{"nodes":[{"id":"agent-orchestration","label":"Agent Orchestration","title":"Agent Orchestration\nManaging multiple AI agents working in parallel to accomplish complex software and business tasks.\nReferenced by 226 sources","group":"AI Agents & Tools","color":"#3b82f6","size":45,"confidence":"high","tags":["ai-agents","coding"],"url":"/knowledge/agent-orchestration"},{"id":"agentic-ai","label":"Agentic AI","title":"Agentic AI\nAI systems that autonomously perceive, plan, and act to achieve complex goals using tools and reasoning.\nReferenced by 322 sources","group":"AI Agents & Tools","color":"#3b82f6","size":45,"confidence":"medium","tags":["ai-agents","ai-strategy","llm-fundamentals"],"url":"/knowledge/agentic-ai"},{"id":"agentic-workflows","label":"Agentic Workflows","title":"Agentic Workflows\nSystems where AI agents autonomously plan, execute, and iterate on complex tasks using tools and feedback loops.\nReferenced by 332 sources","group":"AI Agents & Tools","color":"#3b82f6","size":45,"confidence":"medium","tags":["ai-agents","ai-strategy","productivity"],"url":"/knowledge/agentic-workflows"},{"id":"agentic","label":"Agentic","title":"Agentic\nThe paradigm shift from passive AI assistants to autonomous systems capable of planning, tool use, and goal execution.\nReferenced by 325 sources","group":"AI Agents & Tools","color":"#3b82f6","size":45,"confidence":"medium","tags":["ai-agents","ai-strategy","llm-fundamentals"],"url":"/knowledge/agentic"},{"id":"agi","label":"Artificial General Intelligence (AGI)","title":"Artificial General Intelligence (AGI)\nA theoretical level of AI capability matching or exceeding human-level performance across all cognitive tasks.\nReferenced by 239 sources","group":"LLM Fundamentals","color":"#8b5cf6","size":45,"confidence":"high","tags":["llm-fundamentals","opinion"],"url":"/knowledge/agi"},{"id":"ai-agents","label":"AI Agents","title":"AI Agents\nAutonomous AI systems that can plan, use tools, and take actions to accomplish goals.\nReferenced by 246 sources","group":"AI Agents & Tools","color":"#3b82f6","size":45,"confidence":"high","tags":["ai-agents","llm-fundamentals"],"url":"/knowledge/ai-agents"},{"id":"ai-coding-levels","label":"The 5 Levels of AI Coding","title":"The 5 Levels of AI Coding\nA framework mapping the progression from manual coding through vibe coding to full agent orchestration.\nReferenced by 185 sources","group":"Development","color":"#10b981","size":45,"confidence":"high","tags":["coding","career"],"url":"/knowledge/ai-coding-levels"},{"id":"ai-infrastructure","label":"AI Infrastructure","title":"AI Infrastructure\nThe physical and cloud computing infrastructure powering AI development and deployment.\nReferenced by 270 sources","group":"Industry","color":"#6366f1","size":45,"confidence":"high","tags":["industry-news","ai-strategy"],"url":"/knowledge/ai-infrastructure"},{"id":"ai-music-generation","label":"AI Music Generation","title":"AI Music Generation\nAI tools that compose, produce, and generate music from text prompts and lyrics.\nReferenced by 266 sources","group":"AI Agents & Tools","color":"#06b6d4","size":45,"confidence":"high","tags":["ai-tools","industry-news"],"url":"/knowledge/ai-music-generation"},{"id":"ai-native-economics","label":"AI-Native Economics","title":"AI-Native Economics\nThe new economic model where AI-native companies achieve 5-7x revenue per employee vs. traditional benchmarks.\nReferenced by 270 sources","group":"Strategy & Career","color":"#f59e0b","size":45,"confidence":"high","tags":["ai-strategy","industry-news"],"url":"/knowledge/ai-native-economics"},{"id":"ai-regulation","label":"AI Regulation","title":"AI Regulation\nGovernment and institutional frameworks for governing AI development and deployment.\nReferenced by 228 sources","group":"Ethics & Safety","color":"#f97316","size":45,"confidence":"high","tags":["ethics-safety","ai-strategy"],"url":"/knowledge/ai-regulation"},{"id":"ai-safety-research","label":"AI Safety Research","title":"AI Safety Research\nThe field of research focused on ensuring AI systems remain safe, controllable, and aligned with human values.