We study the dynamics of a lazy random walker who is inactive for extended times and tries to make up for her laziness with very large jumps. She remains in a condition of rest for a time τ derived from a waiting-time distribution , with μW < 2, thereby making jumps only from time to time from a position x to a position x' of a one-dimensional path. However, when the random walker jumps, she moves by quantities l = |x − x'| derived randomly from a distribution , with μξ > 1. The most convenient choice to make up for the random walker laziness would be to select μξ < 3, which in the ordinary case μW > 2 would produce Lévy flights with scaling δ = 1/(μξ − 1) and consequently super-diffusion. According to the Sparre Andersen theorem, the distribution density of the first times to go from xA to xB > xA has the inverse power law form with μFPT = μSA = 1.5. We find the surprising result that there exists a region of the phase space (μξ, μW) with μW < 2, where μFPT > μSA and the lazy walker compensates for her laziness. There also exists an extended region breaking the Sparre Andersen theorem, where the lazy runner cannot compensate for her laziness. We make conjectures concerning the possible relevance of this mathematical prediction, supported by numerical calculations, for the problem of animal foraging.