Deep Dive Intelligence Analysis and Software Assurance

Brad Guider

AI-Driven Quality Intelligence — Testing systems and intelligence analysis that learns, adapts, and proves risk.

I build multi-agent testing systems and methodology frameworks that turn uncertainty into measurable release confidence—across APIs, UI, and CI/CD.

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About

Quality Intelligence Analysis, Cutting-Edge Testing Solutions

I'm Brad Guider, Focused on neural agent-based intelligence analysis and quality assurance that keeps pace with the velocity of AI software development - Systems that don't just run tests, but reason about risk, prioritize effort, and generate evidence stakeholders trust.

My current work spans several flagship initiatives: Foreknowledge Engine (adaptive multi-agent intelligence platform), NAT (AI-powered end-to-end, API testing and security scanning), and BGSTM (a structured 6-phase testing methodology adaptable to Agile, Scrum, Waterfall, and hybrid delivery).

I specialize in Playwright automation, CI/CD quality gates, and full-stack QA platforms (FastAPI/React/PostgreSQL)—with a focus on making testing faster, more reliable, and strategically aligned to business outcomes.

1
Foreknowledge Engine Intel Analysis
2
Neuro Agent Testing AI-powered testing platform
3
BGSTM Proven Software Testing Process
4
QA Solutions — Functional · Compliance · API · UI · CI/CD · Accessibility
Portfolio

Featured Work

Flagship initiatives and how-to projects showcasing AI-driven testing, methodology design, and end-to-end QA engineering.

⭐ Flagship Initiatives

Foreknowledge Engine Flagship

Adaptive Multi-Agent Intelligence Platform

The Foreknowledge Engine is a living, adaptive intelligence analysis platform that fuses timeless strategic wisdom from Sun Tzu's The Art of War with modern multi-agent systems, neural networks, reinforcement learning, and Direct Preference Optimization (DPO). It goes beyond traditional tools by continuously thinking, verifying, and improving itself—producing superior foreknowledge and indirect strategic advantage.

  • Multi-agent reasoning and coordination
  • Continuous verification and self-improvement loops
  • Designed for decision environments with uncertainty and adversarial dynamics
Python Jupyter Multi-Agent RL DPO
Contact for More Info
NAT Flagship

NeuroAgentTest — AI-Powered Constantly Learning Testing & Security Scanning

AI-powered end-to-end functional, compliance, accessibility, API testing and security scanning that learns, adapts, and finds vulnerabilities static tools miss—built on BDI agents and belief-driven prioritization. NAT delivers adaptive, intelligent test coverage that evolves with your system.

  • BDI (Belief–Desire–Intention) multi-agent architecture
  • Adaptive test generation and intelligent vulnerability discovery
  • Full documentation and a dedicated public website available
Python Multi-Agent BDI CI/CD API Security
Website Docs
BGSTM Flagship

Better Global Software Testing Methodology

Methodology-agnostic testing approach that formalizes a 6-phase lifecycle—from planning through reporting—adaptable to Agile, Scrum, Waterfall, and hybrid delivery. BGSTM brings structure and repeatability to testing without sacrificing flexibility.

  • 6-phase lifecycle: Planning → Design → Environment → Execution → Analysis → Reporting
  • Adaptable to Agile, Scrum, Waterfall, and hybrid delivery models
  • Full-stack QA platform built on FastAPI, React, and PostgreSQL
Python React PostgreSQL TypeScript Docker
GitHub

Public Repos - Real World Sharable Solutions

Microsoft Test Solutions

90+ automated tests across 10+ test categories—login, navigation, form validation, search, and more—against a live Microsoft application surface. Includes a live interactive demo and full documentation.

Playwright TypeScript GitHub Actions HTML CSS
GitHub Live Demo Docs
HRM Testing Framework

95 manual test cases and 31 automated tests covering an HR management platform—including an executive-level ROI analysis demonstrating the tangible value of structured QA investment.

Playwright Python JavaScript pytest
GitHub
Testing Framework Examples

Comprehensive solutions using core QA engineering skills—test planning, manual testing, automated test implementation, and reporting—showcasing end-to-end testing capability.

Playwright Python pytest GitHub Actions
GitHub