The race toward practical quantum technologies is underway, with many physical platforms competing to become the foundation of future quantum systems. Photonic graph states — entangled states of light that serve as the backbone of quantum protocols for computing, communication, and sensing — are among the most promising candidates. Photons offer long coherence times, are relatively straightforward to produce, and are flying qubits by nature, making them natural carriers of quantum information. At the same time, photon loss and the difficulty of generating photon-photon entanglement at scale make them among the most challenging to work with. The central obstacle lies in the generation process itself: current schemes for producing graph states via quantum emitters depend on deep circuits and heavy resource overhead that quickly render them impractical. In this talk, I present a unified theoretical framework developed throughout my PhD that systematically targets these costs, maps the optimization landscape of the generation problem, and moves scalable photonic quantum information processing closer to practical reality.