DETAILED ACTION
1. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
2. This communication is in response to the communication filed on 02/03/2026.
3. Receipt of Applicant’s Amendment filed 02/03/2026 is acknowledged. Claims 1-20 are pending in the application.
Information Disclosure Statement
4. The information disclosure statements (IDS) submitted are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Claim Rejections – 35 USC § 103
5. 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.
6. 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.
7. 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.
8. Claims 1-20 are rejected under the first inventor to file provisions of the AIA , 35 U.S.C. 103 as being unpatentable over the combination of Savalle et al. (Pub. No. US 2025/0060949 A1; hereinafter referred to as Savalle), in view of NPL – Andrew McNutt et al. “On the Design of AI-powered Code Assistants for Notebooks”; hereinafter referred to as McNutt).
As per claim 1, Savalle discloses a computing system, comprising:
one or more processors (See Fig. 2); and
one or more non-transitory computer-readable media that collectively store a code editor configured to execute computer-executable code within code cells of a code editor interface, the code editor interface including (See Figs. 6A-7B):
a first interface portion configured to receive user input for defining and editing a set of code cells within the first interface portion, each code cell of the set of code cells being independently executable by the code editor (See Figs. 6A-7B – cell-based notebook editor).
However, Savalle does not explicitly states - a second interface portion including a prompt editor displayed simultaneously with the first interface portion and configured to receive user input for defining and submitting natural language user instructions to a machine-learned generative model; wherein the code editor is configured to automatically modify at least one code cell of the set of code cells based at least in part on the natural language user instructions and an output of the machine-learned generative model in response to the natural language user instructions.
McNutt discloses - a second interface portion including a prompt editor displayed simultaneously with the first interface portion and configured to receive user input for defining and submitting natural language user instructions to a machine-learned generative model (See Figs. 4-8 – displaying simultaneously a prompt editor) wherein the code editor is configured to automatically modify at least one code cell of the set of code cells based at least in part on the natural language user instructions and an output of the machine-learned generative model in response to the natural language user instructions (See Figs. 4-8 – automatically modifying code cell).
Savalle and McNutt are directed to software program development, which are analogous prior art.
It would have been obvious to one ordinary skill in the art before the effective filing date of the claimed invention (first inventor to file provisions of the AIA ) to incorporate and combine Savalle’s large language model for code generation, which includes a prompt editor for said code generation; and further combine it with McNutt’s code assistants for Notebooks; thus, the combination allows the improvement of developers’ experience, by increasing programming productivity, while improving overall quality and robustness of code generated by large language model (See Savalle’s and McNutt’s abstracts and background/introduction).
As per claim 2, Savalle and McNutt disclose the computing system of claim 1 (See claim 1 rejection above, under the first inventor to file provisions of the AIA , 35 USC § 103), wherein the code editor is configured to: populate the at least one code cell with executable code generated by the machine-learned generative model in response to the natural language user instruction (See Savalle’s p. [0071] – executable code; also McNutt’s Figs. 4-8).
As per claim 3, Savalle and McNutt disclose the computing system of claim 2 (See claim 2 rejection above, under the first inventor to file provisions of the AIA , 35 USC § 103), wherein the code editor is configured to: receive, at the first interface portion, a first user input indicative of a modification to the executable code generated by the machine-learned generative model in response to natural language user instruction; and modify the executable code generated by the machine-learned generative model based at least in part on the first user input (See Savalle’s Figs. 6A-7B; also see McNutt’s Figs. 4-8).
As per claim 4, Savalle and McNutt disclose the computing system of claim 2 (See claim 2 rejection above, under the first inventor to file provisions of the AIA , 35 USC § 103), wherein the code editor is configured to: receive, at the second interface portion an additional natural language user instruction for the machine-learned generative model, the additional natural language user instruction indicative of a modification to the executable code generated by the machine-learned generative model in response to the natural language user instruction; and modify the executable code generated by the machine-learned generative model in response to the first user query natural language user instruction based at least in part on an output of the machine-learned generative model in response to the additional natural language user instruction. (See McNutt’s Figs 4-8 – second portion NL instructions and modifications to the code).
As per claim 5, Savalle and McNutt disclose the computing system of claim 2 (See claim 2 rejection above, under the first inventor to file provisions of the AIA , 35 USC § 103), wherein the code editor interface includes a third interface portion configured to receive user input for editing a pipeline using the executable code from the at least one code cell (See Savalle’s Fig. 6B – pipeline).
