Prosecution Insights
Last updated: October 25, 2026
Application No. 19/261,533

AUTOMATED CONTENT CREATION AND CONTENT SERVICES FOR COLLABORATION PLATFORMS

Final Rejection §103
Filed
Jul 07, 2025
Priority
Jun 28, 2023 — provisional 63/523,909 +3 more
Examiner
LE, HUNG D
Art Unit
2161
Tech Center
2100 — Computer Architecture & Software
Assignee
Atlassian US Inc.
OA Round
2 (Final)
90%
Grant Probability
Favorable
3-4
OA Rounds
1y 0m
Est. Remaining
96%
With Interview

Examiner Intelligence

Grants 90% — above average
90%
Career Allowance Rate
990 granted / 1099 resolved
+35.1% vs TC avg
Moderate +6% lift
Without
With
+6.4%
Interview Lift
resolved cases with interview
Typical timeline
2y 4m
Avg Prosecution
23 currently pending
Career history
1127
Total Applications
across all art units

Statute-Specific Performance

§101
13.8%
-26.2% vs TC avg
§103
41.3%
+1.3% vs TC avg
§102
20.6%
-19.4% vs TC avg
§112
8.3%
-31.7% vs TC avg
Black line = Tech Center average estimate • Based on career data from 1099 resolved cases

