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Key Takeaways Agentic AI is transforming software testing. Unlike traditional testing, AI agents autonomously write, execute and evolve tests by reasoning about software behavior.
Successful implementation requires starting with one contained domain, measuring rigorously for 12 weeks and scaling based on validated results.
The biggest barriers to success include treating agents like traditional automation, poor data quality, over-scoping and weak security architecture.
I tested the first AI agents as we were building them. And what fascinated me the most was watching these systems reason through test scenarios that I hadn’t even thought of.
We’re still experimenting with these QA agents under different conditions, but software QA, in my eyes, has changed forever.
We’re watching AI agents write comprehensive test suites in hours instead of weeks, finding obscure bugs that would have taken months to surface and adapting their strategies based on what they learn about your codebase. And I think every company should test the waters before it’s too late.
Related: How Autonomous Agents Are Transforming Software From Passive to Powerful
What is agentic testing doing that traditional approaches can’t?
Writing, executing and evolving tests autonomously by reasoning about software behavior.
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