This session is a practical, hands-on guide for developers wanting to significantly upgrade their AI coding agents without inventing the wheel again. We'll focus on smart integrations of readily available tools, APIs, and open-source libraries. Attendees will learn how to add and slightly modify these components.

Attendees will learn to integrate features such as:
+ deep research capabilities (e.g. open deep research)
+ leveraging an open source high-performance coding agent as part of the multi-agent setup (openhands)
+ Model Context Protocol (MCP) for standardized tool and data access
+ a simple alternative to MCP (e.g. Langchain)
+ internet search (e.g. Perplexity)
+ Flexible management and switching between different LLMs (e.g. by using LangChain)
+ a simple alternative to RAG
+ basic evaluation to track and improve agent effectiveness

The GitHub repository will be shared.