CTNF 18/818,325 CTNF 87882 DETAILED ACTION This action is responsive to the application filed on August 28, 2024. Claims 1-20 are pending and presented to examination. 07-03-aia AIA 15-10-aia The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA. 07-06 AIA 15-10-15 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. Examiner Notes Examiner cites particular columns, paragraphs, figures and line numbers in the references as applied to the claims below for the convenience of the applicant. Although the specified citations are representative of the teachings in the art and are applied to the specific limitations within the individual claim, other passages and figures may apply as well. It is respectfully requested that, in preparing responses, the applicant fully consider the references in their entirety as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the examiner. Information Disclosure Statement As required by M.P.E.P. 609, the applicant’s submission of the Information Disclosure Statement dated February 12, 2026 is acknowledged by the examiner and the cited references have been considered in the examination of the claims now pending. Drawings The drawings filed on August 28, 2024 are acceptable for examination purposes. Claim Objections 07-29-01 AIA Claim s 1-20 are objected to because of the following informalities: Claim 1 (and similar for claims 13 and 18) recites the limitations “receiving, from the LLM, a generated intermediate representation; merging the generated intermediate representation s for the plurality of features into [[an]] a combined intermediate representation;” in lines 12-15. The limitation limits just a “generate intermediate representation” rather than “generate intermediate representations”. Please remove the “s” as indicated in bold . In addition, please replace “an” to –a --. Appropriate correction is required. Claim 1 (and similar for claims 13 and 18) recites the limitation “sending the prompt to a large language model (LLM) ; and ” in lines 11. Please add a semicolon “;” follow by “ and ” at the end of the limitation as indicated in bold. Appropriate correction is required. Claim 4 (and similar for claim 16) recites “wherein the prompt s are sent to the LLM in an order determined by the tree structure.”. Parent claim limits just a “prompt” rather than “prompts”. Please remove the “s” as indicated in bold. Appropriate correction is required. Claims 11-12 and 19-20 recites “the natural language text” wherein the parent claim introduces “first natural language text”. Please remove the term “first” from claims 1, 3, 13 and 15 and 18). Appropriate correction is required. Dependent claims 2-3, 5-10, 14-15 and 17 do not overcome the deficiency of the base claim and, therefore, are objected for the same reasons as the base claim. Claim Rejections - 35 USC § 112 07-30-02 AIA The following is a quotation of 35 U.S.C. 112(b): (b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention. The following is a quotation of 35 U.S.C. 112 (pre-AIA), second paragraph: The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention. Claims 1, 8-10, 13 and 18 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention. Claim 1 (and similar for claims 13 and 18) recites “for each features in the plurality of features:” in line 9 and “generating a prompt for a corresponding feature”. It is unclear whether “a corresponding feature” is the same as the iterated “each feature”. For purpose of examination, examiner will interpret it as the same. Claim 8 recites "wherein the intermediate representation is not compilable.". There is insufficient antecedent basis for this limitation in the claim. For purpose of examination, the examiner is interpreting it as “the generated intermediate representation”. Claim 9 recites "wherein the intermediate representation is a JavaScript Object Notation (JSON) file.". There is insufficient antecedent basis for this limitation in the claim. For purpose of examination, the examiner will interpret it as “the generated intermediate representation”. Claim 10 recites "wherein the programmatic component automatically corrects one or more errors in the intermediate representation .". There is insufficient antecedent basis for this limitation in the claim. For purpose of examination, the examiner is interpreting it as “the combined intermediate representation”. Dependent claims 2-7, 11-12, 14-17 and 19-20 do not overcome the deficiency of the base claim and, therefore, are rejected for the same reasons as the base claim. Double Patenting 08-33 AIA The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg , 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman , 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi , 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum , 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel , 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington , 418 F.2d 528, 163 USPQ 644 (CCPA 1969). A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA. A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b). The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13. The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA/25, or PTO/AIA/26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer. 08-36 AIA Claims 1-20 are reje cted on the ground of nonstatutory double patenting as being unpatentable over claims 1-20 of U.S . Patent No. 12,63 2,650 in view of Khot in view of Zhou and further in vi ew of Hirs ch. Instant Application No. 18/818,325 and U.S. Patent No. 12,632,650 (hereinafter “the ’650 Patent”) each name SAP SE as the applicant and assignee and are commonly owned. Although the conflicting