Insights

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WURC vs. WORK: The Evidentiary Asymmetry Between § 101’s “Inventive Concept” and § 103’s Obviousness Framework 

On February 6, 2026, the Federal Circuit affirmed summary judgment of invalidity under 35 U.S.C. § 101 for all asserted claims across six patents in Innovaport LLC v. Target Corp., No. 24-1545 (Fed. Cir. Feb. 6, 2026) (nonprecedential). The patents claimed systems and methods for providing product location information within a retail store: receiving a customer’s query, searching a database containing product locations and related information, and returning results that included cross-referenced product suggestions. The court found the claims directed to the abstract idea of “collecting, analyzing, retrieving, and displaying information” at Alice step one, then concluded at step two that the additional elements added no “inventive concept.” 

Agentic Coding Is Draining Your Moat 

A practical way to refill it: inventions.md and fast (detailed!) provisional filings. 

In brief: 

Agentic coding collapses the time and capital advantages that used to protect early-stage software companies. When competitors can reach feature parity in days, “shipping faster” stops being a moat and becomes table stakes. 

One of the few levers you can pull early is intellectual property, but only if you capture inventions while you build. 

The simplest workflow I’ve found: instruct your coding agent to surface patentable technical ideas and log them in an inventions.md file, then file provisional patent applications quickly on the ideas that survive a rough patentability screen.

USPTO Leadership Reins in PTAB on AI Eligibility 

The USPTO’s decision in Ex parte Desjardins is good news for applicants in the AI and software spaces. The Appeals Review Panel (ARP), including newly appointed Director John Squires, overturned a Patent Trial and Appeal Board (PTAB) decision that had raised a new § 101 eligibility rejection.  

The PTAB had treated the claims as directed to a mathematical algorithm without integration into a practical application, but the ARP found they reflected concrete improvements in how an AI model functions. This matters beyond one case: the ARP emphasized that eligibility should not be denied merely because claims involve mathematical concepts, algorithms, or machine learning.