DETAILED ACTION
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 .
Response to Amendment
The amendments filed 06/15/2026 have been accepted and considered in this office action. Claims 1-20 have been amended. Claims 1-20 are pending.
Response to Arguments
Applicant’s arguments with respect to claim(s) 1-20 have been considered but are moot in view of new grounds of rejection necessitated by the applicant’s amendments to the claims.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim Rejections - 35 USC § 103
Claims 1-2, 4-6, 8-9, 11-13, 15-19 are rejected under 35 U.S.C. 103 as being unpatentable over Karri et al. (hereinafter Karri) (US 20250077559 A1) in view of Malleshaiah et al (hereinafter Malleshaiah) (US 20220278889 A1).
Regarding claim 1, Karri discloses:
A method comprising steps of:
receiving a request from a natural language conversational interface (Karri, P[0017], P[0019], Karri provides conversational planning user interface through which a common user submits a natural-language request to the common AI service)
analyzing the request with an artificial intelligence (Al) agent to determine an intent of the request, the intent indicating whether the request is to be processed using a knowledge base of the Al agent or using a playbook of a plurality of playbooks (Karri, P[0016]-P[0019], P[0026]-P[0027], teaches analyzing natural-language request with a common AI service/LLM to determine the user's intent and classify the request as either an atomic-agent call or execution of a stored recipe, with the system searching an agent library and recipe library to identify the appropriate processing path. The atomic agent path corresponds to direct AI-agent processing, while the recipe-execution path corresponds to processing using one of a plurality of stored playbooks/recipes); and
responsive to the intent indicating processing using a playbook, processing the request by the Al agent based on the intent, wherein the processing is performed based on a the playbook of a the plurality of playbooks, the playbook being selected from the plurality of playbooks based on the intent, the request, and one or more tools accessible to the Al agent, and the playbook including a series of predefined steps (Karri, P[0018]-P[0019], P[0021]-P[0030], P[0071]-P[0072], Karri interprets the user's intent/request, searches stored recipes, selects the appropriate recipe based on semantic relevance, maps workflow steps to agents form an agent library, and executes the selected recipe stepwise by invoking those agents.)
Karri does not explicitly disclose:
However, Malleshaiah discloses:
where the request relates to user experience associated with one or more users using a network to access services cloud services, the user experience being quantified based on telemetry obtained via inline monitoring of network traffic between the one or more users and the cloud services (Malleshaiah, P[0041], P[0088]-P[0090], P[0103], Malleshaiah monitors users accessing cloud applications/services, performs inline monitoring of traffic between users and cloud services, collects application/network/device-related user-experience metrics, and determines a UEX score from those collected metrics.);
for exploration of data associated with the user experience and reasoning over the data (Malleshaiah, P[0037]-P[0040], P[0117], analyzes digital user experience data including network, application, endpoint metrics, determines likely causes of poor UEX scores, and performs analysis over those UEX measurements).
It would have been obvious to combine Karri’s intent-based natural-language recipe selection and execution (Karri, Abstract) with Malleshaiah’s inline monitoring and quantified user-experience telemetry (Malleshaiah, Abstract) to process network/cloud user-experience requests using selected automated workflows.
Regarding claim 2, the combination of Karri and Malleshaiah discloses the method of claim 1.
The combination further discloses:
wherein the steps further comprise:
determining [[a]] the playbook of the plurality of playbooks to utilize in the processing y classifying the intent as complex based at least in part on the request requiring access to specific data associated with one or more entities, and selecting the playbook based on the intent and a context of the request (Karri, P[0026]-P[0030], P[0040]-P[0042], P[0074]-P[0075], The common AI service classifies a user's utterance as an atomic-agent call or recipe execution, interprets the user's intent, searches the recipe library, selects the best-matching recipe, and uses contextual information required parameters, and the user's query in selecting/executing the workflow. The system determines required input information, restricts access to particular data elements, dynamically collects required parameters, and uses specialized ERP and CRM data agents. "classifying the intent as complex" is read on Karri's classification of a request into recipe execution rather than an atomic-agent call, where recipe execution represents the multi-step/compound processing path requiring multiple agents data inputs).
Regarding claim 4, the combination of Karri and Malleshaiah discloses the method of claim 1.
