DETAILED ACTION
This Action is a response to the filing received 29 January 2024. Claims 1-20 are presented for examination.
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 .
Priority
Applicant’s claim for the benefit of a prior-filed application under 35 U.S.C. 119(e) or under 35 U.S.C. 120, 121, 365(c), or 386(c) is acknowledged.
Information Disclosure Statement
The information disclosure statements (IDS) submitted on 13 May 2025 and 7 April 2026 are being considered by the examiner.
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 invention is directed to an abstract idea without significantly more.
At Step 1 of the eligibility analysis, the claims are evaluated for whether they fall within one of the four statutory categories of patent-eligible subject matter. Claims 1-7 are processes; claims 8-14 are articles of manufacture; and claims 15-20 are machines. The analysis therefore proceeds to Step 2. At Step 2A, Prong 1, the claims are evaluated for whether they recite (set forth or describe) a judicial exception, such as an abstract idea (MPEP §§ 2106.04 and 2106.04(II)(A)(1)). Abstract ideas include mental processes (MPEP § 2106.04(a)). A mental process is thinking that can be performed in the human mind with or without the use of pen and paper, or methods that can be performed mentally or are the equivalent of human mental work (MPEP § 2106.04(a)(2)(III)). Mental process steps may include observations, evaluations, judgments and/or opinions made by a human (id.). A claim that requires a computer may still recite a mental process (MPEP § 2106.04(a)(2)(III)(C)).
Claim 1 recites the following mental process steps: (1) determining, using directed edges of the graph structure, a set of precedent cells from which the code cell depends; and (2) inputting into a machine learning model the natural language command and values from the set of precedent cells pertaining to the code. Element 1 recites an observation, evaluation and/or judgment by a human user that, based on a graph structure representative of an operation, one or more precedent cells exist relating to a particular cell at which a user desires to generate code. Element 2 is an evaluation or judgment by a user that a particular natural language query may represent the desire to have code generated and which includes particular information (the command to generate code and values from the determined precedent cells) necessary to generate the code. In view of the foregoing, claim 1 recites a mental process, and the analysis proceeds to Step 2A, Prong 2.
At Step 2A, Prong 2, the claims are evaluated for whether they include additional elements that integrate the abstract idea into a practical application (MPEP § 2106.04(d)). Relevant considerations include whether the additional elements recite an improvement in the functioning of a computer or other field, implementing the abstract idea in a particular machine, or applying or using the judicial exception in some other meaningful way (MPEP § 2106.04(d)(I)).
Claim 1 recites the following additional elements: (1) receiving, in a code cell connected to a plurality of cells in a graph structure, a natural language command to generate code; (2) receiving, an output from the machine learning model, generated code; and (3) updating the code cell to include the generated code. Element (1) recites necessary pre-solution data gathering; that is, in order to generate code based on a natural language command or query, said command or query must be received to be acted on (MPEP § 2106.05(g)). Elements (2) and (3) recite the insignificant post-solution activity of receiving an output based on an input to a computer operation, and an insignificant application of the result (id.). Of note, element (1) does not describe generating or formulating the natural language command, though in at least some instances such generation could be performed mentally by a human user interacting with a machine learning model or artificial intelligence agent, as examples. Elements (2) and (3) merely recite receiving the output from the model and modifying the code cell to include the generated code, similar to including generated code at a particular portion of a code editing interface. Whether considered individually or in any combination of elements, these additional elements do not integrate the abstract idea into a practical application.
The analysis therefore proceeds to Step 2B, where the claims are evaluated for whether they recite additional elements that amount to significantly more than the abstract idea (MPEP § 2106.05). Here, the analysis with respect to Step 2A, Prong 2 is carried over, and each additional element or combination of elements is evaluated for whether it recites other than what is well-understood, routine and/or conventional activity in the field (MPEP §§ 2106.05 and 2106.05(II)).
Element (1) recites storing and retrieving information from memory, receiving or transmitting data over a network, or receiving data input into a computer interface, which are examples of well-understood, routine and/or conventional computing activities; that is, the natural language command is received, whether from a user or retrieved from local or remote memory or other storage (MPEP § 2106.05(d)). Element (2) recites similar concepts; that is, receiving the results of the command from the machine learning model, depending on whether the machine learning model is locally or remotely stored (id.). Element (3) recites storing information in local or remotely located memory and/or electronic recordkeeping; that is, storing or recording the code in a location in memory or in a record pertaining to the particular cell in the graph structure (id.). Whether considered individually or as an ordered combination, the additional elements recite well-understood, routine and/or conventional general-purpose computing functions.
In view of the foregoing, claim 1 is ineligible under 35 U.S.C. § 101.
Claims 8 and 15 are rejected for similar reasons as those of claim 1 as set forth above. Examiner notes that claim 8 recites a non-transitory computer-readable medium comprising memory with instructions encoded thereon and executable to cause one or more processors to perform the method of claim 1; and claim 15 recites a system comprising memory with instructions encoded thereon and one or more processors configured to execute the instructions to perform the method of claim 1. These additional limitations recite the use of a general-purpose computer as a tool to perform the abstract idea identified above, and therefore fail to integrate the abstract idea into a practical application or recite significantly more.
