DETAILED ACTION
This office action is responsive to amendment filed on December 23, 2025 in this application Perey, U.S. Patent Application No. 18/507,646 (Filed November 13, 2023). Claims 1 - 20 were pending. Claims 1, 2, 8, and 16, are amended. Claims 1 – 20 are pending.
Applicants' arguments have been carefully and respectfully considered and found not persuasive. Accordingly, this action has been made FINAL.
Response to Arguments
1. With respect to Applicant’s argument on pgs. 9 - 10 of the Applicant’s Remarks (“Remarks”) stating that the amended independent claims recite a practical application, examiner respectfully disagrees. See infra § Claim Rejections - 35 USC §101. The argued “accessing” of content items is an additional element to the abstract idea and represents insignificant extra-solution data transmission rather than a practical application of the abstract idea. See MPEP 2106.05(g). The remaining determination steps are part of the abstract idea and do not recite details that meaningfully limit the performance such that they would be a practical application. It is noted that “artificial intelligence agents” are not claimed in the independent claims and are recited at such a high level that they represent mere instruction to apply the abstract idea to a computer.
Therefore, the current claims remain rejected under 35 USC 101.
2. With respect to Applicant’s argument on pgs. 10 - 12 of the Remarks stating that current art fails to teach the newly added limitations directed to contextual data, examiner respectfully disagrees. See infra § Claim Rejections - 35 USC §103 § Claim 1. However, Kirk teaches that the high-level objective is submitted by the client to a large language model along with additional operational constraints. Kirk at ¶¶ 0017, 0028, 0072, 0114 – 0116, and 0136 (high-level objective submission, constraints, sub-processes, execution). Under the broadest reasonable interpretation of “associated with the client device,” the operational constraints disclosed in Kirk as used to process the high-level objective by the LLM are contextual data “associated” with the client request for the objective.
Therefore, the current combination teaches the newly added limitations directed to contextual data.
Claim Objections
In light of Applicant’s amendments, the previous claim objections are withdrawn.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1 - 20 are rejected under 35 U.S.C. 101 because the claimed inventions are directed to non-statutory subject matter. The claimed inventions do not fall within a statutory category of invention because the claimed invention is directed to a “Mental Processes” abstract idea without significantly more.
1. Claims 1, 8, and 16 recite determining, from the high-order objective and based at least in part on the contextual data from the one or more content items, a set of sub-processes available to the computing system that combine to accomplish the high-order objective; generating, for a sub-process from among the set of sub-processes, a logic breakdown comprising a description of the sub-process and its predicted effect toward the high-order objective; which covers performance of the limitations that can be performed in the mind or by pen and paper, but for the recitation of generic computer components.
That is, other than reciting additional elements of generic computer components as well as insignificant extra-solution data gathering / transmission, e.g. accessing and displaying nothing in the claim elements precludes the determination of sub-processes and logic breakdown generation from being performed by a human. See MPEP 2106.05(g). As drafted, the claimed process, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components and insignificant extra-solution data transmission and displaying, which falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application because the claims only recite insignificant extra-solution data transmission and displaying. See MPEP 2106.05(g). Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the identified additional elements of data gathering / transmission and displaying are functions that have been identified by courts as well-understood, routine, and convention activity that do not amount to significantly more than the judicial exception. See MPEP 2106.05(d).
2. Claims 2 and 13 include the same abstract idea of the parent claims and contains additional elements directed to implementing an abstract idea on a generic computer, or merely uses a generic computer or computer components as a tool to perform the abstract idea, and which fails to integrate the judicial exception into a practical application, see MPEP 2106.05(g), and is insufficient to amount to significantly more than the judicial exception, see MPEP 2106.05(f)(2).
3. Claim 3 includes the abstract idea of determining the set of sub-processes available to the computing system comprises identifying one or more computing applications for performing one or more executable actions in furtherance of the high-order objective, which covers performance of the limitations that can be performed in the mind or by pen and paper and does not contain any additional elements.
4. Claim 4 includes the abstract idea determining the set of sub-processes available to the computing system comprises identifying application-specific computer code within a computing application for performing one or more executable actions in furtherance of the high-order objective, which covers performance of the limitations that can be performed in the mind or by pen and paper and does not contain any additional elements.
