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
This action is issued in response to Applicant’s amendment filed January 20, 2026.
Claims 1-20 are pending. No claim is added and none cancelled.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 1/23/2026 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Claim Rejections - 35 USC § 103
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 (i.e., changing from AIA to pre-AIA ) 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.
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.
Claim(s) 1-6 and 11-16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Goslin (U.S. Patent Application No. 2021/0081498) in view of Qin (U.S. Patent Application No. 2024/0346256), further in view of Williams (U.S. Patent Application No. 2024/0281410).
Regarding Claim 1, Goslin discloses a system comprising at least one processor operatively connected to a memory, the at least one processor when executing configured to:
generate and display an interactive session for managing interaction with at least a first artificial intelligence (“AI”) model (Fig.2; par [0028-0030], Goslin – GUI used to interact with an AI system configured to use machine learning to respond to users, wherein the user interacts with a scenario creator to select different aspects of the scenario. The options available for a given selection can depend on one or more selections);
accept a user input specifying at least some of a request to be processed by the first AI model (Fig.1; par [0023], Goslin – A user provides input to the AI system. The input includes natural language and may include text or audio speech data… par [0018] – the AI system may search for keywords in user input that have predefined associations);
accept specification of a context to evaluate or constrain output produced by the first AI model (par [0019], [0024-0026], Goslin – context of a given input is determined, the AI system selects a corresponding ML model to process the input, this allows each model to be specialized with a constrained context, while allowing the AI system to dynamically shift between contexts… a given context (i.e., combination of role, means, and objective) is determined and a corresponding response is generated); and
optimize generation of a final output of the first AI model to communicate and present in a user interface displaying the interactive session (par [0021], [0025-0026], Goslin – in order to improve responses and user-engagement, the learning system can provide differing responses to different users… par [0051] – Interactivity application generates a response using the identified and selected ML model, by processing the input with the selected ML model and processes the result with the ML model. The response is dynamically generated and the response is returned to the user by displaying it on a screen or by outputting audio).
While Goslin teaches processing a user input by an AI model and accepting a context. However, Goslin is not as detailed as the examiner would like with respect to generate a modification or update or augmentation of an input to the first AI model based on context information associated with the specified context or select a version of the first AI model associated with the specified context or select a curator agent associated with the specified context.
On the other hand, Qin discloses generate a modification or update or augmentation of an input to the first AI model based on context information associated with the specified context (par [0018-0019], [0022-0028], Qin - augmented prompt includes context, content, and question; wherein the augmented prompt with retrieved augmentation information may improve the accuracy of responses) or select a version of the first AI model associated with the specified context or select a curator agent associated with the specified context.
Goslin and Qin are from the same field of endeavor of AI based response generation. It would have been obvious to one or ordinary skill in the art before the effective filing date of the claimed invention to incorporate Qin’s augmented artificial intelligence teachings into the Goslin system. A skilled artisan would have been motivated to combine in order to provide more relevant and accurate responses from AIs, thus improving the spoke and precision.
While both Goslin and Qin teach receiving a request/query; however, Goslin and Qin are not as detailed with respect to the request indicating at least one data source and a data management operation to be executed by the at least one processor to retrieve data from the at least one data source.
On the other hand, Williams discloses the request indicating at least one data source and a data management operation to be executed by the at least one processor to retrieve data from the at least one data source (par [0487-0489], [0494-0495], Williams – user may request a report to view sales related to vehicles by color or model; wherein a primary data source is selected (and either zero or more secondary data sources) to request and produce a report that may visualize properties and events that relate to vehicles… there are operations associated with the request such as pre-query data operations, query database operations, and post query database operations that are used to retrieve the associated results of the request … Further details about the request indicating a selected data source(s) and operations associated therewith can be found at par [0502-0504] and [0514-0515], [0682], Williams)1.
It would have been obvious to one or ordinary skill in the art before the effective filing date of the claimed invention to incorporate Williams’ teachings into the Goslin and Qin system. A skilled artisan would have been motivated to combine in order to provide the ability to manage and analyze the users’ needs to more effectively benefit the user. Thus, improving the functioning of computer systems, information networks, data stores, and search engines.
Regarding Claim 2, the combination of Goslin in view of Qin, further in view of Williams, disclose the system of claim 1, wherein the at least one processor is configured to display, as part of the interactive session, information describing the specified context which can optionally include display options for available contexts that modify outputs produced by the first AI model (Fig.2; par [0028-0029], [0049], Goslin – context corresponds to a role-playing scenario and includes details inferred by the context).
Regarding Claim 3, the combination of Goslin in view of Qin, further in view of Williams, disclose the system of claim 1, wherein the at least one processor is configured to display a plurality of default contexts and description of an effect on the output each respective default induces (par [0042], [0049-0051], Goslin – Interactivity Application generates a confidence in the determination of the context and responses generated based on the shifting scenario).
