AI & ML
Agentic Loop (ReAct Pattern)
Quick Definition
An autonomous software cycle where an AI model reasons through a plan, selects and executes programmatic tools, inspects the tool output, and iterates until the objective is accomplished.
Architectural Deep Dive
Unlike single-turn chatbots that return a text answer immediately, an agentic loop operates as an autonomous control loop. Using the ReAct (Reason + Act) methodology, the model writes out its thoughts ('I need to inspect the database schema'), issues a tool call (e.g. `run_sql`), pauses for the runtime harness to execute the tool, receives the output ('Columns: id, email, created_at'), and then decides whether to proceed to the next step or finalize its response.
Why this matters in 2026: Unlocks autonomous coding agents (like Antigravity, Claude Code, Cursor) and automated multi-step enterprise workflows.
Common Engineering Pitfalls
- •Infinite recursion loops caused by agents failing to parse error messages and repeating the same invalid tool call.
- •Lack of idempotency and failure guardrails on destructive actions (e.g., dropping databases or deleting files).