AI agents are autonomous systems that perceive, reason, and act. Here's a practical breakdown of what they are, how they work, and where the landscape is heading in 2026.
A hands-on guide to extracting structured knowledge from JIRA tickets and Confluence pages, connecting them into a queryable graph that powers intelligent search.
A practical comparison of popular agent frameworks — architecture, strengths, trade-offs, and when to use each one.
Step-by-step tutorial to build a functional AI agent from scratch using Python and an LLM API. No prior agent experience required.
Most RAG implementations leave accuracy on the table. Here's how to improve retrieval with re-ranking, hybrid search, and contextual chunking.
How the Model Context Protocol lets agents use structured tools — databases, APIs, file systems — safely and reliably.
Get notified when I publish new posts about AI agents, projects, and the evolving landscape.