The combination further discloses:
wherein the steps further comprise:
generating one or more playbooks based on a playbook generation lifecycle, wherein the playbook generation lifecycle includes creating a playbook in plain language, compiling the playbook in plain language into a directed acyclic graph of predefined macros, converting the directed acyclic graph into an executable playbook program, testing the executable playbook program, reviewing the playbook for approval, and delivering the reviewed playbook to a playbook registry (Karri, P[0015]-P[0025], P[0038]-P[0042], P[0070]-P[0077], teaches the claimed lifecycle substantially as a single reference. Karri receives a natural-language workflow description; decomposes the description into specific steps; identifies predefined atomic agents corresponding to those steps; generates a DAG whose nodes represent the identified agents; converts the natural language description into an executable workflow/control flow; presents the generated control flow/DAG to expert for review, validation, and modification; provides a dry-run mode to test the recipe before deployment; and, once finalized, registers/stores the recipe in the composite-action library/vector database. Karri's reusable atomic agents correspond to the claimed "predefined macros", since each DAG node invokes a predefined parameterized executable agent).
Regarding claim 5, the combination of Karri and Malleshaiah discloses the method of claim 4.
The combination further discloses:
wherein creating a playbook in plain language comprises generating a static playbook in plain language that lays out steps to be taken and one or more tools necessary to complete a task, and generating [[an]]the executable playbook program based thereon by compiling the static playbook into the directed acyclic graph of predefined macros and converting the directed acyclic graph into the executable playbook program (Karri, P[0015]-P[0023], P[0038]-P[0042], P[0070]-P[0072]) teaches generating a natural-language workflow description that specifies the steps/actions to be performed; determined atomic agents/tools needed for those steps; processing the natural language instructions to identify a sequence of actions; generating a DAG representing the workflow; and producing/executing the resulting recipe as an executable control flow. Thus, the natural-language workflow corresponds to the claimed static plain-language playbook, the identified atomic agents corresponds to the necessary tools/predefined macros, and the DAG/control flow corresponds to the executable playbook program generates from that description.).
Regarding claim 6, the combination of Karri and Malleshaiah discloses the method of claim 4.
The combination further discloses:
wherein testing a playbook comprises executing the executable playbook program in testing the playbook in a simulated environment (Karri, P[0025], P[0072], P[0076], Karri performs a dry-run execution of the recipe that simulates the workflow without modifying actual data and also executes recipes in a virtual sandboxes data container) with synthetic data and synthetic configurations representative of the network and the cloud services (Malleshaiah, P[0004]-P[0005], P[0097]-P[0099], P[0124-P[0126], P[0156]-P[0158], teaches synthetic transactions/network probes used as tests for application and services, synthetic measurements in in the context of network/cloud transactions, configurations and system/device/application metrics representative of the monitored cloud environment, and testing against historic cloud system data), and reverting the playbook to a static playbook creation stage of the playbook generation lifecycle responsive to the executable playbook program failing to operate as intended (Karri, P[0023]-P[0025], P[0039], teaches reviewing and modifying the generated workflow, followed by dry-run validation before it is made available to users).
Regarding claim 8, claim 8 recites the non-transitory computer-readable storage medium associated the method of claim 1 and is rejected for the same reasons as above.
Karri further discloses:
A non-transitory computer-readable storage medium having computer-readable code stored thereon for programming one or more processors to perform steps of (Karri, P[0034]):
Regarding claim 9, claim 9 recites the non-transitory computer-readable storage medium associated the method of claim 2 and is rejected for the same reasons as above.
Regarding claim 11, claim 11 recites the non-transitory computer-readable storage medium associated the method of claim 4 and is rejected for the same reasons as above.
Regarding claim 12, claim 12 recites the non-transitory computer-readable storage medium associated the method of claim 5 and is rejected for the same reasons as above.
Regarding claim 13, claim 13 recites the non-transitory computer-readable storage medium associated the method of claim 6 and is rejected for the same reasons as above.
Regarding claim 15, claim 15 recites the cloud-based system associated the method of claim 1 and is rejected for the same reasons as above.
Karri further discloses:
A cloud-based system comprising (Karri, P[0077]):
one or more processors (Karri, P[0077]); and
memory storing computer-executable instructions that, when executed, cause the one or more processors to (Karri, P[0077], P[0082]):
Regarding claim 16, claim 16 recites the cloud-based system associated the method of claim 2 and is rejected for the same reasons as above.
Regarding claim 17, claim 17 recites the cloud-based system associated the method of claim 4 and is rejected for the same reasons as above.
Regarding claim 18, claim 18 recites the cloud-based system associated the method of claim 5 and is rejected for the same reasons as above.
Regarding claim 19, claim 19 recites the cloud-based system associated the method of claim 6 and is rejected for the same reasons as above.
Claims 3 and 10 are rejected under 35 U.S.C. 103 as being unpatentable over Karri et al. (hereinafter Karri) (US 20250077559 A1) in view of Malleshaiah et al (hereinafter Malleshaiah) (US 20220278889 A1) in further view of Sharan et al (hereinafter Sharan) (US 20200175077 A1) and Forte et al. (hereinafter Forte) (US 20220210023 A1).
Regarding claim 3, the combination of Karri and Malleshaiah discloses the method of claim 1.