5. Claims 5 and 17 include the abstract idea generating the logic breakdown comprises generating a plurality of logic sections comprising /textual/ descriptions of the sub-process, which covers performance of the limitations that can be performed in the mind or by pen and paper and does not contain any additional elements.
6. Claim 6 includes the abstract idea generating the logic breakdown comprises …to generate the description of the sub-process from a prompt related to the high-order objective, which covers performance of the limitations that can be performed in the mind or by pen and paper. The claim also contains the additional element of utilizing a large language model which is directed to implementing an abstract idea on a generic computer, or merely uses a generic computer or computer components as a tool to perform the abstract idea, and which fails to integrate the judicial exception into a practical application, see MPEP 2106.05(g), and is insufficient to amount to significantly more than the judicial exception, see MPEP 2106.05(f)(2).
7. Claim 7 includes the abstract idea of updating the logic breakdown for the sub-process based on the user interaction indicating the edit, which covers performance of the limitations that can be performed in the mind or by pen and paper. The claim contains additional elements directed to insignificant extra-solution data transmission that fails to integrate the judicial exception into a practical application, see MPEP 2106.05(g), and is insufficient to amount to significantly more than the judicial exception because data transmission is a function that has been identified by courts as well-understood, routine, and convention activity that does not amount to significantly more than the judicial exception, see MPEP 2106.05(d).
8. Claim 9 includes the same abstract idea of the parent claims and contains additional elements directed to insignificant extra-solution data transmission that fails to integrate the judicial exception into a practical application, see MPEP 2106.05(g), and is insufficient to amount to significantly more than the judicial exception because data transmission is a function that has been identified by courts as well-understood, routine, and convention activity that does not amount to significantly more than the judicial exception, see MPEP 2106.05(d).
9. Claim 10 includes the abstract idea of update parameters of a large language model based on the instruction to modify the sub-process, which covers performance of the limitations that can be performed in the mind or by pen and paper. The claim contains additional elements directed to insignificant extra-solution data transmission that fails to integrate the judicial exception into a practical application, see MPEP 2106.05(g), and is insufficient to amount to significantly more than the judicial exception because data transmission is a function that has been identified by courts as well-understood, routine, and convention activity that does not amount to significantly more than the judicial exception, see MPEP 2106.05(d).
10. Claim 11 includes the abstract idea determine a data source corresponding to the sub-process; and extract data from the data source to generate an output in furtherance of the high-order objective, which covers performance of the limitations that can be performed in the mind or by pen and paper and does not contain any additional elements.
11. Claim 12 includes the same abstract idea of the parent claims and contains additional elements directed to insignificant extra-solution data transmission that fails to integrate the judicial exception into a practical application, see MPEP 2106.05(g), and is insufficient to amount to significantly more than the judicial exception because data transmission is a function that has been identified by courts as well-understood, routine, and convention activity that does not amount to significantly more than the judicial exception, see MPEP 2106.05(d). The claim also contains the additional element of activate the sub-process within the computing system which is directed to implementing an abstract idea on a generic computer, or merely uses a generic computer or computer components as a tool to perform the abstract idea, and which fails to integrate the judicial exception into a practical application, see MPEP 2106.05(g), and is insufficient to amount to significantly more than the judicial exception, see MPEP 2106.05(f)(2).
12. Claim 14 includes the abstract idea of determining the set of sub-processes available to the computing system comprises identifying at least one of an application programming interface or computer code for performing one or more executable actions in furtherance of the high-order objective, which covers performance of the limitations that can be performed in the mind or by pen and paper and does not contain any additional elements.
13. Claim 15 includes the abstract idea of the parent claims and also contains the additional element of utilizing a large language model to generate a proposed action which is directed to implementing an abstract idea on a generic computer, or merely uses a generic computer or computer components as a tool to perform the abstract idea, and which fails to integrate the judicial exception into a practical application, see MPEP 2106.05(g), and is insufficient to amount to significantly more than the judicial exception, see MPEP 2106.05(f)(2).
14. Claim 18 includes the abstract idea of generate an additional logic breakdown for the sub-process, which covers performance of the limitations that can be performed in the mind or by pen and paper. The claim contains additional elements directed to insignificant extra-solution display and data transmission that fails to integrate the judicial exception into a practical application, see MPEP 2106.05(g), and is insufficient to amount to significantly more than the judicial exception because display and data transmission is a function that has been identified by courts as well-understood, routine, and convention activity that does not amount to significantly more than the judicial exception, see MPEP 2106.05(d).
