The Agentic Shift — Why AI Developers Need to Learn MCP Now
Six months ago, Claude could chat. It could write code, explain concepts, draft emails. But when the conversation ended, nothing happened. The AI lived inside a text box. Today, Claude can read you...

Source: DEV Community
Six months ago, Claude could chat. It could write code, explain concepts, draft emails. But when the conversation ended, nothing happened. The AI lived inside a text box. Today, Claude can read your GitHub repo, check open issues, write code, open a pull request, and message your team on Slack — in a single conversation. Not because Claude got smarter. Because someone built the tools that let it act. That shift — from chatbot to agent — is the most important change happening in AI right now. And the developers building the tools that make it possible are in an incredibly valuable position. Three eras of AI development Era 1: Chat (2022–2023) You type a prompt. The model responds. You copy-paste the output somewhere useful. The AI has no context beyond what you paste into the conversation. Every interaction starts from zero. Era 2: RAG and retrieval (2023–2024) Systems start feeding documents into the model's context. Vector databases, embeddings, retrieval pipelines. The AI can "know"