AI Testing Agents
When the agent writes the code, who tests it? Strategies for verifying agent-generated output.
Overview
Agent-generated code needs testing just like human-written code - arguably more. The best approach uses a separate agent as a testing layer: one agent builds, another agent tests.
The Problem
When a human writes code, they have mental context about edge cases, assumptions, and design decisions. When the agent writes code, that context is often incomplete or hallucinated. The code may look correct but fail in ways that are not immediately obvious.
This is not a reason to avoid agent-generated code. It is a reason to test it properly.
Testing by Level
APL 1 · Zero Setup APL1: Manual Review
At APL1, you are copying code from chat. The testing is inherently manual - paste, run, check. The main risk is trusting agent output without running it.
APL 2 · Light Setup APL2: Diff Review
APL2 editors show you diffs before applying changes. Use that. Read every diff. If you do not understand a change, do not accept it.
APL 3 · Dev Setup APL3: Agent-Generated Tests
This is where it gets interesting. At L3, the same agent that writes code can also write tests. But be careful - an agent may write tests that pass but don't actually verify the right behavior.
- Ask the agent to write tests before the implementation (TDD-style)
- Review the test assertions - do they test behavior or just structure?
- Run tests in a separate process, not within the agent session
APL 4 · System Setup APL4: Dedicated Testing Agents
Use separate agents specifically for testing. One agent builds, a different agent reviews and tests. This creates a natural adversarial dynamic.
- Testing agent has read-only access to the code
- Testing agent writes its own test cases from the spec, not the implementation
- Results are logged and available for human review
Tools for Agent Testing
TestSprite* is purpose-built for this - an AI testing agent that automatically generates and runs tests against your application. It works particularly well at APL3 where you need automated verification of agent-generated changes.
The Principle
Never let the same agent that wrote the code be the only one that evaluates it. Separation of concerns applies to agents just as much as it applies to software architecture.
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