Blog
AI engineering insights, practical advice, and things I'm learning.
Ai Engineering
How to Run LLMs Locally on Your Machine
Running AI models locally gives you privacy, speed, and zero API costs. Here's what hardware you need, which tools to use, and how to choose the right model.
Ai Agents
What Are AI Agents and How Do They Work?
AI agents can plan, use tools, and take action autonomously. Here's what they are, how they work under the hood, and what separates useful agents from overhyped demos.
Ai Engineering
Why AI Hallucinates and How to Reduce It
AI hallucination isn't a bug you can patch. It's a consequence of how language models work. Here's what causes it, how to measure it, and what actually reduces it.
Ai Engineering
What Is RAG? Retrieval-Augmented Generation Explained
RAG lets AI models pull in real data before generating a response. Here's how retrieval-augmented generation works, why it matters, and where it breaks down.
Ai Engineering
What Are Embeddings in AI? A Technical Explanation
Embeddings turn text into numbers that capture meaning. Here's how they work, why they matter for search and RAG, and how to choose the right model for your use case.
Ai Engineering
Context Windows Explained: Why Your AI Forgets
Context windows determine how much an AI model can 'see' at once. Here's what they are technically, how attention scales, and practical strategies for working within their limits.
Career
Your Experience Is Your Biggest AI Advantage
Why senior developers and experienced professionals have the biggest advantage with AI. Their judgment and domain knowledge is exactly what makes AI output useful.
Ai Coding
The AI Coding Workflow That Actually Works
The practical coding workflow with AI: what to hand the model, what to review line by line, and when to throw the output away.
Career
Why Most AI Advice Is Terrible
Most AI advice falls into hype or fear. Neither helps. What actually matters: understanding the mechanics, building real skills, and thinking for yourself.
Ai Engineering
What Tokenization Means for Your Prompts
Tokenization isn't just a technical detail. It shapes how LLMs process your input. Understanding it changes the way you write prompts.