@royalaid.eth

100%, to draw an allegory from jet engine development: We know what the goal is, we know we can get there, but its a matter of tuning everything just right to get the loop to complete in a useful way. Some examples of issues that need solving: Context length restrictions - Real time world knowledge is limited Context Retrieval at long lengths - In task knowledge is limited Model Speed (this is getting solved pretty effectively over time) - Feedback cycle during agentic execution Vector-Goal Divergence - agents going off an tangents (looking at you 3.7 sonnet) Model Alignment - Prompts are lossy, this compensates for that All of this can be compensated for through things like RAG and scaffolding and eventually these issues will be solved. Once they are then its just a matter of getting tool_calls wired up, for physical stuff see work @july is doing. Crypto then provides payment rails. Then fully agentic systems can emerge. 10 years feels right.

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