Office Action

§103
Notice of Pre-AIA or AIA Status The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . DETAILED ACTION 1. This Office Action is in response to the amendment filed on 08/06/2026. Claim 1 has been amended. Claims 2-20 have been canceled. Claims 21-39 have been added. Claims 1 and 21-39 are pending. Response to Arguments 2. Applicant's arguments with respect to claims 1 and 21-39 have been considered but are moot in view of the new ground(s) of rejection. Examiner's Note 3. Issue tracking (According to Google): “Issue tracking is the formal process of documenting, prioritizing, assigning, and resolving problems, tasks, or bug reports within a project or organization. Teams typically manage this workflow using dedicated Issue Tracking Software or ticketing systems. How the Issue Tracking Process Works: (1) Creation: A user, customer, or automated system reports a problem, which generates a unique ticket or record. (2) Categorization and Assignment: The system prioritizes the issue and assigns it to a specific team member based on urgency and expertise. (3) Status Tracking: The ticket moves through lifecycle stages—such as Open, In Progress, Resolved, and Closed—providing real-time visibility. (4) Collaboration and History: Team members add comments, logs, and files directly to the ticket, keeping a clear historical record of all changes. Common Use Cases: (1) Software Bugs: Tracking technical defects and errors found during development or QA testing. (2) IT and Customer Support: Managing user requests, service tickets, and customer complaints. (3) Project Management: Monitoring action items, milestones, and feedback across teams.” Initiating a query to a directory platform (According to Google): "Initiating a query to a directory platform refers to the act of submitting a request to a directory service (such as Microsoft Active Directory, LDAP, or an enterprise identity store) to search for, retrieve, or update information about users, devices, or network resources. This process involves defining specific criteria-often using Lightweight Directory Access Protocol (LDAP) syntax-to narrow down the results from a hierarchical data structure." A query prompt (According to Google): "A query prompt is a user-input mechanism, typically in databases or reporting tools, that allows a user to define filter criteria at the moment a report, query, or print job is run. Instead of hardcoding values (e.g., "show sales for January"), a query prompt acts as a placeholder that asks the user to input specific criteria (e.g., "Enter Month") each time the query runs." A generative output engine (According to Google): "A generative output engine (often referred to as a generative AI system, model, or engine) is a type of artificial intelligence designed to create new, original content-such as text, images, audio, video, or software code-by learning patterns from massive datasets. Unlike traditional AI, which is designed to analyze, classify, or predict based on existing data, a generative engine produces fresh, novel outputs that resemble human-created work." The front end of a collaboration system (According to Google): "The front end of a collaboration system is the user-facing layer (client-side) of a digital platform designed to enable teams to work together, communicate, and coordinate tasks. It translates complex backend data and real- time updates into an intuitive Graphical User Interface (GUI), allowing users to view, edit, and interact with shared documents, calendars, messaging, and project management tools directly in a browser or application." Descriptive content (According to Google): "Descriptive content is the information, text, images, or audio that defines, explains, or represents a subject. It acts as the core substance of digital media, literature, or objects, serving to inform or provide meaning. Key examples include website articles, product descriptions, video content, and metadata that describes what an item or media represents." A directory entry (According to Google): "A directory entry is a data structure in a file system that associates a filename with its corresponding file metadata (such as location, inode number, and permissions). It acts as a mapping table to locate file data on a disk, with entries typically including the name, file type, and attributes, serving as a roadmap for organizing files in directories." Are web pages, videos, images, documents or files belonging to directory entries (According to Google): "Yes, webpages, images, and videos on a website are generally stored as files within a directory structure on a server, and they correspond to directory entries within that server's filesystem." A window interface element (According to Google): "A window interface element is a fundamental graphical control element in computing that provides a distinct, usually rectangular, area on a screen to display application content, data, or user interface components. It serves as a container that isolates a program's visual output and interactions from the main system or other applications, allowing for multitasking through features such as moving, resizing, closing, and overlapping." User-generated content (According to Google): "User-generated content (UGC) is any form of content-including images, videos, reviews, blog posts, and social media updates-created voluntarily by customers or fans rather than by the brand itself. It serves as authentic, trustworthy social proof, acting as modern word-of-mouth to influence purchasing decisions." Causing display of a window interface proximate to the word in the graphical user interface (According to Google): "Causing display of a window interface proximate to the word in the graphical user interface" refers to a contextual action where a software program generates a pop-up, menu, dialog box, or tooltip immediately adjacent to a specific piece of text or icon that a user has interacted with (e.g., clicked, hovered, or selected). This technique is a core part of Direct Manipulation User Interfaces (DMUI), allowing users to immediately manipulate or get information about a specific element without navigating to a main menu." Badr et al, US 20260057022, [Badr: Abstract and paragraphs 2 and 4 ("the suggestions may be mere reiterations of past queries or associated with last viewed content. Techniques that provide trend based suggestions may fail to provide tailored suggestions and the suggested query may lead to an imundation of results that are to be navigated to and reviewed to determine why the topic is trending. ", i.e., "query and content suggestion" - 'selectable control' and query issued by users = 'frontend of a collaboration system')] [Badr: Paragraph 8 ("the data descriptive of the change event with the generative