AI Agents & LLM Integration
Building a real, production LLM-powered feature: tool-calling architecture, the propose-then-confirm pattern for anything that writes data, authorization that never trusts the model, and the genuine bugs this kind of system produces.
17 lessons
Beginner
What an AI agent actually isBeginner3 min read·Not startedChoosing an SDK for tool-callingBeginner3 min read·Not startedSystem prompts are generated documents, not static stringsBeginner5 min read·Not startedStructured outputs: getting reliable JSON from an LLMBeginner3 min read·Not startedCost and token budgeting for LLM featuresBeginner3 min read·Not started
Intermediate
Context tools vs action toolsIntermediate4 min read·Not startedThe propose-then-confirm pattern for AI-initiated writesIntermediate3 min read·Not startedIdempotent confirmation and rate limiting AI endpointsIntermediate5 min read·Not startedRetrieval-augmented generation (RAG)Intermediate3 min read·Not startedConversation memory and summarization strategiesIntermediate3 min read·Not startedTool schema designIntermediate3 min read·Not started
Advanced
Authorization for AI agents: never trust the modelAdvanced3 min read·Not startedPrompt cachingAdvanced3 min read·Not startedEvaluating agent behaviorAdvanced3 min read·Not startedReal bugs from building an LLM-powered featureAdvanced13 min read·Not startedMulti-agent orchestrationAdvanced3 min read·Not startedHallucination mitigation and groundingAdvanced3 min read·Not started