This article presents an integrated self-optimizing programmable chemical synthesis and reaction engine, known as the Chemputer, which combines dynamic programming with real-time monitoring and feedback control to enable autonomous chemical synthesis, optimization, and discovery. The system utilizes seven sensors to continuously monitor reactions and incorporates a dynamic programming language (xDL) to enable adaptive execution of chemical procedures. The platform supports closed-loop optimization using in-line spectroscopy techniques such as HPLC, Raman, and NMR, and has been applied to various reactions, including Van Leusen oxazole synthesis, Ugi condensation, and manganese-catalyzed epoxidation, achieving up to 50% yield improvements over multiple iterations. The system also demonstrates the ability to detect critical hardware failures and adapt to changing environmental conditions, such as temperature and color changes, to ensure safe and efficient reaction execution. The Chemputer platform integrates low-cost sensors for monitoring chemical processes, including color, temperature, pH, and conductivity, as well as a vision-based condition monitoring system to enhance autonomy. It also includes a Python-based library for controlling analytical instruments and processing spectral data, enabling the development of a unified framework for chemical discovery and optimization. The system's ability to dynamically execute procedures based on real-time feedback has been demonstrated through various experiments, including the optimization of the Ugi reaction, Van Leusen oxazole synthesis, and manganese-catalyzed epoxidation. The platform's flexibility is further demonstrated through the discovery of new reactions, such as the tosMIC reaction, and the exploration of chemical spaces for trifluoromethylation. The system's integration of process analytical technology and digitalization has the potential to significantly enhance the throughput and efficiency of chemical synthesis, while maintaining flexibility in experimental conditions. The Chemputer represents a fundamental shift from traditional open-loop control systems to a closed-loop platform that enables real-time feedback, self-correction, and dynamic optimization of chemical processes. The system's ability to autonomously execute and optimize chemical procedures has the potential to accelerate chemical research, improve safety, and enable more complex, autonomous molecular discovery workflows.This article presents an integrated self-optimizing programmable chemical synthesis and reaction engine, known as the Chemputer, which combines dynamic programming with real-time monitoring and feedback control to enable autonomous chemical synthesis, optimization, and discovery. The system utilizes seven sensors to continuously monitor reactions and incorporates a dynamic programming language (xDL) to enable adaptive execution of chemical procedures. The platform supports closed-loop optimization using in-line spectroscopy techniques such as HPLC, Raman, and NMR, and has been applied to various reactions, including Van Leusen oxazole synthesis, Ugi condensation, and manganese-catalyzed epoxidation, achieving up to 50% yield improvements over multiple iterations. The system also demonstrates the ability to detect critical hardware failures and adapt to changing environmental conditions, such as temperature and color changes, to ensure safe and efficient reaction execution. The Chemputer platform integrates low-cost sensors for monitoring chemical processes, including color, temperature, pH, and conductivity, as well as a vision-based condition monitoring system to enhance autonomy. It also includes a Python-based library for controlling analytical instruments and processing spectral data, enabling the development of a unified framework for chemical discovery and optimization. The system's ability to dynamically execute procedures based on real-time feedback has been demonstrated through various experiments, including the optimization of the Ugi reaction, Van Leusen oxazole synthesis, and manganese-catalyzed epoxidation. The platform's flexibility is further demonstrated through the discovery of new reactions, such as the tosMIC reaction, and the exploration of chemical spaces for trifluoromethylation. The system's integration of process analytical technology and digitalization has the potential to significantly enhance the throughput and efficiency of chemical synthesis, while maintaining flexibility in experimental conditions. The Chemputer represents a fundamental shift from traditional open-loop control systems to a closed-loop platform that enables real-time feedback, self-correction, and dynamic optimization of chemical processes. The system's ability to autonomously execute and optimize chemical procedures has the potential to accelerate chemical research, improve safety, and enable more complex, autonomous molecular discovery workflows.