Running autonomous agents inside a safe Docker sandbox is huge . It doesn't just suggest code- it runs terminal commands, passes tests,and updates files directly. Being able to plug in any model via LiteLLM is a massive plus, and letting it auto-fix simple GitHub issues saves us hours of tedious work.

The MCP Servers panel is the standout feature for us. Seeing GitHub (STDIO), Slack (SSE), and Linear (SSE) all installed and connected in one place makes the agent genuinely useful rather than theoretical. At Prism Network Limited we maintain internal tools that support property claims handling and contractor coordination. Being able to give the agent controlled access to our repositories, issue tracker, and team chat from that single Customize → MCP Servers view means it can actually move work forward instead of just suggesting code.

The biggest benefit of OpenHands is that it can take a coding task beyond simply generating code and actually work through the task, including making changes, running tests and iterating on the result. I like that it can be connected to tools such as GitHub, Jira and Slack, which makes it easier to fit an AI coding agent into an existing development workflow. For a company like Ebiquity, this could be useful for automating repetitive development or data-engineering tasks and allowing technical teams to spend more time on higher-value work. The open-source/self-hosting option is also interesting from an enterprise perspective because teams have more control over how and where the agent runs.