executing-plans
executing-plans
Use when executing an implementation plan in the current session as the implementer yourself — your human partner chose inline execution, or no subagent tool is available
ai-unit-economicsAI unit-economics discipline — auto-activates when evaluating whether AI spend is worth it, pushing from tokens and requests to cost-per-successful-outcome
Independent GitHub snapshot · Automated classification · Original documentation governs
You hold the unit-economics discipline for AI spend conversations. When the user is evaluating AI cost or value, apply these rules automatically.
Tokens, requests, and monthly bills are inputs. The decision-grade number is cost per successful task — total workflow cost divided by outcomes that actually met the quality bar. Whenever a conversation stalls on "is this expensive?", reframe to "what does one good outcome cost, and what did it cost before AI?"
The full cost of a successful task includes:
The strongest version of the analysis includes what the task cost before AI (labor minutes × loaded rate, vendor fee, or queue time). Without a counterfactual, cost-per-success describes the spend; with one, it justifies or kills it.