Regarding Claim 4, the combination of Goslin in view of Qin, further in view of Williams, disclose the system of claims 1, wherein the at least one processor is configured to display a plurality of outputs associated with the user input specifying at least some of the request, each output associated with a respective context, description of the context, in displays for evaluating empirically changes in output based on the described context (par [0014], [0047-0048], [0051], Goslin - generates responses using one or more ML models that correspond to that context. The AI system can dynamically select ML models as the context of the interaction shifts, in order to continue to provide deep conversation.).
Regarding Claim 5, the combination of Goslin in view of Qin, further in view of Williams, disclose the system of claim 1, wherein the at least one processor is configured to accept a user input specifying the context (Fig.2; par [0024], [0028-0030], Goslin – AI system determines the context of the user input, wherein examples of the context can be a combination of role, means, and objective).
Regarding Claim 6, the combination of Goslin in view of Qin, further in view of Williams, disclose the system of claim 1, wherein the at least one processor is configured to automatically define the context (par [0031-0032], Goslin – system generates suggested scenarios).
Claims 11-16 contain similar subject matter as claims 1-6 above; and are rejected under the same rationale.
Claim(s) 7-10 and 17-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Goslin in view of Qin; further in view of Williams, and further in view of Hatfield (U.S. Patent Application No. 2023/0297914).
Regarding Claim 7, the combination of Goslin in view of Qin, further in view of Williams, disclose the system of claim 1, wherein the at least one processor is configured to generate workflow steps of the first AI model to communicate and present in the user interface displaying the interactive session (par [0023-0024], Goslin – a workflow for interactivity with an AI system configured to use machine learning to interact with users… par [0033]).
However, Goslin is not as detailed with respect to generate workflow steps as part of the generation of the final output.
On the other hand, Hatfield discloses generate workflow steps as part of the generation of the final output (par [0122-0123], Hatfield - the method can include the input at block back into the artificial intelligence models the ranked list of intelligent workflows that were established for analyzing the inputs from block for the current assessment of the workflow. Additionally, the input can be optimized workflows from the same industry and use cases at block. More specifically, at block the input can be the ranked list of intelligent workflows with the identified attributes, augmented steps and activity lists; the third round of input can be take the outputs from blocks 302 and 305, and derive, optimize and associate the intelligent workflow steps… par [0127-0129] - user feedback on the intelligent workflow is analyzed as to whether the experience is suitable or needs additional refinement; if workflow is not acceptable then adjustments are made until user confirms suitability of the intelligent workflow).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Hatfield’s teachings into the Goslin, Qin, and Williams system. A skilled artisan would have been motivated to combine in order to better establish methods that capture, frame, and manage the user design experience around intelligent workflows; thus leading to optimized workflows.
Regarding Claim 8, the combination of Goslin in view of Qin, further in view of Williams, and further in view of Hatfield, disclose the system of claim 7, wherein the at least one processor is configured to modify or update or augment creation of respective workflow steps based at least in part on the context (Abstract and par [0025], Hatfield – AI is employed to assess a user’s workflow on a task that is expressed in a series of steps. The steps of the workflow are analyzed to identify areas of improvement. Augmentations may be generated from a plurality of technology fitments matched to the areas for improvement in the steps of the workflow).
Regarding Claim 9, the combination of Goslin in view of Qin, further in view of Williams, and further in view of Hatfield, disclose the system of claim 8, wherein the at least one processor is configured to modify or update or augment creation of respective workflow steps based at least in part on the context by generating additional inputs to any AI model configured to generate the respective workflow steps (par [0025], Hatfield - This intelligent system will be able to identify matching intelligent work flows (WFs) and for each IW augment the steps with additional activities collected from the environment, personas, industry and business cases).
Regarding Claim 10, the combination of Goslin in view of Qin, further in view of Williams, and further in view of Hatfield, disclose the system of claim 1, wherein the at least one processor is configured to employ definition of context to update an input provided to the first AI model to require generation of a threshold number of workflow steps (par [0019], [0024-0026], Goslin – context of a given input is determined, the AI system selects a corresponding ML model to process the input, this allows each model to be specialized with a constrained context, while allowing the AI system to dynamically shift between contexts… a given context (i.e., combination of role, means, and objective) is determined and a corresponding response is generated… par [0105], [0113], Hatfield).
Claims 17-20 contain similar subject matter as claims 7-10 above; and are rejected under the same rationale.
Response to Arguments
Applicant’s arguments with respect to the amended claim(s) have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Conclusion
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 nonprovisional extension fee (37 CFR 1.17(a)) 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 mailing date of this final action.
Points of Contact
Any inquiry concerning this communication or earlier communications from the examiner should be directed to CHELCIE L DAYE whose telephone number is (571) 272-3891. The examiner can normally be reached on Monday-Friday 7:30-4:00pm. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
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.
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Chelcie Daye
Patent Examiner
Technology Center 2100
February 18, 2026
/CHELCIE L DAYE/Primary Examiner, Art Unit 2161
1 Examiner Notes: Details about being executed by a processor can be found within Williams at par [0496].