Imagine you’re ordering a new phone online. You complete checkout, enter your payment details, and click Pay Now. The button spins for a few seconds. No confirmation appears. Thinking the payment didn’t go through, you click again.
Imagine you’re ordering a new phone online. You complete checkout, enter your payment details, and click Pay Now. The button spins for a few seconds. No confirmation appears. Thinking the payment didn’t go through, you click again.
Open any System Design resource and you will see the same pattern: a question like ‘Design a URL Shortener’ quickly becomes a canvas filled with Kafka, Redis, API Gateways, Load Balancers, Kubernetes, CDNs, and half a dozen databases.
Vikram had read every article he could find about RAG.
He understood the concept. He could explain embeddings at a whiteboard. He knew what a vector store was, how chunking worked, and why retrieval quality depended so heavily on how you split your documents.
Arjun had been working on the same AI feature for three weeks.
It started simple enough. His team wanted a chatbot that could answer questions about their product documentation.
It’s 11:40 PM. Aditya is showing his manager the new AI assistant he built. “Ask it anything,” he says.
His manager types: “What were our total sales last week, and email the summary to the finance team.”
If you’ve ever looked at a high-level design diagram for Netflix, WhatsApp, Uber, Amazon, or any other internet-scale product, you’ve probably had the same reaction most engineers have in the beginning: everything looks wildly different.
In this hands-on AWS project, we’ll build an event-driven automation workflow using Auto Scaling Groups, Lambda, EventBridge, AWS Systems Manager (SSM) and HAProxy to automatically update backend servers whenever your infrastructure scales.
Last month she wired her company’s AI assistant into Slack. It took four days, custom auth, a webhook handler, a brittle little adapter to translate Slack’s API into something the model could call. It worked. Everyone clapped.
“Programs must be written for people to read, and only incidentally for machines to execute.”