How a New QA Professional Can Use the 11-Day Plan to Find Defects in AI Agents

How a New QA Professional Can Use the 11-Day Plan to Find Defects

If you’re just starting out in agent QA, here’s how to apply each day’s focus to systematically uncover issues:

Day 1 – Understand QA Scope for Agents Learn what makes agents different from traditional apps. Focus on reasoning, tool usage, and trust—not just UI or output.

Day 2 – Prompt-Level Testing Try different phrasings, ambiguous inputs, and edge-case prompts. Look for inconsistent or hallucinated responses.

Day 3 – Unit Tests for Reasoning & Tools Write small, focused tests to break the agent’s logic. Simulate missing data, sarcasm, or contradictory instructions.

Day 4 – Trace Logging Review the agent’s trace logs. Look for skipped steps, hallucinated logic, or silent tool failures that aren’t visible in the output.

Day 5 – Tool Call Validation Simulate tool errors like null responses or timeouts. Check if the agent retries, falls back, or fails silently.

Day 6 – Reasoning Path Audits Audit the agent’s logic step-by-step. Did it follow the right process, or jump to conclusions?

Day 7 – Human + Model Judging Compare LLM-generated scores with your own. Look for cases where fluent responses hide flawed reasoning.

Day 8 – Failure Pattern Analysis Tag and group failures. Identify recurring bugs—like always failing when a certain tool is used or when memory is required.

Day 9 – Workflow Simulation Testing Test full user journeys. Look for issues with memory, branching logic, and recovery from mid-flow interruptions.

Day 10 – QA Flywheel Setup Automate your tests. Set up dashboards and alerts to catch regressions early and continuously improve.

Day 11 – Showcase & Reporting Present your findings clearly. Use trace-backed evidence, before/after examples, and a readiness score to build stakeholder confidence.

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