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Prosper0

License: MIT Python

A work-specific exobrain — a locally-sovereign AI assistant scoped entirely to a single employer relationship. Built on the Local Mind Foundation architecture.

When the job changes, the number increments: Prosper0 → Prosper1 → Prosper2. The architecture carries forward. The vault stays archived.


Why This Exists

Most AI productivity tools are designed for individual optimization inside a trust relationship that doesn't exist: the employer trusts the AI, the employee trusts the vendor, and no one has a clear answer for where the data goes.

Prosper0 takes a different position:

  • The operator owns the hardware. The stack runs locally — no cloud, no vendor data custody.
  • The employer can verify everything. Every AI action is logged. Every data transfer is emailed with the employer CC'd. The employer has a paper trail they didn't have to ask for.
  • The AI cannot expand its own permissions. Tool access is controlled by a config file the AI cannot write. Any capability expansion requires the operator to edit the config manually.

This isn't a productivity tool. It's a trust architecture.


Architecture

Six layers, each independently testable:

┌─────────────────────────────────────────────────────────┐
│  Layer 6: Portable Deployment                           │
│  Encrypted USB drive · Hardware-drive pairing ·         │
│  Single desktop shortcut = entire setup                 │
├─────────────────────────────────────────────────────────┤
│  Layer 5: Testing Infrastructure                        │
│  Sample data generator · Model version comparison ·     │
│  Bridge integration tests · Data boundary tests         │
├─────────────────────────────────────────────────────────┤
│  Layer 4: Employer Transparency                         │
│  AI-immutable tool config · Audit trail ·               │
│  Data transfer manifest · Transparency reports          │
├─────────────────────────────────────────────────────────┤
│  Layer 3: Prospero Bridge                               │
│  Context switching · Shared TTF calendar ·              │
│  Mode propagation · Email-CC'd data transfer            │
├─────────────────────────────────────────────────────────┤
│  Layer 2: Prosper0 Vault                                │
│  Work-scoped flat-file vault · Surfacing engine ·       │
│  Webhook handler · Work modes                           │
├─────────────────────────────────────────────────────────┤
│  Layer 1: LLM Stack (von Prosper0)                      │
│  Local inference · Model-agnostic interface ·           │
│  MCP wiring · Orchestrator · Tool config                │
└─────────────────────────────────────────────────────────┘

Layer 1: LLM Stack

The AI brain for the work instance. Local inference only — no cloud API. The inference layer is model-agnostic: swap the model without touching the orchestrator.

  • stack/tools.config.yaml — operator-controlled tool permissions; the AI cannot write this file
  • Model selection is an open deliverable; the interface contract is designed first
  • Version testing harness: run the same prompt battery across model versions and diff the output

See: stack/README.md


Layer 2: Vault

A work-scoped flat-file vault (markdown). Fully separate from any personal exobrain — no shared directories, no passive data flow. Mirrors Marlin patterns but scoped to work context.

  • prosper0.py — surfacing engine (one work task at a time, operator-declared mode)
  • Work-specific modes: available · in-meeting · deep-work · off-hours

See: vault/README.md


Layer 3: Prospero Bridge

The controlled interface between the personal exobrain (Marlin) and the work instance (Prosper0). No data flows automatically. Every crossing is explicit, operator-initiated, and logged.

  • Context switch signal (which instance is active)
  • Shared TTF calendar view (both vaults push tasks with a source: tag; calendar renders both without cross-contaminating vault content)
  • Mode propagation (Marlin mode change → Prosper0 behavioral response)
  • Data transfer: operator initiates → system drafts email → operator sends with employer CC'd → system logs

See: bridge/README.md


Layer 4: Employer Transparency

The structural guarantee that Prosper0 is trustworthy to an employer.

  • tools.config.yaml defines all AI tool access; human-editable only
  • Every AI tool invocation is logged before and after execution
  • Every approved data transfer is logged with content hash, destination, and email message ID
  • Transparency report generator produces human-readable summaries for any time range

See: transparency/README.md


Layer 5: Testing Infrastructure

Every layer is independently testable. No real employer data is ever used in tests.

  • Sample data generator: realistic synthetic vault content
  • Model version comparison harness: capability regression testing across model upgrades
  • Bridge integration tests: end-to-end context switching and transfer flows
  • Data boundary tests: assertion-based proof that vault isolation holds

See: tests/README.md


Layer 6: Portable Deployment

The full stack runs from a USB drive. The reference deployment story: hand someone the drive, ask to put a shortcut on their desktop, done. The drive is encrypted and hardware-paired — physically removing it ends the session cleanly.

Deployment configurations are flexible: vault on host, model on host, or everything on the drive. Size is tracked and optimized as a project statistic.

See: deploy/README.md


Design Decisions

See spec/ for architecture decision records:


Design Decisions

See spec/ for architecture decision records:


Quick Start

cd deploy/
docker compose up -d
./pull-model.sh          # first run only — pulls qwen2.5:7b
docker attach prosper0-orchestrator

Status

Layer Status
Layer 1: LLM Stack ✅ M0–M3 complete — Ariel can start and take input
Layer 4: Employer Transparency ✅ Enforcement chain complete — 33 tests passing
Layers 2, 3, 5, 6 🔲 Not started

Current: Merging M0–M3 to main. Next: live smoke test (docker compose up).

AI: Ariel von Prosper0 — Qwen2.5 7B via Ollama.

Built by Jared Allison. Part of the Local Mind Foundation project.

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Work-scoped exobrain — locally-sovereign AI assistant for a single employer relationship

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