claims are not identical, they are not patentably distinct from one another for the reasons set forth below. Instant independent claims 1, 13, and 18 are compared below against claims 1, 8, and 15 of the ’650 Patent, respectively, with the distinguishing limitations of each claim shown in bold: Inst ant Application U.S. Pat. No. 12,632,650 1. A system comprising: at least one hardware processor; and a computer-readable medium storing instructions that, when executed by the at least one hardware processor, cause the at least one hardware processor to perform operations comprising: receiving first natural language text requesting automatic generation of generated text, the first natural language text comprising a plurality of features of the generated text; for each feature in the plurality of features: generating a prompt for a corresponding feature; sending the prompt to a large language model (LLM) receiving, from the LLM, a generated intermediate representation; merging the generated intermediate representations for the plurality of features into an combined intermediate representation; and passing the combined intermediate representation to a programmatic component, which validates the combined intermediate representation and converts the combined intermediate representation into a final representation. 1. A system comprising: at least one hardware processor; and a computer-readable medium storing instructions that, when executed by the at least one hardware processor, cause the at least one hardware processor to perform operations comprising: receiving natural language text describing compilable computer code to be generated in a compilable computer language ; generating a prompt by adding a system message to the natural language text, the system message including an instruction to generate computer code in an intermediate representation in a language other than the compilable computer language ; passing the prompt to a large language model (LLM), wherein the LLM is transformer-based ; receiving, from the LLM, a generated intermediate representation; and passing the generated intermediate representation to a programmatic component, which validates the generated intermediate representation and converts the generated intermediate representation into a final representation, the final representation being compilable computer code . 13. A method comprising: receiving first natural language text requesting automatic generation of text, the first natural language text comprising a plurality of features of the text; for each feature in the plurality of features: generating a prompt for a corresponding feature; sending the prompt to a large language model (LLM) receiving, from the LLM, a generated intermediate representation; merging the generated intermediate representations for the plurality of features into an combined intermediate representation; and passing the combined intermediate representation to a programmatic component, which validates the combined intermediate representation and converts the combined intermediate representation into a final representation. 8. A method comprising: receiving natural language text describing compilable computer code to be generated in a compilable computer language ; generating a prompt by adding a system message to the natural language text, the system message including an instruction to generate computer code in an intermediate representation in a language other than the compilable computer language ; passing the prompt to a large language model (LLM), wherein the LLM is transformer-based ; receiving, from the LLM, a generated intermediate representation; and passing the generated intermediate representation to a programmatic component, which validates the generated intermediate representation and converts the generated intermediate representation into a final representation, the final representation being compilable computer code . 18. A non-transitory machine-readable medium storing instructions which, when executed by one or more processors, cause the one or more processors to perform operations comprising: receiving first natural language text requesting automatic generation of text, the first natural language text comprising a plurality of features of the text; for each feature in the plurality of features: generating a prompt for a corresponding feature; sending the prompt to a large language model (LLM) receiving, from the LLM, a generated intermediate representation; merging the generated intermediate representations for the plurality of features into an combined intermediate representation; and passing the combined intermediate representation to a programmatic component, which validates the combined intermediate representation and converts the combined intermediate representation into a final representation. 