[P]SROS: Intent-to-Structure OS for agents (planes-based architecture + receipts) – demos + paper

Hi r/MachineLearning,

I’m releasing SROS (Sovereign Recursive Operating System) publicly. It’s an architecture for building agent systems that treats “prompting” as compilation: intent becomes structure, then runs through planes that separate concerns (execution, memory, governance, observability) with receipts as a first-class output.

Site (overview + docs): https://sros.cloud/ 

Planes and agents page: https://sros.cloud/planes-agents 

Architecture page: https://sros.cloud/architecture 

Proof spine (fast): I took YC RFS ideas and compiled 7 MVP demos as a stress test of the pipeline (intent -> structure -> runnable output):

https://ycrfsdemos.sros.cloud/ 

Paper: SROS technical whitepaper is on Zenodo: https://zenodo.org/records/17364378 

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What SROS is (in systems terms)

SROS is structured like an OS: you feed it intent, it produces an intermediate structured representation, then routes work through planes that each do one job well (and produce receipts). 

Intent -> Planes -> Execution (the core loop)

1. Intent Intake 

Normalize and bound the request (scope, constraints, expected artifact types).

2. Compilation (Intent -> Structure) 

Convert intent into a schema-clean package: tasks, tool routing, constraints, and output contracts (not prose).

3. Orchestration Plane 

Sequences steps, manages state transitions, and coordinates agent/tool calls.

4. Execution Plane 

Runs actions (tools, APIs, site updates, build steps), returns structured outputs.

5. Memory Plane 

Stores and retrieves state needed for continuity and multi-step work.

6. Governance Plane 

Applies allow/deny rules, constraint enforcement, and safe fallbacks.

7. Observability Plane 

Produces receipts: what ran, what was allowed, what changed, and why. 

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Why “planes” instead of one monolithic agent

Most agent repos collapse everything into one prompt + tool calls. SROS separates the failure modes:

• execution bugs do not contaminate governance decisions • memory retrieval does not contaminate compilation • observability is not optional logging, it’s a required output contract 

This makes it easier to reason about correctness, regressions, and safe scaling. 

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What I’m asking this community for

I’m not posting for hype. I want technical critique on the architecture and the interface between planes.

1. If you watch one demo, does the “intent -> structure” framing feel like a real wedge or just prompt templating? 2. Where do you see the hardest technical bottleneck: compilation quality, tool reliability, governance design, or memory? 3. If you’ve built agents at scale: what’s the one failure mode you’d pressure-test first? 

Links again:

• SROS overview: https://sros.cloud/  • Docs: https://sros.cloud/docs  • Demos: https://ycrfsdemos.sros.cloud/  • Zenodo paper: https://zenodo.org/records/17364378