ticker

To automate AI agents for software epics, you can use an autonomous orchestration loop that integrates issue tracking with the Claude Code CLI to manage task execution, signal handling, and checkpointing for long-running development cycles.

Test-driven development integrates with autonomous AI coding agents by structuring epic tasks with clear acceptance criteria and specific test commands, ensuring the AI validates code changes against defined tests before reporting task completion.

Yes, running AI agents for issue tracking and coding requires installing the `tk` and `ticker` CLI tools to manage the issue tracker and orchestrate the autonomous agent loops for your development epics.

The best way to manage long-running AI development cycles is using an orchestration skill that handles checkpointing and signal management, allowing AI agents to run in continuous loops until an epic is fully complete.

Yes, you can use an AI agent to autonomously break down a large software feature defined as an epic into manageable tasks, execute the coding, run tests, and report completion while managing the entire process.

Using an issue tracker when automating AI coding agents provides a structured backlog for creating, managing, and tracking tasks and epics, ensuring the autonomous agent loop executes the correct work and reports accurate completion status.