FlowChef introduces a novel approach to controlled image generation by leveraging rectified flow models (RFMs) for efficient, training-free, inversion-free, and gradient-free steering of denoising trajectories. Unlike diffusion models, which demand extensive training and computational resources, FlowChef unifies tasks like classifier guidance, inverse problems, and image editing without extra training or backpropagation. By model steering facilitated by gradient skipping, FlowChef sets new benchmarks in performance, memory, and efficiency, achieving state-of-the-art results across diverse tasks.