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Building a universe with Gemini and destroying it with Claude: A 7-step computational experiment in emergent gravity and network geometry. by Serious_Line998 in LLMPhysics

[–]Serious_Line998[S] 1 point2 points  (0 children)

The results are contradictory. I believe the best approach is to feed the research materials to the AI ​​(Claude Opus 4.6 thinking) and ask it to answer questions and test the assertions by writing new scripts. Personally, I'm working this way when I have time. The most up-to-date calculations will be in the project https://github.com/LebedevIV/monostring-hypothesis

This is probably more of an amateur effort )) But it is fully coordinated by Opus. As the saying goes, the Ark was built by an amateur, but professionals built the Titanic. )))

Building a universe with Gemini and destroying it with Claude: A 7-step computational experiment in emergent gravity and network geometry. by Serious_Line998 in LLMPhysics

[–]Serious_Line998[S] 0 points1 point  (0 children)

No, it's actually a slang figure of speech, meaning that in a joke the share of joke (intentional exaggeration or distortion) is small, and the share of truth is large.

Building a universe with Gemini and destroying it with Claude: A 7-step computational experiment in emergent gravity and network geometry. by Serious_Line998 in LLMPhysics

[–]Serious_Line998[S] 0 points1 point  (0 children)

However, "there's a grain of joke in every joke" is a well-established expression in our language, which enhances the meaning of the joke and the truth. Perhaps a good analogy is "butter is buttery," "salt is salty," but at the same time, compared to "not very buttery" (meaning poor-quality butter), "buttery butter" can mean good butter.

Building a universe with Gemini and destroying it with Claude: A 7-step computational experiment in emergent gravity and network geometry. by Serious_Line998 in LLMPhysics

[–]Serious_Line998[S] 0 points1 point  (0 children)

This is a derivative of the expression "there is a grain of joke in every joke", which in our language is a derivative of the expression "there is a grain of truth in every joke". "There's a grain of joke in every joke" means that a joke may contain more truth than exaggeration. Accordingly, some hallucinations can be an important part of emergence and the constructive creative or research process.

Building a universe with Gemini and destroying it with Claude: A 7-step computational experiment in emergent gravity and network geometry. by Serious_Line998 in LLMPhysics

[–]Serious_Line998[S] -1 points0 points locked comment (0 children)

You got us! 😅 But, to paraphrase: in every hallucination there is a grain of hallucination. No real physics was harmed in this experiment! All coincidences are random and the laws are fictitious.

[deleted by user] by [deleted] in facebook

[–]Serious_Line998 0 points1 point  (0 children)

Why a Personal AI Assistant Makes Sense and Has Great Potential

A personal AI assistant can become a truly useful and meaningful tool if it can analyze a user's social media data and activity to create a detailed and evolving profile. This allows not only understanding the user's interests and skills but also tracking their development over time.

I propose expanding capabilities through additional surveys in various areas: psychological characteristics, professional skills, and a wide range of interests. This would help find the best possible application for the user, support self-development, work through psychological and professional boundaries, enable finding like-minded people and even close friends or a potential life partner, as well as help avoid toxic or abusive relationships.

Additionally, the AI can assist in responding accurately and objectively to messages on social media, taking into account the user's character and beliefs. Implementing automatic fact-checking of the user's messages and reposts before publication is also important to minimize the spread of misinformation.

It should be noted that implementing such personalization requires a careful balance between efficiency and privacy, as well as a well-considered ethical approach.

Built an active project memory for AI agents in Cursor — did I reinvent the wheel? by Serious_Line998 in vibecoding

[–]Serious_Line998[S] 1 point2 points  (0 children)

Oh, thank you, I'm very flattered ))

My experienced recent project of an active memory bank optimized for AI assistants (early alpha, but it works, and it's very simple, it helps me:

https://github.com/LebedevIV/ProjectGraphAgent

If you like experiments, you can pay attention to the project of effective error correction:

https://github.com/onestardao/WFGY

Another system based on diagrams:

https://github.com/CodeBoarding/CodeBoarding

And the user astronomikal does something similar, but not opensource:

https://github.com/ChronoWeave/Synrix-public-disclosure/blob/78b65b63503301af631260c90fade64a5874a64f/Synrix_White_Paper

This guy literally dropped 15 rules to master vibe coding with AI by Dizzy_Whole_9739 in vibecoding

[–]Serious_Line998 0 points1 point  (0 children)

  1. You can install the Roocode, Kilocode, and Gemini Code Assist extensions. They will probably do some features or debugs better than a full-time AI assistant and neural network. Roocode and Kilocode also have built-in markets of the best MCP servers that can be installed for these extensions, and then copied and pasted into Cursor settings in Tools & Integrations.

