How to Stay Valuable as a Software Engineer in the AI Era: A Practical Playbook
In the previous article I argued that AI is not killing software engineering…
Tag
#ai
35 posts
How to Review AI-Generated Code: A Checklist for Catching What the Model Missed
A few months back I approved a PR that was almost entirely AI-generated. It…
How to Debug AI-Generated Code: Understand First, Fix Last
In the last article I wrote about reviewing AI code before it goes in. This one…
The Future of Software Engineering: What AI Changes, What Stays, and Where the Jobs Go
Every few weeks somebody sends me a scary headline — “AI will replace all…
Your AI Bill Just Spiked: How to Debug It and Pinpoint the Cause
The invoice email lands and your AI spend is 4× last week. The instinct is to…
AI Application Performance: Stream First, Shrink the Context, Route the Model
LLM applications have two performance budgets that classic backends don’t worry…
The AI Engineering Vocabulary: Evals, Guardrails, RAG and the Words That Actually Matter
Every field has a vocabulary you have to own before anything else makes sense…
Building an AI FAANG Interview Coach: Run the Code, Don't Let the LLM Grade It
Ask ChatGPT to “review this solution and tell me if I’d pass the interview” and…
Building an AI Astrology (Kundali) Chatbot: Let the LLM Talk, Let the Ephemeris Do the Math
Ask ChatGPT “where was Saturn when I was born, 2:30 pm on 15 August 1990 in New…
Pull Request Best Practices in the AI Era
A pull request is where individual work becomes team work — and where most of…
Git Commit Best Practices in the AI Era
A commit is the smallest unit of a project’s history, and it is written far more…
Code Review Best Practices in the AI Era
Code review is the last line of defence before code becomes everyone’s problem…
LLM Engineering in Production
Most LLM tutorials stop at “call the API and print the result.” Production doesn…
Real Project — Build a RAG Knowledge Bot
This is the capstone project. Everything you’ve learned across the previous…
Prompt Injection — Attacks and Defenses
Prompt injection is the most important security vulnerability in LLM…
Building AI Agents with Tool Use
An LLM by itself can only generate text. It cannot check the weather, query a…
Securing Your LLM Application
Traditional web applications have well-understood security models: validate…
Streaming Responses in Production
A user types a question and clicks send. Without streaming, they stare at a…
Cost Optimization for LLM Applications
Your LLM prototype costs $2/day. Your production system serving 10,000 users…
Evaluating LLM Output Quality
Here is a scenario every LLM engineer has lived through. You tweak a prompt to…
Chunking Strategies — What Nobody Tells You
You built a RAG pipeline. You embedded your documents, stored them in a vector…
Building a RAG Pipeline from Scratch
RAG is the most important pattern in production AI. Not because it is clever…
Vector Databases — Pinecone vs pgvector vs Chroma
In Lesson 5 you built a RAG pipeline using ChromaDB. That was the right choice…
Choosing Between OpenAI, Claude, and Open Source
Choosing a model is one of the first decisions you make when building an LLM…
LLM Observability and Monitoring
Traditional application monitoring asks: “Is the server up? Is latency…
Advanced Prompting — Chain of Thought, Few-Shot
In Lesson 3 you learned the fundamentals — system prompts, output formatting…
How LLMs Actually Work — What You Need to Know
You are going to build production systems on top of LLMs. Before you do, you…
Prompt Engineering Fundamentals
Prompt engineering is your primary interface to the model. In a traditional…
Choosing Models & Building Production AI Apps
You have built prototypes. You have called APIs, written prompts, wired up RAG…
LangChain & AI Orchestration Frameworks
You have a workflow: take user input, search a database, feed results to an LLM…
RAG — Give Your AI a Knowledge Base
LLMs know a lot, but they don’t know your data. They can’t read your company…
LLMs for Programmers — How AI APIs Actually Work
Before you write a single line of AI code, you need a mental model of what you…
Prompt Engineering for Developers
Prompt engineering is not a mystical art. It is software engineering applied to…
Calling LLM APIs — OpenAI, Anthropic & Structured Outputs
This lesson is all code. By the end, you will have working Python scripts that…
AI for Developers — Build with LLMs, RAG & Agents
You don’t need a PhD in machine learning to build with AI. You need to know how…