Pipeline & Observability, Part III
Pipeline & Observability — Part III // September
The final part of the series. Scheduled for September; the two parts before it set up what this one closes out.
Coming soon
Writing
Case studies & technical writing.
Architecture decisions documented in full. How things were built, why they were built that way, and what the tradeoffs were.
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Pipeline & Observability, Part II
Pipeline & Observability — Part II // Coming Soon
Part two of the series: the middle chapter between the pipeline build and the estate's self-documentation layer.
Coming soon
Atlas Pipeline
Infrastructure Dashboard & CI/CD // Coming Soon
Building a live infrastructure dashboard and automated deployment pipeline across ten Cloudflare Workers repos, starting from manual deploys with no audit trail and ending with a self-reporting system that documents its own operation in Discord. A single authenticated event bus accepts three webhook auth dialects, observability Workers proxy GitHub and Cloudflare analytics behind cached endpoints, and identical GitHub Actions workflows deploy every Worker on push, all on free-tier infrastructure at zero cost.
Architecture
The Event Bus
Observability Workers
Phase I — Worker Route Claiming
Phase II — Bot Protection Blocking CI
The next chapter
Pushing the Limits — Overclocking SPECULAR-CORE
SPECULAR-CORE — Hardware Tuning // Case Study
A full system optimisation pass on SPECULAR-CORE: BIOS-level memory and Infinity Fabric synchronisation, a GPU voltage/frequency curve built by hand after a beta tool's batch editor failed, AIO and case cooling tuned around real-time audio noise constraints, and Process Lasso thread scheduling that finally gives Windows architectural awareness of the 9950X3D's dual-CCD layout. Validated through a full overnight stress test with zero crashes, zero thermal events.
Memory & Fabric Sync
GPU V/F Curve
AIO Cooling
Process Lasso CCD Scheduling
Stability Validation
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Building a Private AI Infrastructure From Scratch
Ramone — Local AI System // Case Study
How I designed and built a fully self-hosted AI system running five LLMs locally on consumer hardware — zero cloud dependency, zero data egress. This covers the full stack: WSL2 as the hypervisor layer, Ollama for model serving, Docker for containerisation, and Open WebUI as the interface. Includes the boot automation system, RAG pipeline architecture, and the hardware portability decisions that make the whole thing rebuildable in under 30 minutes.
System Architecture
Model Selection
RAG Pipeline Design
Boot Automation
Hardware Decisions
Workbot Engineering
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Engineering a 15-Stem Dynamic Audio Engine for Competitive Game
SlamPunk — Dynamic Mix Engine // Case Study
A deep technical breakdown of the audio architecture behind SlamPunk — how a 15-stem interactive music system was designed to mirror player performance in real time, the MetaSound graph structure, the Blueprint logic driving intensity transitions, and the spectral carving decisions that keep competitive gameplay cues surgically clear at peak musical intensity.
Stem Architecture
MetaSound Design
Blueprint Logic
Submix Hierarchy
Sidechain Ducking
Export Pipeline
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Building an Autonomous Generative Audio-Visual System
SONIN — Dual-Engine Generative System // Case Study
A full technical breakdown of SONIN — an autonomous digital instrument built in Max/MSP that composes its own evolving music and visuals in real time by continuously listening and reacting to the sounds it creates. Covers the dual-engine architecture, the three engineering problems that nearly broke it, and the DSP solutions that made it stable.
Melodic Engine
Granular Synthesis
Feedback Loop
GPU Visual Pipeline
DSP Problem Solving
Max/MSP Architecture
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