The field of hardware development and verification is witnessing a significant shift towards the adoption of Large Language Models (LLMs) to improve efficiency and accuracy. Researchers are exploring the potential of LLMs in various aspects of hardware development, including debugging, code generation, and verification. The use of LLMs is shown to enhance the debugging process by accurately identifying and fixing bugs, and improving code generation capabilities through domain adaptation and prompt-guided reasoning. Furthermore, LLMs are being leveraged to automate the verification process, reducing manual effort and improving coverage. Notable papers in this area include VeriDebug, which presents a unified LLM approach for Verilog debugging, and ChiseLLM, which introduces a domain-adapted LLM for Chisel code generation. Another significant contribution is UVM^2, an automated verification framework that leverages LLMs to generate and refine UVM testbenches. Additionally, ComplexVCoder is an LLM-driven framework that systematically generates complex Verilog code, outperforming state-of-the-art frameworks in terms of function correctness.