AI History & Key Milestones
From the theoretical foundations of 1950 to modern agentic frameworks, Model Context Protocol (MCP), Vibecoding, and Spec-Driven Development.
Turing Test Proposed
Alan Turing introduces the Turing Test in "Computing Machinery and Intelligence", establishing an empirical standard for evaluating machine intelligence.
AI Term Coined at Dartmouth
The term "Artificial Intelligence" is coined at the Dartmouth Conference, formally establishing AI as a distinct research discipline.
Deep Blue Defeats Kasparov
IBM's Deep Blue defeats world chess champion Garry Kasparov, proving AI's ability to dominate complex heuristic search and strategic computation.
Watson Wins Jeopardy!
IBM Watson beats top human champions on Jeopardy!, demonstrating major breakthroughs in question answering and natural language retrieval.
Deep Learning Revolution (AlexNet)
AlexNet wins the ImageNet competition by a historic margin, igniting the modern deep learning and GPU-accelerated neural network revolution.
AlphaGo Defeats Lee Sedol
DeepMind's AlphaGo defeats 18-time world Go champion Lee Sedol 4-1, mastering an intuition-driven game using deep reinforcement learning.
Transformer Architecture
Google publishes "Attention Is All You Need", introducing the self-attention Transformer architecture that underpins all modern LLMs.
Creation of LangChain
Harrison Chase creates LangChain, an open-source framework enabling developers to chain LLMs with external tools, memory stores, document loaders, and autonomous agent loops.
ChatGPT Public Launch
OpenAI releases ChatGPT, democratizing conversational AI and accelerating generative AI adoption across consumer and enterprise software.
Multimodal Frontier Era
Frontier models such as GPT-4o, Claude 3.5 Sonnet, and Gemini 1.5 deliver native multimodal intelligence spanning text, vision, audio, and code reasoning.
Model Context Protocol (MCP)
Anthropic releases the open Model Context Protocol (MCP), establishing a universal, secure communication standard for connecting AI agents directly to tools, APIs, and data sources.
Vibecoding Paradigm
Popularized by Andrej Karpathy, Vibecoding defines a new software creation model where developers express intent and high-level architecture in natural language while AI writes and maintains the code.
A2A (Agent-to-Agent Protocols)
Emergence of standardized Agent-to-Agent (A2A) orchestration protocols, enabling distributed multi-agent swarms to negotiate, delegate sub-tasks, and collaborate autonomously.
Git Spec Kit - SDD
Spec-Driven Development (SDD) formalized through Git Spec Kit, marrying version-controlled specifications with automated AI execution pipelines for reliable, auditable code generation.
OpenClaw Autonomous Agent Framework
OpenClaw establishes an extensible agent platform providing full system execution, MCP connectivity, multi-step planning, and end-to-end autonomous engineering capabilities.
Building the Next Generation of AI Systems
From foundational knowledge to hands-on agent engineering with MCP, LangChain, and autonomous pipelines. Let's build your next AI solution together.