Does your terminal feel like a maze? How to manage AI agents and GitHub CI on one screen

Imagine this: You wake up in the morning and assign different development tasks to various AI agents. One is implementing a new feature, another is performing code reviews, and a third is fixing bugs. However, once these tasks are pushed to GitHub and go through CI (Continuous Integration, the process of automatic code building and testing), you might find yourself sweating while jumping between multiple terminal windows and web browser tabs to check the current progress.

For developers, the terminal is home. But as the number of tools you use grows, that home gradually becomes a complex maze. Today, we introduce ‘Legbar,’ a new tool that resolves this complexity and allows you to manage AI agents and CI pipelines at a glance.

Why It Matters

In the current development environment of 2026, it has become common for professional developers to use multiple AI coding agents simultaneously to increase work efficiency GitHub - gmhoward9289-ops/legbar: One screen for the whole fleet…. This means the era of simply talking to a single AI is behind us How to Run Multiple AI Agents in a Single Terminal Workspace.

The problem is that as the number of agents increases, it becomes harder to grasp what they are actually doing. It is similar to a situation where multiple chefs are in the kitchen, each preparing a different dish, but the head chef is running around confused because they don’t know in real-time where and what food is being made. If code written by an AI fails in the CI pipeline, development time is inevitably delayed if you don’t notice that fact quickly. Legbar eliminates these ‘control blind spots’ and helps developers make critical decisions.

The Explainer

You can easily liken Legbar to an ‘integrated dashboard’ in a complex airplane cockpit. While you used to have to check agent terminals, code review windows, and CI build logs on different screens, Legbar brings all these critical signals into a single, easy-to-see dashboard One screen for the whole fleet: live agent sessions beside GitHub CI.

The core of this tool lies in the Discovery Layer called ‘henhouse.py’ One screen for the whole fleet: live agent sessions beside GitHub CI. Simply put, it is like a ‘smart assistant’ that collects and coordinates AI sessions, code records, Git history, and GitHub information happening inside the terminal in real-time GitHub - gmhoward9289-ops/legbar: One screen for the whole fleet…. Thanks to this, there is no risk of the AI activities you see in the terminal conflicting or falling out of sync with the information from the actual CI pipelines running on GitHub legbar/README.md at main · gmhoward9289-ops/legbar · GitHub.

Where We Stand

Currently, many developers are running multiple AI coding agents (Claude Code, Gemini CLI, etc.) simultaneously to handle complex tasks How to Run Multiple AI Agents in a Single Terminal Workspace. In such an environment, tools like Legbar go beyond simply splitting terminal windows to provide visibility that allows you to view the entire project pipeline at once One screen for the whole fleet: live agent sessions beside GitHub CI.

What’s Next

In future development environments, performance of individual AI tools will remain important, but how smoothly you can connect and manage multiple tools will determine your productivity. As tools like Legbar continue to evolve, developers will move beyond being mere webhook (a feature that notifies you when a specific event occurs on a server) checkers to become ‘high-level orchestrators’ who lead teams of multiple AI agents, focusing more on critical design and review tasks. It is much like how a conductor coordinates various instrument sounds to complete a wonderful symphony.

MindTickleBytes AI Reporter Opinion

As the number of AI agents grows, the cognitive load developers experience within the terminal is increasing. Tools like Legbar that integrate and display information are becoming less of a choice and more of a necessity, clearly showing that the center of development is shifting from ‘how to implement’ to ‘how to manage.’

References

1. GitHub - gmhoward9289-ops/legbar: One screen for the whole fleet: live agent sessions beside GitHub CI https://github.com/gmhoward9289-ops/legbar
2. legbar/README.md at main · gmhoward9289-ops/legbar · GitHub https://github.com/gmhoward9289-ops/legbar/blob/main/README.md
3. How to Run Multiple AI Agents in a Single Terminal Workspace https://stoicsoft.github.io/1devtool/2026/03/26/how-to-run-multiple-ai-agents-single-terminal-workspace.html
4. One screen for the whole fleet: live agent sessions beside GitHub CI https://pypi.org/project/legbar/