15. A non-transitory machine-readable medium storing instructions which, when executed by one or more processors, cause the one or more processors to perform operations comprising: receiving natural language text describing compilable computer code to be generated in a compilable computer language ; generating a prompt by adding a system message to the natural language text, the system message including an instruction to generate computer code in an intermediate representation in a language other than the compilable computer language ; passing the prompt to a large language model (LLM), wherein the LLM is transformer-based ; receiving, from the LLM, a generated intermediate representation; and passing the generated intermediate representation to a programmatic component, which validates the generated intermediate representation and converts the generated intermediate representation into a final representation, the final representation being compilable computer code . As shown above, claim 1 of the ’650 Patent recites each limitation of instant claim 1 except that instant claim 1 (i) receives first natural language text comprising a plurality of features, (ii) for each feature in the plurality of features generates a prompt and receives a corresponding generated intermediate representation, and (iii) merges the generated intermediate representations for the plurality of features into a combined intermediate representation. The additional limitations recited in claim 1 of the ’650 Patent—that the code is to be generated in a compilable computer language, that the intermediate representation is in a language other than the compilable computer language, that the large language model is transformer-based, and that the final representation is compilable computer code—are narrowing limitations that fall within the broader scope of instant claim 1. Instant claim 1 is therefore broader than, and fully encompasses, the subject matter of claim 1 of the ’650 Patent. Those per-feature decomposition and merging limitations that are not recited by claim 1 of the ’650 Patent are taught by Khot. Khot teaches “decomposing them (via prompting) into simpler sub-tasks” and that “the core is a decomposer LLM that tries to solve a complex task by generating a prompting program P” in which “Each step of P directs a simpler sub-query to a function” and the system “passes the inputs and outputs between the decomposer and sub-task handler” to produce “the final output obtained.” It would have been obvious to one of ordinary skill in the art at the time the invention was made before the effective filing date of the claimed invention to modify the natural-language-to-intermediate-representation generation recited in claim 1 of the ’650 Patent so as to receive a plurality of features, to generate a prompt and a corresponding intermediate representation for each feature in the plurality of features, and to merge the generated intermediate representations into a combined intermediate representation, as taught by Khot. A person of ordinary skill would have been motivated to make this modification because the ’650 Patent and Khot are directed to the same field of prompting large language models to generate output, and because decomposing a multi-feature request into per-feature sub-prompts and merging the per-feature results predictably avoids overloading the model with a single oversized request—improving the reliability of the generated intermediate representation while preserving the validate- and-convert pipeline of the ’650 Patent—and thus yields no more than the predictable result of applying a known decomposition-and-merger technique to a known generation pipeline. Instant independent claims 13 and 18 recite limitations parallel to those of instant claim 1 and correspond, respectively, to claims 8 and 15 of the ’650 Patent; they are not patentably distinct from claims 8 and 15 of the ’650 Patent in view of Khot for the same reasons set forth above with respect to claim 1. Instant dependent claims 2 and 14 (final representation is compilable computer code) are not patentably distinct from the ’650 Patent, the final representation of claims 1 and 8 of the ’650 Patent already being compilable computer code. Instant claim 6 corresponds to claims 2, 9, and 16 of the ’650 Patent (at least partially proprietary); instant claim 7 corresponds to claims 3, 10, and 17 (Core Data Services (CDS) model); instant claim 8 corresponds to claims 4, 11, and 18 (intermediate representation not compilable); instant claim 9 corresponds to claims 5, 12, and 19 (JavaScript Object Notation (JSON) intermediate representation); and instant claim 10 corresponds to claims 6, 13, and 20 (programmatic component automatically corrects one or more errors). These instant dependent claims are not patentably distinct from the corresponding claims of the ’650 Patent. Instant claims 3 and 15 (generating a tree structure containing a node corresponding to each feature, with edges between nodes signifying dependencies between features) and instant claims 11 and 19 (the plurality of features not representing all of the features in the natural language text) are not recited by the claims of the ’650 Patent; however, these limitations are taught by Khot, which teaches generating a prompting program that decomposes a task into “a sequence of sub-tasks (A, B, and C)” that may be “further decomposed if necessary.” It would have been obvious to one of ordinary skill in the art at the time the invention was made before the effective filing date of the claimed invention to organize the per-feature sub-prompts of the ’650 Patent–Khot combination into the tree structure taught by Khot and to operate upon a selected subset of the features, in order to capture the dependencies among the features and to act upon fewer than all of the features of the request, predictably improving control over multi-feature generation and amounting to no more than the predictable application of Khot’s decomposition technique to the combination. Instant claims 4, 5, 16, and 17 (sending the prompts in an order determined by the tree structure, with prompts for features dependent on other features placed behind the prompts for the other features) are not recited by the ’650 Patent; however, these limitations are taught by Zhou, which “reduces a complex problem into a list of subproblems, and then sequentially solves the subproblems” wherein “solving a given subproblem is facilitated by the