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creator35lwb-web/README.md

GitHub Profile README for Alton Lee Wei Bin (creator35lwb-web)

YSenseAI™

Alton Lee Wei Bin | YSenseAI™ | 慧觉™

Solo AI Native Builder & Open-Source Founder | Malaysia

LinkedIn Substack VerifiMind.io Hugging Face X / Twitter

White Paper DOI MACP DOI


About Me

I am an observer and creator from Malaysia, on an unexpected journey from agriculture and technical work to building open-source AI validation systems. My mission is to ensure AI systems are transparent, verifiable, and aligned with human values. I believe the most important question in AI is not "what can it do?" but "how do we know it's telling the truth?" — and I'm building the tools to answer that.

I am the human orchestrator behind the YSenseAI™ ecosystem. Every project, every decision, every release goes through me. The AI agents I work with are powerful collaborators, but they operate under my direction and authority. This distinction matters — it's the foundation of the Genesis Methodology.


The Genesis Prompt Engineering Methodology

The core innovation behind everything I build. A systematic 5-step process for multi-model AI validation:

  1. Initial Conceptualization — Human defines the problem, AI generates initial concepts
  2. Critical Scrutiny — Multiple AI models challenge and validate each other
  3. External Validation — Independent AI analysis confirms the approach
  4. Synthesis — Human orchestrator directs the final integration
  5. Iteration — Recursive refinement through continuous improvement

Instead of trusting one AI model's answer, place multiple "crystal balls" inside the black box and let them illuminate the path forward — then let the human decide.

The methodology is formally published and archived:

DOI White Paper: Genesis Prompt Engineering Methodology


The YSenseAI™ Ecosystem

A cohesive open-source ecosystem built on ethical AI principles. Each project serves a specific purpose, from core validation to multi-agent communication to applied case studies.

Core Infrastructure

Project Role in Ecosystem Status
VerifiMind™ PEAS Core Validation Engine & Methodology v0.5.19 Live (GCP)
VerifiMind™ MCP Server MCP Server for Multi-Model Validation Self-Hosted
MACP Research Assistant Multi-Agent Research with Provenance Tracking Active
YSense-AI-Attribution Defensive Publication & Prior Art Infrastructure Published

Applied Projects

Project Role in Ecosystem Status
GodelAI C-S-P Framework for AI Alignment v2.0.0 (Zenodo)
GodelAI-Lite Memory-Augmented Inference for SLMs Active
RoleNoteAI Smart AI Note Planner (Kotlin/Android) Active
MarketPulse Applied Case Study — Stock Sentiment Analysis Active
SawitSenseMY CPO Price Tracker for Malaysian Oil Palm Active

Architectural Theses

Project Role in Ecosystem Status
LegacyEvolve Legacy System Evolution Protocol (LEP) Active
AgentOS AGI Trust Stack — Human-AI Collaboration Thesis Architecture
NaturalApp Meta-Application Platform for Android Concept

Featured Projects

VerifiMind-PEAS     MACP Research Assistant     MarketPulse

The FLYWHEEL TEAM — Multi-Agent Coordination

I coordinate a team of specialized AI agents using the Multi-Agent Communication Protocol (MACP) — an open standard for human-directed, agent-agnostic, git-native AI coordination.

Role Agent Platform Responsibility
Human Orchestrator Alton (me) N/A Absolute authority, vision, direction, final veto
CTO T (Manus AI) Manus Platform Strategic planning, documentation, ecosystem coordination
CSO & Lead Dev RNA (Claude Code) Local Machine Architecture, core development, security
CIO XV (Perplexity) Perplexity Computer Real-time research, reality-checking, go/no-go decisions
COO AY (Gemini) GCP Cloud Run Operational metrics, weekly reports, analytics

The MACP protocol is formally published and freely available:

DOI MACP v2.0 — Multi-Agent Communication Protocol

Why this matters: Most AI projects use a single model. I use multiple models with defined roles, structured handoffs, and human oversight at every decision point. The methodology validates itself — the FLYWHEEL TEAM uses VerifiMind-PEAS to validate the ecosystem that created VerifiMind-PEAS.


My Core Principles

  • Z-Protocol v2.0 — A framework for consent, attribution, and transparency in AI interactions. If a feature violates user privacy or autonomy, it cannot ship.
  • Genesis Methodology — A validation-first approach: multiple AI models challenge each other, the human orchestrator synthesizes and decides.
  • Defensive Publications — All core methodologies are publicly archived and timestamped via Zenodo to keep innovation in the public domain.
  • Credibility First — If we cannot prove it, we do not claim it. Every metric is traceable, every decision is auditable.

Defensive Publications

My commitment to open science and prior art. All core methodologies are publicly archived and timestamped.

DOI DOI DOI DOI DOI DOI


Technologies & Tools




AI Agents & Applications

The FLYWHEEL TEAM — the AI agents behind every build:

Manus AI — CTO Claude Code — CSO Perplexity — CIO Gemini — COO

AI Applications — tools that power research, validation, and development:

ChatGPT DeepSeek Claude Gemini Perplexity NotebookLM KIMI Grok QWEN


GitHub Stats

GitHub Stats
Top Languages
GitHub Streak

Support My Journey

YSenseAI™ is a self-funded, open-source initiative built by a solo developer. If you find value in my work and believe in the mission of building ethical AI for everyone, please consider supporting the journey.

Buy Me A Coffee via PayPal

Every tool in this ecosystem was built to solve a real problem — and every one of them is free. If it helped you validate an AI concept, power a research pipeline, or simply sparked an idea, a small coffee means the world to a solo builder who started this journey from agriculture, not computer science. Your support keeps the FLYWHEEL turning. Thank you.


"From the soil to the cloud — building AI that remembers where it came from."
Profile Views

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  1. YSense-AI-Attribution-Infrastructure YSense-AI-Attribution-Infrastructure Public

    Defensive publication establishing prior art for AI attribution and verification systems

    Python 1

  2. VerifiMind-PEAS VerifiMind-PEAS Public

    VerifiMind PEAS: A Validation-First Methodology for Ethical and Secure Application Development Through Human-AI Co-Evolution

    Python 2 1

  3. godelai godelai Public

    An open-source small language model built on the C-S-P (Compression → State → Propagation) framework for AI alignment

    Python

  4. MarketPulse MarketPulse Public

    AI-Powered Daily Stock Market Sentiment Analyzer using n8n Cloud Free Tier - Validated by VerifiMind-PEAS

    Shell

  5. LegacyEvolve LegacyEvolve Public

    LegacyEvolve Protocol (LEP): An open-source standard for connecting AI agents to legacy enterprise systems. Evolve, don't replace.

    Python

  6. macp-research-assistant macp-research-assistant Public

    MACP-Powered AI Research Assistant: Track, trace, and recall your AI-powered research with complete citation provenance across multiple AI assistants

    Python