Lifecycle Circuit
AI-assisted project orchestration and dev history
LC is a structured execution workspace for collaboration between developers and AI agents. It connects project context, tasks, decisions, implementation history, reviews and execution state within a single traceable development workflow. Rather than treating AI agents as isolated coding tools, LC provides them with controlled access to project context and preserves the results of their work as part of the project history. Tasks, decisions and implementation feedback remain linked, making it possible to understand not only what was changed, but why and under which constraints. LC follows a human-controlled orchestration model: agents assist with analysis and implementation, while task state, review, acceptance and final decisions remain under developer control. The system can exchange project knowledge with MiMa while remaining independent from any specific agent, model or external tracker.
- Role
- Creator, Product Architect, System Analyst
- System
- Java 21 / Spring Boot / Thymeleaf / PostgreSQL / MCP
Development without losing context
Software development with AI often breaks down not because an agent cannot write code, but because project context is scattered across chats, task trackers, repositories, and personal notes. LC keeps projects, tasks, decisions, implementation history, and feedback in a single structured workspace. Each task preserves not only its current state, but also the path that led to it: the initial request, refinements, implementation attempts, review comments, and final result. Through MCP, AI agents can retrieve the relevant project context and return structured updates directly to LC. The developer remains responsible for review and final decisions, while the system preserves continuity between separate work sessions and different agents.