model to generate the one or more query suggestions can be performed in response to determining, by the computing system, the change event is associated with the one or more particular topics", i.e., "generative model to generate the one or more query suggestions" = 'generative')] [Badr: Paragraph 8 ("data descriptive of the second change event with the generative model to generate one or more second query suggestions")] [Badr: Paragraph 9 ("a selection of at least one of the one or more query suggestions or the change event summary and providing, by the computing system, a search results interface for display. The search results interface can include a plurality of search results responsive to a search query associated with the one or more query suggestions. The plurality of search results can include the one or more web resources. In some implementations, the method can include receiving, by the computing system, a selection of at least one of the one or more query suggestions or the change event summary and providing, by the computing system, a model-generated content item for display. The model-generated content item can be generated with the generative model. ")] [Badr: Paragraphs 29 and 31 ("In some implementations, the web resources can be processed with the generative model to generate a change event summary. The change event summary can summarize what has changed as outlined by the web resources. The change event summary can include a topic overview, an indicator of what has changed, and/or what effect that change has. The query with the web resource(s) and/or the change event summary can be provided to a user as a query suggestion with a preview of the answer to the question posed by the query" AND "Once a trend and/or change is detected, a generative model can generate a suggested query (e.g., a suggested question) and may process a plurality of search results of the query to generate a summary that can be provided with the query suggestion", i.e., "change event summary" or "a preview of the answer" or query results = 'a generative response from the external generative output engine'; "a trend and/or change is decteced" = generating 'predefined query prompt text designating a proposed action; "a summary" = 'at least a portion of the extracted description content from the directory entry ')]. Adada et al, US 20240256618, [Adada: Abstract ("The acts include generating a prompt that is to be input to a generative language model. The prompt includes conversational input set forth by a user. The acts further comprise providing the prompt as input to the generative language model, and receiving conversational output from the generative language model, where the generative language model generated the conversational output based upon the prompt")] [Adada: Paragraph 164 ("the method further comprises providing supplemental content related to the conversational output for display on a dynamically updatable display pane on the computing device. ")]. Manavoglu et al, US 20240256757, [Manavoglu: Abstract ("The acts include providing a prompt to a generative language model, where the generative language model generales output based upon the prompt, identifies text in the output that is to be associated with a supplemental content item, and assigning a hyperlink to the text in the output. Upon the hyperlink being selected or hovered over, the supplemental content item is displayed")]. Piagentini et al, US 20230065188, [Piagentini: Abstract (“automatic support service that includes receiving a request for additional assistance for an error from a user interface, retrieving error information from a logging system for the error, generating an error information collection interface, in response to the request, populating the error information collection interface with the error information from the logging system, sending the error information collection interface to be displayed to the user by the user interface, and receiving additional error information from the user via the error information collection interface”, i.e., ‘automatic issue creation in an issue tracking platform’)] [Piagentini: Figures 4-7 and paragraphs 11 and 15 (“FIG. 7 is a diagram of one embodiment of a ticket initiation interface for a user”, i.e., ‘a frontend of a collaboration system’ and “The user can complete the ticket and submit the ticket to the support team” i.e., ‘user-generated content’)] [Piagentini: Paragraphs 29 and 38 (“the automated support service backend 121 to pre-populate a new support tick for the user so the user can review and submit with minimal additional work in most cases”, i.e., ‘user input … to a text fragment’)] [Piagentini: Figure 6C and Figure 7 and paragraph 43 (“The user can be shown this interface to confirm that a ticket submission is requested in response to the request for additional information. If the user requests to submit a support ticket, then this request can result in the receiving and display of the example interface of FIG. 8.”, ‘selectable link to the new issue record’ and ‘overlapping’)] [Piagentini: Paragraph 42 (“When the user has completed updating and reviewing the support ticket interface, then the user can input a submission request or similarly interact with the support ticket interface to request a submission to the support team (Block 223). The automated support service UI component can then forward the collected error information, completed support service ticket, and similar information to the automated support service backend. The submitted information can include the pre-populated information and further attachments such as a HAR file”, i.e., ‘predefine query prompt’)] [Piagentini: Paragraphs 27 and 30 (“The knowledge base API 113 enables queries for the knowledge base 125 to identify and retrieve knowledge based articles. The knowledge base API 113 can provide support for structured queries, full text searches,” i.e., ‘API endpoint’)]. Claim Rejections - 35 USC § 103 4. In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status. 