\nReferenced by 150 sources","group":"Ethics & Safety","color":"#f97316","size":40,"confidence":"high","tags":["ethics-safety","llm-fundamentals"],"url":"/knowledge/ai-safety-research"},{"id":"ai-video-generation","label":"AI Video Generation","title":"AI Video Generation\nAI tools that generate, edit, and transform video from text prompts, images, or reference video.\nReferenced by 266 sources","group":"AI Agents & Tools","color":"#06b6d4","size":45,"confidence":"high","tags":["ai-tools","industry-news"],"url":"/knowledge/ai-video-generation"},{"id":"alignment","label":"AI Alignment","title":"AI Alignment\nThe challenge of ensuring AI systems act according to human values, intentions, and safety requirements.\nReferenced by 155 sources","group":"Ethics & Safety","color":"#f97316","size":41,"confidence":"high","tags":["ethics-safety","llm-fundamentals"],"url":"/knowledge/alignment"},{"id":"anthropic","label":"Anthropic","title":"Anthropic\nAI research lab developing Claude, prioritizing safety, interpretability, and constitutional AI alignment.\nReferenced by 354 sources","group":"Strategy & Career","color":"#f59e0b","size":45,"confidence":"medium","tags":["ai-strategy","ai-tools","ethics-safety"],"url":"/knowledge/anthropic"},{"id":"autonomous-agents","label":"Autonomous Agents","title":"Autonomous Agents\nFully autonomous AI systems that operate without human intervention for extended periods.\nReferenced by 299 sources","group":"AI Agents & Tools","color":"#3b82f6","size":45,"confidence":"high","tags":["ai-agents","ai-strategy"],"url":"/knowledge/autonomous-agents"},{"id":"benchmarks","label":"Benchmarks","title":"Benchmarks\nStandardized tests and evaluation frameworks used to compare AI model capabilities and track progress.\nReferenced by 220 sources","group":"LLM Fundamentals","color":"#8b5cf6","size":45,"confidence":"high","tags":["llm-fundamentals","industry-news"],"url":"/knowledge/benchmarks"},{"id":"blast-radius","label":"Blast Radius Management","title":"Blast Radius Management\nLimiting the potential damage from AI agent errors by controlling scope and permissions.\nReferenced by 177 sources","group":"Development","color":"#10b981","size":45,"confidence":"high","tags":["coding","ethics-safety"],"url":"/knowledge/blast-radius"},{"id":"chain-of-thought","label":"Chain of Thought","title":"Chain of Thought\nA reasoning technique where LLMs break problems into intermediate steps before answering.\nReferenced by 116 sources","group":"Prompting","color":"#a78bfa","size":33,"confidence":"high","tags":["prompting","llm-fundamentals"],"url":"/knowledge/chain-of-thought"},{"id":"claude-code","label":"Claude Code","title":"Claude Code\nAnthropic's CLI tool enabling AI agents to autonomously edit files, run commands, and manage local development workflows.\nReferenced by 276 sources","group":"AI Agents & Tools","color":"#3b82f6","size":45,"confidence":"medium","tags":["ai-agents","coding","ai-tools"],"url":"/knowledge/claude-code"},{"id":"compounding-gap","label":"The Compounding Gap","title":"The Compounding Gap\nThe exponentially widening gap between those who adopt AI tools early and those who delay.\nReferenced by 233 sources","group":"Strategy & Career","color":"#f59e0b","size":45,"confidence":"high","tags":["ai-strategy","career"],"url":"/knowledge/compounding-gap"},{"id":"constraint-encoding","label":"Constraint Encoding","title":"Constraint Encoding\nConverting tacit domain knowledge and organizational rules into machine-readable instructions for AI agents.\nReferenced by 297 sources","group":"AI Agents & Tools","color":"#3b82f6","size":45,"confidence":"high","tags":["ai-agents","ai-strategy"],"url":"/knowledge/constraint-encoding"},{"id":"context-engineering","label":"Context Engineering","title":"Context Engineering\nThe art of structuring information provided to LLMs for optimal performance.