Project Management

AI Operating Systems: What’s Your Experience?

Agile Artificial Intelligence Innovation

Bruce Buryo

Community Champion

I’ve been following the rapid development of AI operating systems (AI OS) that can go beyond answering questions to planning, executing multi-step tasks, using tools, interacting with applications, and maintaining context across workflows.

For those who are actively using or building an AI OS, what has your experience been like? What capabilities have had the biggest impact on your work, and where do you still see limitations? I’m interested in hearing real-world experiences, whether you’re using an existing solution or a custom setup.

Posted: Jun 30, 2026 1:54 AM

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Luis Branco CEO| Business Insight, Consultores de Gestão, Ldª Carcavelos, Lisboa, Portugal

This raises an important question.

In my experience, the greatest value of an AI Operating System is not its ability to execute more tasks, but its ability to preserve context, reasoning and continuity across those tasks.

Planning, tool orchestration and workflow automation are becoming increasingly capable.
The harder challenge is ensuring that decisions remain coherent as objectives evolve, new information emerges and multiple interactions accumulate over time.

Perhaps the next generation of AI Operating Systems will be defined less by the number of capabilities they integrate and more by their ability to preserve high-quality judgment throughout an extended decision process.

Posted: Jun 30, 2026 3:34 AM

Imran Afzal Author| The Strategic PMO Cary, NC, United States

Bruce,

I've been experimenting with what many would describe as a custom AI Operating System using Cursor, MCP integrations, and models such as Gemini and Claude connected to Jira, Confluence, and other delivery artifacts.

The biggest impact hasn't been task automation. It's been the ability to move from questions to investigation. Instead of manually collecting information across dozens of projects, I can ask natural language questions, retrieve portfolio data, identify patterns, generate analyses, and create visualizations in minutes rather than hours.

What has surprised me most is how much this changes the quality of governance discussions. The outputs aren't the end product—they become inputs into portfolio reviews, leadership meetings, and dependency discussions where people make trade-off decisions. The AI accelerates the preparation, but the real value comes from improving the conversations and decisions that follow.

Where I still see limitations is that today's AI Operating Systems can preserve context exceptionally well, but they still depend on organizations having clear governance, consistent terminology, and explicit decision-making. If the underlying data is fragmented or strategic priorities are ambiguous, the AI simply becomes more efficient at surfacing inconsistent information.

For me, the next frontier isn't just building AI Operating Systems that can execute more tasks. It's building organizations that can externalize enough of their judgment for those systems to support consistent decision-making over time.

Posted: Jun 30, 2026 2:49 PM

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