A Practical LLM Application Roadmap: From RAG to Agent Workflows
If you want to take LLMs beyond simple demos and turn them into real work tools, use this roadmap. It walks through a systematic technical build for solving business problems—from RAG-based knowledge retrieval to designing agents that can p
Evaluating and Debugging LLM Agents: Strategies for Reliability in Non-Deterministic Systems
How do you test non-deterministic LLM agents and make them more reliable? This post covers practical methods: agent trace analysis, tool-call validation, unit and integration testing strategies, and production monitoring.
LLM Agent Tool Use: From Function Calling to MCP
A complete breakdown of tool use, the core mechanism that lets LLM agents interact with the outside world. We compare OpenAI Function Calling, Anthropic Tool Use, and the Model Context Protocol (MCP) side by side with code.
LLM Agent Memory System Design: From Short-Term Memory to Long-Term Memory
Design a memory architecture so LLM agents can retain context and learn over the long term. This post covers conversation-history management, summarization-based compression, and vector-DB long-term memory, with practical code.