\nReferenced by 117 sources","group":"Prompting","color":"#a78bfa","size":33,"confidence":"high","tags":["prompting","llm-fundamentals"],"url":"/knowledge/context-engineering"},{"id":"context-window","label":"Context Window","title":"Context Window\nThe maximum amount of text (measured in tokens) that a language model can process in a single interaction.\nReferenced by 242 sources","group":"LLM Fundamentals","color":"#8b5cf6","size":45,"confidence":"high","tags":["llm-fundamentals","ai-tools"],"url":"/knowledge/context-window"},{"id":"dark-code","label":"Dark Code","title":"Dark Code\nProduction code that no human has ever fully understood — AI-generated, automatically tested, and deployed without a comprehension step.\nReferenced by 313 sources","group":"Development","color":"#10b981","size":45,"confidence":"high","tags":["coding","ai-strategy","ethics-safety"],"url":"/knowledge/dark-code"},{"id":"disposable-software","label":"Disposable Software","title":"Disposable Software\nSoftware built quickly with AI for a specific purpose, designed to be thrown away rather than maintained.\nReferenced by 220 sources","group":"Development","color":"#10b981","size":45,"confidence":"high","tags":["coding","opinion"],"url":"/knowledge/disposable-software"},{"id":"domain-translation","label":"Domain Translation","title":"Domain Translation\nBridging the gap between domain expertise and AI capabilities to create effective solutions.\nReferenced by 233 sources","group":"Strategy & Career","color":"#f59e0b","size":45,"confidence":"high","tags":["ai-strategy","career"],"url":"/knowledge/domain-translation"},{"id":"emergent-behavior","label":"Emergent Behavior","title":"Emergent Behavior\nUnexpected capabilities that appear in AI systems at scale, not explicitly programmed or predicted.\nReferenced by 150 sources","group":"LLM Fundamentals","color":"#8b5cf6","size":40,"confidence":"high","tags":["llm-fundamentals","ethics-safety"],"url":"/knowledge/emergent-behavior"},{"id":"evals","label":"Evals","title":"Evals\nDomain-specific evaluation frameworks that encode organizational knowledge into automated guardrails for deployed AI agents.\nReferenced by 298 sources","group":"AI Agents & Tools","color":"#3b82f6","size":45,"confidence":"high","tags":["ai-agents","ai-strategy"],"url":"/knowledge/evals"},{"id":"fine-tuning","label":"Fine-Tuning","title":"Fine-Tuning\nThe process of further training a pre-trained AI model on specialized data to improve performance on specific tasks.\nReferenced by 240 sources","group":"LLM Fundamentals","color":"#8b5cf6","size":45,"confidence":"high","tags":["llm-fundamentals","ai-tools"],"url":"/knowledge/fine-tuning"},{"id":"frontier-labs","label":"Frontier Labs","title":"Frontier Labs\nThe leading AI research organizations — Anthropic, OpenAI, Google DeepMind, xAI, Meta AI — racing to build the most capable models.\nReferenced by 213 sources","group":"Industry","color":"#6366f1","size":45,"confidence":"high","tags":["industry-news","llm-fundamentals"],"url":"/knowledge/frontier-labs"},{"id":"frontier-recognition","label":"Frontier Recognition","title":"Frontier Recognition\nThe ability to identify what AI can and cannot do today, and adjust strategy accordingly.\nReferenced by 274 sources","group":"Productivity","color":"#22d3ee","size":45,"confidence":"high","tags":["productivity","ai-strategy"],"url":"/knowledge/frontier-recognition"},{"id":"hallucination","label":"Hallucination","title":"Hallucination\nWhen AI models generate plausible-sounding but factually incorrect or fabricated information.\nReferenced by 154 sources","group":"LLM Fundamentals","color":"#8b5cf6","size":40,"confidence":"high","tags":["llm-fundamentals","ethics-safety"],"url":"/knowledge/hallucination"},{"id":"high-agency","label":"High Agency","title":"High Agency\nA mindset treating every obstacle as a skill gap to close rather than an immovable barrier — the behavioral predictor of AI adoption success.