This depends on whether you are dealing with processes subject to entropic decay (they break apart and “die” without effort-input) or entropic growth (they optimize under their own power). For the former case, the Nirvana fallacy remains a fallacy; for the latter case, you are in deep trouble if you try to go with the first “good enough” alternative rather than defining a unique best solution and then trying to hit it as closely as possible.
This depends on whether you are dealing with processes subject to entropic decay (they break apart and “die” without effort-input) or entropic growth (they optimize under their own power). For the former case, the Nirvana fallacy remains a fallacy; for the latter case, you are in deep trouble if you try to go with the first “good enough” alternative rather than defining a unique best solution and then trying to hit it as closely as possible.