BUILDING
RELIABLE SYSTEMS.
I am Kanchan Maji, a Python backend and automation developer. I focus on building reliable systems with clear logic, maintainable structure, and practical outcomes.
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Engineering with
Clarity & Discipline.
I believe good engineering begins with mental clarity. Systems reflect the thinking behind them — unclear thinking leads to fragile software.
I approach both code and learning with discipline, patience, and long-term focus. Rather than rushing for complexity, I value simplicity that holds under pressure.
This mindset is influenced by philosophical and contemplative traditions that emphasize awareness, responsibility, and intentional action.
PRINCIPLE 01
Simplicity is a feature, not a limitation.
PRINCIPLE 02
Consistency beats intensity.
PRINCIPLE 03
Understanding comes before optimization.
PRINCIPLE 04
Tools evolve, fundamentals endure.
DEPLOYED ARSENAL
Python
C++
MySQL
Git
Linux
PHP
COMPILING... (AIMS)
AI / ML Engineer
Integrating Neural Networks with backend logic.
DevOps Specialist
Mastering CI/CD, Kubernetes, and Cloud Scaling.
The Path So Far.
First Exposure to Code
My journey began with basic HTML. Writing simple markup and seeing it rendered visually sparked a strong interest in how logic transforms into real, usable output.
Python & Databases
As my interest grew, I transitioned into Python for backend logic and automation. Alongside this, I learned SQL and core DBMS concepts such as schema design, indexing, and data consistency.
Deployment & Systems
I began working with real-world tooling — deployment workflows, hosting environments, domains, ports, Git, and GitHub. This phase shifted my focus from writing code to delivering reliable systems in production.
Currently focused on backend scalability, automation workflows, and infrastructure fundamentals.
My Methodology.
How I learn, debug, and maintain productivity in a high-pressure environment.
Community First
I don't learn in isolation. I am active in Discord dev communities, reviewing code, asking for architectural advice, and helping peers debug.
The AI Protocol
Copilot, not Creator.
I use LLMs to explain complex documentation, debug obscure errors, and optimize logic. I never copy-paste code I do not understand.
- Understanding Concepts
- Error Analysis
- Documentation Summary
AI: "You are missing an index on 'user_id'..."
Action: *I read MySQL docs on B-Tree indexing -> Implements fix manually*
Reading Logs
Video tutorials are slow. I prefer official documentation. I maintain a reading log to track every concept learned in Python, C++, and System Design.
Project-Based Learning
Theory is useless without application. I build real tools—bots, scrapers, and portals—to cement my knowledge.
BEST
FIVE
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