System Capabilities

ENGINEERING INTELLIGENCE.

A technical overview of the tools, systems, and engineering practices I use to build scalable web platforms, reliable backend services, and AI-powered SDLC orchestration workflows.

web

Frontend Architecture

React Next.js TypeScript Tailwind CSS MUI Vite

Building scalable, performance-focused, and maintainable frontend systems with reusable components, clean state management, responsive UI, and production-ready architecture.

neurology

AI SDLC & Agentic Systems

  • Spec-Driven Development90%
  • AI SDLC Orchestration85%
  • Agentic Workflows85%
  • Cursor / Claude / OpenCode
  • AI Code Review80%
  • Human-in-the-Loop Validation90%

Backend & Core

RUNTIME
Node.js
FRAMEWORK
NestJS
LANGUAGES
Python / TypeScript
DATABASE
MySQL / MongoDB
API DESIGN
REST APIs

Infrastructure & Delivery

account_tree

Version Control & PR Flow

Git, GitHub, branch strategy, PR reviews, and release workflows.

science

Automation & Testing

Playwright, unit testing, AI-assisted validation, and quality gates.

desktop_windows

Desktop Tooling

Tauri, Rust bridge, Python process execution, and local developer automation.

monitoring

Deployment & Monitoring

CI/CD pipelines, build automation, logs, and production readiness checks.

memory
SDLC_CORE
description
Specs
event_note
Planning
code
Implementation
rate_review
Review
science
Testing
rocket_launch
Delivery
Methodology

A SPEC-DRIVEN APPROACH TO AI-POWERED DELIVERY

My engineering approach combines clear specifications, scalable architecture, AI agent workflows, and human review checkpoints. Instead of relying on vague prompts, I prefer structured systems where requirements become specs, specs become plans, plans become implementation, and every output is reviewed before it reaches production.

01
Requirements to Clear Specs

Convert business requirements and JIRA stories into structured, implementation-ready specifications.

02
Plan Before Implementation

Use AI agents to generate step-by-step technical plans before writing production code.

03
AI Execution with Human Review

Let AI agents implement, review, and fix code while humans validate architecture, quality, and intent.

04
Quality Gates Before Delivery

Use reviews, test cases, validation checks, and PR summaries to reduce risk before release.