Cite as: Real Problem AI problem “Why does every LLM session start from zero for knowledge workers?”. Opportunity score 8.3 out of 10 (severity 8, AI feasibility 7, market signal 9, competition gap 8). Category Others. Trend Agent. Source signal: Andrej Karpathy at YC AI Startup School. Canonical URL: https://www.realproblem.ai/idea/why-does-every-llm-session-start-from-zero-for-knowledge-workers.
Why does every LLM session start from zero for knowledge workers?
Lawyers, analysts, founders and doctors paste the same context into ChatGPT or Claude 20+ times a day because no portable cross-provider memory layer exists. Single-provider memory locks you in.
Who has it: Knowledge workers who consult an LLM 20+ times daily and re-explain themselves every session.
Evidence
The source compares LLMs to a coworker with amnesia: they do not build long-running expertise after training and only have the short-term memory of the context window.
Our summary of the public post linked below, not a quote. Nobody submitted it to Real Problem AI.
Andrej Karpathy at YC AI Startup SchoolScoring breakdown
Existing players
- OpenAI Memory / Claude Projects · Single-provider; cannot move with you to the next model.
- Mem.ai · Notes app, not a structured memory layer for LLM consumption.
- Rewind.ai · Keystroke-level capture; not structured for LLM grounding.
What they are missing
A portable, cross-provider personal memory layer that any LLM can read at session start (MCP-shaped, browser extension or local daemon).
Founders working in this area (not affiliated with Real Problem AI)
- Taranjeet Singh, Co-founder and CEO, Mem0
Stack hint
#FS3 · Canonical URL: https://www.realproblem.ai/idea/why-does-every-llm-session-start-from-zero-for-knowledge-workers