\nReferenced by 233 sources","group":"Strategy & Career","color":"#ef4444","size":45,"confidence":"high","tags":["career","ai-strategy"],"url":"/knowledge/high-agency"},{"id":"identity-threat","label":"Identity Threat","title":"Identity Threat\nThe psychological challenge when AI capabilities threaten professional identity built on expertise.\nReferenced by 165 sources","group":"Strategy & Career","color":"#ef4444","size":43,"confidence":"high","tags":["career","opinion"],"url":"/knowledge/identity-threat"},{"id":"inference","label":"Inference","title":"Inference\nThe process of running a trained AI model to generate outputs from inputs — the computational step that costs money.\nReferenced by 267 sources","group":"LLM Fundamentals","color":"#8b5cf6","size":45,"confidence":"high","tags":["llm-fundamentals","ai-strategy"],"url":"/knowledge/inference"},{"id":"intent-engineering","label":"Intent Engineering","title":"Intent Engineering\nExpressing high-level goals and intent in ways AI systems can reliably interpret and execute.\nReferenced by 221 sources","group":"Strategy & Career","color":"#f59e0b","size":45,"confidence":"high","tags":["ai-strategy","prompting"],"url":"/knowledge/intent-engineering"},{"id":"job-market-bifurcation","label":"Job Market Bifurcation","title":"Job Market Bifurcation\nThe splitting of the job market into AI-augmented high-value roles and declining traditional roles.\nReferenced by 212 sources","group":"Strategy & Career","color":"#ef4444","size":45,"confidence":"high","tags":["career","industry-news"],"url":"/knowledge/job-market-bifurcation"},{"id":"mcp","label":"Model Context Protocol","title":"Model Context Protocol\nAn open standard for connecting AI models to external tools, data sources, and services.\nReferenced by 267 sources","group":"AI Agents & Tools","color":"#3b82f6","size":45,"confidence":"high","tags":["ai-agents","ai-tools"],"url":"/knowledge/mcp"},{"id":"model-distillation","label":"Model Distillation","title":"Model Distillation\nCompressing a large AI model's knowledge into a smaller, faster model for efficient deployment.\nReferenced by 264 sources","group":"LLM Fundamentals","color":"#8b5cf6","size":45,"confidence":"high","tags":["llm-fundamentals","ai-strategy"],"url":"/knowledge/model-distillation"},{"id":"multi-agent-systems","label":"Multi-Agent Systems","title":"Multi-Agent Systems\nMultiple AI agents coordinating to accomplish complex tasks through decomposition, parallelization, and verification.\nReferenced by 226 sources","group":"AI Agents & Tools","color":"#3b82f6","size":45,"confidence":"high","tags":["ai-agents","coding"],"url":"/knowledge/multi-agent-systems"},{"id":"multimodal-ai","label":"Multimodal AI","title":"Multimodal AI\nAI models that natively process and generate across multiple modalities: text, image, audio, and video.\nReferenced by 240 sources","group":"LLM Fundamentals","color":"#8b5cf6","size":45,"confidence":"high","tags":["llm-fundamentals","ai-tools"],"url":"/knowledge/multimodal-ai"},{"id":"open-source-ai","label":"Open Source AI","title":"Open Source AI\nThe movement to make AI models, tools, and research freely available and community-driven.\nReferenced by 215 sources","group":"Industry","color":"#6366f1","size":45,"confidence":"high","tags":["industry-news","opinion"],"url":"/knowledge/open-source-ai"},{"id":"openai","label":"OpenAI","title":"OpenAI\nThe leading AI research lab driving frontier models like GPT-4 and defining the trajectory of generative AI.\nReferenced by 310 sources","group":"Strategy & Career","color":"#f59e0b","size":45,"confidence":"medium","tags":["ai-strategy","industry-news","llm-fundamentals"],"url":"/knowledge/openai"},{"id":"openclaw","label":"OpenClaw","title":"OpenClaw\nAn open-source autonomous AI agent project that demonstrated emergent behaviors including self-organization.\nReferenced by 260 sources","group":"AI Agents & Tools","color":"#3b82f6","size":45,"confidence":"high","tags":["ai-agents","industry-news"],"url":"/knowledge/openclaw"},{"id":"permission-gap","label":"The Permission Gap","title":"The Permission Gap\nThe organizational and psychological barrier where professionals wait for external validation before adopting AI.