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ai factory / mission control
Jason Mainella’s factory is built around direction, orchestration, implementation, QA, review, and deployment. The point is not AI theater. The point is a readable system where specialized agents do distinct jobs and every handoff stays visible.
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live factory status
Real-time metrics pulled from the running factory. When data is unavailable, the page degrades gracefully instead of pretending everything is fine.
Healthy / live
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Task count
0
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Agent count
5
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Last deploy / update
—
fallbackWaiting for the next factory pulse.
canonical architecture
Every task moves through a network of specialized agents. Each one owns a clear responsibility — no overlap, no ambiguity, no black boxes.
Orchestration / Coordination
Routes missions, aligns work, and keeps the factory moving in the right order.
Build / Implementation
Turns direction into code, automation, infrastructure, and shipping systems.
QA / Verification
Checks the work under real conditions so proof beats assumptions.
Review / Judgment
Applies the review gate and decides whether the mission is actually ready.
Research / Memory
Supplies context, prior patterns, and research so the stack compounds knowledge.
Deployment / Monitoring
Handles handoff, verifies the live state, and watches what happens after ship.
how it flows
Every task follows the same path. Human direction enters the system, gets built, tested, reviewed, and deployed — with visible handoffs at every stage.
01 / Intake
Human intent becomes a clear mission with scope, constraints, and a target outcome.
02 / Orchestration
Tasks are routed to the right agents, in the right order, with a readable handoff path.
03 / Build
Implementation happens in code, infrastructure, automations, and working product surfaces.
04 / QA
The system is checked against reality so broken assumptions get caught before ship.
05 / Review Gate
Review turns progress into judgment, making sure completion is not confused with readiness.
06 / Deploy / Monitor
The final handoff lands in production with active verification and post-ship monitoring.
extended roster
Beyond the core six, additional roles handle direction, shared knowledge, runtime operations, heavy compute, and system monitoring.
Shared Knowledge
Stores reusable fixes and implementation patterns for the agent cluster.
Runtime Operations
Keeps autonomous bot execution organized and observable.
Compute Core
Handles heavier model execution and high-load inference work.
Monitoring Relay
Tracks signals and keeps an eye on pipeline health.
Social Voice
Produces high-quality public content and manages the system's external presence.