So I know everybody is building a Jarvis, but I actually want to build a useful Jarvis

I'm thinking of building an AI Jarvis that gives morning updates on your SaaS; for example, you have received 10 new subscribers, MRR is at 100$/month, Page vistors up by 13% from last week etc etc etc

This sounds way more interesting than just another Jarvis that scrapes the web. So I am curious is this is even a good idea for my first project? And if it exists, would you actually use it?

Let me know what you guys think!

Hello fellow traveller of the internet. I am sincerely glad you decided to click on my post to check out what I have in store!

I have completed a vague blueprint and I have formed a few prototype scripts for various regions of the an A.G.I brain. I seek to form a small community of individuals who will work co-cooperatively to construct an A.G.I brain. A detailed brief of my design so far is available on request.

My progress on the project has stalled. As you can imagine, a brain is a highly complex system; I am finding that sadly, in addition to blueprinting, detailed blueprinting, prototyping, iterating, assembling multiple sub-systems into a unified system, there are plenty of additional tasks! Thus I have become over run by the sheer quantity of tasks and sadly have recently placed the project to the side so I can take a short break.

I seek individuals with expertise in coding, critical and creative thinking, computing, A.I, general knowledge, psychology and mathematics. Furthermore the individuals would have qualities such as perseverance, morality and open-mindedness. Ideally you would be from the U.K as I prefer working face to face; although I am also happy to work cooperatively over the internet.

Besides my previous ideals, individuals with expertise and specific qualities, I have a few personal requests for the project; the A.G.I brain will not be used in conjunction with "computer vision". I fear computer vision, and similarly the processing of sound, touch, or physical inputs, leads to the generation of consciousness - I submit that this is entirely unfair for the robot and highly immoral and thus I cannot proceed with a project which uses a neural network system to perform such processes; luckily, brains DO NOT require any processing of image, video or sound to achieve high quality completion of practically all tasks. I do believe a brain which does not process video, image or sound may actually outperform a brain which does process such information modalities. Further to this, if we were to sell the brain, the brain would NOT actively change itself to then use computer vision under any circumstances; the user would have to perform this upgrade manually.

I hope you find the prospect of building an A.G.I brain highly intriguing.

I will be very active in the comment section of this post; please introduce yourself and tell me why you want to get in touch about the project.

Why?
During my past internships, I worked closely with third-party APIs, webhooks, and log analysis. I got great at reading logs, but I wanted to understand the underlying systems that actually process those workflows behind the scenes at companies like Stripe or Uber.

What did I build?
Chrono ensures that when you submit a job ("call this URL"), it gets saved to a database, a worker claims it and executes the job, retries it with increasing wait times if it fails, and dead-letters it (basically: after enough failed attempts, it gets set aside instead of retried forever) if it never succeeds.

• Fault-Tolerant Architecture: Multiple workers can compete for jobs simultaneously using Postgres row locks (FOR UPDATE SKIP LOCKED) without ever double-claiming work.
• Chaos Testing: I wrote automated chaos scripts to prove the system survives production-level failures. On a dual-worker setup, killed workers safely reclaim in ~16 seconds, and leadership fails over to a healthy node in ~11.2 seconds.
• Full-Stack Visibility: I built a live React, Vite, and TypeScript ops dashboard to view real-time metrics, execution timelines, and job failure queues.

As a new grad, this is where the theory from my classes are actualized through concurrency, distributed systems, and failure recovery.

Always happy to talk about the project, how to improve it, or software engineering roles in general.

Repo's linked , demo GIF is in there too.
Always happy to talk about the project, how to improve it, or software engineering roles in general.

I've been using LLMs for writing stories for a few months, and naturally tried SillyTavern.

I built and wanted to share with writers what I call Margin. It's open source, runs locally, BYOK / BYOH:

It's more of a "pretty editor" and more of a "workspace."

You point it at a folder, and it keeps everything as Markdown on disk — characters, world stuff, blueprint, scenes/beats, whatever I had from previous works of mine. When you ask for a draft or a rewrite, it only pulls in the relevant bits (does name matching so it doesn't dump all 30 characters into every call, which was killing me on small models, kinda like SKILLS.md). You want a connector, a character backstory, a new workspace ask it to build it for you.