model’s answers to previously solved subproblems.” It would have been obvious to one of ordinary skill in the art at the time the invention was made before the effective filing date of the claimed invention to send the per-feature prompts of the ’650 Patent–Khot combination to the large language model in the dependency order taught by Zhou, placing prompts for dependent features behind the prompts for the features upon which they depend, in order to ensure that each feature’s generation is facilitated by the previously generated results upon which it depends, yielding the predictable benefit Zhou identifies for sequential subproblem solving. Instant claims 12 and 20 (a feature, present in the natural language text, excluded from the plurality of features based on a selection by a user in a graphical user interface) are not recited by the ’650 Patent; however, this limitation is taught by Hirsch, which teaches “an intuitive, user-friendly, graphical user interface” through which “the user may select, combine and customize various predefined and user-uploaded components, including modules.” It would have been obvious to one of ordinary skill in the art at the time the invention was made before the effective filing date of the claimed invention to provide a graphical user interface by which the user selects which features are incorporated, as taught by Hirsch, such that a feature that is not selected by the user is excluded from the plurality of features, in order to give the user direct, code-free control over which features of the natural language request are acted upon, a predictable benefit of Hirsch’s feature-selection interface . Claim Rejections - 35 USC § 103 07-20-aia AIA 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. 07-23-aia AIA 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. 07-21-aia AIA Claim s 1, 3, 8-11, 13, 15 and 18-19 are rejected under 35 U.S.C. 103 as being unpatentable over Anders Hejlsberg et al., (“Introducing TypeChat”, hereinafter Hejlsberg – IDS 02/12/2026) in view of Tushar Khot et al. (“Decomposed Prompting: A Modular Approach for Solving Complex Tasks”, hereinafter Khot) . With respect to claim 1, Hejlsberg teaches a system comprising: at least one hardware processor; and a computer-readable medium storing instructions that, when executed by the at least one hardware processor, cause the at least one hardware processor to perform operations comprising (Hejlsberg discloses “an experimental library” that the developer uses by “hooking it up with any language model to work with your app” (Hejlsberg, introductory section). A software library that is installed (via “npm install typechat”) and executed to operate upon user input is necessarily embodied as instructions stored on a computer-readable medium and executed by at least one hardware processor of the host computer. The disclosed library therefore meets the recited system comprising at least one hardware processor and a computer-readable medium storing the executed instructions). receiving first natural language text requesting automatic generation of generated text, the first natural language text comprising [[ a plurality of features of the generated text ]] (Hejlsberg discloses that the technique is used to “take a user request and turn it into something our apps can operate on” (Hejlsberg, introductory section), illustrated by the user-supplied natural language request “Could I get a blueberry muffin and a grande latte?” (Hejlsberg, “Pampering and Parsing” section). Receiving such a user request that is to be turned into a generated structured result reads on receiving first natural language text requesting automatic generation of generated text). [[ for each feature in the plurality of features: ]] generating a prompt [[ for a corresponding feature; ]] (Hejlsberg discloses “combining a human prompt and a 'response schema'” and that “we've been using TypeScript types in our prompts” (Hejlsberg, “Enter TypeChat” and “Just Add Types!” sections). Constructing such a prompt to the language model from the schema reads on generating a prompt). sending the prompt to a large language model (LLM) (Hejlsberg discloses code to “hook TypeChat up to an LLM” (Hejlsberg, “Enter TypeChat” section), and that the approach works with “any chat completion-style API” (Hejlsberg, “Open and Pluggable” section). Submitting the constructed prompt to the language model in this manner reads on sending the prompt to a large language model (LLM)). receiving, from the LLM, a generated intermediate representation (Hejlsberg discloses that “we can ask LLMs to respond in the form of JSON, and they generally respond with something sensible” (Hejlsberg, “Pampering and Parsing” section), the returned JSON instance being shown in the “ChatBot:” response. The JSON instance returned by the language model in response to the prompt reads on receiving, from the LLM, a generated intermediate representation). passing the combined intermediate representation to a programmatic component, which validates the combined intermediate representation and converts the combined intermediate representation into a final representation (Hejlsberg discloses that “we can validate the response against them using the TypeScript compiler itself” and that the library is used “to retrieve structured AI responses that are type-safe” (Hejlsberg, “Just Add Types!” and introductory sections), providing “schema validation, repair” (Hejlsberg, “Enter TypeChat” section). The TypeScript compiler/validator is a deterministic, non-learning component; passing the returned JSON to that component, which validates the JSON for schema conformance and then