AI/ML Engineer 2026: Skills, Roles & Career Guide Beyond Model Building If you’re planning a career in artificial intelligence or machine learning in 2026, there’s an important shift you need to understand: AI/ML engineering is no longer just about building machine learning models. The modern AI/ML engineer works across software engineering, data pipelines, cloud infrastructure, […]
The Hidden Technical Debt in Your RAG System 80% of RAG implementations fail in production. Here’s where teams unknowingly accumulate RAG technical debt โ and how to fix it before it becomes expensive. Retrieval-Augmented Generation (RAG) has become one of the most popular approaches for building AI applications that can answer questions using private or […]
๐๐๐ถ๐น๐ฑ๐ถ๐ป๐ด ๐๐ ๐๐ฝ๐ฝ๐? ๐๐ผ๐ป’๐ ๐ฆ๐ธ๐ถ๐ฝ ๐๐๐ ๐๐๐ฎ๐ฟ๐ฑ๐ฟ๐ฎ๐ถ๐น๐ Ready to ship your LLM app to production? Not so fast. A raw LLM pipeline blindly trusts inputs and outputsโmaking it vulnerable to hallucinations, prompt injections, and data leaks. At a recent AI meetup, I found many developers building apps without guardrails. Common belief? “LLMs have built-in safety.” […]
Building a Practical Multi-Agent Architecture for Automated Workflows From single-LLM pipelines to a multi-agent architecture where each agent is assigned specific skills and the workflow is fully automated end-to-end. Architecture Overview (Simple & Modular) I designed the system using 5 core agents, each with a clearly defined responsibility: 1๏ธโฃ Supervisor Agent Owns the task Decides […]