15. Claim 19 includes the abstract idea of generate, based on the instruction to modify the sub-process, a new logic breakdown for the sub-process, which covers performance of the limitations that can be performed in the mind or by pen and paper. The claim contains additional elements directed to insignificant extra-solution data transmission that fails to integrate the judicial exception into a practical application, see MPEP 2106.05(g), and is insufficient to amount to significantly more than the judicial exception because data transmission is a function that has been identified by courts as well-understood, routine, and convention activity that does not amount to significantly more than the judicial exception, see MPEP 2106.05(d).
16. Claim 20 includes the abstract idea of determine a data source corresponding to the sub-process; extract data from the data source to generate an output in furtherance of the high-order objective, which covers performance of the limitations that can be performed in the mind or by pen and paper. The claim contains additional elements directed to insignificant extra-solution data transmission that fails to integrate the judicial exception into a practical application, see MPEP 2106.05(g), and is insufficient to amount to significantly more than the judicial exception because data transmission is a function that has been identified by courts as well-understood, routine, and convention activity that does not amount to significantly more than the judicial exception, see MPEP 2106.05(d).
Claim Rejections 35 U.S.C. §103
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 of this title, 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.
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.
Claims 1 – 20 are rejected under 35 U.S.C. 103 as being unpatentable over Kirk, United States Patent Application Publication No. 2025/0123894 (Published April 17, 2025, filed October 17, 2023) (“Kirk”) in view of Du et al., United States Patent Application Publication No. 2025/0094137 (Published March 20, 2025, filed September 15, 2023) (“Du”).
Claims 1, 8, and 16
With respect to claims 1, 8, and 16, Kirk teaches the invention as claimed including a computer-implemented method comprising: receiving, from a client device, a high-order objective to be achieved within a computing system; accessing one or more content items associated with the client device, the one or more content items providing contextual data relevant to the high-order objective; determining, from the high-order objective and based oat least in part on the contextual data from the one or more content items, a set of sub-processes available to the computing system that combine to accomplish the high-order objective; generating, for a sub-process from among the set of sub-processes, a logic breakdown comprising a description of the sub-process and its predicted effect toward the high-order objective; {A high-level objective such as “a complex, large-scale objective,” i.e. a “computer process,” specified as a text-based semantic goal to achieve from a client, is submitted to a large language model which decomposes the objective into structured sub-process content items based on additional operational constraints specified by the client, generates a response containing an allocation scheme for the sub-processes, and executes the steps of the sub-processes by assigning them to particular AI bot applications. Kirk at ¶¶ 0017, 0028, 0072, 0114 – 0116, and 0136 (high-level objective submission, constraints, sub-processes, execution); 0015, 0031, and 0096 (sub-processes are allocated to AI bots, based on constraints, which are computer “scripts, programs or services that are configured to perform a specific operation”); id. at ¶ 0048 (display for viewing the sub-processes, monitoring the tasks the AI bots are performing, and for configuring resource allocations); id. at ¶ 0054 (data is extracted from a data source by a bot performing a sub-process); id. at ¶¶ 0114, 0116, 0125, 0130 (input constraints [metric] for achieving the high-level goal are input by the user); id. at ¶ 0120 (input constraints can be changed and sub-process allocation scheme can be re-allocated in response); id. at ¶ 0026 (APIs); id. at fig. 13.}
However, Kirk doesn’t explicitly teach the limitation:
and providing the logic breakdown for display via the client device. {Du does teach this limitation. Du teaches that the method for using a large language model to generate a series of sub-processes for accomplishing an objective, as taught in Kirk, may include where the user submits a natural language description of a high-level goal for an application under development to a large language model which generates a graphical user interface displaying a sequence of stages (sub-processes) representing application modules designed to carry out each step in the process of accomplishing the high-level goal where the user can manipulate the user interface to modify the logic of the presented stages. Du at ¶¶ 0028 – 0032 & 0035; id. at ¶¶ 0055 & 0269 (text fields are presented on stages and may be edited by user); id. at ¶¶ 0255 & 0295 (APIs may be specified to provide data sources for application).