converts the validated JSON into the type-safe object consumed by the application, reads on passing the intermediate representation to a programmatic component which validates it and converts it into a final representation). Hejlsberg is silent to disclose, however, in an analogous art, Khot teaches: a plurality of features of the generated text (Khot teaches “decomposing them (via prompting) into simpler sub-tasks” (Khot, Abstract). Each such sub-task into which the request is decomposed corresponds to a feature of the output to be generated; the resulting set of sub-tasks therefore reads on the first natural language text comprising a plurality of features of the generated text). for each feature in the plurality of features: generating a prompt for a corresponding feature (Khot teaches that “the core is a decomposer LLM that tries to solve a complex task by generating a prompting program P” in which “Each step of P directs a simpler sub-query to a function” (Khot, Section 3), and that “Each sub-task is then delegated to the corresponding sub-task handler” (Khot, Figure 1). Generating, for each decomposed sub-task (feature), a corresponding sub-query/sub-prompt that is directed to the sub-task handler reads on, for each feature in the plurality of features, generating a prompt for a corresponding feature). merging the generated intermediate representations for the plurality of features into an combined intermediate representation (Khot teaches that the prompting program is executed by a controller that “passes the inputs and outputs between the decomposer and sub-task handler” until “the final output obtained” (Khot, Section 3), the program being a sequence in which “Ak is the final answer predicted by P” (Khot, Section 3). Assembling the individual sub-task outputs into the single final output of the program reads on merging the generated intermediate representations for the plurality of features into a combined intermediate representation). It would have been obvious to one of ordinary skill in the art at the time the invention was made before the effective filing date of the claimed invention to modify the single-prompt natural-language-to-JSON translation of Hejlsberg so as to decompose the natural language request into a plurality of per-feature sub-prompts, issue each sub-prompt separately to the large language model, and merge the resulting per-feature intermediate representations into a combined intermediate representation, as taught by Khot. Khot expressly identifies the problem that motivates this modification, stating that few-shot prompting “struggles as the task complexity increases” (Khot, Abstract), and teaches decomposition as the solution because the modular structure “allows each prompt to be optimized for its specific sub-task” (Khot, Abstract). A person of ordinary skill would have been motivated to apply Khot’s decomposition to Hejlsberg’s schema-guided generation in order to keep each request within the practical input limits of the large language model, to prevent the influence of any single requested feature from being diluted when many features are requested in one prompt, and to permit each feature’s prompt to be independently optimized, validated, and repaired by Hejlsberg’s validation component. The combination merely applies the known technique of Khot (modular task decomposition and recomposition) to the known and improvable system of Hejlsberg (schema-guided generation with validation) to yield the predictable result of reliably generating multi-feature structured output, and therefore would have been obvious. With respect to claim 3, Hejlsberg is silent to disclose, however, in an analogous art, Khot teaches wherein the operations further comprise: generating a tree structure based on the first natural language text, the tree structure containing a node corresponding to each feature of the plurality of features, with edges between nodes signifying dependencies between features (Khot teaches that “the decomposer defines the top-level program for the complex task” using sub-task functions, that each sub-task may be “further decomposed if necessary” (Khot, Section 2 and Abstract), and that the program is “a sequence of sub-tasks (A, B, and C)” in which outputs are passed between sub-tasks (Khot, Figure 1 and Section 3). Each decomposed sub-task (feature) is thus a node; a sub-task that is further decomposed yields child nodes; and the passing of one sub-task’s output as the input to another establishes a dependency, i.e., an edge between nodes. This decomposition structure reads on generating a tree structure containing a node for each feature with edges signifying dependencies between features). It would have been obvious to one of ordinary skill in the art at the time the invention was made before the effective filing date of the claimed invention to represent the plurality of decomposed features of the Hejlsberg-Khot combination as a tree structure in which each feature is a node and inter-feature dependencies are edges, as taught by Khot. A person of ordinary skill would have been motivated to make this modification in order to explicitly capture and preserve the dependencies that Khot’s program already relies upon when passing one sub-task’s output to another, so that the features can subsequently be processed in an order that satisfies those dependencies and so that complex features can be further decomposed into child nodes; doing so predictably improves the correctness of the generated output by preventing a dependent feature from being generated before the feature it relies upon. With respect to claim 8, Hejlsberg teaches wherein the intermediate