AI Agent or n8n Workflow? Choose Determinism Before Autonomy
Use deterministic workflow automation for predictable work and AI agents for ambiguous decisions. A practical framework for choosing where each belongs.
Practical engineering studies, intelligent systems, and open software projects by Ray. Built with clarity, zero bloat, and verified evidence.
In-depth engineering notes, multi-agent review workflows, and developer infrastructure explained through working examples.
Use deterministic workflow automation for predictable work and AI agents for ambiguous decisions. A practical framework for choosing where each belongs.
Explore the structural patterns, tool permissions, and human approval gates required to build reliable, always-on AI agent architectures using GitHub Actions and automated backends.
A systematic way to diagnose Android crashes that appear only after R8 optimization, from retracing stack traces to writing the narrowest keep rule that fixes the real boundary.
Focused software and productivity tools designed and engineered by RayLabs.
Zero-subscription Obsidian vault synchronization using personal GitHub repositories with automatic 3-way merge conflict safety.
Monumental presentation clock designed for speakers and conferences, featuring zero-jitter tabular numerals, ambient audio, and full-screen projection.
Public repositories and active software tools created by Ray across Android, web, and automation.
A modular, high-performance base utility architecture for modern Android and Kotlin applications.
AI-powered platform for comprehensive health analysis, skin cancer detection, and personal diagnostics.
Curated high-resolution anime digital artwork and wallpaper curation application.
RayLabs publishes canonical technical notes here first, then syndicates select articles to the wider Medium community.
A multi-agent review pipeline for AI coding work separates implementation, independent review, final audit, and human approval.
Choose where an AI coding agent should run by separating interactive development, always-on orchestration, and heavy build workloads.

A Product Manager can spend one hour discussing a user story, another hour reviewing a roadmap, and looking at metrics.