Kirk and Du are analogous art because they are from the “same field of endeavor” and are both from the same “problem-solving area.” Specifically, they are both from the field of software development, and both are trying to solve the problem of how to use AI to help assist the software development process.
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to combine using a large language model to generate a series of sub-processes for accomplishing an objective, as taught in Kirk, with displaying the sub-processes, as taught in Du. Du teaches LLM output may require further improvement which can be provided by a user. Du at ¶ 0258. Therefore, one having ordinary skill in the art would have been motivated to combine using a large language model to generate a series of sub-processes for accomplishing an objective, as taught in Kirk, with displaying the sub-processes, as taught in Du, for the purpose of using a known method of displaying LLM output for user editing with a method that requires user feedback on LLM output.}
Claims 2 and 13
With respect to claims 2 and 13, Kirk and Du teach the invention as claimed including:
wherein determining the set of sub-processes comprises utilizing one or more artificial intelligence agents to determine a set of executable actions operable within the computing system. {A large language model is used to process a high-level objective such as “a complex, large-scale objective,” to identify required sub-processes for execution. Kirk at ¶¶ 0017, 0028, 0072, 0136.}
Claim 3
With respect to claim 3, Kirk and Du teach the invention as claimed including:
wherein determining the set of sub-processes available to the computing system comprises identifying one or more computing applications for performing one or more executable actions in furtherance of the high-order objective. {A high-level objective such as “a complex, large-scale objective,” i.e. a “computer process,” is specified as a text-based semantic goal to achieve is submitted to a large language model which decomposes the objective into structured sub-processes, generate a response containing an allocation scheme for the sub-processes, execute the steps of the sub-processes by assigning them to particular AI bot applications. Kirk at ¶¶ 0017, 0028, 0072, 0136 (high-level objective submission, sub-processes, execution); 0015 & 0031 (sub-processes are allocated to AI bots which are computer “scripts, programs or services that are configured to perform a specific operation”); id. at ¶ 0048 (display for viewing the sub-processes, monitoring the tasks the AI bots are performing, and for configuring resource allocations); id. at ¶ 0054 (data is extracted from a data source by a bot performing a sub-process); id. at ¶¶ 0114, 0116, 0125, 0130 (input constraints [metric] for achieving the high-level goal are input by the user); id. at ¶ 0120 (input constraints can be changed and sub-process allocation scheme can be re-allocated in response); id. at ¶ 0026 (APIs); id. at fig. 13.}
Claim 4
With respect to claim 4, Kirk and Du teach the invention as claimed including:
wherein determining the set of sub-processes available to the computing system comprises identifying application-specific computer code within a computing application for performing one or more executable actions in furtherance of the high-order objective. {A high-level objective such as “a complex, large-scale objective,” i.e. a “computer process,” is specified as a text-based semantic goal to achieve is submitted to a large language model which decomposes the objective into structured sub-processes, generate a response containing an allocation scheme for the sub-processes, execute the steps of the sub-processes by assigning them to particular AI bot applications. Kirk at ¶¶ 0017, 0028, 0072, 0136 (high-level objective submission, sub-processes, execution); 0015 & 0031 (sub-processes are allocated to AI bots which are computer “scripts, programs or services that are configured to perform a specific operation”); id. at ¶ 0048 (display for viewing the sub-processes, monitoring the tasks the AI bots are performing, and for configuring resource allocations); id. at ¶ 0054 (data is extracted from a data source by a bot performing a sub-process); id. at ¶¶ 0114, 0116, 0125, 0130 (input constraints [metric] for achieving the high-level goal are input by the user); id. at ¶ 0120 (input constraints can be changed and sub-process allocation scheme can be re-allocated in response); id. at ¶ 0026 (APIs); id. at fig. 13.}
Claims 5 and 17
With respect to claims 5 and 17, Kirk and Du teach the invention as claimed including:
