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As AI agents become more involved in development and testing, I’m wondering how this should change the way we manage QA work.
An agent-native project workspace could allow agents to:
Own specific testing or development tasks
Access relevant project and test context
Update results and report findings
Work on multiple tasks in parallel
Hand work back to humans for review
Keep agent activity and decisions traceable
SpiraTest is already moving in this direction with AI capabilities and MCP support, so I’m curious where this could go next.
I’ve also been looking at [name redacted], which takes a broader approach by putting AI agents and human teammates into the same project workspace.
For SpiraTest users, would you want AI agents to become actual participants in the QA workflow, with their own ownership and accountability?
Hello,
Ownership and accountability are two different things, and conflating them is where this gets risky.
Ownership - an agent being assigned a task, holding it, working it, reporting on it — is fine and useful. That's just task routing. Give an agent the "regenerate these API tests" task and let it own the execution.Accountability - being answerable for an outcome - an agent cannot actually hold. When a released bug slips through, "the agent owned that test" is not an answer anyone can act on. Accountability has to trace back to a human or a team. An agent can't be disciplined, can't learn from a postmortem the way a person does, can't be held responsible in any sense that matters.So my honest answer to your direct question - would you want AI agents to become actual participants with their own ownership and accountability? - is: participants with ownership, yes; with accountability, no. The agent can own the work; a human owns the outcome.The moment an org lets accountability quietly shift to the agent, it's created a place for responsibility to disappear, and QA is exactly the function where you can least afford that.
Regards,Victoria -
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