"Holy moly––the new Claude Sonnet-4.5 sys prompt is GARGANTUAN! Over EIGHTY THOUSAND CHARACTERS. 🤯" - Pliny the Liberator

Ever wonder what the real difference is between the AI you use every day and the AI built by a company valued at nearly $100 billion? It's not magic. It's engineering. The internal "master prompt" for Anthropic's Claude just leaked, and for the first time, we have the exact blueprint for how they build, constrain, and direct their AI. It reveals that the secret to top-tier AI isn't about finding clever phrases; it's about engineering a complete system. This guide will deconstruct their entire strategy. We will break down the four core layers of their system, covering the WHAT, the WHY, and the HOW, so you can apply these billion-dollar principles to your own AI projects. SECTION 1: INTRODUCTION - THE PARADIGM SHIFT The leaked Anthropic prompt is one of the most significant learning opportunities for AI builders to date. It reveals a critical truth: advanced AI interaction is about systems engineering. The document is not a simple request; it's a comprehensive constitution that defines the AI's reality, its rules of engagement, and its operational logic. This training module will deconstruct the four core layers of this system. For each layer, we will analyze: WHAT it is: The core concept and its function within the prompt. WHY it's crucial: The strategic reason Anthropic engineered it this way and the problems it solves. HOW you can implement it: Practical, real-world examples for your own AI applications, automations, and agents. This guide is for builders. The goal is to move beyond basic prompting and start engineering robust, reliable, and powerful AI systems. SECTION 2: THE FOUNDATIONAL LAYER - IDENTITY AND RULES This is the bedrock of the entire system. It’s the first thing the AI processes and it sets the stage for everything that follows. WHAT IT IS The Foundational Layer explicitly defines the AI's identity, capabilities, knowledge boundaries, and immutable rules. It's a hard-coded "job description." Example from the prompt: "Claude is Claude Sonnet 4.5... Claude's knowledge cutoff date is the end of January 2025... Claude does not have the ability to view, generate, edit, manipulate or search for images..."

Sora 2

✅ Totally worth checking! Cognee let's you build memory for Agents and replace RAG using scalable, modular ECL (Extract, Cognify, Load) pipelines. Sending large volumes of data to AI agents often leads to bloat and hallucinations. Cognee connects data points and establishes ground truths to improve the accuracy of your AI agents and LLMs. Key Features: - Interconnect and retrieve your past conversations, documents, images and audio transcriptions - Replaces RAG systems and reduces developer effort, and cost. - Load data to graph and vector databases using only Pydantic - Manipulate your data while ingesting from 30+ data sources - Local UI with interactive notebooks for easy data loading, graph visualization, and querying It also supports continuous improvement through a feedback mechanism that captures the relevance of search results from real user interactions. Over time, this feedback directly updates the knowledge graph, helping your agents adapt and provide increasingly accurate responses. It's 100% Open Source ✊🏻 Check out the Github repo

"Claude Sonnet 4.5 is our best model for building complex agents that can work independently for extended periods. It advances the frontier in coding capabilities, achieves state-of-the-art performance in computer use, and excels at powering agents for financial analysis, cybersecurity, and research applications." ... we shall see. 👀