u/mercurias98

Most so called second brain tools are just storage with a search bar. You capture something, it sits there, you retrieve it later if you remember to look. That is not a second brain, that is a better organised pile.

A real second brain should work on continuity. Your thoughts do not exist in isolation, they build on each other, contradict each other, cluster around themes you did not even consciously notice. A system that just stores and retrieves is missing the entire point.

Here is how I have been thinking about building aevron.co

When you capture something it does not just get filed away. It gets tagged and connected to everything else you have put in. Not just because the topics sound similar but with actual reasoning on why two ideas are linked and what that connection actually means. Contradictions between your own captures get flagged. Insights get generated from the connections not just the individual ideas in isolation.

Then it goes a layer deeper. When a cluster of connected ideas starts forming around a theme you never explicitly labeled, the system identifies it and synthesises across the whole cluster. Not just these things are related but here is the actual thesis sitting underneath all of them.

Every time you open it there is something already developed waiting. Connections made, contradictions flagged, insights generated, themes synthesised. All from what you put in.

That is at least my version of what a second brain should actually do

Most so called second brain tools are just storage with a search bar. You capture something, it sits there, you retrieve it later if you remember to look. That is not a second brain, that is a better organised pile.

A real second brain should work on continuity. Your thoughts do not exist in isolation, they build on each other, contradict each other, cluster around themes you did not even consciously notice. A system that just stores and retrieves is missing the entire point.

Here is how I have been thinking about it.

When you capture something it does not just get filed away. It gets tagged and connected to everything else you have put in. Not just because the topics sound similar but with actual reasoning on why two ideas are linked and what that connection actually means. Contradictions between your own captures get flagged. Insights get generated from the connections not just the individual ideas in isolation.

Then it goes a layer deeper. When a cluster of connected ideas starts forming around a theme you never explicitly labeled, the system identifies it and synthesises across the whole cluster. Not just these things are related but here is the actual thesis sitting underneath all of them.

Every time you open it there is something already developed waiting. Connections made, contradictions flagged, insights generated, themes synthesised. All from what you put in.

That is at least my version of what a second brain should actually do

One very common misconception in AI i notice is people think a very detailed prompt can generate the right and meaningful output. While that is partially true but that prompt itself is depended on the input or i would like to context you provide it. Because the prompt and instructions gets built around that context.

So poor context + good prompt = poor output and rich context + good prompt = rich output.

And by Context i not only mean your ideas, thoughts, observations, strategies, hypothesis, etc. Context actually means how are all these ideas connected to each other and why are they evern connected. What hidden insight each connection is signalling at and whats the impact of all these connections on our thinking.

Notion and obsidian are good at storing your ideas, thoughts, etc and they give you a visually good filing cabinet. You could use them to organise and find connections yourself if you have less number ideas but what if you have months or years of ideas and observations?

So that is where we need a system which not only focuses on capturing your thoughts but primarily hunting for those connections within your thought process which we would not have been able to find. Not only that but an exploration session which has would have all the context and helps you explore an idea or a connection even further.

One very common misconception in AI i notice is people think a very detailed prompt can generate the right and meaningful output. While that is partially true but that prompt itself is depended on the input or i would like to context you provide it. Because the prompt and instructions gets built around that context.

So poor context + good prompt = poor output and rich context + good prompt = rich output.

And by Context i not only mean your ideas, thoughts, observations, strategies, hypothesis, etc. Context actually means how are all these ideas connected to each other and why are they evern connected. What hidden insight each connection is signalling at and whats the impact of all these connections on our thinking.

Notion and obsidian are good at storing your ideas, thoughts, etc and they give you a visually good filing cabinet. You could use them to organise and find connections yourself if you have less number ideas but what if you have months or years of ideas and observations?

So that is where we need a system which not only focuses on capturing your thoughts but primarily hunting for those connections within your thought process which we would not have been able to find. Not only that but an exploration session which has would have all the context and helps you explore an idea or a connection even further.

Almost every other AI tool today has a AI chatbot now I have a question on the style and approach of the AI chatbot.

Do you prefer a chatbot that is just a good conversationalist or one that comes into every session with a clear intent?

For example, My AI Chatbot called explorer is not a traditional, in a sense that It has one job which is to elevate your thinking. And that only really works if it does not just agree with you, mirror you back or stay surface level. It has to stay one step ahead, not come down to your level and actually push you to go deeper on an idea rather than just nod along to what you already think.