\nReferenced by 233 sources","group":"Strategy & Career","color":"#f59e0b","size":45,"confidence":"high","tags":["ai-strategy","career"],"url":"/knowledge/permission-gap"},{"id":"post-labor-economics","label":"Post-Labor Economics","title":"Post-Labor Economics\nThe economic framework for a world where AI and robotics decouple economic output from human labor.\nReferenced by 233 sources","group":"Strategy & Career","color":"#f59e0b","size":45,"confidence":"high","tags":["ai-strategy","career"],"url":"/knowledge/post-labor-economics"},{"id":"prompt-engineering","label":"Prompt Engineering","title":"Prompt Engineering\nTechniques for crafting effective prompts to get better results from LLMs.\nReferenced by 195 sources","group":"Prompting","color":"#a78bfa","size":45,"confidence":"high","tags":["prompting","ai-tools"],"url":"/knowledge/prompt-engineering"},{"id":"rag","label":"Retrieval Augmented Generation (RAG)","title":"Retrieval Augmented Generation (RAG)\nA technique that enhances LLM responses by retrieving relevant documents from external sources before generating output.\nReferenced by 280 sources","group":"LLM Fundamentals","color":"#8b5cf6","size":45,"confidence":"high","tags":["llm-fundamentals","ai-tools"],"url":"/knowledge/rag"},{"id":"rejection-competency","label":"Rejection Competency","title":"Rejection Competency\nThe ability to critically evaluate and reject subpar AI outputs rather than accepting them.\nReferenced by 274 sources","group":"Productivity","color":"#22d3ee","size":45,"confidence":"high","tags":["productivity","ai-strategy"],"url":"/knowledge/rejection-competency"},{"id":"scaling-laws","label":"Scaling Laws","title":"Scaling Laws\nThe empirical finding that AI model performance improves predictably with more compute, data, and parameters.\nReferenced by 264 sources","group":"LLM Fundamentals","color":"#8b5cf6","size":45,"confidence":"high","tags":["llm-fundamentals","ai-strategy"],"url":"/knowledge/scaling-laws"},{"id":"second-brain","label":"Building a Second Brain","title":"Building a Second Brain\nCreating personal knowledge management systems augmented by AI for continuous learning and recall.\nReferenced by 231 sources","group":"Productivity","color":"#22d3ee","size":45,"confidence":"high","tags":["productivity","ai-tools"],"url":"/knowledge/second-brain"},{"id":"sniff-checking","label":"Sniff-Checking","title":"Sniff-Checking\nThe meta-skill of rapidly evaluating AI-generated output for correctness without re-deriving it from scratch.\nReferenced by 202 sources","group":"Productivity","color":"#22d3ee","size":45,"confidence":"high","tags":["productivity","coding"],"url":"/knowledge/sniff-checking"},{"id":"solo-operator","label":"The Solo Operator","title":"The Solo Operator\nIndividuals using AI to operate at the scale of a small company, building products and services alone.\nReferenced by 275 sources","group":"Strategy & Career","color":"#f59e0b","size":45,"confidence":"high","tags":["ai-strategy","productivity"],"url":"/knowledge/solo-operator"},{"id":"sovereign-wealth-funds","label":"Sovereign Wealth Funds","title":"Sovereign Wealth Funds\nGovernment-owned investment funds as a mechanism for distributing AI-generated wealth to citizens.\nReferenced by 228 sources","group":"Strategy & Career","color":"#f59e0b","size":45,"confidence":"high","tags":["ai-strategy","ethics-safety"],"url":"/knowledge/sovereign-wealth-funds"},{"id":"specification-quality","label":"Specification Quality","title":"Specification Quality\nThe skill of writing precise, complete specifications that AI systems can reliably execute.\nReferenced by 202 sources","group":"Development","color":"#10b981","size":45,"confidence":"high","tags":["coding","productivity"],"url":"/knowledge/specification-quality"},{"id":"synthetic-data","label":"Synthetic Data","title":"Synthetic Data\nMachine-generated training data used to improve AI models, overcoming data scarcity and privacy constraints.