Claims 2, 9 and 16 additionally recite that the input into the machine learning model further includes contextual schema from a data frame indicated by the natural language command, which represents an evaluation or judgment by a human user as to what added information should be included in the machine learning input. This represents an additional mental process step.
Claims 3, 10 and 17 further recite that the values from the set of precedent cells pertaining to the code are computed from language of the precedent cells using a sequential ordering dictated by the directed edges. Based on a graph structure viewable by the user, this is an additional evaluation, observation and/or judgment by the user regarding which cells are precedent cells based on the graph structure. This represents an additional mental process step.
Claims 4, 11 and 18 further recite encoding the cells by aggregating project-level metadata and metadata for each cell while omitting outputs from each of the cells. This represents an additional observation, evaluation and/or judgment by the human user as to what information to encode for the cells based on other information regarding the project and the cells included in the graph structure. This represents an additional mental process step.
Claims 5, 12 and 19 further recite performing the encoding in response to a save operation, which represents an insignificant application, and therefore does not integrate the abstract idea into a practical application or recite significantly more.
Claims 6-7, 13-14 and 20 further recite that the machine learning model is a large language model into which a latent representation of the natural language command and the values from the precedent cells are input. This represents an additional observation, evaluation and/or judgment by the human user as to the format of and the information to be included in the input to the machine learning model, which represents an additional mental process step. Additionally and/or in the alternative, this represents a translation of data from a first format into a second format, recited at a high level of generality such that said translation may be performed mentally and/or by the use of pen and paper. This also represents an additional mental process step.
In view of the foregoing, claims 2-20 are also ineligible under 35 U.S.C. § 101.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. In particular:
Cerar et al., U.S. 2020/0174756 A1 (“Cerar”) teaches the following limitations of claim 1: A method comprising: receiving, in a code cell connected to a plurality of cells in a graph structure, a … command to generate code (Cerar, e.g., ¶76, “When a user creates workflow components at a visual level of representation … e-commerce platform 100 may be creating the code that underlies the visual representation …”); determining, using directed edges of the graph structure, a set of precedent cells from which the code cell depends (Cerar, e.g., ¶75, “one workflow component may contain an input condition … which flows into a next workflow component containing a compare and branching decision point …”); … receiving, as output …, generated code; and updating the code cell to include the generated code (Cerar, e.g., ¶76, “When a user creates workflow components at a visual level of representation … e-commerce platform 100 may be creating the code that underlies the visual representation …” See also, e.g., ¶74, “capabilities for providing different levels of representation may extend to adding new workflow components … user may be able to select and move across a spectrum of representations …” Examiner’s note: a user may add and edit a workflow component to a workflow (i.e., a command), and in response thereto, when the addition is done via the visual representation level, code is generated corresponding to the new or modified workflow component, to include consideration of inputs (i.e., from a precedent cell)).
Cerar does not more particularly teach that the command is a natural language command to generate code, input into a machine learning model along with values from the set of precedent cells pertaining to the code, and receiving code as output from the machine learning model. A complete review of the prior art shows that these additional limitations, when considered in combination with the other limitations of claim 1, are not clearly taught, suggested and/or rendered obvious by additional prior art references. This is at least consistent with similar findings made by the European Patent Office in a search report dated 7 April 2026 and a copy of which having been submitted into the record on the same date.
Examiner has identified particular references contained in the prior art of record within the body of this action for the convenience of Applicant. Although the citations made are representative of the teachings in the art and are applied to the specific limitations within the enumerated claims, the teaching of the cited art as a whole is not limited to the cited passages. Other passages and figures may apply. Applicant, in preparing the response, should consider fully the entire reference as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art and/or disclosed by Examiner.
Examiner respectfully requests that, in response to this Office Action, support be shown for language added to any original claims on amendment and any new claims. That is, indicate support for newly added claim language by specifically pointing to page(s) and line number(s) in the specification and/or drawing figure(s). This will assist Examiner in prosecuting the application.
When responding to this Office Action, Applicant is advised to clearly point out the patentable novelty which he or she thinks the claims present, in view of the state of the art disclosed by the references cited or the objections made. He or she must also show how the amendments avoid such references or objections. See 37 C.F.R. 1.111(c).
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Any inquiry concerning this communication or earlier communication from Examiner should be directed to Andrew M. Lyons, whose telephone number is (571) 270-3529, and whose fax number is (571) 270-4529. The examiner can normally be reached Monday to Friday from 10:00 AM to 6:00 PM ET. If attempts to reach Examiner by telephone are unsuccessful, Examiner’s supervisor, Wei Mui, can be reached at (571) 272-3708. Information regarding the status of an application may be obtained from the Patent Center system. For more information about the Patent Center system, see https://www.uspto.gov/patents/apply/patent-center. If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call (800) 786-9199 (in USA or Canada) or (571) 272-1000.
/Andrew M. Lyons/Primary Examiner, Art Unit 2191
Prosecution Insights