The thing that makes this possible is that Explorer always has updated context on you. It already knows which scenarios you are likely to push back on, how you tend to argue a specific angle and where your thinking usually goes. So it is not coming in blind like most chatbots do. It knows enough about how you think to challenge you in a way that is actually specific to you and not just generic pushback.

So it is not friendly in the way most chatbots are. It feels more like a thinking partner that challenges you than an assistant that just helps you feel good about your ideas.

Do you think this approach will create friction in user experience or will it actually help you push forward in your thinking??

Almost every other AI tool today has a AI chatbot now I have a question on the style and approach of the AI chatbot.

Do you prefer a chatbot that is just a good conversationalist or one that comes into every session with a clear intent?

For example, My AI Chatbot called explorer is not a traditional, in a sense that It has one job which is to elevate your thinking. And that only really works if it does not just agree with you, mirror you back or stay surface level. It has to stay one step ahead, not come down to your level and actually push you to go deeper on an idea rather than just nod along to what you already think.

The thing that makes this possible is that Explorer always has updated context on you. It already knows which scenarios you are likely to push back on, how you tend to argue a specific angle and where your thinking usually goes. So it is not coming in blind like most chatbots do. It knows enough about how you think to challenge you in a way that is actually specific to you and not just generic pushback.

So it is not friendly in the way most chatbots are. It feels more like a thinking partner that challenges you than an assistant that just helps you feel good about your ideas.

Do you think this approach will create friction in user experience or will it actually help you push forward in your thinking??

I have realised that how we think and process things has a lot to do with the tools we use. And we do it in layers.

To store ideas there is Notion, Obsidian, Roam, pen and paper. To generate something or learn we jump to an AI tool. And honestly that constant juggling between systems is one of the main reasons thinking stays fragmented and goes nowhere.

There is a layer missing in between. Whatever you capture should not just sit there in storage. Your ideas should get connected, with actual reasoning on why the connection exists. Contradictions in your own thinking should get flagged. Your thought process should get synthesised. And the whole thing should keep compounding on its own so you are not hopping to another tool every time you want an output.

That is the layer I have been building.

The system does all of that but it also builds a thinker model, basically a mental model of how you think, reason and approach things. So the system always has context of who you are, not just what you have captured but how you actually think.

This means it does not hit the storage dead end that Notion and Obsidian always hit. It uses that context to help you elevate your thinking, find connections you would not have caught yourself, surface contradictions you did not notice and develop your ideas further.

Capture, connect, develop. All in one place without switching tools.

Will you guys be willing to give it a shot? I am curious to know what do you think about this middle layer.

I have realised that how we think and process things has a lot to do with the tools we use. And we do it in layers.

To store ideas there is Notion, Obsidian, Roam, pen and paper. To generate something or learn we jump to an AI tool. And honestly that constant juggling between systems is one of the main reasons thinking stays fragmented and goes nowhere.

There is a layer missing in between. Whatever you capture should not just sit there in storage. Your ideas should get connected, with actual reasoning on why the connection exists. Contradictions in your own thinking should get flagged. Your thought process should get synthesised. And the whole thing should keep compounding on its own so you are not hopping to another tool every time you want an output.

That is the layer I have been building.

The system does all of that but it also builds a thinker model, basically a mental model of how you think, reason and approach things. So the system always has context of who you are, not just what you have captured but how you actually think.

This means it does not hit the storage dead end that Notion and Obsidian always hit. It uses that context to help you elevate your thinking, find connections you would not have caught yourself, surface contradictions you did not notice and develop your ideas further.

Capture, connect, develop. All in one place without switching tools.

Will you guys be willing to give it a shot? I am curious to know what do you think about this middle layer.

I have realised that how we think and process things has a lot to do with the tools we use. And we do it in layers.

To store ideas there is Notion, Obsidian, Roam, pen and paper. To generate something or learn we jump to an AI tool. And honestly that constant juggling between systems is one of the main reasons thinking stays fragmented and goes nowhere.

There is a layer missing in between. Whatever you capture should not just sit there in storage. Your ideas should get connected, with actual reasoning on why the connection exists. Contradictions in your own thinking should get flagged. Your thought process should get synthesised. And the whole thing should keep compounding on its own so you are not hopping to another tool every time you want an output.