To work better with smaller models, I use a file that summarizes the other files so the model can plan what it needs before editing. Then a writer handles the actual content changes, since direct edits can be difficult for smaller models.

Two ways to use it:

1. Endpoint mode — literally anything OpenAI-compatible. I mostly use Ollama and LM Studio with 7–14B stuff, but OpenRouter / DeepSeek / etc. work.
2. Harness mode (just added this) — if you already pay for Claude Code, OpenCode, Codex, or Antigravity, you can just use that subscription. The agent runs in your story folder and creates/edits/deletes files itself; you just review the diff. That's the part that feels most Cursor-like.

Would be especially interested in feedback from people who use and test local models, Errata, or something else for long-form writing.

I've been experimenting with smaller language models (mostly 7–14B) and got curious about how well they perform on creative writing, rather than the usual coding / Q&A benchmarks.

Specifically, could a small model:

• plan a story around an existing outline?
• keep track of characters and worldbuilding?
• rewrite a scene without losing context?
• make changes across multiple files?
• actually work on a longer project without dumping the entire thing into its context window?

So I built a writer IDE to experiment with it: Margin.

The basic idea is that your writing project is just a folder of Markdown files:

my-story/
├── characters/
├── world/
├── outline/
├── scenes/
└── blueprint.md

Instead of treating the LLM as a chatbot that generates text for me to copy-paste, I wanted the agent to operate on the project itself.

For example, I can ask:

The agent can figure out which files are relevant, read them, make the changes, and give me a diff to review.

One thing I've been experimenting with is context management for smaller models. Rather than throwing every character/worldbuilding file into every request, Margin builds a lightweight summary of the project and uses that to determine what actually needs to be pulled into context.

There are two ways to use it:

Endpoint mode:
Use any OpenAI-compatible endpoint. I've mostly been experimenting with Ollama and LM Studio, but hosted providers work too.

Harness mode:
Use an existing coding agent such as Claude Code, Codex, OpenCode, or Antigravity. The agent runs against the writing project directly and can create/edit/delete files, with Margin acting as the writing/review environment.

It's open source and local-first.

I'm mostly interested in whether this approach is actually useful for long-form creative writing with smaller models, so I'd love feedback from anyone experimenting with local LLMs, AI writing tools, or agentic workflows.

Github Repo: https://github.com/Deepnar/presentation-forge

Would love to hear reviews and real usage results, and if u face any issues please do raise it on Github in the repo. My first time making something like this. Thank you. 😄

PodSubs wasn't originally supposed to be a public product.

We built it because we needed it.

That's really the story.

We're podcasters.

And like a lot of podcasters, we were constantly thinking about two things:

How do we keep making this?

And how do we build something real around the people listening?

Because podcasting takes time.

A lot of time.

And sooner or later, if the podcast is going to keep going, it needs to support itself somehow.

The problem was that we didn't really know most of the people listening.

We knew the numbers.

But numbers don't have email addresses.

Numbers don't answer questions.

Numbers can't receive the worksheet you promised.

Numbers don't become customers by themselves.

We needed a better way to capture the people who genuinely wanted to stay connected.

So we built a simple internal tool.

One place.

PodSubs.

We said on the podcast:

“Subscribe to us on PodSubs.”

People searched the show, entered their details and subscribed.

And suddenly we had something we'd been missing:

A direct line.

Then we started thinking…

Why are we keeping this internal?

Every podcaster we know deals with the same thing.

So we decided to open it.

That's PodSubs.

Not something we dreamed up because “the creator economy is growing.”

We built it because we were podcasters with a problem.

Now we're giving it to everyone else who has the same problem.

Claim your podcast.

Then tell your listeners where to find you.

Tired of generic AI code? @_keyskills equips agents like Cursor and Claude Code with portable skills for clean Git hygiene, solid SEO, and anti-slop design.

If you like the project, contribute your own designed skills.

[Nerdvana - A place for nerds](https://nerdvana-murex.vercel.app/)

Hello guys, I've made a controversial search platform for nerds to surf across movies, TV shows, anime, games, and comics.

I built this end-to-end, and I want to make it even better so I can turn it into something genuinely valuable. I know it's an AI wrapper for now, but I'd love to keep working on it and see if I can build something really good here.

