Typed handoffs
Designed explicit state and capability boundaries between planning, execution, and review.
Infrastructure system
Local AI Orchestration
A local AI platform that gives planning, focused execution and independent review explicit jobs and visible receipts.
- My contribution
- Platform architecture · workflow design · operational evidence
- Timeframe
- Phased platform program
- Status
- Ongoing
THE WORK IN ONE LINE
A task connects to a bounded capability and a retained result. The case separates qualified and planned capabilities.
Sanitized architecture replay
Explore the control plane
No live models, services, addresses, or private topology.
FROM SOURCE TO SOMETHING USEFULExplore a layer
One connected system.
Data + code + design
Checked values
Validate the calculation before it becomes a claim. A useful answer separates what is known from what still needs review.
Implemented capability
Planning
Turns an objective into explicit, bounded steps before tools are used.
01Goal decomposition
02Dependency ordering
03Stop conditions
Observable proof
Typed plans and checkpoint artifacts
Replay timeline
Source-grounded brief
00:00 / 00:20
Planning
Objective received
Create a private, source-grounded analytical brief.
02 / The problem
Make a multi-tool workflow inspectable.
Local AI systems often accumulate models and scripts faster than operational trust. The goal was to make capability, routing, evidence, and safety explicit across a modular platform.
03 / What I built
Miguel used typed state, deterministic selection rules, an action boundary, and receipt-oriented QA to make multi-step work observable. The public replay is sanitized and does not connect to the private platform.
04 / Result & scope
What changed. What comes next.
Sanitized architecture, capability-ledger, routing, and QA artifacts from the local AI platform workspace. Related PC and NAS sources document AgentOps and the video-to-research pipeline.
Evidence and replay
Captured receipts and QA artifacts so runs can be inspected after completion.
Local-first routing
Separated task intent from provider choice to support private, swappable runtimes.
01Choose the job before the model
Typed workflow contracts describe what a task needs before choosing a compatible provider or runtime. This separates product intent from model inventory.
02Prove what actually ran
Action receipts and review artifacts connect requests to results. A listed capability is different from an activated tool, and the interface keeps that distinction visible.
03Current scope
The retained platform checkpoint qualified an earlier runtime phase. Office, audio and media host surfaces remain activation-disabled, and full natural-language specialist routing is still in progress.
04Cross-machine operations
Related AgentOps work connects queues, shared context and visible worker health across the desktop, laptop and NAS. A running memory dashboard and coordination source were inspected. This integration work is distinct from the capabilities of installed upstream agents.
05Video as research material
A separate video-processing pipeline retains timestamps across transcripts, sampled frames, OCR and optional visual captions. It connects media preparation to searchable context while keeping the source moment available for review.
More of the work