5. The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action: A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made. 6. Claims 1, 21-24, 26 and 29-38 are rejected under 35 U.S.C. 103 as being unpatentable over Piagentini et al (US 20230065188), in view Bar-on et al (US 20200210439). Claim 1: Piagentini suggests a computer-implemented method for automatic issue creation in an issue tracking platform [Piagentini: Abstract (“automatic support service that includes receiving a request for additional assistance for an error from a user interface, retrieving error information from a logging system for the error, generating an error information collection interface, in response to the request, populating the error information collection interface with the error information from the logging system, sending the error information collection interface to be displayed to the user by the user interface, and receiving additional error information from the user via the error information collection interface”, i.e., ‘automatic issue creation in an issue tracking platform’)], comprising: cause display of a graphical user interface of a frontend of a collaboration system on a display of a client device, the graphical user interface comprising a content region including user-generated content of an electronic document [Piagentini: Figures 4-7 and paragraphs 11 and 15 (“FIG. 7 is a diagram of one embodiment of a ticket initiation interface for a user”, i.e., ‘a frontend of a collaboration system’ and “The user can complete the ticket and submit the ticket to the support team” i.e., ‘user-generated content’)]. Piagentini suggests in response to a user input provided with respect to a text fragment in for a proposed action associated with issue creation [Piagentini: Paragraphs 29 and 38 (“the automated support service backend 121 to pre-populate a new support tick for the user so the user can review and submit with minimal additional work in most cases”, i.e., ‘user input … to a text fragment’)]. Piagentini suggests the [[a]] proposed action; and at least a portion of the text fragment [Piagentini: Paragraph 42 (“When the user has completed updating and reviewing the support ticket interface, then the user can input a submission request or similarly interact with the support ticket interface to request a submission to the support team (Block 223). The automated support service UI component can then forward the collected error information, completed support service ticket, and similar information to the automated support service backend. The submitted information can include the pre-populated information and further attachments such as a HAR file”, i.e., ‘predefine query prompt’)]. Piagentini suggests providing the service query content item [[prompt]] to an external generative output engine Piagentini suggests obtaining a generative response from the external generative output engine, the generative response including a set of field values for a new issue [Piagentini: Paragraphs 18 and 29 (“reducing the frequency of support ticket generation by users where they are facing a known issue even if it is a very new issue”)] [Piagentini: Paragraph 60 (“Industry-specific; Artificial intelligence (AI); Application marketplace (“app store”); Data modeling; Security; and Identity and access management (IAM)”)]. [Piagentini: Paragraphs 18 and 29 (“reducing the frequency of support ticket generation by users where they are facing a known issue even if it is a very new issue”)]. Piagentini suggests transmitting a request to an API endpoint of the issue tracking platform, the request including set of field values [Piagentini: Paragraphs 27 and 30 (“The knowledge base API 113 enables queries for the knowledge base 125 to identify and retrieve knowledge based articles. The knowledge base API 113 can provide support for structured queries, full text searches,” i.e., ‘API endpoint’)]. Piagentini suggests receiving an API response indicating creation of a new issue record. Piagentini suggests causing display of a selectable link to the new issue record in a window interface element proximate to the text fragment [[word]] in the graphical user interface, the[Piagentini: Figure 6C and Figure 7 and paragraph 43 (“The user can be shown this interface to confirm that a ticket submission is requested in response to the request for additional information. If the user requests to submit a support ticket, then this request can result in the receiving and display of the example interface of FIG. 8.”, ‘selectable link to the new issue record’ and ‘overlapping’)]. Bar-on suggests obtaining a generative response from the external generative output engine, the generative response including a set of field values for a new issue [Bar-on: Paragraphs 66 and 80 (“he recommendation includes a suggestion to create a new issue request having a particular title or subject matter”)] [Bar-on: Paragraph 70 (“in particular the predictive model server 108 of the issue tracking system 100, can be configured to leverage, utilize, or employ any suitable pattern recognition or classification algorithm, probabilistic model, machine learning technique (whether trained or untrained), artificial intelligence method”)]. Both references (Piagentini and Bar-on) taught features that were directed to analogous art and they were directed to the same field of endeavor, such as data processing. It would have been obvious to one of ordinary skill in the art at the time the invention was made, having the teachings of Piagentini and Bar-on before him/her, to modify the system of Piagentini with the teaching of Bar-on in order to process data using a machine learning model [Bar-on: Paragraphs 66, 70 and 80]. Claim 21: The combined teachings of Piagentini and Bar-on suggest wherein the predefined prompt text designates field name context for a title, a description, a state, and an assignee of the new issue record [Piagentini: Paragraph 42 (“When the user has completed updating and reviewing the support ticket interface, then the user can input a submission request or similarly interact with the support ticket interface to request a submission to the support team (Block 223). The automated support service UI component can then forward the collected error information, completed support service ticket, and similar information to the automated support service backend. The submitted information can include the pre-populated information and further attachments such as a HAR file”, i.e., ‘predefine query prompt’)]; the set of field values comprises a title value, a description value, a state value, and an assignee value, each field value of the set of field values corresponding to a respective field of the new issue record [Piagentini: Paragraph 42 (“When the user has completed updating and reviewing the support ticket interface, then the user can input a submission request or similarly interact with the support ticket interface to request a submission to the support team (Block 223). The automated support service UI component can then forward the collected error information, completed support service ticket, and similar information to the automated support service backend. The submitted information can include the pre-populated information and further attachments such as a HAR file”, i.e., ‘predefine query prompt’)];; the structured data request body is transmitted to the API endpoint of the issue tracking platform as part of the request; and the API endpoint of the issue tracking platform is configured