Quiz on Developing LLM Applications with Python
A diagnostic quiz for Python LLM apps, checking APIs, prompts, LangChain, RAG, embeddings, vector databases, agents, and MCP tool connections.
MCP
Inside Claude Code: Understanding How Context, Tokens, Tools, and Subagents Work
Claude Code assembles layered context from rules, Skills, MCP, files, and tool output, then manages tokens and subagents while running tests.
The Invisible API Revolution: How AI Agents Quietly Reshaped the Internet’s Plumbing
AI agents are becoming primary API consumers. MCP, A2A, and agentic protocols may change API design, traffic patterns, rate limits, and value metrics.
Python-Based Learning Roadmap for LLM Application Development
A Python roadmap for LLM apps: call APIs, craft prompts, add RAG, build agents, and use MCP while managing reliability, security, and cost.