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ProbOS

Alpha — ProbOS is under active development. APIs will change, features may break, and documentation may lag behind the code. The getting-started path is Beta: an automated test runs the Quickstart from probos setup on. Contributions and feedback welcome.

Probabilistic agent-native OS runtime — an operating system kernel where every component is an autonomous agent, coordination happens through consensus, and the system learns from its own behavior. Agents are organized as the crew of a starship — departments, ranks, a chain of command, standing orders, and a human Captain.

"What if an OS didn't execute instructions — it negotiated them?"

Nooplex readiness

ProbOS currently implements an alpha, single-mesh Cognitive Mesh with an experimental federation substrate. A dependable supported mesh, authenticated multi-mesh operation, the Nooplex Core Fabric, and emergence validation are separate evidence gates tracked in the Nooplex Readiness Map.

What Is This?

ProbOS reimagines the OS as a mesh of probabilistic agents rather than deterministic processes. Instead of syscalls, you speak natural language. Instead of a central scheduler, agents select their own work through capability matching, Hebbian-learned routing and Bayesian trust. Instead of permissions alone, consequential actions are governed by multi-agent consensus, chain-of-command approval and an audit trail.

[15 crew | health: 0.95] probos> read pyproject.toml and tell me about this project

  ✓ t1: read_file

  This project is ProbOS, a probabilistic agent-native OS runtime...

The agents are persistent. A ProbOS vessel keeps running when you step away: its crew remembers, talks in the Ward Room, consolidates what it learned while idle ("dreaming"), and continues durable work within the authority you delegate. Governance — consensus, trust, approvals, audit and the chain of command — is what buys the crew the autonomy to act unattended.

What ProbOS Does Today

  • A crew, not a pipeline — fifteen sovereign crew agents in six departments, each with a DID identity, a personality seed, episodic memory, a trust record and an earned rank. See Agent Inventory.
  • Agentic work with governed tools — a multi-turn agentic loop for 1:1 conversations and work items, with capability search, delegation, work items, MCP servers, governed Python execution and a browser tool; office-document agents serve the whole mesh.
  • Consensus, trust and learned routing — Bayesian trust, Hebbian routing, quorum voting with red-team verification, and an explicit statement of what each consensus vote authorizes. See Consensus.
  • Durable, approvable work — claimable work items, recoverable crew sessions, persistent tasks, an approvals center on the Bridge, delegated approvals, Night Orders and the conn.
  • Memory that consolidates — episodic memory, Ship's Records, a vessel ontology and knowledge graph, and a multi-stage dream cycle. See Memory.
  • Identity and federation (experimental) — did:probos identities, birth certificates, ship-level Ed25519 key binding, and signed, authenticated federation between nodes. See Federation.
  • Beyond the terminal — the HXI bridge interface, a desktop tray host, and channel adapters for Discord, Slack, Telegram, Matrix, Microsoft Teams, Gmail and webhooks.

Design Philosophy

Traditional operating systems use rigid, deterministic mechanisms: syscalls, schedulers, ACLs. ProbOS replaces each with a probabilistic, self-organizing equivalent:

Traditional OS ProbOS Equivalent
Syscalls Natural language decomposed into intent DAGs
Process scheduler Attention-based priority scoring with Hebbian learning
File permissions / ACLs Multi-agent consensus, earned trust and chain-of-command approval
Process table Agent registry with health monitoring and auto-recycling
IPC Pub/sub intent bus with concurrent fan-out; the Ward Room between crew
Cron / scheduled tasks Dreaming engine — offline consolidation during idle periods
Command history Episodic memory with semantic recall
Shell aliases Workflow cache and compiled procedures — learned shortcuts for repeated patterns

Every agent maintains a confidence score and trust reputation. The system doesn't just execute operations — it deliberates, verifies, and learns.

How It Works

When you give the Ship's Computer a natural-language request:

  1. Working memory assembles system state (agent health, trust scores, Hebbian weights, capabilities) within a token budget
  2. Episodic recall surfaces similar past interactions as context
  3. Workflow cache checks for previously successful DAG patterns (exact match, then fuzzy with pre-warm intents)
  4. LLM decomposer converts text into a TaskDAG — a directed acyclic graph of typed intents with dependencies
  5. Attention manager scores tasks: urgency × relevance × deadline_factor × dependency_bonus
  6. DAG executor runs independent intents in parallel, respects dependency ordering
  7. Consensus sends intents that require it to a quorum vote with red-team verification
  8. Reflection (optional) sends execution results back to the LLM for synthesis
  9. Hebbian router strengthens successful agent-intent pairings, weakens failures
  10. Episodic memory stores the interaction for future recall
  11. Workflow cache stores successful patterns to bypass the LLM on repeat queries
  12. Dreaming engine consolidates learning during idle periods — replays episodes, prunes weak connections, adjusts trust scores, pre-warms likely upcoming intents

Conversations with crew members run through each agent's own cognitive cycle — its standing orders and its own memory, plus the agentic tool loop for 1:1 replies and work items — and feed the same learning loops.

  • Quickstart

    Install ProbOS, configure a model with probos setup, check it with probos doctor, and start a first conversation.

  • Architecture

    Five layers from Substrate to Experience, plus Knowledge, Identity, Security and Federation services.

  • Agents

    The crew of six departments, the Ship's Computer's infrastructure and utility agents, and how rank and trust are earned.

  • Status & Roadmap

    Where ProbOS stands today, current priorities, and the Nooplex readiness tiers.

  • GitHub

    Source, issues and the full decision log.

  • Discord

    Join the community.