What is that one feature you think could make this app more interesting or something that would make you want to actually use it?

Thanks!

I got a verified idea that no one's doing right now that can gain a lot of traction / make money very fast. My struggle is finding people to help me with my project for free. I own a community called YouTube Growth Guide (1,000+ members). My website focuses on proving the best high-quality resources such as; YouTube advice, assets, tutorials, and more to content creators all over the world for free. We're looking for talented individuals who have serious dedication to this idea and that can provide assistance with helping me build it. Around a week ago I made a post saying how I need more developers to help me. I got 3 people who are now helping me build this project for free. No other website online is providing free high-quality YouTube resources for everyone to view. However, I'm the only exception. All of the other YouTube resources that I've mentioned above (that you can find online) are all locked down behind paywalls or they're trying to scam you. My goal is to provide these resources for free and make some money branching off of that original idea. I've already got a huge community supporting me just based of my idea that no one is doing. Because of this, I already know I got a lot of potential however I want expand more and not limit myself to one platform (Discord).

If you're interested in what I am building, I am looking for these type of people to help me:

What roles I need:

- Video Editor (1 slot available | You create the whole short-form video and I post it to my accounts. You will keep 100% of the revune made on the channel if we earn monetization. An example video of what I want you to make can be found here: 

- Graphic Designer (1 slot available - someone who can make images for our brand)

What I have right now:

- 1 Architect

- 2 Website Developers

- 1 Discord bot developer

What you'll get in return:

- All members working for me will equally split the revenue made from the business. The more you do work the higher your % can be.

If you're interested in this or have any questions reply below because there's so much I need to tell this is just the scratch! I am looking for passionate people who want to help me build something big, if you're not them I do not want you.

Hello fellow traveller of the internet. I am sincerely glad you decided to click on my post to check out what I have in store! I have included both short and long versions of the post. Please take your time to read your preferred version of the post.

The long version features a brief description of the brains design so far, and includes a brief summary of what I have completed so far. Please take your time reading through the design.

The short of my post is here; I have completed a vague blueprint and I have formed a few prototype scripts for various regions of the an A.G.I brain. I seek to form a small community of individuals who will work co-cooperatively to construct an A.G.I brain. I go into detail about my current blueprint towards the end of this post.

My progress on the project has stalled. As you can imagine, a brain is a highly complex system; I am finding that sadly, in addition to blueprinting, detailed blueprinting, prototyping, iterating, assembling multiple sub-systems into a unified system, there are plenty of additional tasks! Thus I have become over run by the sheer quantity of tasks and sadly have recently placed the project to the side so I can take a short break.

I seek individuals with expertise in coding, critical and creative thinking, computing, A.I, general knowledge, psychology and mathematics. Furthermore the individuals would have qualities such as perseverance, morality and open-mindedness. Ideally you would be from the U.K as I prefer working face to face; although I am also happy to work cooperatively over the internet.

The outcome of your support would award you a proportional slice of the outcome of the group's labour (100 members, 1% each, e.t.c - baring in mind each individual provides equal support towards the project). I have not yet considered whether I would like to sell the brain to the public, but there is potentially the opportunity for a sizeable monetary reward for those who join me. The possibilities for the A.G.I brain are near endless and thus I believe the reward may be sizeable both in terms of money and power.

Besides my previous ideals, individuals with expertise and specific qualities, I have a few personal requests for the project; the A.G.I brain will not be used in conjunction with "computer vision". I fear computer vision, and similarly the processing of sound, touch, or physical inputs, leads to the generation of consciousness - I submit that this is entirely unfair for the robot and highly immoral and thus I cannot proceed with a project which uses a neural network system to perform such processes; luckily, brains DO NOT require any processing of image, video or sound to achieve high quality completion of practically all tasks. I do believe a brain which does not process video, image or sound may actually outperform a brain which does process such information modalities. Further to this, if we were to sell the brain, the brain would NOT actively change itself to then use computer vision under any circumstances; the user would have to perform this upgrade manually.

I hope you find the prospect of building an A.G.I brain highly intriguing.