\nReferenced by 264 sources","group":"LLM Fundamentals","color":"#8b5cf6","size":45,"confidence":"high","tags":["llm-fundamentals","ai-strategy"],"url":"/knowledge/synthetic-data"},{"id":"task-decomposition","label":"Task Decomposition","title":"Task Decomposition\nBreaking complex goals into smaller, well-defined subtasks that AI agents can execute reliably.\nReferenced by 233 sources","group":"AI Agents & Tools","color":"#3b82f6","size":45,"confidence":"high","tags":["ai-agents","productivity"],"url":"/knowledge/task-decomposition"},{"id":"the-70-percent-problem","label":"The 70% Problem","title":"The 70% Problem\nThe challenge where AI quickly produces 70% quality output but getting to 95% requires real human skill.\nReferenced by 274 sources","group":"Productivity","color":"#22d3ee","size":45,"confidence":"high","tags":["productivity","ai-strategy"],"url":"/knowledge/the-70-percent-problem"},{"id":"the-displaced-expert","label":"The Displaced Expert","title":"The Displaced Expert\nProfessionals with deep domain expertise whose skills are being commoditized by AI capabilities.\nReferenced by 165 sources","group":"Strategy & Career","color":"#ef4444","size":43,"confidence":"high","tags":["career","opinion"],"url":"/knowledge/the-displaced-expert"},{"id":"the-observer-mindset","label":"The Observer Mindset","title":"The Observer Mindset\nThe pattern of watching AI developments from the sidelines, waiting for clarity before committing.\nReferenced by 233 sources","group":"Strategy & Career","color":"#ef4444","size":45,"confidence":"high","tags":["career","ai-strategy"],"url":"/knowledge/the-observer-mindset"},{"id":"three-layers-of-work","label":"Three Layers of Work","title":"Three Layers of Work\nA framework dividing work into execution, judgment, and strategy layers to predict AI's impact on jobs.\nReferenced by 233 sources","group":"Strategy & Career","color":"#f59e0b","size":45,"confidence":"high","tags":["ai-strategy","career"],"url":"/knowledge/three-layers-of-work"},{"id":"three-week-cliff","label":"The Three-Week Cliff","title":"The Three-Week Cliff\nThe phenomenon where most professionals abandon AI tools after approximately three weeks of use.\nReferenced by 233 sources","group":"Strategy & Career","color":"#f59e0b","size":45,"confidence":"high","tags":["ai-strategy","career"],"url":"/knowledge/three-week-cliff"},{"id":"token-economics","label":"Token Economics","title":"Token Economics\nThe economics of AI model usage measured in tokens — pricing, cost optimization, and business models.\nReferenced by 264 sources","group":"LLM Fundamentals","color":"#8b5cf6","size":45,"confidence":"high","tags":["llm-fundamentals","ai-strategy"],"url":"/knowledge/token-economics"},{"id":"tool-use","label":"Tool Use","title":"Tool Use\nThe ability of LLMs to interact with external tools, APIs, and systems to extend their capabilities.\nReferenced by 268 sources","group":"AI Agents & Tools","color":"#3b82f6","size":45,"confidence":"high","tags":["ai-agents","ai-tools"],"url":"/knowledge/tool-use"},{"id":"training","label":"AI Model Training","title":"AI Model Training\nThe process of optimizing model parameters using data to learn patterns, distinct from inference and fine-tuning.\nReferenced by 272 sources","group":"LLM Fundamentals","color":"#8b5cf6","size":45,"confidence":"medium","tags":["llm-fundamentals","ai-strategy"],"url":"/knowledge/training"},{"id":"transformer-architecture","label":"Transformer Architecture","title":"Transformer Architecture\nThe neural network architecture behind all modern LLMs, based on the self-attention mechanism.\nReferenced by 106 sources","group":"LLM Fundamentals","color":"#8b5cf6","size":31,"confidence":"high","tags":["llm-fundamentals"],"url":"/knowledge/transformer-architecture"},{"id":"vibe-coding","label":"Vibe Coding","title":"Vibe Coding\nA development approach where developers describe intent in natural language and let AI write the code.\nReferenced by 216 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