As per claim 6, Savalle and McNutt disclose the computing system of claim 2 (See claim 2 rejection above, under the first inventor to file provisions of the AIA , 35 USC § 103), wherein the code editor is configured to modify the at least one code cell by creating the at least one code cell and populating it with the output of the machine-learned generative model in response to the natural language user intruction (See Savalle’s Figs. 6A-7B; also McNutt’s Figs. 4-8).
As per claim 7, Savalle and McNutt disclose the computing system of claim 1 (See claim 1 rejection above, under the first inventor to file provisions of the AIA , 35 USC § 103), wherein: the one or more non-transitory computer-readable media collectively store a plurality of machine-learned generative models; and the second interface portion is configured to receive user input for defining and submitting natural language user instructions to the plurality of machine-learned generative models (See McNutt’s Figs. 4-8).
As per claim 8, Savalle and McNutt disclose the computing system of claim 1 (See claim 1 rejection above, under the first inventor to file provisions of the AIA , 35 USC § 103), wherein the machine-learned generative model includes a sequence processing model (See Savalles’s abstract – LLM).
As per claim 9, Savalle and McNutt disclose the computing system of claim 8 (See claim 8 rejection above, under the first inventor to file provisions of the AIA , 35 USC § 103), wherein the sequence processing model includes a large language model (See Savalle’s abstract – LLM).
As per claim 10, Savalle and McNutt disclose the computing system of claim 1 (See claim 1 rejection above, under the first inventor to file provisions of the AIA , 35 USC § 103), wherein: the first interface portion is configured to simultaneously display at least two code cells of the set of code cells; and the first interface portion is configured to receive user input to manipulate executable code within each of the at least two code cells of the set of code cells (See Savalle’s Figs. 6A-7B; also see McNutt’s Figs. 4-8).
Claim 11-12 are essentially the same as claims 1-2 except that it is set forth the claimed invention as a method, and it is rejected with the same reasoning as applied hereinabove.
As per claim 13, Savalle and McNutt disclose the computer-implemented method of claim 11 (See claim 11 rejection above, under the first inventor to file provisions of the AIA , 35 USC § 103), wherein, the method further comprises: receiving, by the one or more processors at the first interface portion of the code editor interface, a third user input for modifying the second code cell; and modifying, by the one or more processors, the second computer-executable code of the second code cell based at least in part on the third user input (See Fig. 6B – modifying second and third cell; also see McNutt’s Figs. 4-8).
As per claim 14, Savalle and McNutt disclose the computer-implemented method of claim 11 (See claim 11 rejection above, under the first inventor to file provisions of the AIA , 35 USC § 103), wherein: the code editor interface includes a third interface portion configured to receive user input for editing a pipeline using the first computer-executable code and the second computer-executable code (See Fig. 6B – pipeline; also see McNutt’s Figs. 4-8).
As peer claim 15, Savalle and McNutt disclose the computer-implemented method of claim 11 (See claim 11 rejection above, under the first inventor to file provisions of the AIA , 35 USC § 103), wherein: the second interface portion is configured to receive user input for defining and submitting natural language user instructions to a plurality of machine-learned generative models (See McNutt’s Figs. 4-8).
As per claim 16, Savalle and McNutt disclose the computer-implemented method of claim 11 (See claim 11 rejection above, under the first inventor to file provisions of the AIA , 35 USC § 103), wherein the machine-learned generative model includes a sequence processing model (See abstract – LLM; also see McNutt’s abstract).
Claims 17-20 are essentially the same as claims 11-14 except that they are set forth the claimed invention as a non-transitory computer-readable storage media, and they are rejected with the same reasoning as applied hereinabove.
Response to Arguments
9. Applicant's arguments have been considered but are moot in view of new ground(s) of rejection. In these arguments applicant relies on the amended claims and not the original ones. See above rejections under 35 USC § 103 for response to arguments.
10. Please see M.P.E.P. 2111 Claim Interpretation; Broadest Reasonable Interpretation [R-9]; 2111.01 Plain Meaning [R-9]: III. “Plain Meaning” Refers to the ordinary and customary meaning given to the term by those of ordinary skill in the art”
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. Claims must be given the broadest reasonable interpretation during examination, and limitations appearing in the specification but not recited in the claim are not read into the claims (See M.P.E.P. 2111 [R-I]).
Conclusion
11. Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP§ 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any extension fee pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to FRANCISCO JAVIER APONTE whose telephone number is (571)270-7164. The examiner can normally be reached on M-F: 8-4.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, James Trujillo can be reached on 571-272-3677. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/FRANCISCO J APONTE/Primary Examiner, Art Unit 2151 05/12/2026.
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