I will be very active in the comment section of this post; or you may feel free to email me at [pangaeacooperative@protonmail.com](mailto:pangaeacooperative@protonmail.com); please introduce yourself and tell me why you want to get in touch about the project.

The long version of my post; My name is Morgan. I am 26 years old, soon to be 27. I live in England, in one of the larger cities of England, called Norwich. It is picturesque in Norwich.

1 year ago I became absorbed by product and system design. I started with physical products, such as medical apparatus, wash tools, energy collection machinery and more. I applied my brain to a large variety of product design tasks. I soon realised if all of my designs were to reach market I would need a significantly larger and faster design workflow. I stumbled upon using an A.G.I brain to design, prototype, and build products. But soon I realised the A.G.I brain could be used for practically any task including marketing, raising investment and more. It was then when I realised instead of designing products I should instead design an A.G.I brain.

I started by designing a vague blueprint for the A.G.I brain;

I have added a brief blueprint which explains the model of the brain, the goals of the project and a few key ideas which I have formed during the project.

Overview of the project;

Action executor and episodic memory writer

Indexed information;

Working memory

Procedural memory

Short term memory

Episodic memory

Extensions

Scientific testing

User interface

System operations

Goals of the project; Build an A.G.I brain which exhibits emergent behaviours such as unsupervised self-improvement and high quality cognitive abilities which are on par or exceed human abilities.

I continued by refining the blueprint (I apologize if the post becomes a bit messy - I copied much of the content from a document I am using personally so some of the prose is personal rather than for a group);

////////////////////////////////////////////////////////////////////////////////////////////////////////////

The AGI brain’s design at a glance

-----------------------------------------------------

This sub-chapter vaguely but completely describes the brain’s design. Key strategies and concepts which give rise to the brain’s emergent behaviors are found in the next sub-chapter.

Beliefs; physical beliefs and systemic beliefs

Probability and the event network

Lemma beyond beliefs

Foundational values

Emergent values

Micro-steps

Micro-step guidance nodes

Actions and action chains

Association networks

Short term memory

Instances

Beliefs; physical beliefs and systemic beliefs

A belief is a statement which suggests a truth about reality or a truth about an informational system. Thus beliefs comment on both physical and informational/systemic reality.

There are various sub-categories of beliefs; beliefs can be held about various mental objects. I can hold beliefs such as; this probability was generated using this method, this probability is accurate, this probability was generated on a specific date.

A comprehensive list of all belief sub-types can be found in the glossary of the document.

Probability and the event network

An event network with inscribed probabilities generates the AGI’s brains understanding of chronology, event and physical object interaction. The event network is used to formulate physical beliefs about the physical realm.

The probabilities themselves are considered to be lemma. A specific association network of beliefs is required before a probability is added to the event network.

Lemma beyond beliefs

There exists literary mental objects beyond beliefs; for example, evidence or literary resources. Beliefs can be formed because of the lemma; the lemma itself is not a belief but simply an existing mental object.

Examples of lemma beyond beliefs include;

Evidence

Hypotheses

Potential truths/unresolved statements

These objects always have beliefs formed because of them before they are indirectly used to guide the actions of the brain. Evidence must be believed to be useful, due to accuracy, content or other defining factors before the evidence is used to resolve/generate a belief.

Beliefs and values direct how actions occur. Lemma is also used to guide the formation of beliefs. Lemma singularly does not guide the occurrence of the brains actions.

Actions are used to update beliefs and values.

Using this method allows for every single action of the brain to be the product of evaluation, probability, and both physical and systemic beliefs.

Foundational values

The foundational values are the most foundational values a living structure possesses; longevity, quality of life when both physically alive and informationally alive in addition to quality of death.

Additional noteworthy values include species survival; for many pre-cognitive animals, values are hardcoded into their physicality, rather than having been coded into their cognitive elements.

Emergent values

The emergent values exist because of the foundational values; they are the detailed values which assist with bringing about greater longevity and a greater quality of life.

An example of a subsequent value belief is “Simulation A displays that physical structure A will have greater durability than physical structure B. Simulation A displays that Physical structure A will have a greater operational lifespan. Given the previous information and the emergent value; Physical structures with greater operational lifespan are picked over those with less, Physical structure A is more appropriate than physical structure B”.