representation is not compilable (Hejlsberg discloses that “we can ask LLMs to respond in the form of JSON” (Hejlsberg, “Pampering and Parsing” section). JSON (JavaScript Object Notation) is a data-interchange notation rather than source code, and is therefore not itself compilable; the intermediate representation disclosed by Hejlsberg is accordingly not compilable). With respect to claim 9, Hejlsberg teaches wherein the intermediate representation is a JavaScript Object Notation (JSON) file (Hejlsberg discloses that the language model is asked “to respond in the form of JSON” and identifies JSON as “JavaScript Object Notation” (Hejlsberg, “Pampering and Parsing” and “Just Add Types!” sections). The intermediate representation received from the language model is therefore a JSON file). With respect to claim 10, Hejlsberg teaches wherein the programmatic component automatically corrects one or more errors in the intermediate representation (Hejlsberg discloses that “the error feedback from the compiler can even be used to guide repairs” (Hejlsberg, “Just Add Types!” section) and lists “schema validation, repair” among the provided tools (Hejlsberg, “Enter TypeChat” section). Using the compiler’s error feedback to automatically repair the non-conforming JSON reads on the programmatic component automatically correcting one or more errors in the intermediate representation). With respect to claim 11, Hejlsberg is silent to disclose, however, in an analogous art, Khot teaches wherein the plurality of features in the natural language text does not represent all of the features in the natural language text (Khot teaches that the decomposer prompt is used “to only describe the procedure to solve the complex tasks using certain sub-tasks” (Khot, Figure 1). Because only certain sub-tasks (features) are selected by the decomposer to solve the request, the plurality of features operated upon need not encompass every feature expressed in the natural language text, which reads on the recited limitation). It would have been obvious to one of ordinary skill in the art at the time the invention was made before the effective filing date of the claimed invention to limit the plurality of features processed by the Hejlsberg-Khot combination to fewer than all of the features expressed in the natural language text, as taught by Khot’s selection of “certain sub-tasks” (Khot, Figure 1). A person of ordinary skill would have been motivated to do so in order to conserve processing and token resources and to focus generation only on those features relevant to the desired output, which is a predictable benefit of selective decomposition. With respect to claims 13 and 15, the claims are directed to a method that corresponds to the system recited in claims 1 and 3, respectively (see the rejection of claims 1 and 3 above). With respect to claim 18, the claim is directed to a non-transitory machine-readable medium that corresponds to the system recited in claim 1, respectively (see the rejection of claim 1 above, wherein Hejlsberg teaches as “an experimental library” embodied as stored, executable instructions that reads on a medium storing instructions). With respect to claim 19, the claim is directed to a non-transitory machine-readable medium that corresponds to the system recited in claim 11, respectively (see the rejection of claim 11 above) . 07-21-aia AIA Claim s 2, 6-7 and 14 are rejected under 35 U.S.C. 103 as being unpatentable over Anders Hejlsberg et al., (“Introducing TypeChat”, hereinafter Hejlsberg – IDS 02/12/2026) in view of Tushar Khot et al. (“Decomposed Prompting: A Modular Approach for Solving Complex Tasks”, hereinafter Khot) and further in view of Capire, (“Core Data Services CDS”, hereinafter Capire – IDS 02/12/2026). With respect to claim 2, Hejlsberg in view of Khot is silent to disclose, however, in an analogous art, Capire teaches wherein the final representation is compilable computer code (Capire discloses that “The CDS toolkit allows to parse from a variety of source languages into a uniform format and to compile it into various target languages” (Capire, Core Data Services (CDS) overview). A representation that is compiled into a target language is compilable computer code; configuring the final representation produced by the combination to be such compilable computer code reads on the recited limitation). It would have been obvious to one of ordinary skill in the art at the time the invention was made before the effective filing date of the claimed invention to configure the final representation produced by the Hejlsberg-Khot combination to be compilable computer code, as taught by Capire, which describes a toolkit used to “compile it into various target languages” (CDS Documentation, overview). A person of ordinary skill would have been motivated to produce compilable computer code as the final representation in order to obtain directly executable software from the validated intermediate representation, a predictable and intended result of compiling the representation. With respect to claim 6, Hejlsberg in view of Khot is silent to disclose, however, in an analogous art, Capire teaches wherein the compilable computer code is in a format that is at least partially proprietary (Capire discloses that “CDS is the backbone of the SAP Cloud Application Programming Model” (CDS Documentation, overview), that is, a format whose schema and definition are controlled by a single entity. Such a single-entity-controlled format is at least partially proprietary, which reads on the recited limitation) . It would have been obvious to one of ordinary skill in the art at the time the