to cause creation of the new issue record in a project of the issue tracking platform using the set of field values [Piagentini: Paragraphs 27 and 30 (“The knowledge base API 113 enables queries for the knowledge base 125 to identify and retrieve knowledge based articles. The knowledge base API 113 can provide support for structured queries, full text searches,” i.e., ‘API endpoint’)]. Bar-on suggests the set of field values is inserted into a structured data request body formatted according to a JavaScript Object Notation ("JSON") format [Bar-on: Paragraph 122 (“In other examples, the issue request can take the form of a formatted (e.g., JavaScript object notation or extensible markup language and the like) file transmitted from a client device or a client application to a host service”)]. Both references (Piagentini and Bar-on) taught features that were directed to analogous art and they were directed to the same field of endeavor, such as data processing. It would have been obvious to one of ordinary skill in the art at the time the invention was made, having the teachings of Piagentini and Bar-on before him/her, to modify the system of Piagentini with the teaching of Bar-on in order to process data using JSON format [Bar-on: Paragraph 122]. Claim 22: The combined teachings of Piagentini and Bar-on suggest wherein the set of field values includes a title value and a description value for the new issue record [Piagentini: Paragraph 29 (“pre-populate a new support tick for the user so the user can review and submit with minimal additional work in most cases”)]. Claim 23: The combined teachings of Piagentini and Bar-on suggest storing the selectable link as supplemental content associated with the text fragment [Piagentini: Paragraphs 32, 36 and 37 (“a link labeled ‘learn more’ is included and can be utilized to activate the support service UI component, which will initiate a knowledge base query”)]. Claim 24: The combined teachings of Piagentini and Bar-on suggest wherein the request includes a project identifier associated with the new issue record [Bar-on: Paragraphs 11, 17, 27 and 76 (“associated with a project, and identifying the seed issue records” ; “project name; issue type; a name or identity”)]. Both references (Piagentini and Bar-on) taught features that were directed to analogous art and they were directed to the same field of endeavor, such as data processing. It would have been obvious to one of ordinary skill in the art at the time the invention was made, having the teachings of Piagentini and Bar-on before him/her, to modify the system of Piagentini with the teaching of Bar-on in order to identify a project [Bar-on: Paragraph 76]. Claim 26: The combined teachings of Piagentini and Bar-on suggest wherein the window interface element is rendered as a floating window overlaying a portion of the content region [Piagentini: Figure 6C and Figure 7 and paragraph 43 (“The user can be shown this interface to confirm that a ticket submission is requested in response to the request for additional information. If the user requests to submit a support ticket, then this request can result in the receiving and display of the example interface of FIG. 8.”, ‘selectable link to the new issue record’ and ‘overlapping’)]. Claim 29: Claim 29 is essentially the same as claim 1 except that it sets forth the claimed invention as a system rather than a method and rejected under the same reasons as applied above. Claim 30: The combined teachings of Piagentini and Bar-on suggest wherein the selectable control is displayed within an overlay user interface rendered over the content region [Piagentini: Figure 6C and Figure 7 and paragraph 43 (“The user can be shown this interface to confirm that a ticket submission is requested in response to the request for additional information. If the user requests to submit a support ticket, then this request can result in the receiving and display of the example interface of FIG. 8.”, ‘selectable link to the new issue record’ and ‘overlapping’)] [Piagentini: Paragraph 29 (“pre-populate a new support tick for the user so the user can review and submit with minimal additional work in most cases”)]. Claim 31: The combined teachings of Piagentini and Bar-on suggest wherein the proposed action corresponds to a content modification action selected from a set of content modification actions [Piagentini: Figure 6C and Figure 7 and paragraph 43 (“The user can be shown this interface to confirm that a ticket submission is requested in response to the request for additional information. If the user requests to submit a support ticket, then this request can result in the receiving and display of the example interface of FIG. 8.”, ‘selectable link to the new issue record’ and ‘overlapping’)] [Piagentini: Paragraph 29 (“pre-populate a new support tick for the user so the user can review and submit with minimal additional work in most cases”)]. Claim 32: The combined teachings of Piagentini and Bar-on suggest wherein the generative output engine is communicably coupled to the system through an application programming interface [Piagentini: Paragraphs 27 and 30 (“The knowledge base API 113 enables queries for the knowledge base 125 to identify and retrieve knowledge based articles. The knowledge base API 113 can provide support for structured queries, full text searches,” i.e., ‘API endpoint’)]. Claim 33: The combined teachings of Piagentini and Bar-on suggest wherein the generative response is formatted according to a structured data format [Piagentini: Paragraphs 27 and 62 (“The knowledge base API 113 can provide support for structured queries,”)]. Claim 34: The combined teachings of Piagentini and Bar-on suggest wherein the instructions cause the system to authenticate the user selection before providing the service query content item [Piagentini: Paragraph 15 (“The user can complete the ticket and submit the ticket to the support team along with the collected and pre-populated error information. The automated support service can also send notifications to the support team upon initial request for information about the error as well as upon submission of the ticket”)] [Piagentini: Paragraphs 27 and 62 (“The knowledge base API 113 can provide support for structured queries,”)]. Claim 35: The combined teachings of Piagentini and Bar-on suggest wherein the API endpoint causes the issue tracking platform to create the new issue record in a particular project [Piagentini: Paragraphs 27 and 62 (“The knowledge base API 113 can provide support for structured queries,”)] [Piagentini: Paragraphs 27 and 30 (“The knowledge base API 113 enables queries for the knowledge base 125 to identify and retrieve knowledge based articles. The knowledge base API 113 can provide support for structured