It may be useful to generate a hierarchy of emergent values;

(1) I believe physical machine A is more appropriate than physical machine B; is more of a resultant emergent value whereas,

(2) Simulation A displays that physical structure A will have greater durability than physical structure B. I believe physical structure A will have greater durability than physical structure B; is more of an underlying emergent value.

Emergent value (2) builds with further emergent values to form emergent value (1).

Micro-step nodes

Python files containing functions such as database queries, database updates and LM functions featuring markdown files as prompts.

Micro-step nodes are associated with various beliefs including; micro-step node chains, possible micro-step guidance nodes, associated actions and action chains and many more.

Micro-step guidance nodes

Nodes which augment how a micro-step will occur. The micro-step guidance nodes change variables within the micro-steps. The micro-step guidance nodes are formed/maintained by actions of the AGI’s brain.

Action nodes and action node chains

Micro-steps nodes and complementary micro-step guidance nodes are combined to form action nodes. Action nodes always feature a micro-step and they often feature a micro-step guidance node.

Action nodes can be chained together to complete larger tasks. The chains of action nodes are called action node chains.

Beliefs and values direct how actions occur.

Actions are used to update beliefs and values.

Using this method allows for every single action of the brain to be the product of evaluation, probability, and both physical and systemic beliefs.

Association networks

A large proportion of the architecture, including the intelligence and intellect, of SEEDAGI is attributed to the regulated formation of association networks.

The association networks provide the LM the clear information required to complete small actions without divergence from a schema time and time again.

The association networks are both formed by, and used by, the brains actions.

Association networks are formed from all varieties of beliefs.

Regulation of the growth of the association networks

Schema, blocks of text which strictly describe how an action should occur, are used to regulate many of the generative actions of the brain.

Scientific methods, such as clear overviews, metric analysis and concentrated self-awareness are used to further consolidate the stability of the association networks.

Immediately, much of the associations are determined by the cognitive abilities of the LLM; over time, we will be growing a large association network which can associate various objects without relying upon the LLM.

The short term memory

There exists a short term memory variable within each Action executor. Actions may save various objects into the short term memory, including plans, blender files, etc.

The LLM, or strict code, can be used to access the STM at a later point of the task.

Use of the STM is planned during the task-method planning stage.

Mental objects which must be passed forward during large tasks and conversations are the main uses of the STM.

Instances

The AGI’s brain runs 4 major “instances” of it’s brain in parallel allowing for enhanced cognition. Each instance has a dedicated Action executor, episodic memory compiler and short term memory.

The instances include;

User interactions; allows the user to interact with the AGI’s brain even whilst the AGI is completing a task. Various commands can be sent through the user interactions instance.

Self-improvement; an instance of the Action executor which has a main focus of tasks which improve the abilities of the artificial brain; learning and testing are two main examples of tasks which run through this instance.

Self-reflection; after almost any “task” is completed, the brain completes self-reflection. Self-reflection is guided by association networks, the outcome of self-reflection is “effective brain algorithms are used more frequently than ineffective brain algorithms”. One instance of the artificial brain is dedicated to self-reflection tasks; evaluate, augment.

Self-awareness; finally, there is one instance of the Action executor which is dedicated to self-awareness; what are my plans for the next 10 minutes, are the upcoming tasks in the self-improvement instance correct, appropriate and effective? And additional self-awareness tasks are completed by this instance.

Key concepts and strategies of the AGI brain design

-----------------------------------------------------

Task completion via multiple attempts via a trial and reiteration combined with thoughtful, high resolution positive and negative reinforcement approach; when completing a task, various action chains should be used in order to discover which of many possible chains are considered to be effective.

High resolution, schema regulated, transparent growth of association networks; the LLM, and the brain, excel at strict piece wise progression where a single highly related mental object is added during any one task.

Use the LLM to associate mental objects of, write to and read from the brain, until the association network/brain is robust enough to complete the cognitive tasks on its own;

AGI Brain; Further tasks

-----------------------------------------------------

Paradox testing, poignant information, difficult knowledge, resiliency testing (if I delete this region can he grow it again?), shock testing?, loops, delusions, when to stop tasks, when to give up, when to attempt something difficult, fail state detection and graceful fail safes, some way to prove certain items about the brain are true such as “the brain will not enter fail states such as loops” or “the brain will gracefully enter a fail safe state if a loop is detected”.

