down that wall by doing one specific job extremely well: it interprets the proprietary data structures of major page builders and exposes them as clean, reasoned components an agent can read, edit, and write back safely. For a WordPress agency managing a diverse client portfolio, that means one agent session can now navigate Elementor logic on one site and Bricks logic on another without a context switch, without a corrupted page, and without a developer manually babysitting every operation. AI agents can now interpret the proprietary data structures of major page builders, allowing you to manage a diverse portfolio of client sites through a single unified interface. That is not a future promise, Mihai. That is the architecture this course is built on.