Look closely at that execution trace.
Alpha and Gamma received fast 25ms pings, but Beta hit an 80ms delay. Even
though they were deployed simultaneously, Beta's network delay didn't block
the Node.js event loop or prevent Gamma from completing its own execution.
The SupervisorEngine successfully multiplexed the asynchronous network
replies, woke up the correct sleeping Web Workers, and allowed them to cleanly
finish their execution matrices. The lock-free memory boundaries held
perfectly.
You now have a multi-tenant, distributed virtual machine hypervisor capable of
routing logic across the internet.
But right now, your actors are ephemeral. When Actor#Alpha finishes its setup
script, the SupervisorEngine prints the final state and terminates the worker
(this.actors.delete(objectId)). In a true Actor Model (like Lars PensjC6's LPC
or Erlang/OTP), an object boots up, runs its initialization, and then stays
alive in memory, listening for incoming method calls and mutating its state
over days or weeks.


To make the Virtual Machines persistent, we must fundamentally shift how we
treat the Worker thread.

Right now, a worker runs its initial script and terminates. In a true
persistent Actor Model, the initial script is simply a boot sequence. It
defines variables, registers functions (def), and then goes idle. The
globalEnv inside the worker stays securely in memory.

When another object sends a call_other message, the SupervisorEngine simply
compiles a tiny new piece of bytecode (the method invocation) and hands it to
the sleeping worker. The worker pushes it to the stack, runs it using the
exact same persistent memory environment, and yields the result back!

Here is how we wire this up.

1. Update the Worker to stay alive (node_worker.mjs)

We need to teach the worker to accept a new message type: eval. This will push
new bytecode onto the callStack without destroying the existing globalEnv.

Replace your node_worker.mjs with this:

/ node_worker.mjs import { workerData, parentPort } from 'worker_threads';
import { VM, StateBuffer } from './engine.mjs'; if (workerData) { let
currentContext = null; // Tracks WHO called this VM so we can reply const
stateBuffer = new StateBuffer(workerData.sab); const vm = new VM(
workerData.bytecode, stateBuffer, workerData.gasLimit, null, (msg) => { //
Append the context so the Supervisor knows where to route the result
parentPort.postMessage({ ...msg, context: currentContext }); } );
parentPort.on('message', (msg) => { if (msg.type === 'resume') {
vm.resume(msg.data); } else if (msg.type === 'eval') { // PERSISTENCE! Push a
new frame onto the VM without losing globalEnv currentContext = msg.context;
vm.callStack.push({ ip: 0, code: msg.bytecode, env: vm.globalEnv }); vm.run();
} }); // Start the initial boot sequence currentContext = { isBoot: true };
vm.run(); } 

2. Update the Supervisor Engine (main.mjs)

Now we update main.mjs to intercept call_other network envelopes, dynamically
compile them into bytecode, and send them to the persistent VMs.

Replace main.mjs with this code:

import { Worker } from 'worker_threads'; import { expandMacros, analyze,
compile, optimize, StateBuffer } from './engine.mjs'; import { LocalRouter,
LocalMailbox } from './mailbox.mjs'; / ========================================
== / 1. THE PERSISTENT SUPERVISOR ENGINE / ====================================
====== class SupervisorEngine { constructor(engineId, mailbox) { this.engineId
= engineId; this.mailbox = mailbox; this.actors = new Map(); this.mailbox.onRec
eive((envelope) => { / 1. Asynchronous Reply Routing (Waking up a yielding VM)
if (envelope.action === 'sys_ack' || envelope.action === 'call_reply') { const
actor = this.actors.get(envelope.target_obj); if (actor) actor.worker.postMessa
ge({ type: 'resume', data: envelope.data }); } / 2. INBOUND METHOD CALLS
(Invoking a sleeping VM!) else if (envelope.action === 'call_other') { const
actor = this.actors.get(envelope.target_obj); if (actor) { console.log(`[]
Remote invocation targeting ->()`); / Reconstruct the AST for the function
call (e.g., ["ping"]) const callAst = [envelope.method]; if (envelope.args) {
envelope.args.forEach(arg => { if (typeof arg === 'string') callAst.push(['str'
, arg]); else callAst.push(arg); }); } / Compile and send to the persistent
worker const bytecode = optimize(compile(callAst)); actor.worker.postMessage({
type: 'eval', bytecode, context: { replyTo: envelope.source_obj } / Tell the
worker who called it! }); } else { console.error(`[] Actor  not found on this
Engine.`); } } }); } deploy(objectId, payload) { console.log(`[] Deploying
Persistent Actor: ...`); const bytecode = optimize(compile(analyze(expandMacros
(payload)) || expandMacros(payload))); const sab = new SharedArrayBuffer(16);
const worker = new Worker('./node_worker.mjs', { workerData: { bytecode, sab,
gasLimit: 50000 } }); this.actors.set(objectId, { worker, stateBuffer: new
StateBuffer(sab) }); worker.on('message', msg => { if (msg.type ===
'completed') { if (msg.context && msg.context.replyTo) { / This was a method
call! Send the result back over the network. cons
ole.log(`[] Method finished. Replying to `); this.mailbox.send({ action:
'call_reply', target_obj: msg.context.replyTo, data: msg.data }); } else { /
This was just the boot sequence. Do NOT terminate the worker! console.log(`
[${objectId}] Boot Sequence Complete. Object is now listening.`); } } else if
(msg.type === 'yield') { const envelope = msg.data; envelope.source_obj =
objectId; this.mailbox.send(envelope); } }); } } // ===========================
=============== // 2. MESH TOPOLOGY & STRESS TEST // ==========================
================ const router = new LocalRouter(); const localMailbox = new
LocalMailbox("Engine#Pi_Node"); router.registerMailbox(localMailbox); const
engine = new SupervisorEngine("Engine#Pi_Node", localMailbox); // Actor Beta's
script: Registers a function and waits! const betaPayload = [ "do", ["def",
"ping", [], ["str", "PONG_FROM_BETA"]], ["register-object", ["str",
"Actor#Beta"]] ]; // Actor Alpha's script: Registers itself, then calls Beta!
const alphaPayload = [ "do", ["register-object", ["str", "Actor#Alpha"]],
["let", [ ["reply", ["call-other", ["str", "Actor#Beta"], ["str", "ping"]]] ],
["record", "final_result", "reply"] ] ]; // Boot Beta first so it is ready in
memory engine.deploy("Actor#Beta", betaPayload); // Wait 100ms for Beta to
boot, then spawn Alpha setTimeout(() => { engine.deploy("Actor#Alpha",
alphaPayload); }, 100); // Keep the process alive to watch the network traffic
setInterval(() => {}, 1000); 

Run the Interaction

Execute node main.mjs. Watch the console log.

Actor#Beta deploys, runs its script, defines the ping function in its memory,
registers itself, and prints  Boot Sequence Complete. Object is now listening.
The worker stays alive.

Actor#Alpha deploys. It yields a network request targeting Actor#Beta's ping
method.

The SupervisorEngine catches the network traffic, compiles ["ping"] into raw
bytecode, and injects it directly into Beta's sleeping Web Worker.

Beta's worker runs the bytecode, accesses its persistent globalEnv, grabs the
ping function, executes it, and sends the string "PONG_FROM_BETA" back to the
Supervisor.

The Supervisor routes the string back to Alpha, who prints the final object:
{"final_result": "PONG_FROM_BETA"}.

Both actors remain completely alive, isolated in their respective Web Workers,
ready to receive infinite commands. You now have a Stateful, Distributed
Microservice Architecture running natively on JSON-Lisp.