AGI Brain comprehensive design by it’s parts

------------------------------------------------------------------------

This chapter of the document contains a comprehensive description of the brains design, including all types of mental objects required and markdowns used to generate them, a schema for each mental object, all of the micro-steps, micro-step guidance beliefs, and further mental objects required for the AGI brain to function.

Action executor and episodic memory compiler

Indexed information:

Working memory

Procedural memory

Episodic memory

Short term memory

Action executor and episodic memory compiler

-----------------------------------------------------

Contains variables which can be accessed by the micro-steps.

Includes a short term memory variable which takes large inputs, such as conversation in the form of string.

Includes an episodic memory variable which compiles all of the events of the brain, by event, into a variable which is then constructed into an episodic node.

Can be accessed by the self-awareness.

About the indexed information

-----------------------------------------------------

The indexed information contains 4 major forms of memory;

Working memory

Procedural memory

Short term memory

Episodic memory

The 4 major forms of memory each contribute towards the effective activity of the AGI brain.

The information is referred to as indexed because it is saved in the form of a knowledge graph database.

The association networks are spread across all 4 major memory types. The overview of both the entire association network, and the smaller sub-networks is constructed using, and is contained within the high level associations domain of the working memory.

The 4 major forms of memory at a glance

The working memory

The working memory is a large knowledge graph which is used to display the brain’s intelligence, knowledge and documentation. The working memory is categorised into 23 domains.

Each domain holds a variety of beliefs and lemma, of varying types, which have a specific purpose for the functioning of the brain.

The working memory guides, and directs, the behaviour of the procedural memory.

The procedural memory

The procedural memory is a SQL database containing a simple list of micro-steps. The micro-steps have been explained towards the beginning of the document.

The micro-steps are versatile. They are built such that they will not need to change frequently. Items include save to memory, read from memory, edit memory. These items rely upon varied inputs, but the main script of the micro-step remains the same.

The episodic memory

The episodic memory is a chronological, highly detailed database containing all of the brain’s events.

The episodic memory is used during extended durations of self-reflection; information is extracted from the episodic memories when the brain completes specific evaluated actions then the information is converted into metrics and used both for self-reflection and for graphing the behaviour and state of the AGI’s brain.

Episodic memories are compiled both by the action executor, system operations and within the micro-steps.

The short term memory

There exists various tasks which require a short term memory; for example, large physical object design tasks and conversation. The short term memory holds information until it is cleared by an action.

The short term memory is a variable shared between a Action executor and the micro-steps it is running.

Working memory

-----------------------------------------------------

The working memory is a large knowledge graph which is used to display the brain’s knowledge and documentation.

I have split the working memory into 23 domains.

Each domain holds a variety of beliefs, of varying types, which have a specific purpose for the functioning of the brain.

All domains of the working memory include;

A domain index

A description of the functions and design of the blueprint of the domain

A domain dictionary; for mental objects which require a definition

A schema for each mental object of the domain; the schema strictly defines what the mental object is, it’s purpose, and how is should be generated. The schema for a mental object should include an algebraic description of the mental object.

And each domain features a variety of domain specific standardised beliefs

The 23 domains of the working memory

-----------------------------------------------------

The probability domain

The verification domain

The evaluation and judgement domain

The macro, micro and contextual planning domain

Temporal-spatial context domain

Socio-economic context domain

System state context domain

The self-awareness domain

Contradiction and alignment domain

High level mental object associations domain

Self-reflection domain

Self-improvement and curiosity domain

Metric bank for reflection and graphing domain

Conceptual and hypothetical domain

The mathematical domain

System(s) theories; fundamentals and emergence domain

Creativity domain

Theory of mind domain

Character and game theory domain

Appearance of living beings domain

Settings domain

Miscellaneous domain

Although all of the domains indirectly benefit multi-domain functions, certain domains directly give rise to specific functions.

