Guide contents
Hands-on Guide: Autonomous AI Agents on Open-Source Stack & Free APIs
If you want to build an AI agent, the first question is usually not \"which architecture to choose\", but \"where do I even start and what do I need\".
This guide is available to AI-Base subscribers
Get full access to this practical guide, ready-made configurations and terminal scripts.
Related Ecosystem Resources
Explore practical workflows, core terminology, and engineering tools
Top 5 AI Tools of the Month: Breakthroughs for Agents and Developers
A curated review of 5 innovative AI tools of the month: Monid's unified 1,800+ API gateway, Dial virtual numbers, HydraDB OSS graph memory, Doop collaborative canvas, and Orato speech coach.
Part II. AI Agent Architecture: From Model to Memory and Tools
A deep engineering dive: tokenization, KV-cache, sampling determinism, the training stack, quantization, context engineering, the safety stack, production RAG, ReAct, and multi-agent swarm systems.
MCP (Model Context Protocol)
An open standard from Anthropic based on JSON-RPC 2.0 for unified bidirectional connection of AI assistants to external tools, databases, and system environments.
MCP Server
A software service or background process that implements the MCP specification, providing external AI clients with standardized access to function execution, resource reading, and prompt templates.
Anthropic releases FlashProve in open source, a tool for provable inference
Anthropic published a prototype of an open cryptographic protocol called FlashProve that lets anyone verify a model response without access to model weights.
Harvard Opens Free Detailed Course on ML Systems Engineering
Harvard has opened access to CS249r, a course focused on the infrastructure behind training, inference and deployment of AI models. The materials include TinyTorch, interactive labs, MLSys·im and lecture slides.