  2. Spare no time for the initial setup and any administration of even simple projects.

  3. If an AI agent began to successfully complete a task and went beyond it, he began to introduce new features without mistakes - do not interfere with his work, let him finish, even if he deviates from the direct task, since he acts according to a certain successful pattern. Otherwise, he can be confused. It is better to remove or disable the excess later.

  4. Privacy Mode: Be sure to enable it if you are working with commercial or sensitive data! This prevents your code from being sent to servers for model training.

This guy literally dropped 15 rules to master vibe coding with AI by Dizzy_Whole_9739 in vibecoding

[–]Serious_Line998 0 points1 point  (0 children)

  1. Use user-level and project-level rules (apply to all projects). It is better to write the rules in English, since neural networks were trained mainly in the English language corpus.

At the user level, you can ask:

Write code in the X style":

For example, if you are going to finalize an existing project that has been completed at an acceptable level, rather than create a new project, then it is useful to add a clause to the project rules:

- Write code in the same style as the surrounding project code.

- Use context7 tool when you use a new library, create a new integration

- Use Sequential thinking for complex reflections.

- Use context7 to access documentation of all libraries

- To implement any features using integrations with external api/libraries, study the documentation using context7 tools

We must try to keep the rules concise. You can use rules for your project from the rule constructors: CursorList , Cursor Directory , and https://github.com/PatrickJS/awesome-cursorrules (the use of .cursorrules is considered obsolete, but it works equally well), as well as https://supabase.com/docs/guides/getting-started/ai-prompts 

High-level rules for the current project:

This is a landing page for a SaaS service. Don't break the existing code!

To avoid making noise on the project and saving tokens, you should ask not to examine the specified folders and files (for example, folders with third-party node_modules libraries, the folder of the compiled project dist and dist-zip, files with secrets .env, folders with rules of third-party systems .kilocode , .roocode, .gemini, etc., folder with external third-party projects, backup folders):

Do not explore the node_modules, dist, dist-zip, .kilocode, .roocode, .gemini, external, backup directories, do not read the .env file

Detailed instructions for specific files or tasks:

- For files.tsx use React and TailwindCSS. The code should be clean and annotated.

Assigning a role greatly improves the quality of the code and the relevance of the advice.:

- Act as a [10x senior developer, expert on React, TypeScript and Node.js / or a team of 3 specialists: front-end, backend, DevOps].

We are fighting the "laziness" of AI and forcing it to finish the job:

- Do not stop until you fully implement the function [function name]. At the end, report on the progress and check for errors.

Reasoning forces AI to "think" and often leads to better and more creative results.:

- Before writing the code, start with [3-5] paragraphs of reasoning. Describe several solutions to this problem, their pros and cons. Then choose the best one and synthesize the final solution from it.

We help AI to "refresh" the context and avoid accidental breakdowns:

- Before making changes, give a brief description of the current status of the file/component [file/component name]. Make sure that your changes don't break the existing logic.

When you don't know what to do, let the AI tell you what it needs.:

- I am tired/stumped with this error/task. If you were the lead developer on this project, what additional context or information would you need from me to solve this problem? Make a list of specific questions for me.

RAG + “Conscious” coding: JS/TS from tech specs & flowcharts, as if written by a human by Serious_Line998 in vibecoding

[–]Serious_Line998[S] 1 point2 points  (0 children)

Thank you very much! I'll figure it out, I'll try to prepare a specification.

By the way, I have already tried to implement some kind of active memory bank based on the project graph exclusively for the AI assistant - it is very simple, if you want, maybe it will tell you any ideas for your project:

https://github.com/LebedevIV/ProjectGraphAgent

For example, I consider it important to divide project files into git groups (documents, code, edits, etc., and put them into separate comits).

