AI / Agentic AI Interview Questions
Explain the execution flow of a ReAct agent handling a failed tool call?
sequenceDiagram
participant A as Agent
participant T as Tool
A->>T: Tool call based on Thought
T-->>A: Error or unexpected result
A->>A: Observes failure, reasons about alternative
A->>T: Retries with adjusted approach
T-->>A: Success or further failure
A->>A: Continues loop or escalates
- The agent generates a thought about what action to take and selects a tool accordingly
- It executes the tool call, but the tool returns an error or unexpected result, such as a failed API request
- Because ReAct explicitly folds observations back into context, the agent sees this failure as part of its next reasoning step, rather than the loop silently continuing as if it had succeeded
- The agent reasons about why the call likely failed and what alternative approach might work, such as retrying with different parameters or trying a different tool entirely
- It takes the revised action and continues the loop, or, if it's exhausted reasonable alternatives or its turn budget, escalates to a human or returns a partial result
This explicit failure-handling step is exactly what a purely generative, non-agentic system lacks, without an observation step, there's no mechanism forcing the model to notice and react to something having gone wrong.
What forces the agent to notice a tool call failed?
What can happen if the agent exhausts its turn budget after repeated failures?
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