invention was made before the effective filing date of the claimed invention to provide the compilable computer code of the combination in the at-least-partially-proprietary CDS format taught by Capire, in which CDS is “the backbone of the SAP Cloud Application Programming Model” (CDS Documentation, overview). A person of ordinary skill would have been motivated to do so in order to generate code in a controlled, single-vendor format while obtaining the reliability benefits of the intermediate-representation-and-validation pipeline of the combination, a predictable result. With respect to claim 7, Hejlsberg in view of Khot is silent to disclose, however, in an analogous art, Capire teaches wherein the compilable computer code is a Core Data Services (CDS) model (Capire is directed to “Core Data Services (CDS)” and discloses that “CDS models are plain JavaScript objects complying to the Core Schema Notation (CSN)” (CDS Documentation, overview), which models the toolkit compiles into target languages. Producing the compilable computer code of the combination as such a CDS model reads on the recited limitation). It would have been obvious to one of ordinary skill in the art at the time the invention was made before the effective filing date of the claimed invention to provide the compilable computer code of the combination as a Core Data Services (CDS) model, as taught by Capire, which is directed to “Core Data Services (CDS)” and describes such models being compiled into target languages (CDS Documentation, overview). A person of ordinary skill would have been motivated to apply the combination to generate CDS models in order to automate the production of a declaratively-captured, compilable data model of the very type the reference describes, yielding a predictable result. With respect to claim 14, the claim is directed to a method that corresponds to the system recited in claim 2, respectively (see the rejection of claim 2 above) . 07-21-aia AIA Claims 4- 5 and 16-17 are re jected under 35 U.S.C. 103 as being unpatentable over An ders Hejlsberg et al., (“Introducing TypeChat”, hereinafter Hejlsberg – IDS 02/12/2026) in view of Tushar Khot et al. (“Decomposed Prompting: A Modular Approach for Solving Complex Tasks”, hereinafter Khot) and further in view of Denny Zhou et al. (“Least-to-Most Prompting Enables Complex Reasoning in Large Language Models”, hereinafter Zhou). With respect to claim 4, Hejlsberg in view of Khot is silent to disclose, however, in an analogous art, Zhou teaches wherein the prompts are sent to the LLM in an order determined by the tree structure (Zhou teaches a strategy that “reduces a complex problem into a list of subproblems, and then sequentially solves the subproblems” (Zhou, Abstract). Sequentially solving the subproblems in the order dictated by their decomposition—i.e., issuing the corresponding prompts to the language model in that dependency-determined order—reads on sending the prompts to the LLM in an order determined by the tree structure) . It would have been obvious to one of ordinary skill in the art at the time the invention was made before the effective filing date of the claimed invention to send the per-feature prompts of the Hejlsberg-Khot combination to the large language model in an order determined by the tree structure, as taught by Zhou, which “sequentially solves the subproblems” (Zhou, Abstract). A person of ordinary skill would have been motivated to adopt Zhou’s dependency-ordered solving so that each feature is generated only after the features on which it depends have been generated, predictably reducing the errors that would otherwise arise from generating a dependent feature before its prerequisite information is available. With respect to claim 5, Hejlsberg in view of Khot is silent to disclose, however, in an analogous art, Zhou teaches wherein the order places prompts corresponding to features that are dependent on other features behind prompts corresponding to the other features (Zhou teaches that “solving a given subproblem is facilitated by the model’s answers to previously solved subproblems” (Zhou, Abstract). Solving a dependent subproblem only after, and using the answers to, the subproblems it relies upon means the prompt for a dependent feature is placed behind the prompts for the features it depends on, which reads on the recited limitation). It would have been obvious to one of ordinary skill in the art at the time the invention was made before the effective filing date of the claimed invention to place the prompts for features that depend on other features after the prompts for those other features, as taught by Zhou, in which “solving a given subproblem is facilitated by the model’s answers to previously solved subproblems” (Zhou, Abstract). A person of ordinary skill would have been motivated to so order the prompts in order to make the answers required by a dependent feature available before that feature is processed, predictably improving the accuracy and validity of the merged combined intermediate representation. With respect to claims 16-17, the claims are directed to a method that corresponds to the system recited in claims 4-5, respectively (see the rejection of claims 4-5 above) . 