wherein generating the logic breakdown comprises generating a plurality of logic sections comprising descriptions of the sub-process. {A high-level objective such as “a complex, large-scale objective,” i.e. a “computer process,” is specified as a text-based semantic goal to achieve is submitted to a large language model which decomposes the objective into structured sub-processes, generate a response containing an allocation scheme for the sub-processes, execute the steps of the sub-processes by assigning them to particular AI bot applications. Kirk at ¶¶ 0017, 0028, 0072, 0136 (high-level objective submission, sub-processes, execution); 0015 & 0031 (sub-processes are allocated to AI bots which are computer “scripts, programs or services that are configured to perform a specific operation”); id. at ¶ 0048 (display for viewing the sub-processes, monitoring the tasks the AI bots are performing, and for configuring resource allocations); id. at ¶ 0054 (data is extracted from a data source by a bot performing a sub-process); id. at ¶¶ 0114, 0116, 0125, 0130 (input constraints [metric] for achieving the high-level goal are input by the user); id. at ¶ 0120 (input constraints can be changed and sub-process allocation scheme can be re-allocated in response); id. at ¶ 0026 (APIs); id. at fig. 13.}
Claim 6
With respect to claim 6, Kirk and Du teach the invention as claimed including:
wherein generating the logic breakdown comprises utilizing a large language model to generate the description of the sub-process from a prompt related to the high-order objective. {A high-level objective such as “a complex, large-scale objective,” i.e. a “computer process,” is specified as a text-based semantic goal to achieve is submitted to a large language model which decomposes the objective into structured sub-processes, generate a response containing an allocation scheme for the sub-processes, execute the steps of the sub-processes by assigning them to particular AI bot applications. Kirk at ¶¶ 0017, 0028, 0072, 0136 (high-level objective submission, sub-processes, execution); 0015 & 0031 (sub-processes are allocated to AI bots which are computer “scripts, programs or services that are configured to perform a specific operation”); id. at ¶ 0048 (display for viewing the sub-processes, monitoring the tasks the AI bots are performing, and for configuring resource allocations); id. at ¶ 0054 (data is extracted from a data source by a bot performing a sub-process); id. at ¶¶ 0114, 0116, 0125, 0130 (input constraints [metric] for achieving the high-level goal are input by the user); id. at ¶ 0120 (input constraints can be changed and sub-process allocation scheme can be re-allocated in response); id. at ¶ 0026 (APIs); id. at fig. 13.}
Claim 7
With respect to claim 7, Kirk and Du teach the invention as claimed including:
receiving, via a control element displayed on the client device, a user interaction indicating an edit to the logic breakdown; and updating the logic breakdown for the sub-process based on the user interaction indicating the edit. {The user submits a natural language description of a high-level goal for an application under development to a large language model which generates a graphical user interface displaying a sequence of stages (sub-processes) representing application modules designed to carry out each step in the process of accomplishing the high-level goal where the user can manipulate the user interface to modify the logic of the presented stages. Du at ¶¶ 0028 – 0032 & 0035; id. at ¶¶ 0055 & 0269 (text fields are presented on stages and may be edited by user); id. at ¶¶ 0255 & 0295 (APIs may be specified to provide data sources for application).}
Claim 9
With respect to claim 9, Kirk and Du teach the invention as claimed including:
wherein providing the logic breakdown for display comprises providing a textual description of the sub-process for display via the client device. {The user submits a natural language description of a high-level goal for an application under development to a large language model which generates a graphical user interface displaying a sequence of stages (sub-processes) representing application modules designed to carry out each step in the process of accomplishing the high-level goal where the user can manipulate the user interface to modify the logic of the presented stages. Du at ¶¶ 0028 – 0032 & 0035; id. at ¶¶ 0055 & 0269 (text fields are presented on stages and may be edited by user); id. at ¶¶ 0255 & 0295 (APIs may be specified to provide data sources for application).}
Claim 10
With respect to claim 10, Kirk and Du teach the invention as claimed including:
wherein the instructions, when executed by the at least one processor, further cause the system to: receive, from the client device, an instruction to modify the sub-process; and update parameters of a large language model based on the instruction to modify the sub-process. {The user submits a natural language description of a high-level goal for an application under development to a large language model which generates a graphical user interface displaying a sequence of stages (sub-processes) representing application modules designed to carry out each step in the process of accomplishing the high-level goal where the user can manipulate the user interface to modify the logic of the presented stages. Du at ¶¶ 0028 – 0032 & 0035; id. at ¶¶ 0055 & 0269 (text fields are presented on stages and may be edited by user); id. at ¶¶ 0255 & 0295 (APIs may be specified to provide data sources for application).}
Claim 11
With respect to claim 11, Kirk and Du teach the invention as claimed including:
wherein the instructions, when executed by the at least one processor, further cause the system to: determine a data source corresponding to the sub-process; and extract data from the data source to generate an output in furtherance of the high-order objective.
