TL;DR

• You need four things, nothing more: a laptop, AI, time, and commitment. No budget, no cohort.
• Build one small reference app first (Python + PostgreSQL). Prove it runs standalone, then in Docker. This is a requirement, not optional, and you deploy this same app at every level.
• Get the AI to draft a personal learning plan around that app, not a generic course. Tell it your background, your hours per week, and whether certification matters to you.
• Certification (CKA/CKAD) is optional. It may help with jobs or promotions, it costs money and time, and this series doesn’t require it either way.
• Learn through AI Q&A, not lectures: get quizzed, explain concepts back, get pushed on guesses.
• Round it out with YouTube for what needs to be seen, AI-generated diagrams mid-conversation, and the official Kubernetes docs, which are better as a learning tool than most people realize.
• Turn the AI’s draft plan into real commitments with a “done” bar per level.
• Prompt for learning, not answers: put the first attempt on yourself, use the AI to check it.
• Take notes in your own words, and draw diagrams, on paper or in a tool like Excalidraw.
• Type new YAML and commands yourself instead of copy-pasting; it’s where you catch mistakes.

What This Actually Takes

You need four things to learn Kubernetes this way, and nothing beyond them: a laptop, access to AI, time, and commitment. No budget line, no employer-sponsored training slot, no waiting for a cohort to start.

Vibe Coding - The Background

The year is 2025. The way we build software—whether it’s a simple three-page website or a complex system with dozens of microservices—has undergone a dramatic transformation. We’ve shifted from scouring forums like Stack Overflow and reading technical blogs found via Google to having interactive conversations with LLMs (Large Language Models) and AI agents.

AI and LLMs have democratized access to technology. Today, you don’t need a formal background in software engineering to create websites or applications. With the help of AI, anyone can build software. This cultural shift is now often called “Vibe Coding.”

Previously, I wrote about modern-day education. In this post, let’s explore how the role of the college lecturer has evolved over time.

Traditionally, lecturers were at the heart of higher education. Their primary responsibility was to deliver lectures—bringing a human touch to the world of reading and writing. These sessions, often informal in tone, helped break down complex topics into digestible chunks. The setting was familiar: four walls, a blackboard and chalk—or later, a whiteboard and marker.

In the past, formal education was primarily accessible through schools, colleges, and universities. However, this is no longer the only path to gaining knowledge. Today, with the vast array of modern tools and technologies available online, self-education has become more viable than ever. If you have the motivation and discipline, you can learn virtually any subject without attending a traditional institution.

Education is now widely accessible through various online resources, including:

Introduction

This is an anchor post about machine learning and artificial intelligence.

Observations On AI

• Revolution in Text Generation: Generative AI is making significant strides in text production, promising a surge in the quality and quantity of text-based content. This encompasses everything from blog posts and articles to comprehensive reference books, transforming how information is created and disseminated.

• Advancements In AI-Generated Imagery: The evolving capabilities of AI in image generation are noteworthy. These advancements are set to enrich various fields with innovative and creative visual content, offering new dimensions in digital art, marketing, and visual storytelling.