Hi! I made a BOTEC model on AI agents economic feasibility in the near term. You can find it here. It combines the half-life analysis of agent reliability with real inference costs. The core idea is that if agent cost per successful outcome scales exponentially with task length, and human cost scales linearly, it creates a sharp viability boundary that cost reductions alone cannot meaningfully shift. The only parameter that matters much is the agent's half-life (reliability horizon), which is precisely the thing that requires the continual learning breakthrough (which I think is essential for AGI-level agents) that some place 5-20 years away. I think this has underappreciated implications for the $2T+ AI infrastructure investment thesis.
Hi! I made a BOTEC model on AI agents economic feasibility in the near term. You can find it here.
It combines the half-life analysis of agent reliability with real inference costs. The core idea is that if agent cost per successful outcome scales exponentially with task length, and human cost scales linearly, it creates a sharp viability boundary that cost reductions alone cannot meaningfully shift. The only parameter that matters much is the agent's half-life (reliability horizon), which is precisely the thing that requires the continual learning breakthrough (which I think is essential for AGI-level agents) that some place 5-20 years away. I think this has underappreciated implications for the $2T+ AI infrastructure investment thesis.