{A high-level objective such as “a complex, large-scale objective,” i.e. a “computer process,” is specified as a text-based semantic goal to achieve is submitted to a large language model which decomposes the objective into structured sub-processes, generate a response containing an allocation scheme for the sub-processes, execute the steps of the sub-processes by assigning them to particular AI bot applications. Kirk at ¶¶ 0017, 0028, 0072, 0136 (high-level objective submission, sub-processes, execution); 0015 & 0031 (sub-processes are allocated to AI bots which are computer “scripts, programs or services that are configured to perform a specific operation”); id. at ¶ 0048 (display for viewing the sub-processes, monitoring the tasks the AI bots are performing, and for configuring resource allocations); id. at ¶ 0054 (data is extracted from a data source by a bot performing a sub-process); id. at ¶¶ 0114, 0116, 0125, 0130 (input constraints [metric] for achieving the high-level goal are input by the user); id. at ¶ 0120 (input constraints can be changed and sub-process allocation scheme can be re-allocated in response); id. at ¶ 0026 (APIs); id. at fig. 13.}
Claim 12
With respect to claim 12, Kirk and Du teach the invention as claimed including:
wherein the instructions, when executed by the at least one processor, further cause the system to: receive, from the client device, an instruction to activate the sub-process; and activate the sub-process within the computing system. {A high-level objective such as “a complex, large-scale objective,” i.e. a “computer process,” is specified as a text-based semantic goal to achieve is submitted to a large language model which decomposes the objective into structured sub-processes, generate a response containing an allocation scheme for the sub-processes, execute the steps of the sub-processes by assigning them to particular AI bot applications. Kirk at ¶¶ 0017, 0028, 0072, 0136 (high-level objective submission, sub-processes, execution); 0015 & 0031 (sub-processes are allocated to AI bots which are computer “scripts, programs or services that are configured to perform a specific operation”); id. at ¶ 0048 (display for viewing the sub-processes, monitoring the tasks the AI bots are performing, and for configuring resource allocations); id. at ¶ 0054 (data is extracted from a data source by a bot performing a sub-process); id. at ¶¶ 0114, 0116, 0125, 0130 (input constraints [metric] for achieving the high-level goal are input by the user); id. at ¶ 0120 (input constraints can be changed and sub-process allocation scheme can be re-allocated in response); id. at ¶ 0026 (APIs); id. at fig. 13.}
Claim 14
With respect to claim 14, Kirk and Du teach the invention as claimed including:
wherein determining the set of sub-processes available to the computing system comprises identifying at least one of [an application programming interface] or computer code for performing one or more executable actions in furtherance of the high-order objective. {A high-level objective such as “a complex, large-scale objective,” i.e. a “computer process,” is specified as a text-based semantic goal to achieve is submitted to a large language model which decomposes the objective into structured sub-processes, generate a response containing an allocation scheme for the sub-processes, execute the steps of the sub-processes by assigning them to particular AI bot applications. Kirk at ¶¶ 0017, 0028, 0072, 0136 (high-level objective submission, sub-processes, execution); 0015 & 0031 (sub-processes are allocated to AI bots which are computer “scripts, programs or services that are configured to perform a specific operation”); id. at ¶ 0048 (display for viewing the sub-processes, monitoring the tasks the AI bots are performing, and for configuring resource allocations); id. at ¶ 0054 (data is extracted from a data source by a bot performing a sub-process); id. at ¶¶ 0114, 0116, 0125, 0130 (input constraints [metric] for achieving the high-level goal are input by the user); id. at ¶ 0120 (input constraints can be changed and sub-process allocation scheme can be re-allocated in response); id. at ¶ 0026 (APIs); id. at fig. 13.}
of an application programming interface {APIs may be specified to provide data sources for application. Du at ¶¶ 0255 & 0295; see also Kirk at ¶ 0026.}
Claim 15
With respect to claim 15, Kirk and Du teach the invention as claimed including:
