AI DEVELOPMENT / DEDICATED BUILD

Project MIND

A human-autonomy-preserving AI architecture that combines specialized agents, explicit memory and provenance, verification, tools, scientific workflows, robotics, HPC, and quantum acceleration without treating the quantum computer as the mind itself.

What it is

This page separates the concept, implementation path, interactive experiment, evaluation criteria, failure modes, and sources so the topic can be studied without relying on a summary tile.

Core concepts

The orchestration layer coordinates specialized agents rather than assuming one model does every job.
Memory stores claims, provenance, task state, and review history separately from transient model context.
Verification gates distinguish generated hypotheses from checked evidence.
Tools and external actions remain permissioned and auditable.
Classical compute handles general reasoning/workflow; accelerators such as GPUs, FPGAs, robotics, laboratory instruments, and quantum systems are specialized resources.

Architecture / workflow

Accept a task with goals, constraints, authority, and evidence requirements.
Decompose work into specialized agent contracts.
Retrieve prior knowledge with provenance.
Run tools or simulations inside bounded environments.
Verify outputs against tests/evidence, request human review where required, then publish or act only within granted authority.

Technical foundations

A task graph can represent dependencies, ownership, evidence, and retry state.
Event logs enable replay and postmortem analysis.
Content-addressed or versioned artifacts reduce ambiguity about which evidence a result used.
Capability-based permissions can restrict each agent/tool to the minimum authority needed.

Evaluation checklist

Task correctness and evidence coverage.
Reproducibility from logs and artifacts.
Unauthorized-action rate must remain zero.
Recovery from agent/tool failure.
Human ability to inspect, override, and stop workflows.

Failure modes and limits

Agent coordination can create hidden coupling and correlated failure.
Memory without provenance becomes an amplifier for stale information.
Verification layers can become ceremonial if tests do not target real failure modes.
Powerful tools require stronger permissions, isolation, and review boundaries.

Practical build path

Use the existing Agent Workbench to test bounded task contracts.
Add provenance-aware memory and replayable traces.
Integrate specialized tools behind explicit capability boundaries.
Expand toward scientific/robotic/HPC/quantum gateways only when each layer has independent tests and human oversight.

Primary / authoritative references

Search the Learn library for related lessons →

AUTHORED STUDY COMPANION / 3.2

Coordinate roles with testable artifacts

Prerequisites. Typed tools, dependency graphs, hashing and explicit acceptance criteria.

A coordinator should know which artifact satisfies each task dependency. The local MIND companion uses three deterministic roles. The planner records inputs (1,2,3) and expected sum 6. The executor computes the sum. The verifier compares the computed artifact with the explicit expected value. Each role's serialized artifact receives a SHA-256 digest in the event ledger.

This differs from counting evidence-looking words: a verifier must inspect the actual artifact and a discriminating criterion. A digest identifies bytes; it does not certify their truth or the competence of the author. Dependencies are checked before a role runs, and a JSON round trip demonstrates a serializable checkpoint. A failed validation produces blocked, not a decorated completion status.

The fixture represents coordination protocol, not autonomous LLM collaboration or distributed consensus. All roles run sequentially in one process. To extend it, introduce an artifact schema, injected failures, persisted attempts, cancellation and an idempotent executor. Separate a role's claim that it succeeded from the verifier's observable result.

Coordinate roles with testable artifacts — model structure
Element	Model	Interpretation
Planner	Inputs + expected result	Defines the contract
Executor	Computed sum	Produces an inspectable artifact
Verifier	Equality check + status	Gates acceptance

Predict, run, compare

The valid fixture produces sum 6 and three artifact digests. Injecting failed validation leaves status blocked even though the plan and computation artifacts exist.

Download executable notebooks and source Inspect source ↗

Open mind.ipynb in the package. Run cells in order, compare with the reference, then change the stated input. Restart the kernel to reset.

Computed reference result — local CPU fixture

{
  "artifacts": {
    "plan": {
      "expected": 6,
      "inputs": [
        1,
        2,
        3
      ]
    },
    "execute": {
      "sum": 6
    },
    "verify": {
      "passed": true
    }
  },
  "ledger": [
    {
      "task": "plan",
      "sha256": "b5215ff2cc8b56ff328d53ca6e2aacd6f2b98ee2e20d456ce71b97ae5c623934",
      "dependencies": []
    },
    {
      "task": "execute",
      "sha256": "867d1af71a0a107e2288a8fb6309e5d820595a55b272cf8057496958d093e92a",
      "dependencies": [
        "plan"
      ]
    },
    {
      "task": "verify",
      "sha256": "748eda8085f7e3c82149775d9542083427f0f8a955173c4a0ed18c85c69c5c09",
      "dependencies": [
        "plan",
        "execute"
      ]
    }
  ],
  "status": "verified fixture",
  "role_type": "deterministic functions; not autonomous LLM agents"
}

This is the recorded result of the included code under the package environment. It is not a live service or device measurement.

Extend the experiment

Replace the sum with a parser-validation task. Store the input fixture, exact output, schema version and check result; then reject a stale artifact from a previous input.

Check your reasoning: What does an artifact hash establish?

The exact artifact bytes it identifies — Correct. A digest supports identity and integrity comparisons.
That the artifact is scientifically true — Truth requires a claim-specific check.
That a human approved execution — Approval is a separate recorded authorization event.

This is an explained self-check, not a certification of mastery.

Claim-specific sources

Reviewed 2026-10-02: this worked example and its explicit assumptions. Source links and notebook results do not establish production or hardware validation.