The combination does not explicitly disclose:
wherein the steps further comprise:
managing [[a]] the plurality of playbooks for processing requests, wherein the managing comprises maintaining a playbook quality tag for each of the plurality of playbooks, the playbook quality tag for a given playbook of the plurality of playbooks being assigned based on user feedback associated with prior responses generated by the given playbook, and wherein the processing of the request comprises selecting the playbook from the plurality of playbooks based at least in part on the playbook quality tag
However, Sharan discloses:
wherein the steps further comprise:
managing [[a]] the plurality of playbooks for processing requests, wherein the managing comprises maintaining a playbook quality tag for each of the plurality of playbooks (Sharan, P[0035]-P[0036], P[0053], Sharan stores and manages multiple playbooks, permits priority levels to be associated with playbooks, and provides a rating/comment system or playbook quality control)),
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Karri in view of Malleshaiah and Sharan. Doing so would have provided Sharan’s playbook rating/quality control functionality with Karri’s registered recipe library and Malleshaiah’s UEX processing to associate stored playbooks with quality indications for improved playbook management and selection.
Sharon does not explicitly disclose:
the playbook quality tag for a given playbook of the plurality of playbooks being assigned based on user feedback associated with prior responses generated by the given playbook, and wherein the processing of the request comprises selecting the playbook from the plurality of playbooks based at least in part on the playbook quality tag
However, Forte discloses:
the playbook quality tag for a given playbook of the plurality of playbooks being assigned based on user feedback associated with prior responses generated by the given playbook, and wherein the processing of the request comprises selecting the playbook from the plurality of playbooks based at least in part on the playbook quality tag (Forte, P[0010], P[0012], P[0027]-P[0035], P[0103]-P[0106], P[0173], Forte records prior user acceptance/rejection/customization of proposed playbooks, incorporates that feedback into numerical action relevance/weight, lowers future recommendation probability for rejected actions, increases treatment of manually selected actions, and uses the resulting scores/weights to determine later playbook recommendations).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Karri in view of Malleshaiah, Sharan, and Forte. Doing so would have provided Forte’s use of prior user feedback to adjust future palybook reccomendations with Sharan’s playbook rating/quality control functionality with Karri’s registered recipe library and Malleshaiah’s UEX processing to predictably use feedback derived quality information to improve subsequent playbook selection.
Regarding claim 10, claim 10 recites the non-transitory computer-readable storage medium associated the method of claim 3 and is rejected for the same reasons as above.
Claims 7, 14, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Karri et al. (hereinafter Karri) (US 20250077559 A1) in view of Malleshaiah et al (hereinafter Malleshaiah) (US 20220278889 A1) in further view of Sharan et al (hereinafter Sharan) (US 20200175077 A1).
Regarding claim 7, the combination of Karri and Malleshaiah discloses the method of claim 4.
The combination further discloses:
wherein delivering a playbook comprises registering the playbook to a playbook registry responsive to the reviewing of the playbook completing without comments, and wherein the playbook registry comprises the plurality of playbooks (Karri, P[0023]-P[0025], P[0039]-P[0040], P[0071], teaches presenting the generated recipe/DAG for expert review and modification, finalizing the recipe after review, and registering the finalized executable recipe into the composite-action library/vector database, which stores a plurality of recipes for subsequent retrieval execution. Thus, finalization following review corresponds to completion of review without further comments/modifications, followed by registration in the playbook registry.),
The combination does not explicitly disclose:
each playbook in the playbook registry being associated with a respective playbook quality tag assigned based on user feedback associated with prior responses generated by the respective playbook However, Sharon discloses:
each playbook in the playbook registry being associated with a respective playbook quality tag assigned based on user feedback associated with prior responses generated by the respective playbook (Sharan, P[0053], teaches associating stored/shared playbooks with a rating and comment system for playbook quality control, thus, teaching a respective quality indication associated with individual stored playbooks).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Karri in view of Malleshaiah and Sharan. Doing so would have provided Sharan’s playbook rating/quality control functionality with Karri’s registered recipe library and Malleshaiah’s UEX processing to associate stored playbooks with quality indications for improved playbook management and selection.
Regarding claim 14, claim 14 recites the non-transitory computer-readable storage medium associated the method of claim 7 and is rejected for the same reasons as above.
Regarding claim 20, claim 20 recites the cloud-based system associated the method of claim 7 and is rejected for the same reasons as above.
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SHASHIDHAR S MANOHARAN whose telephone number is (571)272-6772. The examiner can normally be reached M-F 8:00-4:00.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Andrew Flanders can be reached at 571-272-7516. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/SHASHIDHAR SHANKAR MANOHARAN/Examiner, Art Unit 2655
/ANDREW C FLANDERS/Supervisory Patent Examiner, Art Unit 2655
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