further comprising utilizing a large language model to generate a proposed action. {A high-level objective such as “a complex, large-scale objective,” i.e. a “computer process,” is specified as a text-based semantic goal to achieve is submitted to a large language model which decomposes the objective into structured sub-processes, generate a response containing an allocation scheme for the sub-processes, execute the steps of the sub-processes by assigning them to particular AI bot applications. Kirk at ¶¶ 0017, 0028, 0072, 0136 (high-level objective submission, sub-processes, execution); 0015 & 0031 (sub-processes are allocated to AI bots which are computer “scripts, programs or services that are configured to perform a specific operation”); id. at ¶ 0048 (display for viewing the sub-processes, monitoring the tasks the AI bots are performing, and for configuring resource allocations); id. at ¶ 0054 (data is extracted from a data source by a bot performing a sub-process); id. at ¶¶ 0114, 0116, 0125, 0130 (input constraints [metric] for achieving the high-level goal are input by the user); id. at ¶ 0120 (input constraints can be changed and sub-process allocation scheme can be re-allocated in response); id. at ¶ 0026 (APIs); id. at fig. 13.}
Claim 18
With respect to claim 18, Kirk and Du teach the invention as claimed including:
wherein the instructions, when executed by the at least one processor, further cause the computing device to: provide a control element for display via the client device; and generate an additional logic breakdown for the sub-process based on a user interaction with the control element. {The user submits a natural language description of a high-level goal for an application under development to a large language model which generates a graphical user interface displaying a sequence of stages (sub-processes) representing application modules designed to carry out each step in the process of accomplishing the high-level goal where the user can manipulate the user interface to modify the logic of the presented stages. Du at ¶¶ 0028 – 0032 & 0035; id. at ¶¶ 0055 & 0269 (text fields are presented on stages and may be edited by user); id. at ¶¶ 0255 & 0295 (APIs may be specified to provide data sources for application).}
Claim 19
With respect to claim 19, Kirk and Du teach the invention as claimed including:
wherein the instructions, when executed by the at least one processor, further cause the computing device to: receive, from the client device, an instruction to modify the sub-process; generate, based on the instruction to modify the sub-process, a new logic breakdown for the sub-process; and provide, for display via the user interface, the new logic breakdown. {The user submits a natural language description of a high-level goal for an application under development to a large language model which generates a graphical user interface displaying a sequence of stages (sub-processes) representing application modules designed to carry out each step in the process of accomplishing the high-level goal where the user can manipulate the user interface to modify the logic of the presented stages. Du at ¶¶ 0028 – 0032 & 0035; id. at ¶¶ 0055 & 0269 (text fields are presented on stages and may be edited by user); id. at ¶¶ 0255 & 0295 (APIs may be specified to provide data sources for application).}
Claim 20
With respect to claim 20, Kirk and Du teach the invention as claimed including:
wherein the instructions, when executed by the at least one processor, further cause the computing device to: determine a data source corresponding to the sub-process; extract data from the data source to generate an output in furtherance of the high-order objective; and provide the output for display via the user interface. {A high-level objective such as “a complex, large-scale objective,” i.e. a “computer process,” is specified as a text-based semantic goal to achieve is submitted to a large language model which decomposes the objective into structured sub-processes, generate a response containing an allocation scheme for the sub-processes, execute the steps of the sub-processes by assigning them to particular AI bot applications. Kirk at ¶¶ 0017, 0028, 0072, 0136 (high-level objective submission, sub-processes, execution); 0015 & 0031 (sub-processes are allocated to AI bots which are computer “scripts, programs or services that are configured to perform a specific operation”); id. at ¶ 0048 (display for viewing the sub-processes, monitoring the tasks the AI bots are performing, and for configuring resource allocations); id. at ¶ 0054 (data is extracted from a data source by a bot performing a sub-process); id. at ¶¶ 0114, 0116, 0125, 0130 (input constraints [metric] for achieving the high-level goal are input by the user); id. at ¶ 0120 (input constraints can be changed and sub-process allocation scheme can be re-allocated in response); id. at ¶ 0026 (APIs); id. at fig. 13.}
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
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//T.H./ February 18, 2026
Examiner, Art Unit 2199
/LEWIS A BULLOCK JR/Supervisory Patent Examiner, Art Unit 2199