Ideas worth
thinking through.
Practical guides to web development and AI. Learn how the tools work and when they can help.
Curiosity with
a purpose.
Clear answers, examples and diagrams to help you plan your next project.
A good RAG system knows when it cannot answer
The practical anatomy of a document assistant that cites its sources, respects permissions and handles the question the documents cannot answer.
Before you give an AI agent a tool, draw this map
A readable blueprint for permissions, approval points and recovery in workflows where an AI system can take action.
Your AI demo works. Is the product ready?
A launch checklist for teams building LLM features: representative tests, failure handling, latency, cost and human trust.
Python or .NET for an AI application? Ask a better question
How to choose a stack around deployment, team skills, data and integration needs instead of treating languages as a contest.
The instruction hidden inside the document
What prompt injection looks like in a real assistant, why a stronger prompt is insufficient and how to contain the damage.
The AI feature that should have been a form
A simple decision framework for knowing when to use conventional software, retrieval, generation or an agent.
The invisible work behind a website that feels fast
A practical guide to LCP, INP and layout stability, and why motion should help a visitor understand the page.