Measure AI Agent Value With New Token Dollar Ratio Metric

I mean, this kinda makes sense, but my biggest debate and pushback to this statement is that right now tokens are, for some organizations, rivaling payroll budgets. At that level of value expenditure, that is really hard to argue when there's any sort of ambiguity. If that's the case, we fire them.

@svpino this is such a clean way to frame the roi.

@svpino that's just a cost-benefit analysis, the real question is whether that ratio grows over time

@svpino value per token dollar looks like a new metric.

@svpino 代理盈亏四个数据就够了呀

@svpino this is the only agent metric that actually matters and almost nobody tracks it. everyone measures capability, not whether it paid for itself.

This is gold. Finally a practical metric instead of hype. "Value per token dollar" cuts through everything. Two agents on the same model spending the same tokens but delivering wildly different ROI is the real differentiator. The 0-person company angle is wild. Makes me wonder how high that ratio can realistically go before we’re all running micro-empires. What value-per-token wins have you seen so far? @matrix_build @svpino

@svpino Yep, this is the correct coordinate for me. Not can the agent do task X, but does the runtime produce more value than the token burn.

@svpino So basically ROI but for people who don't want to say ROI. Got it.

@svpino Value per token dollar is a useful metric. But in practice, error recovery, security overhead, and failure modes quietly erode that ratio. Curious if anyone has data on how it holds up outside controlled environments?