queries, full text searches,” i.e., ‘API endpoint’)]. . Claim 36: The combined teachings of Piagentini and Bar-on suggest wherein the window interface element includes a content summary generated by the generative output engine [Bar-on: Paragraphs 43 and 116 (“Data extracted from such issue records that can be consumed by the predictive model server 108 to train and/or define one or more operations of the predictive model server 108 can include, but may not be limited to: issue title; issue description; issue summary; issue links; issue relationships”)]. Both references (Piagentini and Bar-on) taught features that were directed to analogous art and they were directed to the same field of endeavor, such as data processing. It would have been obvious to one of ordinary skill in the art at the time the invention was made, having the teachings of Piagentini and Bar-on before him/her, to modify the system of Piagentini with the teaching of Bar-on in order to implement data summarization [Bar-on: Paragraphs 43 and 116]. . Claim 37: The combined teachings of Piagentini and Bar-on suggest wherein the predefined prompt text is retrieved from a database of preconfigured [Piagentini: Paragraph 15 (“The user can complete the ticket and submit the ticket to the support team along with the collected and pre-populated error information. The automated support service can also send notifications to the support team upon initial request for information about the error as well as upon submission of the ticket”)]. Claim 38: Claim 38 is essentially the same as claim 1 and rejected under the same reasons as applied above. 7. Claim 25 is rejected under 35 U.S.C. 103 as being unpatentable over Piagentini et al (US 20230065188), in view Bar-on et al (US 20200210439), and further in view of Ennis, JR. et al (US 20110004914). Claim 25: The combined teachings of Piagentini, Bar-on and Ennis suggest wherein the selectable control is displayed in response to a cursor hover input proximate to the text fragment [Ennis: Paragraph 45 (“Hovering over one of the circles below the issue graph causes a list of any new issues or any issues that were resolved during the corresponding time period to be displayed in a viewing window”)]. Three references (Piagentini, Bar-on and Ennis) taught features that were directed to analogous art and they were directed to the same field of endeavor, such as data processing. It would have been obvious to one of ordinary skill in the art at the time the invention was made, having the teachings of Piagentini, Bar-on and Ennis before him/her, to modify the system of Piagentini and Bar-on with the teaching of Ennis in order to enable hovering using a cursor [Ennis: Paragraph 45]. 8. Claim 27 is rejected under 35 U.S.C. 103 as being unpatentable over Piagentini et al (US 20230065188), in view Bar-on et al (US 20200210439), and further in view of Shah et al (US 20230334773). Claim 27: The combined teachings of Piagentini, Bar-on and Shah suggest wherein the generative response is generated using a large language model coupled to the generative output engine [Shah: Paragraph 7 (“providing the scripted prompt as input to a large language model (LLM) and outputting, with the LLM, the simulation scenario based on the contextual information in the scripted promp”)] [Shah: Paragraph 78 (“In some embodiments, the simulation module 204 includes multiple machine-learning models. A first machine-learning model may receive as input the scripted prompt and one or more 3D digital twins and output the simulation scenario. A second machine-learning model may receive the simulation scenario or digital media and style-reference media as input and output stylized digital media that blends the simulation scenario or digital media with the style-reference media. In some embodiments, the first machine-learning model is an LLM and the second machine-learning model is a style transfer machine-learning model.”)]. Three references (Piagentini, Bar-on and Shah) taught features that were directed to analogous art and they were directed to the same field of endeavor, such as data processing. It would have been obvious to one of ordinary skill in the art at the time the invention was made, having the teachings of Piagentini, Bar-on and Shah before him/her, to modify the system of Piagentini and Bar-on with the teaching of Shah in order to implement multiple machine learning models including large language model [Shah: Paragraphs 7 and 78]. 9. Claims 28 and 39 are rejected under 35 U.S.C. 103 as being unpatentable over Piagentini et al (US 20230065188), in view Bar-on et al (US 20200210439), and further in view of Carlson et al (US 20040199762). Claim 27: The combined teachings of Piagentini, Bar-on and Carlson suggest wherein the selectable link is selectable to cause redirection of the graphical user interface to an issue view of the new issue [Carlson: Paragraph 40 (“When the user selects one of these links … The new, encrypted URL is returned to the browser via a redirect procedure. This return of the URL will tell the browser to issue a new request using the new, encrypted URL. This URL return can alternatively be done by returning a page to the browser with a link to the resource using the new URL along with or without a message”)]. Three references (Piagentini, Bar-on and Carlson) taught features that were directed to analogous art and they were directed to the same field of endeavor, such as data processing. It would have been obvious to one of ordinary skill in the art at the time the invention was made, having the teachings of Piagentini, Bar-on and Carlson before him/her, to modify the system of Piagentini and Bar-on with the teaching of Carlson in order to implement data redirection [Carlson: Paragraph 40]. Claim 39: Claim 39 is essentially the same as claim 28 and rejected under the same reasons as applied above. Conclusion 10. Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a). A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any extension fee pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the date of this final action. 11. Any inquiry concerning this communication or earlier communications from the examiner should be directed to [Hung D. Le], whose telephone number is [571-270-1404]. The examiner can normally be communicated on [Monday to Friday: 9:00 A.M. to 5:00 P.M.]. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Apu Mofiz can be reached on [571-272-4080]. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see http://pair-direct.uspto.gov. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, contact [800-786-9199 (IN USA OR CANADA) or 571-272-1000]. Hung Le 09/22/2026 /HUNG D LE/Primary Examiner, Art Unit 2161
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Prosecution Timeline

