A computer system comprising: one or more processors ; and one or more computer-readable hardware storage devices having stored thereon computer-executable instructions, when executed by the one or more processors, cause the computer system to: within an architecture that includes one or more analyzer components , receive a notification indicating that a codebase has undergone a change, the change to the codebase is received from a user via an interface represented by a development environment during a code development process; access a change context that provides context for the change; perform , by one of the one or more analyzer components, analysis of the change using at least a portion of the change context, wherein the at least one analyzer component uses a learning model ; detect receipt of a result of the analysis; cause at least some information of the result to be rendered to a user via the interface, the information including a suggestion on how to improve the codebase with respect to the change that was made to the codebase; determine how the user responded to the rendered information; and dynamically update the learning model used by the at least one analyzer component based on how the user responded to the rendered information so that the at least one analyzer component can provide a more refined suggestion in a subsequent analysis during the code development process. one or more processors ; and one or more computer-readable hardware storage devices having stored thereon computer-executable instructions, when executed by the one or more processors, cause the computer system to: within an architecture that includes one or more analyzer components , receive a notification indicating that a codebase has undergone a change, the change to the codebase is received from a user via an interface represented by a development environment during a code development process; access a change context that provides context for the change; perform , by one of the one or more analyzer components, analysis of the change using at least a portion of the change context, wherein the at least one analyzer component uses a learning model ; detect receipt of a result of the analysis; cause at least some information of the result to be rendered to a user via the interface, the information including a suggestion on how to improve the codebase with respect to the change that was made to the codebase; determine how the user responded to the rendered information; and dynamically update the learning model used by the at least one analyzer component based on how the user responded to the rendered information so that the at least one analyzer component can provide a more refined suggestion in a subsequent analysis during the code development process. within an architecture that includes one or more analyzer components , receive a notification indicating that a codebase has undergone a change, the change to the codebase is received from a user via an interface represented by a development environment during a code development process; access a change context that provides context for the change; perform , by one of the one or more analyzer components, analysis of the change using at least a portion of the change context, wherein the at least one analyzer component uses a learning model ; detect receipt of a result of the analysis; cause at least some information of the result to be rendered to a user via the interface, the information including a suggestion on how to improve the codebase with respect to the change that was made to the codebase; determine how the user responded to the rendered information; and dynamically update the learning model used by the at least one analyzer component based on how the user responded to the rendered information so that the at least one analyzer component can provide a more refined suggestion in a subsequent analysis during the code development process. <EOS>