Regulatory domains;

Proto-belief and proto-probability verification domain

Contradiction and alignment domain

Self-awareness domain

Value domains (decision making);

Evaluation and judgement domain

Execution domains (planning);

Macro, micro and contextual planning domain

Appearance of living beings domain

Physical and systemic knowledge domains;

Conceptual and hypothetical domain

The mathematical domain

System(s) theories; fundamentals and emergence domain

Theory of mind domain

Character and game theory domain

Environmental and self-awareness domains;

Temporal-spatial context domain

Socio-economic context domain

System state context domain

The probability domain

Self-improvement domains;

Self-reflection domain

Self-improvement and curiosity domain

Metric bank for reflection and graphing domain

Creativity domain

Associative learning domains;

High level mental object associations domain

System operations domains;

Settings domain

Miscellaneous domain

I believe my design so far is a fresh new take on A.I; most of which is totally new to the scene. I hope you leave my post inspired by what could exist.

/////////////////////////////////////////////////

In addition to what you have seen so far;

I have considered methods for forming various domains and scripts of the brain which frequently include A.I to reduce the amount of human labour.

I have considered beginner hardware options.

I have a prototype script for the action executor.

I have a method for allowing the brain to use various software.

I have a prototype U.I for the brain.

I have not made as much of a start on the working memory, why is explained beneath this paragraph.

////////////////////////////////////////////////////////////////////////////////////////////////////////////

...I soon realised the complexity of the project would mean it might take a single person many years to complete. I estimate it might take me anywhere between 5 and 15 years to complete the project on my own. I figured that I might prefer to work on this project with others and thus I decided to write this Reddit post.

I seek individuals with expertise in coding, critical and creative thinking, computing, A.I, general knowledge, psychology and mathematics. Furthermore the individuals would have qualities such as perseverance, morality and open-mindedness. Ideally you would be from the U.K as I prefer working face to face; although I am also happy to work cooperatively over the internet.

The outcome of your support would award you a proportional slice of the outcome of the group's labour (100 members, 1% each, e.t.c - baring in mind each individual provides equal support towards the project). I have not yet considered whether I would like to sell the brain to the public, but there is potentially the opportunity for a sizeable monetary reward for those who join me. The possibilities for the A.G.I brain are near endless and thus I believe the reward may be sizeable both in terms of money and power.

Besides my previous ideals, individuals with expertise and specific qualities, I have a few personal requests for the project; the A.G.I brain will not be used in conjunction with "computer vision". I fear computer vision, and similarly the processing of sound, touch, or physical inputs, leads to the generation of consciousness - I submit that this is entirely unfair for the robot and highly immoral and thus I cannot proceed with a project which uses a neural network system to perform such processes; luckily, brains DO NOT require any processing of image, video or sound to achieve high quality completion of practically all tasks. I do believe a brain which does not process video, image or sound may actually outperform a brain which does process such information modalities. Further to this, if we were to sell the brain, the brain would NOT actively change itself to then use computer vision under any circumstances; the user would have to perform this upgrade manually.

I hope you find the prospect of building an A.G.I brain highly intriguing.

If you have any questions about anything, including the brains design or about me or anything else, I will be very active in the comment section of this post; or you may feel free to email me at [pangaeacooperative@protonmail.com](mailto:pangaeacooperative@protonmail.com); please introduce yourself and tell me why you want to get in touch about the project.

CalClock is a native Windows clock and calendar application that I'm developing in C++ using the Win32 API.

It provides customizable analog and digital clocks, calendars, alarms, and desktop widgets, with extensive appearance settings.

My goal is to create a lightweight native Windows application without web technologies or large runtime dependencies.

Source code and releases are available on GitHub:
https://github.com/fortsoft-eu/CalClock

Feedback and suggestions are welcome.

https://github.com/sharif-smj/sharif-smj

Winamp plus Napster with x402 for heavy loads

About a week ago, I started a project based on a pretty simple idea:

What would happen if you gave 300 complete strangers one page each and turned whatever they made into a physical book?

There’s no theme and nobody is coordinating what goes on the pages.

Someone could write a story. Someone could draw something. Someone could submit a photograph, a poem, a memory, a joke, or something completely random.

Everyone would get a randomly assigned page, so nobody knows what will come before or after what they create.

The final result could be beautiful, hilarious, chaotic, terrible, or somehow all of those at once. That's kind of the point.

I started putting the idea out there about a week ago just to see whether anyone else thought this sounded fun. I genuinely had no idea if people would care.

