Kevin Surace on The Future of Generative AI and QA Testing | Ep 270 | DevReady Podcast

·50 min·3 clips

$120 billion a year is spent on end-to-end testing, and less than a billion goes to technology.

Kevin opens after Anthony admits a LinkedIn profile will not really cover the story. Kevin gives the short version: he was tied to early voice AI at General Magic, so the assistant tools getting attention now come with a lot of history. The tone stays loose. Kevin jokes that he gets blamed for plenty these days, especially as AI assistants replace or augment offshore customer support work. That tension sits under the whole conversation: AI is not just a headline, it changes staffing, cost, and day to day operations. QA becomes the useful test case. Kevin talks about a platform where tests can be run, adjusted, and run again fast enough that turnaround time becomes the thing to notice. He is direct about automation. Recorder tools with copilots, he says, are not the same as systems that write scripts and create new test cases. That difference matters when teams are buying tools. His wider point is simple: a weak model does not prove the stronger version is fantasy. If one model invents references, the lesson may be that the vendor is wrong, not that the job cannot be done. He applies the same thinking to QA automation. Some companies may never solve fully autonomous scripting because their products and incentives were built for another route. The Wipro and Tata example makes it plain. Kevin says a vendor in the recorder space would not offer fully autonomous scripting because more tool complexity meant more hourly labor. That turns a technical discussion into a business warning. Service models can slow down tools that would reduce service work. Anthony keeps the conversation practical and aware of time. The ending feels like a founder chat with more left in it, with Kevin sending listeners to his website and LinkedIn instead of forcing a tidy final slogan.

As heard by us

AI test generation, labor economics, and a pointed look at where QA is headed.

Kevin Surace treats software testing as a question of labor, speed, and who gets paid when AI starts writing the work. He traces the path from General Magic and early voice AI to the present, then makes the case that autonomous test generation already exists and can write tests…

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Why you'd press play

You want a blunt take on AI that writes tests, not just flashy demos.

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