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This week our conversation is with my friend John Rogitz, who is the managing patent attorney at Rogitz & Associates. John is a second generation patent attorney with more than 15 years worth of experience. He and his form work primarily in the software space, representing some of the largest video game companies in the world, which allows him to work not only on video games, but also on virtual and augmented reality technologies as well. And John also represents both well-established, large entities and start-up companies, with much of the rest of his work relating to Artificial Intelligence and Machine Learning. And in addition to his role managing the firm’s day-to-day operations, John also finds time to serve on the Executive Committee of the IP Section of the California Lawyers Association, teach as an adjunct professor at Trinity Law School, and occasionally write for us at IPWatchdog.com.

Being one of the more thoughtful patent practitioners I know, and someone who has auditioned numerous available AI tools for practitioners, I invited John to join my last intro to patent practice class to discuss prosecution strategy with my students this summer. While he was in town for that purpose we recorded this podcast. Not surprisingly, our conversation heavily focused on all-things software, both from the perspective of a technologist and the perspective of a patent professional searching, drafting and ultimately working with patent examiners to get allowances. So, we spent time discussing both the 2019 patent eligibility guidance, as well as several of the more recent guidelines from the Patent Office, including the Office’s AI guidance. 

We also spent a good deal of time discussing obviousness, KSR, and how at least sometimes, perhaps even often depending on the wording of the rejection from the examiner, you really only need to argue a lack of teaching, suggestion and motivation to persuade examiners that the claims you seek are nonobvious and allowable.

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