20 articles
A complete guide to building predictable, production-ready AI agents. Learn why deterministic routing, structured outputs, and state machines are mandatory for enterprise AI.
Why the Model Context Protocol (MCP) is being replaced by deterministic Agent Skills for production AI systems.
Why one agent isn't enough. We explore the design patterns of Multi-Agent Systems (MAS), including Leader-Worker, Hierarchical Teams, and Shared Memory architectures.
The Framework Showdown. Comparing the architecture, complexity, and performance of the top 3 agent frameworks.
The Enterprise Choice. Why LangGraph is the standard for high-reliability, long-running agent systems.
The Hybrid Approach. How to combine LangGraph's control with CrewAI's collaboration for the ultimate system.
Watch the agent work. How to capture and stream the 'Thought' and 'Action' phases to the UI in real-time.
The snapshot of intelligence. Managing variables, message history, and flags within a running agent.
The successor to the Loop. Understanding the need for cyclic graphs in agent development.
Designing the flowchart of intelligence. Understanding nodes, edges, and state transitions.
The building blocks of LangGraph. Learning how to write functions that play nice with the graph schema.
Stability in the graph. Using edges and state counters to prevent infinite loops and ensure predictable behavior.
Managing the perimeter. Using specialized nodes to filter inputs and validate final results.
Hands-on: Convert a simple LangChain AgentExecutor into a controlled LangGraph workflow.
The logic of the graph. Mastering how to route control based on tool calls, state variables, and LLM output.
Setting boundaries. How to implement hard limits on cycles and token usage within your agent graphs.
Resilience by design. How to handle tool failures and rate limits within the agent graph.
The zero-trust agent. How to implement verification steps that ensure output quality before finishing.
The pause button. Implementing 'interrupts' that allow humans to review and edit agent state before final actions.
Hands-on: Build a complex research agent with routing, loop guards, and a validation gate.