Agentic OS - The tool to rule them all
By: Ran Banker
🧗 The Challenge
With the pace of the agentic landscape, we quickly find ourselves with several agentic tooling in our working enviornment. The tools run in silos, they each learn about us seperatly without sharing knowledge. We are missing a telemtric view to correlate between the different tools and understand how they are impacting our work, token usage. In some case the underlying tooling like Hermes or OpenClaw offer a rudementary UI that is limited with how we want to shape the tools usage.
💡 What's cool?
Use your agentic coding assistant to build your own customized Agentic OS. Wrap each agentic tool, share knowledge between the tools, provide the missing telemetry, and offer a unified UI to best orchestrate and control the agentic tools.
⚠️ Disclaimer & Scope
In this post I will share several authors of their vision of a possible implementation of an Agentic OS. This is by no means an exhaustive list, but rather a collection of ideas and concepts that I found interesting.
🎯 The Solution
📊 Conclusion & Insights
The shift toward unified, fused execution spaces eliminates critical serialization latency. This directly correlates to immense compute cost efficiency, allowing us to serve 4× more requests on the same hardware footprint while vastly improving the developer experience.
⏭️ Suggested Next Steps
Future iterations will explore custom CUDA compilation for the Bloom Filter modules. Review our “Core Engine Spec” documentation on the Prompt-Notes core developer engine portal for deeper implementation details.
🙏 Acknowledgments
We want to thank the following individuals and groups across our engineering divisions for their collaborative efforts in moving this platform architecture forward:
- Infrastructure Provisioning: For edge validation testing and runtime profile tracking.
- Core ML Frameworks: For compute allocation overhead support.
