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The repeating cycle where a model thinks, calls a tool, reads the result, and decides what to do next until the task is done.
An agentic loop is the core engine of any agent: the model proposes an action (usually a tool call), the runtime executes it, feeds the output back into the context, and the model decides whether to act again or stop. This is what separates an agent from a single prompt-response — it can chain dozens of steps and react to what it finds. Example: 'fix the failing test' becomes run tests, read the error, edit the file, run tests again, repeat until green.
Plainly
Think of Agentic Loop as a simple recipe for doing the work better. The repeating cycle where a model thinks, calls a tool, reads the result, and decides what to do next until the task is done.
In practice
Use it when you need a repeatable method instead of guessing from vibes. In practice, define the owner, input, output, and failure mode before you rely on it.