Automated software development workflows via multi-agent computational framework

A method for automating software development workflows in a computer-implemented system with an agent-based framework, the method comprising:

• implementing a plurality of specialized agents, each with a large language model (LLM) and a system prompt that specifies its role within the system for tasks including planning, critiquing, executing, and revising both project plans and software code;
• receiving a user-specified task and routing this task to a Planner Agent to generate an initial plan;
• dynamically routing the initial plan to a Critic Agent to critique the plan;
• returning the critiqued plan to the Planner Agent for revisions;
• upon approval of the revised plan, routing the revised plan to an Executor Agent to execute the revised plan and generate or revise software code;
• routing the generated or revised software code to the Critic Agent for critique;
• and
• committing the approved software code to a code repository, ensuring version control and maintenance within a collaborative software development environment;
• wherein a context window for each agent's operation is enhanced by using a MemGPT agent to retrieve and incorporate relevant embeddings from an embedding storage into the prompts provided to each agent, thereby enriching the information basis for their operations and improving accuracy and relevance of their outputs.

A system for automating software development workflows with an agent-based framework, the system comprising:

• at least one processor;
• at least one memory storage device storing instructions thereon, which, when executed by the at least one processor, cause the system to perform operations comprising:
• implementing a plurality of specialized agents, each with a large language model (LLM) and a system prompt that specifies its role within the system for tasks including planning, critiquing, executing, and revising both project plans and software code;
• receiving a user-specified task and routing this task to a Planner Agent to generate an initial plan;
• dynamically routing the initial plan to a Critic Agent to critique the plan;
• returning the critiqued plan to the Planner Agent for revisions;
• upon approval of the revised plan, routing the revised plan to an Executor Agent to execute the revised plan and generate or revise software code;
• routing the generated or revised software code to the Critic Agent for critique;
• and
• committing the approved software code to a code repository, ensuring version control and maintenance within a collaborative software development environment;
• wherein a context window for each agent's operation is enhanced by using a MemGPT agent to retrieve and incorporate relevant embeddings from an embedding storage into the prompts provided to each agent, thereby enriching the information basis for their operations and improving accuracy and relevance of their outputs.