Generating personalized coaching advice using integrated programmatic and specialized guided and constrained artificial intelligence

A system to guide an Artificial Intelligence (AI) engine to generate personalized coaching advice for a user using an online learning platform based on user interaction data and learning patterns comprises:

• one or more processors of a computer system;
• and
• one or more memories, coupled to the one or more processors, that store code and execution of the code by the one or more processors causes the computer system to perform operations comprising:
• collecting media stream data and user interaction data, via a data collector, wherein the media stream data includes webcam feed, microphone audio, screen captures, and system audio, and user interaction data includes keystrokes, mouse clicks, URLs visited, active application data, active window data, and window titles;
• analyzing the collected data, via an analyzer, by utilizing machine learning algorithms to identify specific learning patterns of the user;
• classify the analyzed data into positive learning patterns (posi-patterns) and negative learning patterns (anti-patterns), wherein classifying the data into positive and negative learning patterns includes identifying one or more matching learning patterns corresponding to the analyzed data;
• generating a coaching prompt to guide the AI engine, via a prompt generator, to generate personalized coaching advice for the user based on the identified one or more learning patterns and a prompt structure, wherein the prompt structure is generated by a prompt engineer using prompt engineering techniques;
• utilizing the generated coaching prompts by the AI engine to generate personalized coaching advice based on the classified learning patterns using a coaching advice generator;
• and
• displaying the generated personalized coaching advice to the user, via a user interface, wherein the personalized coaching advice addresses specific behaviors detected during the user's online learning session and suggests corrective actions to improve learning patterns.