Jul 07, 2025
Application Filed
May 06, 2026
Non-Final Rejection mailed — §103
Aug 06, 2026
Response Filed
Sep 24, 2026
Final Rejection mailed — §103 (current)

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Applications granted by this same examiner with similar technology

Patent 12769800
METHOD AND SYSTEM OF IDENTIFYING AND ALLOCATING SENTIMENT ATTRIBUTION
2y 4m to grant Granted Oct 20, 2026
Patent 12743447
READING COMPRESSED DATA DIRECTLY INTO AN IN-MEMORY STORE
1y 8m to grant Granted Sep 22, 2026
Patent 12724780
RECOVERY OF ROW DATA STORED VIA DIFFERENT STORAGE MECHANISMS
2y 1m to grant Granted Sep 01, 2026
Patent 12705279
DISPLAY APPARATUS, BACKGROUND MUSIC PROVIDING METHOD THEREOF AND BACKGROUND MUSIC PROVIDING SYSTEM
2y 6m to grant Granted Aug 11, 2026
Patent 12694009
TRACKING EVALUATION OF WORKLOAD STABILITY THROUGH PERFORMANCE INDEXING
2y 1m to grant Granted Jul 28, 2026
Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

3-4
Expected OA Rounds
90%
Grant Probability
96%
With Interview (+6.4%)
2y 4m (~1y 0m remaining)
Median Time to Grant
Moderate
PTA Risk
Based on 1099 resolved cases by this examiner. Grant probability derived from career allowance rate.

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