That is the layer I have been building.

The system does all of that but it also builds a thinker model, basically a mental model of how you think, reason and approach things. So the system always has context of who you are, not just what you have captured but how you actually think.

This means it does not hit the storage dead end that Notion and Obsidian always hit. It uses that context to help you elevate your thinking, find connections you would not have caught yourself, surface contradictions you did not notice and develop your ideas further.

Capture, connect, develop. All in one place without switching tools.

Will you guys be willing to give it a shot? I am curious to know what do you think about this middle layer.

I have realised that how we think and process things has a lot to do with the tools we use. And we do it in layers.

To store ideas there is Notion, Obsidian, Roam, pen and paper. To generate something or learn we jump to an AI tool. And honestly that constant juggling between systems is one of the main reasons thinking stays fragmented and goes nowhere.

There is a layer missing in between. Whatever you capture should not just sit there in storage. Your ideas should get connected, with actual reasoning on why the connection exists. Contradictions in your own thinking should get flagged. Your thought process should get synthesised. And the whole thing should keep compounding on its own so you are not hopping to another tool every time you want an output.

That is the layer I have been building.

The system does all of that but it also builds a thinker model, basically a mental model of how you think, reason and approach things. So the system always has context of who you are, not just what you have captured but how you actually think.

This means it does not hit the storage dead end that Notion and Obsidian always hit. It uses that context to help you elevate your thinking, find connections you would not have caught yourself, surface contradictions you did not notice and develop your ideas further.

Capture, connect, develop. All in one place without switching tools.

Will you guys be willing to give it a shot? I am curious to know what do you think about this middle layer.

Most note taking tools like Notion, Roam and Obsidian have gotten really good at storing what you think. Some even let you link notes and build graphs. But that is where they stop. And even the AI tools that have come out recently, yes they can remember what you said in a conversations and surface it back, but there is still no real active retrieval of context, no connections between your ideas, no contradictions being flagged, no hidden insights between your connected ideas and no synthesis happening across everything you have captured. They store or they remember. That is it.

But i am trying to change that gap, so here's a glimpse of what i am doing. There's an AI tool and within that, there's a thinker model which get built every time you capture or interact with the tool.

The thinker Model currently produces a structured cognitive map with these fields:

• thinking_style
• reasoning_direction
• epistemic_stance
• active_frontier
• settled_territory
• core_resistances
• generative_triggers
• dead_zones
• drift_flags

The reason why this model is different is because, this model gets updated on two occasions, once, every time you capture any idea, thought, etc and twice, on cron job at a specific time interval which is an automatic function. So the updated model is always pulled into context by all the agents to refer whenever they are connecting ideas, finding hidden insights from your knowledge graph, developing an output and also analysing what you have captured.

One very important distinction is, the agents referring the thinker model are doing so, to not mirror or think like you. They have a role based identity which clearly lets them adapt you and help you elevate your thinking.

Think of it like notion, roam or obsidian but with full context window to become your thinking partner and not just storage of your ideas.

Do you think this is a meaningful differentiation layer?

Most note taking tools like Notion, Roam and Obsidian have gotten really good at storing what you think. Some even let you link notes and build graphs. But that is where they stop. And even the AI tools that have come out recently, yes they can remember what you said in a conversations and surface it back, but there is still no real active retrieval of context, no connections between your ideas, no contradictions being flagged, no hidden insights between your connected ideas and no synthesis happening across everything you have captured. They store or they remember. That is it.

But i am trying to change that gap, so here's a glimpse of what i am doing. There's an AI tool and within that, there's a thinker model which get built every time you capture or interact with the tool.

The thinker Model currently produces a structured cognitive map with these fields:

• thinking_style
• reasoning_direction
• epistemic_stance
• active_frontier
• settled_territory
• core_resistances
• generative_triggers
• dead_zones
• drift_flags

The reason why this model is different is because, this model gets updated on two occasions, once, every time you capture any idea, thought, etc and twice, on cron job at a specific time interval which is an automatic function. So the updated model is always pulled into context by all the agents to refer whenever they are connecting ideas, finding hidden insights from your knowledge graph, developing an output and also analysing what you have captured.

One very important distinction is, the agents referring the thinker model are doing so, to not mirror or think like you. They have a role based identity which clearly lets them adapt you and help you elevate your thinking.