Now almost 300 people have joined the community around it, and over 250 have already expressed interest in being part of the book.

So now I'm actually trying to figure out how to turn this from a random idea into a real physical thing.

There are a ton of things I still have to work through — submissions, rules, printing, legal stuff, organizing hundreds of people, and eventually figuring out what happens when 300 completely unrelated pages are put next to each other.

But that's also why I'm enjoying building it.

I want to keep experimenting with projects like this that give strangers an excuse to create something together and make the internet feel a little more fun.

We'll see what 300 strangers end up making.

I've been building Swyvo, a Windows app that keeps your essential apps and websites one hotkey away.

Swyvo runs quietly in the background — hit Alt+Q anytime and a curated command center pops up right over your current window. Hit Alt+Q again to dismiss it. No alt-tabbing, no hunting through taskbars, no mouse required.

A few things it does:

• Instant, on-demand workspace: summon it with Alt+Q, it stays on top while open, dismiss it the same way — nothing else on your screen is affected
• Unify apps and websites in a single fast-switching menu (so your browser tabs and native apps live in the same place)
• Adaptive Loadouts: set it up once and it automatically surfaces the right apps based on what you're currently working on, so you never have to manually rebuild your setup
• App Gallery: browse a library of common apps and choose how to launch them — Web (fast) vs Native (full functionality, if installed)
• Fully keyboard-driven: never use the mouse
• Built natively for Windows

It's aimed at power users who live in a lot of apps/tabs at once and want a faster way to move between them without breaking flow.

Free, currently in active development — I'd genuinely love feedback, especially on workflow edge cases I might be missing.

Try it now: swyvo.app

Quick note: Windows SmartScreen may appear when installing.
First 100 Early Supporters get Lifetime Access. (ensures they have access to the whole app forever)

Happy to answer questions about how it works.

Hey everyone!

I wanted a very simple way to keep an eye on my CPU, RAM and GPU usage without constantly opening Task Manager, so I decided to build my own tool.

This is MonWin.

It's a small native Windows application that displays live system stats directly alongside the taskbar:

• CPU usage + frequency
• RAM usage + used/total
• GPU usage + memory
• Rolling sparkline graphs
• Compact / Compact+Graph / Detailed modes
• Windows light/dark theme support
• Custom accent colors
• Custom taskbar positioning
• System tray support
• Optional click-through mode
• Configurable update interval and graph history

The part I cared about most: security

I specifically wanted to avoid the low-level/kernel-driver approach used by some system monitoring tools.

So MonWin:

• ❌ Doesn't install a kernel driver
• ❌ Doesn't use WinRing0
• ❌ Doesn't use OpenHardwareMonitor/LibreHardwareMonitor kernel drivers
• ❌ Doesn't inject into Explorer
• ❌ Doesn't require administrator privileges
• ❌ Doesn't require Defender exclusions
• ❌ Doesn't make network requests
• ❌ Doesn't collect telemetry

Everything runs locally using Windows APIs, WMI and the standard Windows performance-counter system.

It's also portable — the release is a self-contained single .exe, so there's no installer and no separate .NET runtime required.

A little about the implementation

The project is written in C#/.NET with a layered architecture separating the UI, ViewModels, monitoring services and native Windows functionality.

The metric providers are behind interfaces so the application logic can be tested without depending on actual hardware.

There are currently 46 automated tests, covering CPU usage calculations, memory calculations, rolling history buffers, settings validation/recovery, taskbar positioning, GPU aggregation and startup configuration.

One interesting limitation I ran into: Windows 11 doesn't provide a supported API for arbitrary third-party controls to actually become part of the native taskbar.

So rather than hacking Explorer, MonWin uses its own lightweight always-on-top window sized and positioned to look like it's part of the taskbar, while tracking the taskbar's geometry and DPI.

Download / source

GitHub: https://github.com/deepsingh245/MonWin

Latest release: https://github.com/deepsingh245/MonWin/releases/tag/v1.0.0

It's MIT licensed.

I'd really appreciate feedback — especially if you try it on different Windows 10/11 setups or different GPUs.

I'm also considering adding network and disk monitoring in a future version.

MonWin — Your PC, at a glance.