This article presents an integrated self-optimizing programmable chemical synthesis and reaction engine, which enables real-time adaptation and optimization of chemical reactions. The system utilizes seven sensors to monitor reactions continuously and employs a dynamic programming language to scale up reactions, detect endpoints, and identify hardware failures. It demonstrates the use of in-line spectroscopy (HPLC, Raman, NMR) for closed-loop optimization, achieving up to 50% yield improvements in several reactions. The system also enables the discovery of new molecules through an experimental pipeline for trifluoromethylation reactions. The system is built on the chemputation framework, which provides a universal ontology for chemical synthesis. It integrates process sensors and analytical instruments with a chemical processing unit (Chemputer), allowing for autonomous execution and optimization of literature protocols. The system uses telemetry data and predefined rules for dynamic procedure execution, self-correction, and real-time decision-making. The system includes hardware and software support for low-cost sensors, dynamic χDL for feedback control, software for analytical instrument control, and a χDL-based package for iterative reaction optimization. These components enable the first demonstration of an automated tandem of discovery-optimization framework that uses XDL code as input and returns optimized XDL as output. The system was tested on several reactions, including the four-component Ugi reaction, Van Leusen oxazole synthesis, manganese-catalyzed styrene epoxidation, and two previously unreported reactions. It also demonstrated the self-correcting execution of two functional group interconversion reactions using feedback from temperature and color sensors. The system's ability to dynamically execute instructions with real-time adaptation to changing process parameters is key to its effectiveness. It was used to optimize reaction conditions for multicomponent, heterocycle, and catalytic reactions using feedback from 19F NMR, HPLC-DAD, and Raman spectroscopy. The system also demonstrated how to extend the closed-loop approach to facilitate compound discovery and optimization. The system's framework allows for the execution of chemical reactions in a closed-loop manner, enabling the discovery of new molecules and optimization of reaction conditions. It provides a universal approach for optimizing digital recipes and can accommodate any further module developments following the χDL standard. The system's integration of low-cost sensors and process analytical technology instruments enhances process control and insight, shifting the Chemputer platform from open-loop to closed-loop control. The system's ability to adapt to changing conditions and optimize reactions in real-time represents a significant advancement in automated chemical synthesis.This article presents an integrated self-optimizing programmable chemical synthesis and reaction engine, which enables real-time adaptation and optimization of chemical reactions. The system utilizes seven sensors to monitor reactions continuously and employs a dynamic programming language to scale up reactions, detect endpoints, and identify hardware failures. It demonstrates the use of in-line spectroscopy (HPLC, Raman, NMR) for closed-loop optimization, achieving up to 50% yield improvements in several reactions. The system also enables the discovery of new molecules through an experimental pipeline for trifluoromethylation reactions. The system is built on the chemputation framework, which provides a universal ontology for chemical synthesis. It integrates process sensors and analytical instruments with a chemical processing unit (Chemputer), allowing for autonomous execution and optimization of literature protocols. The system uses telemetry data and predefined rules for dynamic procedure execution, self-correction, and real-time decision-making. The system includes hardware and software support for low-cost sensors, dynamic χDL for feedback control, software for analytical instrument control, and a χDL-based package for iterative reaction optimization. These components enable the first demonstration of an automated tandem of discovery-optimization framework that uses XDL code as input and returns optimized XDL as output. The system was tested on several reactions, including the four-component Ugi reaction, Van Leusen oxazole synthesis, manganese-catalyzed styrene epoxidation, and two previously unreported reactions. It also demonstrated the self-correcting execution of two functional group interconversion reactions using feedback from temperature and color sensors. The system's ability to dynamically execute instructions with real-time adaptation to changing process parameters is key to its effectiveness. It was used to optimize reaction conditions for multicomponent, heterocycle, and catalytic reactions using feedback from 19F NMR, HPLC-DAD, and Raman spectroscopy. The system also demonstrated how to extend the closed-loop approach to facilitate compound discovery and optimization. The system's framework allows for the execution of chemical reactions in a closed-loop manner, enabling the discovery of new molecules and optimization of reaction conditions. It provides a universal approach for optimizing digital recipes and can accommodate any further module developments following the χDL standard. The system's integration of low-cost sensors and process analytical technology instruments enhances process control and insight, shifting the Chemputer platform from open-loop to closed-loop control. The system's ability to adapt to changing conditions and optimize reactions in real-time represents a significant advancement in automated chemical synthesis.