Think of it like notion, roam or obsidian but with full context window to become your thinking partner and not just storage of your ideas.

Do you think this is a meaningful differentiation layer?

Most note taking tools like Notion, Roam and Obsidian have gotten really good at storing what you think. Some even let you link notes and build graphs. But that is where they stop. And even the AI tools that have come out recently, yes they can remember what you said in a conversations and surface it back, but there is still no real active retrieval of context, no connections between your ideas, no contradictions being flagged, no hidden insights between your connected ideas and no synthesis happening across everything you have captured. They store or they remember. That is it.

But i am trying to change that gap, so here's a glimpse of what i am doing. There's an AI tool and within that, there's a thinker model which get built every time you capture or interact with the tool.

The thinker Model currently produces a structured cognitive map with these fields:

• thinking_style
• reasoning_direction
• epistemic_stance
• active_frontier
• settled_territory
• core_resistances
• generative_triggers
• dead_zones
• drift_flags

The reason why this model is different is because, this model gets updated on two occasions, once, every time you capture any idea, thought, etc and twice, on cron job at a specific time interval which is an automatic function. So the updated model is always pulled into context by all the agents to refer whenever they are connecting ideas, finding hidden insights from your knowledge graph, developing an output and also analysing what you have captured.

One very important distinction is, the agents referring the thinker model are doing so, to not mirror or think like you. They have a role based identity which clearly lets them adapt you and help you elevate your thinking.

Think of it like notion, roam or obsidian but with full context window to become your thinking partner and not just storage of your ideas.

Do you think this is a meaningful differentiation layer?

When you give an attachment to an AI tool, it does not really know what to extract from it so it just pulls out generic stuff. Unless you specifically tell it what to look for, you get a very surface level output.

But here is how I approached this differently.

I have built a cognitive map of how you as a user think. The tool already knows what you have captured in the past, what it connected to and why. So now when you upload any attachment, the agents refer to that cognitive context and figure out what is actually worth extracting for you specifically, without you having to say anything.

So instead of generic extraction, it is pulling out what is relevant to how you think and what you have been working on.

But if you do want to tell it specifically what to look for, your instruction overrides the cognitive context because now it has a clear direction from you. The context still kicks in but after the extraction, to connect what was pulled out to everything else you have captured.

Curious what you guys think about this approach.

When you give an attachment to an AI tool, it does not really know what to extract from it so it just pulls out generic stuff. Unless you specifically tell it what to look for, you get a very surface level output.

But here is how I approached this differently.

I have built a cognitive map of how you as a user think. The tool already knows what you have captured in the past, what it connected to and why. So now when you upload any attachment, the agents refer to that cognitive context and figure out what is actually worth extracting for you specifically, without you having to say anything.

So instead of generic extraction, it is pulling out what is relevant to how you think and what you have been working on.

But if you do want to tell it specifically what to look for, your instruction overrides the cognitive context because now it has a clear direction from you. The context still kicks in but after the extraction, to connect what was pulled out to everything else you have captured.

Curious what you guys think about this approach.

When you give an attachment to an AI tool, it does not really know what to extract from it so it just pulls out generic stuff. Unless you specifically tell it what to look for, you get a very surface level output.

But here is how I approached this differently.

I have built a cognitive map of how you as a user think. The tool already knows what you have captured in the past, what it connected to and why. So now when you upload any attachment, the agents refer to that cognitive context and figure out what is actually worth extracting for you specifically, without you having to say anything.

So instead of generic extraction, it is pulling out what is relevant to how you think and what you have been working on.

But if you do want to tell it specifically what to look for, your instruction overrides the cognitive context because now it has a clear direction from you. The context still kicks in but after the extraction, to connect what was pulled out to everything else you have captured.

Curious what you guys think about this approach.

Guys i am in the middle of building an AI tool and i have a genuine question.

The tool builds a cognitive/mental model of how you think, reason, linguistic patterns, behavioural patterns, etc. I dont want to pollute this model with excess and unnecessary context. I want to keep it as original as possible and close to how a specific user thinks.

But the main question is what qualifies as thinking here?? We all think in reference to a lot of things and many of the references and sources are external. And now with AI and contenrt all around us, the originality is kind of getting compromised.

So the main question is, what qualifies as person's original thinking and is it even okay to differentiate??