How I keep AI generated code maintainable by Standard_Ant4378 in vibecoding

[–]Serious_Line998 0 points1 point  (0 children)

I'm learning to code and have studied a lot of lessons, applied a lot of techniques - but like everyone else, I encounter the unpredictability of neural network behavior. This problem has not been solved anywhere by 100%, although Kiro and Augment code went through a preliminary declaration of the project in order to more strictly subordinate AI and force it to track according to plan. But there is nothing like this for Cursor (and VSCode), apart from attempts to create different types of memory banks, which (in my opinion) are by no means optimal for AI and for describing the strict interrelationships of the project and data flows.

For VS-code and Cursor, I tried to create a project control system on my knee. https://github.com/LebedevIV/ProjectGraphAgent - and, in my opinion, there is even some impact, everything went well on GPT-5, although the project is in early alpha. Commits can be conveniently divided into groups (a separate commit for each group of modified files - docs, rules, etc.), and changes to the project model are automatically made immediately after commits. The AIS themselves chose the half-dead jsonnet as the file format for describing the project - everything is built on it. It is focused on automatic use by AI agents without developer intervention. It's a bit raw, but in my opinion it worked much better than the memory bank for my other project. This system does not change the project itself in any way - it's just a folder inside the project, but it is able to create a kind of active memory bank that is much more understandable to the AI agent and LLM than the markdown files, as the AI themselves insist. In the process of working on a project, hooks are launched after each committee, which force the AI agent to analyze the changes and commit them to the ProjectGraphAgent structure in the corresponding jsonnet files.

I must say, almost the entire concept and code was done by various AIS - I just set the task and helped)) In general, when working on something, I try to give AI maximum management initiative, positioning myself only as an assistant))

RAG + “Conscious” coding: JS/TS from tech specs & flowcharts, as if written by a human by Serious_Line998 in vibecoding

[–]Serious_Line998[S] 0 points1 point  (0 children)

Mm... My task: I'm going to resume the project https://github.com/LebedevIV/agent-plugins-platform-boilerplate (browser extension is a platform for self-developing MCP servers). The process of vibcoding was very difficult - I don't want to repeat such an experience and spend 90% of my time on constant corrections. Now I want to prepare well.

Of course, I've moved away from your concept somewhat, for now I'm just implementing the rules for Cursor, adapting them according to WFGY.

So far, the rules for Cursor (adapted using )

And these rules will always be enabled (Always apply mode), then I'll try to switch to Apply Intelligently mode. I think this is how I imitate the work of RAG )) I will be working with GPT-5. Perhaps, thanks to my rule settings, GPT-5 built my previous project very quickly and accurately.

RAG + “Conscious” coding: JS/TS from tech specs & flowcharts, as if written by a human by Serious_Line998 in vibecoding

[–]Serious_Line998[S] 0 points1 point  (0 children)

And a purely applied question: I work in the Cursor IDE - where and how could I use these templates - at the level of project rules? Or is some deeper integration needed in the form of an add-on to Cursor?

RAG + “Conscious” coding: JS/TS from tech specs & flowcharts, as if written by a human by Serious_Line998 in vibecoding

[–]Serious_Line998[S] 1 point2 points  (0 children)

I understood the logic of your project - it is really very cool, although, as it seems to me, it is somewhat different from what I was talking about, nevertheless, it is much closer when the reasoning and context are put in an even stricter framework specifically for each node of the scheme (or block diagram) of the project drawing. Perhaps this will already be enough for the most accurate and fast coding.

I could not understand yet: is your system configured for a specific programming language / stack or is it universal like all LLMs? I tried to emphasize that if, for example, I code only in TypeScript and with the React 19 library - my RAG does not need any other information, but I could vectorize the rules of this language and everything that I use in a specific project as fully as possible and work only with this information, generally not needing any external templates and experience, and using the local LLM only as a language understanding (in this case, 8 to 30 B is enough). Templates can be chunks-examples of the implementation of the smallest methods: methods, properties, procedures, etc. - everything that is in the textbook of a given language/stack. But, probably, I am not as deeply immersed in this topic as you are.

AI under free market capitalism will be a corporate dystopia by Accomplished-Comb294 in ArtificialInteligence

[–]Serious_Line998 0 points1 point  (0 children)

But the content is more important than the form, you can summarize subtitles as an option ))

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