Stop building linear chains and start building event-driven agent loops.

Stop building linear chains and start building event-driven agent loops.

Most developers start by chaining LLM calls sequentially. That works for simple tasks, but it breaks the moment your agent encounters an edge case or a tool error. The workflow stalls, the context gets muddy, and your user experience suffers.

Instead, move toward a state-machine architecture. Treat your agent’s state as an immutable object passed between functions. Each function represents a node in a graph, and your logic defines the transitions based on the tool outputs.

This approach gives you a massive technical advantage: observability. Because you have a clear state object, you can log the exact input/output of every step. If an agent fails, you don't just see a generic error; you see exactly which node triggered the transition and why the tool execution failed.

Here is an actionable tip: Implement a simple retry policy at the node level, not the agent level. If a tool-calling function fails due to a rate limit or a malformed JSON output, catch the exception within the node and transition to a specialized correction node rather than failing the entire execution.

How are you handling state persistence in your current agentic workflows?

#AIEngineering #LLMs #AgenticWorkflows #SoftwareArchitecture #DeveloperExperience