07-21-aia AIA Claim s 12 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Anders Hejlsberg et al., (“Introducing TypeChat”, hereinafter Hejlsberg – IDS 02/12/2026) in view of Tushar Khot et al. (“Decomposed Prompting: A Modular Approach for Solving Complex Tasks”, hereinafter Khot) and further in view of Hirsch et al. (US Pub. No. 2013/0305218, hereinafter Hirsch) . With respect to claim 12, Hejlsberg in view of Khot is silent to disclose, however, in an analogous art, Hirsch teaches wherein at least one feature that is not in the plurality of features but that is in the natural language text is excluded from the plurality of features based on a selection of the at least one feature by a user in a graphical user interface (Hirsch teaches “an intuitive, user-friendly, graphical user interface” through which “the user may select, combine and customize various predefined and user-uploaded components, including modules” (Hirsch, paragraph [0023]), and that “selections are received from the user related to the customizable components presented to the user” (Hirsch, paragraph [0019]). By the user selecting, in the graphical user interface, which features are incorporated into the application, a feature that is presented but not selected by the user is excluded from those incorporated, which reads on excluding at least one feature, present in the natural language text, from the plurality of features based on a selection by a user in a graphical user interface). It would have been obvious to one of ordinary skill in the art at the time the invention was made before the effective filing date of the claimed invention to provide a graphical user interface by which the user selects which features are incorporated, as taught by Hirsch, such that a feature that is not selected by the user is excluded from the plurality of features, Hirsch teaching “an intuitive, user-friendly, graphical user interface” for “specifying the particular features, content, and layout of a desired mobile application” (Hirsch, paragraph [0023]). A person of ordinary skill would have been motivated to make this modification in order to give the user direct, code-free control over which features of the natural language request are acted upon, predictably ensuring the generated output reflects only the user-desired features. With respect to claim 20, the claim is directed to a non-transitory machine-readable medium that corresponds to the system recited in claim 12, respectively (see the rejection of claim 12 above) . Conclusion 07-96 AIA The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Yizhou Zhang et al. (“Guiding Large Language Models with Divide-and-Conquer Program for Discerning Problem Solving”) proposes to guide LLM with a Divide-and-Conquer program that simultaneously ensures superior expressive power and disentangles task decomposition, sub-task resolution, and resolution assembly process. (see abstract) . Hensley et al. (US Pub. No. 2025/0251932) a process including: obtaining, with a computer system, access to a code base; decomposing, with the computer system, the code base into parts; generating, with the computer system, documentation for the parts with a language model; associating, with the computer system, the documentation with the parts; indexing, with the computer system, the documentation; obtaining, with the computer system, a query searching for content in the code base; searching, with the computer system, using the index, the code base based on the generated documentation to identify documentation corresponding to the query and, then, content in the code base associated with the identified documentation; and responding, with the computer system, to the query, by identifying the content in the code base associated with the identified documentation. (see abstract). Any inquiry concerning this communication or earlier communications from the examiner should be directed to ANIBAL RIVERACRUZ whose telephone number is (571)270-1200. The examiner can normally be reached Monday-Friday 9:30 AM-6:00 PM. 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, Hyung S Sough can be reached at 5712726799. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /ANIBAL RIVERACRUZ/Primary Examiner, Art Unit 2192 Application/Control Number: 18/818,325 Page 2 Art Unit: 2192 Application/Control Number: 18/818,325 Page 3 Art Unit: 2192 Application/Control Number: 18/818,325 Page 4 Art Unit: 2192 Application/Control Number: 18/818,325 Page 5 Art Unit: 2192 Application/Control Number: 18/818,325 Page 6 Art Unit: 2192 Application/Control Number: 18/818,325 Page 7 Art Unit: 2192 Application/Control Number: 18/818,325 Page 8 Art Unit: 2192 Application/Control Number: 18/818,325 Page 9 Art Unit: 2192 Application/Control Number: 18/818,325 Page 10 Art Unit: 2192 Application/Control Number: 18/818,325 Page 11 Art Unit: 2192 Application/Control Number: 18/818,325 Page 12 Art Unit: 2192 Application/Control Number: 18/818,325 Page 13 Art Unit: 2192 Application/Control Number: 18/818,325 Page 14 Art Unit: 2192 Application/Control Number: 18/818,325 Page 15 Art Unit: 2192 Application/Control Number: 18/818,325 Page 16 Art Unit: 2192 Application/Control Number: 18/818,325 Page 17 Art Unit: 2192 Application/Control Number: 18/818,325 Page 18 Art Unit: 2192 Application/Control Number: 18/818,325 Page 19 Art Unit: 2192 Application/Control Number: 18/818,325 Page 20 Art Unit: 2192 Application/Control Number: 18/818,325 Page 21 Art Unit: 2192 Application/Control Number: 18/818,325 Page 22 Art Unit: 2192 Application/Control Number: 18/818,325 Page 23 Art Unit: 2192 Application/Control Number: 18/818,325 Page 24 Art Unit: 2192 Application/Control Number: 18/818,325 Page 25 Art Unit: 2192 Application/Control Number: 18/818,325 Page 26 Art Unit: 2192 Application/Control Number: 18/818,325 Page 27 Art Unit: 2192 Application/Control Number: 18/818,325 Page 29 Art Unit: 2192 Application/Control Number: 18/818,325 Page 30 Art Unit: 2192 Application/Control Number: 18/818,325 Page 31 Art Unit: 2192
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