I'm considering dropping out of college to pursue this business idea — I'd appreciate a brutally honest evaluation.
Hi everyone, I’m a CS student in Korea. (of course southern)
Lately I’ve been thinking a lot about how LLMs are changing the way we learn and collaborate.
Most of my actual development process now happens inside GPT/Claude conversations:
- learning concepts
- debugging
- architecture decisions
- implementation
- exploration and trial/error
But team collaboration still mostly works like it did before LLMs:
- Notion pages
- Slack messages
- meetings
- manually written documentation
And that feels increasingly strange to me.
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I remember Andrej Karpathy talking about the idea of an “LLM-generated wiki” — where your conversations become a kind of personal knowledge repository.
But I think the interesting part starts *after* that.
What happens when:
- each person has their own evolving AI-generated memory/wiki
- an agent manages and understands that memory
- agents can selectively communicate with each other
- knowledge flows from:
- personal memory
- → team memory
- → organizational memory
Instead of documentation being manually written and maintained, the organization gradually accumulates structured knowledge through everyday work and conversations.
And not just from LLM chats either.
Potentially from:
- Slack
- Notion
- PR reviews
- meeting transcripts
- dev logs
- issue trackers
- internal docs
- voice conversations
- IDE workflows
- and other operational data
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The thing I’m interested in is not:
> “AI writes docs for humans.”
But more:
> “Can organizations develop a persistent memory layer managed by agents?”
For example:
- I spend 3 hours discussing JWT auth strategies with Claude
- another teammate explores RAG chunking with GPT
- someone else solves CUDA optimization issues
Right now, most of that context disappears or becomes fragmented across chats and docs.
But theoretically, agents could:
- extract important decisions
- preserve reasoning context
- build graph-structured knowledge
- understand ownership/privacy boundaries
- and later answer questions on behalf of individuals or teams
So instead of:
> “Who knows this?”
or:
> “Where was that Notion page?”
the organization itself becomes queryable.
Almost like:
- organizational long-term memory
- but agent-native
- and continuously evolving
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Some ideas I’ve been prototyping:
- conversation graph visualization
- automatic knowledge extraction
- graph/wiki memory structures
- agent-based retrieval
- privacy-aware access control
- hierarchical memory aggregation
I’m seriously considering turning this into a real startup/product.
But I honestly don’t know whether this is:
- genuinely useful infrastructure
- an inevitable direction for LLM-native teams
- or just another layer of AI-generated complexity
So I’d genuinely love honest feedback from people here.
Especially:
- would you actually use something like this?
- does this solve a real pain point?
- are there existing products already doing this well?
- what part sounds most compelling or unnecessary?
- does this feel like a real market, or just an interesting idea?
Curious what people think.